ÖGBMT/ÖGMP  Joint Annual Meeting 2026

Aim: Accurate prediction of respiratory motion is essential for bridging imaging latencies for active motion management in external beam radiotherapy. Deep learning approaches, such as long short-term memory (LSTM) networks, have shown promising performance, but their data requirements and generalizability across institutions remain unclear. In the context of radiotherapy surface imaging, this study investigates training dataset size requirements and evaluates cross-institution performance using different surface imaging systems.
Methods: For Institute I, breathing motion data from 207 patients with mainly lung or other thoracic malignancies acquired with an optical surface scanner (C-RAD AB, Uppsala, Sweden) was included. 41 patients were randomly selected for independent model evaluation. The remaining 166 patients were used to train LSTM networks to predict breathing amplitude and phase within a 500 ms horizon. Training was performed using an increasing number of patient datasets (5,10,20,…,166). To assess cross-institution generalizability, breathing data of 67 patients suffering mainly from oesophageal or other thoracic malignancies from Institute II acquired with an infrared camera system monitoring reflective markers on the patient’s chest (RPM, Varian Medical Systems, Palo Alto, CA) was used. Motion prediction performance was evaluated using the root mean square error (RMSE) of the breathing amplitude.
Results: The LSTM model using 30 patients for training achieved a RMSE of 0.14 mm (median breathing amplitude of test cohort: 1.4 mm). Adding more training data led to a plateau in performance gains. For the test data from Institute II (median breathing amplitude: 3.9 mm) a RMSE of 0.30 mm was achieved.
Conclusion: LSTM-based breathing motion prediction requires only a small number of patient datasets to achieve robust performance. Furthermore, the model demonstrated strong generalizability across institutions and surface scanner systems, supporting its potential for clinical deployment in motion-managed radiotherapy.

Extracting waveforms from electrocardiography (ECG) printouts remains a difficult task even today. A recent challenge organized by Physionet highlights the need for practical solutions which could give access to billions of ECGs globally stored in image formats. A key limitation of the Physionet challenge is its focus on a single fixed layout (3x4 matrix), which does not reflect the variety encountered across devices and health care systems.

To account for variations in ECG layouts and styles, we develop an ECG paper synthesis tool that is capable of generating different layouts (3x4, 6x2, 12x1, optional rhythm strips) with random positioning and styling of visual elements. High-fidelity segmentation masks for each ECG trace are generated. We use this tool to create random images and masks on-the-fly while training a 2D U-Net to segment each pixel into background, 12 leads and rhythm. Post-processing is applied on the segmentation output to extract the 12-lead ECG time-series.

Trained on augmented synthetic images, the pipeline is evaluated on internal, real-world ECG images in two ways. First, for a set of 5011 images, extracted signals are visually overlaid with the original image and the signal quality is judged independently by three team members. Through majority voting, we find the quality to be “good but some errors” or “excellent” in 92.9% of cases, while only 2.4% are “bad” extractions (remaining 4.7% are “invalid” or inconclusive images). Second, a subset of 960 high-quality digital PDFs with available ground-truth signals are quantitatively evaluated. We obtain a median signal to noise ratio (SNR) of 41.2dB (IQR: 34.4dB).

The presented workflow allows development of ECG digitization algorithms using fully synthetic data. The derived pipeline achieves qualitatively good ECGs signals for a majority of images. The high SNR highlights strong model performance, paving the way for large-scale biosignal data access from paper-based ECGs.

Introduction
Dyskalemia, encompassing hyperkalemia (K⁺ ≥ 5.5 mEq/L) and hypokalemia (K⁺ ≤ 3.5 mEq/L), is a frequent electrolyte disorder with potentially fatal cardiac consequences, requiring timely monitoring. While diagnosis depends on invasive and time-consuming blood tests, the strong influence of serum K⁺ on ECG morphology enables ECG-based assessment. To overcome the limited generalizability of prior DNN approaches based on proprietary data, we introduce an open benchmark dataset of ECGs paired with serum K⁺ measurements (within 1 hour) from a diverse emergency department and ICU cohort, and use it to train a deep neural network (DNN) for dyskalemia prediction.

Methods
Ten-second 12-lead ECG recordings from the MIMIC-IV-ECG dataset were paired with serum K+ concentrations from the MIMIC-IV database within a one-hour window, resulting in 162,318 samples from 74,488 patients. Signals were bandpass filtered (0.5-100 Hz), z-normalized, and divided via patient-level split into training (80%), validation (10%), and test (10%) sets. Multiple DNN architectures, including 1D ResNet, CNN-LSTM and CNN-Transformer (Conformer) with multimodal fusion, were trained to distinguish healthy from dyskalemic patients. Performance was evaluated using the area under the receiver operating characteristics curve (AUC).

Results
Best performance was achieved with a Conformer architecture (1D CNN + Transformer), yielding AUCs of 0.802 for hypokalemia and 0.728 for hyperkalemia in binary classification. In a cost-sensitive 7-class severity task, performance remained strong for severe hypokalemia (AUC 0.769 for K⁺ < 2.5 mEq/L) but declined for severe hyperkalemia (AUC 0.624 for K⁺ > 6.5 mEq/L), likely due to potassium-specific label noise such as hemolysis and timestamp inaccuracies. Ongoing work focuses on improved data curation, subgroup analyses, and external validation.

Conclusion
This study provides preliminary evidence that ECG-based deep learning can support non-invasive dyskalemia screening, with reliable hypokalemia detection and ongoing efforts to resolve current limitations in hyperkalemia prediction through dataset refinement and external validation.

Hintergrund und Zielstellung:
Die Anpassung von Hörgeräten oder Hörimplantaten erfordert die Einstellung des elektrischen Stimulationsbereichs. In der klinischen Praxis basiert diese in der Regel auf subjektiven Angaben der Patienten zur wahrgenommenen Lautheit der Reize. Diese Rückmeldungen sind jedoch nicht immer zuverlässig, insbesondere bei Patientengruppen mit eingeschränkter Kommunikationsfähigkeit. Objektive Verfahren, etwa die Analyse hirnelektrischer Aktivität mittels Elektroenzephalographie (EEG), könnten hier eine wertvolle Ergänzung darstellen. Ziel dieser Studie ist es zu untersuchen, ob Transformer-basierte neuronale Netzwerke aus EEG-Daten die individuelle Unbehaglichkeitsschwelle zuverlässig erkennen können und ob Attention-Mechanismen zusätzlich Einblicke in die zugrunde liegenden neuronalen Muster erlauben.

Methodik:
Es wurden 33 normalhörende Erwachsene im Alter von 18 bis 30 Jahren untersucht. Den Probanden wurden akustische Stimuli mit variierenden Schallpegeln präsentiert, während sie die empfundene Lautheit subjektiv bewerteten. Parallel dazu wurden kortikale Potentiale mittels EEG aufgezeichnet. Die EEG-Daten wurden mit einem Transformer-basierten Deep-Learning-Modell analysiert, das Attention-Mechanismen nutzt, um zwischen den Zielklassen „zu laut“ und „nicht zu laut“ zu unterscheiden. Zusätzlich wurden Attention Maps ausgewertet, um relevante zeitliche und räumliche Merkmale der EEG-Signale zu identifizieren.

Ergebnisse:
Das Transformer-Modell erreichte eine Klassifikationsgenauigkeit von bis zu 85 % sowie einen AUC-Wert von bis zu 0,96 bei der Erkennung von als „zu laut“ empfundenen Stimuli. Die Analyse der Attention Maps zeigte, dass das Modell gezielt auf spezifische zeitliche EEG-Segmente und Kanäle fokussiert, die mit der Lautheitswahrnehmung assoziiert sind, was auf eine inhaltlich sinnvolle Repräsentation der Daten hindeutet.

Schlussfolgerung:
Die Ergebnisse verdeutlichen das hohe Potenzial Transformer-basierter EEG-Klassifikationen zur objektiven Bestimmung der Unbehaglichkeitsschwelle. Darüber hinaus ermöglichen Attention Maps nicht nur eine leistungsfähige Klassifikation, sondern auch ein besseres Verständnis der zugrunde liegenden neuronalen Prozesse, was einen wichtigen Schritt in Richtung interpretierbarer und klinisch einsetzbarer KI-basierter Anpassungsverfahren darstellt.

Introduction
Organoids are increasingly used as three-dimensional in vitro models in fundamental research, disease modelling, drug discovery or precision medicine. To better access their electrophysiological activity, it is advantageous to interface them with electrodes from multiple sides. As conventional microelectrode arrays (MEAs) are fabricated in a cleanroom using mask-based processes, the manufacturing possibilities on three-dimensional, sensitive substrates are limited. Here, we present reusable inkjet-printed three-dimensional microelectrodes on novel laser-cut substrates with cavities for extracellular electrophysiology of brain organoids.
Methods
Three-dimensional substrates were laser-cut from poly(methyl methacrylate) (PMMA) sheets. Gold and epoxy-based dielectric SU-8 ink were inkjet-printed using commercial Dimatix Samba Materials Cartridges with a drop volume of 2.4 pL to form MEAs in the cavities. The conductive polymer poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) was electrodeposited on top of the gold electrodes to improve stability, impedance, and the neural interface. The laser-engraved wells were analyzed with height profilometry and cross-section cuts. To characterize the printed three-dimensional MEAs on PMMA, we conducted electrochemical impedance spectroscopy, resistance measurements of conductive lines through the wells, and brightfield microscopy.
Results
Laser cutting resulted in substrates with outer dimensions of 40 x 40 mm and a central engraved cavity with an outer diameter of approximately 3 mm and a depth of 1 mm. The average impedance of the gold electrodes, with diameters ranging from 40 to 80 µm at 1 kHz, was 54 kΩ and decreased about tenfold after PEDOT:PSS electrodeposition. In ongoing experiments, the printed three-dimensional well-MEAs are used to record from electrogenic organoids.
Conclusion
We inkjet-printed gold microelectrodes into laser-cut three-dimensional wells and successfully electrodeposited PEDOT:PSS onto them, thereby reducing impedance and improving the multi-site electrical interface with organoids. Our reusable electrode arrays are well suited for biotechnological applications.

Introduction
Organic semiconductor films based on bulk heterojunction blends stand out for their high power conversion efficiency and easy fabrication. Beyond photovoltaic performance, understanding their stability in biological environments and interfacial behavior in complex media is critical for expanding these materials into new applications, including bioelectronic implants.

Methods
PM6:Y6 thin-films were exposed to controlled aqueous electrolyte environments, while impedance spectroscopy and transient photovoltage analysis were used to quantify charge carrier dynamics, the electrochemical interface, and capacitive ion movement at the device-electrolyte boundary over several days. Data from electrical analyses were used as input for a physics-informed model to better understand charge transport mechanisms and current distribution under ionic coupling conditions.

Results
PM6:Y6 films retain robust charge transport characteristics when interfaced with electrolytes. Our electrolyte interface measurements reveal a distinct modulation of interfacial capacitance and increased generated photovoltage upon light illumination after several days. Our results suggest that the PM6:Y6 interface exhibits stability in solvated environments without significant loss of electronic functionality. The combined experimental and modeling results suggest stable mixed ionic-electronic behavior at the interface.

Conclusion
Our work underscores stable interfacial characteristics of PM6:Y6 heterojunctions in simulated biological environments. The combined evidence supports the potential for PM6:Y6 systems beyond traditional photovoltaics toward applications requiring functional performance in ionic or aqueous environments, such as photoactive implants.

Introduction
Optoelectronic neurostimulation offers a promising strategy for wireless, minimally invasive modulation of neuronal activity. By converting light into electrical stimuli at the cell-material interface, photoactive implants enable signal transmission with high temporal control. However, poorly understood charge-transfer mechanisms and an incomplete understanding of how different stimulation parameters affect neurons comprise critical aspects that demand detailed studies. In particular, the relative contributions of capacitive and faradaic processes remain insufficiently characterized, complicating the design of safe stimulation protocols. Here, we investigate PM6:Y6 bulk heterojunction layers for controlled neuronal stimulation, focusing on mechanisms underlying electrical signal transmission.

Methods
First, the electrophotoresponse of PM6:Y6 films on ITO-coated glass substrates was characterized by recording the light-induced voltage of the PM6:Y6 layer relative to the ITO reference through an electrolyte solution. Primary rat neurons were then cultured on the electrode surface for 14 days, subsequently treated with varied pulse patterns using a high-power LED at 660 nm wavelength. Cumulative light energy and stimulation frequency were varied to change the relative amount of faradaic and capacitive effects. Immunofluorescence staining was performed to assess activity-related markers and gain insights into underlying stimulation mechanisms.

Results
Characterization of the electrophotoresponse of the PM6:Y6 device revealed mixed capacitive-faradaic responses at the electrode-electrolyte interface, which remained stable over several days of incubation. These results were then used to define distinct neuronal stimulation protocols controlling the faradaic contribution by adjusting the light pulse length. This variation in pulse length could be shown to elicit distinct changes in neuronal activity using immunostaining of neuronal activity marker expression.

Conclusion
This work demonstrates that PM6:Y6 bulk heterojunctions enable light-driven wireless electrical neurostimulation with charge-transfer mechanisms dependent on the used stimulation protocol. The combined electrical and molecular biological analysis provides a means to better understand the interface of the optoelectronic PM6:Y6 films and living cells.

Introduction
This study evaluates organic photovoltaic (OPV) electrodes as a promising platform for next-generation retinal implants. These materials provide flexible and biocompatible interfaces capable of driving network-mediated ret-inal activation through wireless near-infrared (NIR) light stimulation. By leveraging the retina’s preserved signal-ing circuitry, this organic prosthetic approach offers a potential strategy for restoring vision in advanced outer-retinal degenerative diseases such as retinitis pigmentosa and age-related macular degeneration.
Methods
Ultrathin, flexible D18:Y6 electrodes were tested using ex-vivo blind mouse (rd10) retinal explants. Stimulation was performed using NIR light pulses (780 nm) with varying pulse durations (20–50 ms) and intensities. Neu-ronal responses of retinal ganglion cells (RGCs) were recorded using micro-electrode arrays (MEAs) and patch-clamp recordings. Biocompatibility was assessed using mouse retinal explants and human iPSC-derived retinal organoids.
Results
NIR stimulation of D18:Y6-coated electrodes successfully triggered RGC activity through network-mediated neural pathways. Spike response profiles and response latencies indicated that, particularly at longer pulse dura-tions, Faradaic charge injection is a primary mechanism for neuronal activation. Neuronal output was precisely modulated by adjusting light intensity and pulse duration. Biocompatibility assays confirmed that D18:Y6-based materials are non-cytotoxic and maintain the structural integrity of retinal tissue over the tested periods.
Conclusion
These findings validate the photoelectric performance and biological safety of D18:Y6-based OPV electrodes. This platform enables precise, wireless NIR stimulation, offering a minimally invasive and high-resolution ap-proach to vision restoration. While long-term stability and fabrication remain challenges, this technology pro-vides a solid framework for future retinal implants and organic neuroprosthetic interfaces.

Introduction
The effects of anti-cancer drugs on 3D spheroids can be assessed using electrical impedance spectroscopy (EIS) performed on microelectrode arrays (MEAs). However, in planar MEAs, the solid substrate limits nutrient diffusion to the bottom of the spheroids. In addition, spheroid placement and stabilization on planar MEAs are challenging. To overcome these limitations, mesh MEAs are investigated here, allowing the culture medium to surround 3D cell-cultured spheroids and improving mass transport conditions.
Methods
The mesh MEA (MultiChannelSystem MCS GmbH, Germany) comprised of 60 electrodes of 30 µm diameter and an inter-electrode spacing of 200 µm, fabricated on a polyimide mesh. Spheroids of 250 µm size were generated from the HT-29 cell line and cultivated on mesh MEAs for 96 hours. Navitoclax (10 µM) was tested against untreated spheroids (n = 5 per group). EIS was performed using the impedance analyzer ISX-3 (Sciospec GmbH, Germany). The relative impedance change (RIC) was calculated to assess mesh MEA performance.
Results
The mesh MEA enabled easy placement and stable holding of spheroids. Cells proliferated around the mesh structure, allowing for impedance measurements inside the spheroid and at its periphery. In both control and Navitoclax-treated groups, RIC increased up to 48 hours. After this time point, RIC values stabilized in the control group, whereas a reduction in RIC was observed in the Navitoclax-treated spheroids. On rigid planar MEAs, a large percentage of spheroids moved during culture. Additionally, impedance signals were declining, potentially due to the formation of a necrotic core within the spheroids.
Conclusion
Mesh MEAs provide a robust platform for stable spheroid cultivation and long-term EIS measurements. Drug-induced effects can be reliably detected using mesh MEAs for 3D in vitro drug screening applications. Future work will focus on testing drug effects on spheroids derived from different cell lines on the same mesh MEA.

Überblick über Methoden für die Bestimmung der SPECT-Auflösung von Gammakameras

Johannes Holzmannhofer, UK f. Nuklearmedizin und Endokrinologie, SALK BetriebsgmbH, LKH Salzburg, Salzburg, Österreich, j.holzmannhofer@salk.at

Einleitung
Für konventionelle SPECT-Gammakameras basierend auf Detektoren mit NaI(Tl)-Einkristallen sind lt. NEMA NU 1 “Performance Measurements of Gamma Cameras” zwei unterschiedliche Methoden zur Bestimmung der SPECT-Auflösung definiert: die Messung von Punktquellen in Luft (“w/o scatter”) und die Messung von Linienquellen in Was-ser (“with scatter”). Für Gammakameras mit pixelierten Detektoren haben manche Hersteller eigene Prüfverfahren ba-sierend auf den oben genannten Verfahren entwickelt. Weiters gibt es ein speziell für Herz-Gammakameras vorges-chlagenes Prüfverfahren, welches in OVE EN IEC 63073-1:2023 “Spezielle bildgebende Systeme in der Nuklearmedizin – Merkmale und Prüfbedingungen, Teil 1: Kardiale SPECT” spezifiziert ist.
Methods
Die verschiedenen Methoden für die Bestimmung der SPECT-Auflösung werden vorgestellt. Diese Methoden wurden an einer konventionellen SPECT-Gammakamera angewandt. Die Auswertung der rekonstruierten Datensätze erfolgte mit einer eigenen – mit MatLab entwickelten – Software und die Ergebnisse wurden verglichen.
Conclusion
Die Prüfverfahren sind messtechnisch in der Praxis gut umzusetzen. Ob die Messdaten mit der erforderlichen räumli-chen Auflösung rekonstruiert werden können, hängt weitgehend davon ab, ob der Hersteller lediglich klinische Rekon-struktionsparameter zulässt, oder ob diese Parameter weitgehend frei konfiguriert werden können.

Ziel
Die patientenspezifische Dosimetrie ist ein wichtiger Bestandteil moderner Radionuklidtherapien und spielt insbesondere bei neuen Radiopharmaka eine zentrale Rolle. Die 3D-SPECT/CT-basierte Dosimetrie ermöglicht dabei eine detaillierte Analyse der räumlichen Dosisverteilung und bietet methodische Vorteile gegenüber planaren Ansätzen. Neben der Risikoorganabschätzung gewinnt insbesondere die Erfassung der Tumordosen an Bedeutung, da sich diese im Verlauf mehrerer Therapiezyklen verändern können, während Organdosen vergleichsweise stabil bleiben. Als praxisnahes Anwendungsbeispiel wird die Dosimetrie bei der CCK2R-gerichteten Peptidrezeptor-Radionuklidtherapie mit ¹⁷⁷Lu-DOTA-MGS5 vorgestellt, wobei tracer-spezifische Herausforderungen, insbesondere die Berechnung der Magenwanddosis, diskutiert werden.

Material und Methoden
Die 3D-Dosimetrie basiert auf quantitativen SPECT/CT-Aufnahmen zu vier Zeitpunkten nach Applikation des Radiopharmakons, wodurch zeitabhängige Aktivitätsverteilungen in Organen und Tumoren bestimmt werden können. Bei jedem weiteren Zyklus ist eine posttherapeutische SPECT/CT-Aufnahme ausreichend, um die Dosimetrie entsprechend zu aktualisieren. Der tomographische Ansatz erlaubt eine anatomisch präzise Zuordnung der Aktivität und ermöglicht die Anwendung einer Partialvolumenkorrektur, die insbesondere für die Berechnung der Tumordosis relevant ist. Die absorbierte Dosis der jeweiligen Organe und Tumore wird sowohl organbasiert nach dem MIRD-Konzept als auch mittels Voxeldosimetrie berechnet.

Ergebnisse
Im Vergleich zur organbasierten Dosimetrie erlaubt die Voxeldosimetrie die Darstellung räumlich inhomogener Dosisverteilungen, welche insbesondere für Risikoorgane bedeutsam sein können. Gleichzeitig werden Limitationen der Voxeldosimetrie bei deformierbaren Organen wie der Magenwand deutlich. Die Aktualisierung der Dosimetrie anhand posttherapeutischer SPECT/CT-Aufnahmen ermöglicht die Erfassung der zeitlichen Entwicklung der Organ- und Tumordosen über den gesamten Therapieverlauf.

Schlussfolgerungen
Die 3D-SPECT/CT-Dosimetrie stellt eine wesentliche Grundlage für die personalisierte Radionuklidtherapie dar. Insbesondere die zyklusweise Ermittlung der Tumordosen ist für die Interpretation von Therapieeffekten und die klinische Einführung neuer Tracer wie ¹⁷⁷Lu-DOTA-MGS5 von großer Bedeutung.

Introduction
Im Jahre 2010 wurde im Rahmen der Europäischen Gesellschaft für Nuklearmedizin (EANM) eine Initiative zur Harmonisierung der PET-Scanner gestartet, die sich EANM Research for Life, kurz EARL, nennt. In Europa gab es zu dieser Zeit bei den eingesetzten PET-Scannern eine große technologische Vielfalt, sodass eine Akkreditierung nach der EARL-1-Initiative den Fokus auf Integration und Harmonisierung hatte. Heute gewinnt durch den raschen Anstieg von Multicenterstudien die EARL-Akkreditierung immer mehr an Bedeutung, und die Vergleichbarkeit von PET-Untersuchungsergebnissen auch mit Ländern außerhalb Europas wird immer dringlicher.
Methods
Die EARL-Version 2 seit dem Jahr 2019 legt den Fokus auf Qualität und die Akkreditierung technologisch state-of-the-art PET-Scanner mit neuen, anspruchsvolleren und engeren Grenzwerten. Mit dem heurigen Jahr wurden für die Überprüfung der Kalibrierung die Grenzwerte weiter verschärft und für die Bildqualität eine neue Auswertemethode eingeführt. Die Berechnung nach Standard Uptake Values (SUVs) wird von der Berechnung nach Contrast Recovery Coefficients (CRCs) abgelöst. Zusätzlich ist eine Akkreditierung von 177Lu für SPECT in Planung.
Results
Die heuer neu definierten Grenzwerte und die neu eingeführten Auswertemethoden stellen einen Schritt der EARL-PET-Akkreditierungen in Richtung internationaler Harmonisierung dar. Sie ermöglichen eine robustere, effektivere, verlässlichere und vereinfachte PET-Anerkennung bei der Teilnahme an Multicenterstudien.
Conclusion
Der Vortrag gibt einen kurzen Rückblick über die Entwicklung von EARL in den letzten 15 Jahren, befasst sich mit den aktuellen Standards und den heuer neu gestalteten Akkreditierungsanforderungen, beschreibt die eingesetzten Phantome und Methoden und zeigt die Effekte einer Akkreditierung auf.

Das medizinische Leistungsspektrum befindet sich in einem raschen und kontinuierlichen Wandel, dessen sichere und effiziente Umsetzung die zentrale Einbindung von Medizinphysikerinnen erfordert. Für den Bereich ionisierender Strahlung sind aktuell nur minimale Erfordernisse an Medizinphysikerinnen sowie deren Tätigkeitsbereiche in der Medizinischen Strahlenschutzverordnung geregelt. Technologische Innovationen – etwa KI-basierte Anwendungen wie automatische Konturierungsalgorithmen in der Radioonkologie – erweitern das Einsatzspektrum der Medizinphysik erheblich und stellen zugleich neue Anforderungen an Qualitätssicherung und Validierung. Parallel dazu führen Automatisierung und Standardisierung zu einer Reduktion des Zeitaufwands bestimmter Tätigkeiten.

Im Jahr 2018 veröffentlichte die Österreichische Gesellschaft für Medizinische Physik (ÖGMP) eine Personalbedarfsempfehlung für die Strahlentherapie/Radioonkologie, die nun angesichts der fortschreitenden Entwicklungen – insbesondere in der Präzisionsradiotherapie – einer Aktualisierung bedurfte. Darüber hinaus wurden erstmals Empfehlungen für die Radiologie sowie die Nuklearmedizin, einschließlich Hybridbildgebung, erarbeitet. Im Rahmen dieser Aktualisierung wurden zudem europäische und internationale Modelle (u. a. der DGMP, EFOMP, EU, IAEA) eingehend evaluiert, validiert und im Hinblick auf nationale Rahmenbedingungen miteinander verglichen.

Für den Personalbedarf von Medizinphysiker:innen wurden zusätzlich Anwendungen nichtionisierender Strahlung, Beratungstätigkeiten, Ausbildung sowie potenzielle Synergieeffekte zentraler und überregionaler Strukturen ergänzt.

Das vorgestellte Modell basiert auf einer Excel-basierten Berechnung, die den Bedarf an medizinphysikalischen Vollzeitäquivalenten unter Berücksichtigung abteilungsspezifischer Faktoren ermittelt.

Introduction
The transmembrane potential (Vm) is a fundamental bioelectric property of cells that plays an active role in regulating cell proliferation, differentiation, and tissue organization. There is increasing evidence that alterations in Vm are not merely consequences of malignant transformation, but rather, they function as upstream regulators of cancer initiation, progression, and therapeutic response. This study examines Vm as a unifying bioelectric hallmark of cancer and assesses its relevance for diagnosis and therapy.
Methods
We systematically analyzed experimental studies across multiple cancer models to assess the relationship between Vm states, cellular behavior, and therapeutic interventions. Data from electrophysiological measurements, molecular perturbations of ion channels, bioelectric modulation strategies, and computational modeling approach-es were integrated to evaluate the causal relationship between Vm dynamics and oncogenic phenotypes.
Results
Malignant cells exhibited consistent depolarization compared to non-malignant cells. This depolarization was associated with increased proliferation, loss of differentiation, acquisition of stem cell-like traits, and enhanced metastatic potential. Conversely, induced hyperpolarization suppressed tumor growth, promoted differentiation, and inhibited cancer stem cell activity. Vm oscillations regulate cell-cycle transitions and coordinate multicellular tumor behavior. Of note, bioelectric alterations often preceded the morphological and genetic hallmarks of malignancy, establishing Vm as an early predictive biomarker. Using pharmacological, genetic, optogenetic, or physical approaches, including tumor-treating fields, to modulate Vm produced selective anti-tumor effects with limited toxicity. Computational modeling enabled the prediction of Vm-dependent signaling states and treatment responses.
Conclusion
Vm emerges as a central regulator of cancer biology, integrating ion-channel activity with signaling, metabolism, and tissue-level organization. Its measurability, reversibility, and predictive capacity position Vm as a powerful diagnostic and therapeutic target. Incorporating Vm-based biomarkers and modulation strategies into precision oncology offers a complementary systems-level approach to current molecular and immunological therapies.

Mathematical representations of voltage-gated ion channels are fundamental to in silico electrophysiology. Personalization remains constrained by model complexity, parameter identifiability, and the experimental effort required to calibrate mechanistic gating schemes. Traditional methodologies—the Hodgkin–Huxley (HH) and Markov (hidden Markov model, HMM) formalisms—balance computational efficiency against mechanistic interpretability, and vice versa. This work contends that control-oriented system identification can serve as a complementary paradigm for ion-channel modeling in precision electrophysiology, enabling rapid development of accurate, protocol-conditioned macroscopic current models directly derived from voltage-clamp input/output data. Building on nonlinear block-structured models (e.g., Hammerstein–Wiener) and transfer-function characterizations of channel dynamics, we delineate a practical pipeline for obtaining stable, simulation-efficient models and integrating them into patient- or cell-specific digital twins. We examine accuracy–complexity trade-offs in relation to HH/HMM baselines, propose personalization workflows aligned with contemporary cardiac digital twin calibration methods, and summarize validation requirements pertinent to clinical translation.

Introduction
Computer simulations are widely used for studying bioelectric activity of the nervous system. Modelling body surface distributions of compound nerve action potentials (CNAPs) is computationally challenging due to the complex nerve structure containing thousands of axons. Previously, we proposed a two-domain model for reduc-ing computational load, that contained the passive volume conductor (first domain) and a line shaped source structure (second domain) allowing for continuous superposition of distributed activity on multiple axons. Here, we apply this concept to an anatomically realistic geometry for the first time.

Methods
The right tibial nerve was modeled in finite element discretization by a curved line defined by equally spaced unit dipoles. A lead field matrix was computed linking all source points along the nerve with all field points on the body surface. The body surface potential generated by a single axon was computed using an ion-current model of propagating action potentials. The CNAP was obtained by convolving the axon potentials in each source point with the temporal distribution function of all axons.

Results
Computation of the lead field matrix for a finite element model of the right leg (approximately 50,000 nodes on body surface; 189 source points; 5 mm spacing) took approximately 20 minutes on a standard computer. Simula-tion of neuro-potentials (15 ms time window; 0.02 ms resolution) took under a second (MATLAB). A bipolar derivation over the tibial nerve in the popliteal fossa (31 mm electrode spacing) produced a morphologically plau-sible signal (latency 8.6 ms, amplitude 2.5 μVpp).

Conclusion
The proposed method for simulating potential fields generated by volley conduction in peripheral nerves re-quires a relatively low computational load and may qualify as a helpful scientific tool in neurophysiology. After experimental validation, future simulations may contribute to improved signal registration by exploiting a better understanding of CNAP distributions on the body surface.

INTRODUCTION
Ventricular stiffness is a crucial diagnostic and prognostic indicator of diastolic function, influenced by both physiological and pathological factors. However, assessing ventricular stiffness and diastolic function in a clinical setting remains challenging. Cardiac Multifrequency Magnetic Resonance Elastography (MMRE) has emerged as a promising tool for evaluating stiffness in both left (LV) and right ventricle (RV). This study aimed to explore the capability of cardiac MMRE to non-invasively quantify the diastolic ventricular stiffness in adult healthy controls (HC) and its physiological variation with age and sex.

METHODS
We prospectively included 40 HC (49.0 years ± 23.21; 22 male) who underwent cardiac MMRE. Shear waves at frequencies of 80, 90, and 100 Hz were introduced using pressurized-air actuators. During a total of three breath-holds, full 3D wave fields were acquired in diastole by electrocardiography-triggered multi-slice spin-echo, echo-planar imaging. Shear wave speed (SWS) maps were reconstructed for the LV and RV as surrogate for tissue stiffness.

RESULTS
No significant correlations were found between age and SWS in either the LV (R² = 0.076, p = 0.090) or RV (R² = 0.086, p = 0.070) across the entire HC cohort. However, an interaction effect between age and sex was identified. Specifically, female exhibited a significant increase in ventricular stiffness with advancing age in both the LV (R² = 0.2573, p = 0.0377) and RV (R² = 0.3550, p = 0.0116), whereas male did not demonstrate a similar age-related stiffness progression (R² = 0.0104, p = 0.6510 for LV and R² = 0.0109, p = 0.6433 for RV).

CONCLUSION
Ventricular stiffening with physiological aging affects female, but not male. Cardiac MMRE shows promise as a clinical tool for the non-invasive quantification of diastolic ventricular stiffness.

Background
Uveal melanomas and adjacent organs at risk (OARs) represent some of the smallest and most challenging structures to depict and define in radiotherapy. Historically, dedicated ocular proton therapy centers have used a geometrical model-based planning approach for target definition to effectively utilize their sharp beam penumbras. This work presents a workflow to integrate modern imaging modalities into the structure definition process. It aims to reduce uncertainties arising from the necessary assumptions inherent in model-based approaches.

Methods
Patient preparation includes tantalum clip marker surgery; a planning CT acquired in the treatment position with an LED-based gaze-steering setup (Figure 1); high-resolution MR imaging using microcoils; fundus photography; and biometric and ultrasound measurements. RayStation, including the RayOcular module, is used to register MR and CT images based on clip positions, which appear as well-defined artifacts. A three-dimensional eye model is geometrically adapted to the MR and CT images. During alignment, the eye size is verified against biometric measurements, and realistic clip-to-sclera distances are checked for positional confirmation. In the integrated fundus projection, the model is fused with the fundus images based on the optic disc and tumor position visible in the MR sequences.

Results
Macula position can be determined fundus image based within registration uncertainties. Tumor base definition can be initiated in the MRI fundus projection and refined through integration of fundus image topography and ultrasound-derived dimensions overcoming image stack limitations. The target volume can be reviewed and adapted slice-wise on MR or CT images (Figure 2) or within an anatomically precise 3D model for review with the opthalmologist.

Conclusion
Combining multiple imaging modalities with ophthalmologic measurements in the creation of a high-resolution eye model allows for a target and OAR definition approach that overcomes both the resolution limits of individual imaging modalities and the intrinsic uncertainties of a purely model-based approach.

Goal
In carbon-ion radiotherapy (CIRT), the prescribed RBE-weighted dose depends on the clinical RBE model in use. Differences between the LEM1- and mMKM-based dose systems make it difficult to directly compare treatment plans, reported doses, and clinical experience across centres. This study introduces an LETd-based framework that links RBE differences between these dose systems and quantifies how model-related uncertainties may af-fect clinical dose interpretation.
Materials and methods
Monte Carlo simulations of clinical carbon-ion beams and treatment-relevant fields were performed. Dose-averaged LET (LETd), mixed-beam radiosensitivity (α_mix), and RBE were evaluated for both LEM1- and mMKM-based dose systems. Based on the observed LETd dependence, a simplified analytical relationship was established to estimate inter-system RBE differences and associated uncertainty.
Results
Substantial deviations between simulated α_mix and in-vitro reference data were observed at low to intermediate LETd, reaching up to 240% at LETd = 22.5 keV/μm for pencil beams. These deviations translated into a systemat-ic RBE overestimation in the mMKM-based clinical dose system. A logarithmic–logistic function well described the LETd dependence of α_mix differences between the two clinical systems. Using this formulation, inter-system RBE differences could be predicted within ±1% when α_mix difference was known, and within ±3% using LETd alone. The proposed relationship allows localisation of regions where inter-system RBE differences may become clinically relevant and can be used for comparative patient plan analysis.
Conclusions
This study provides a practical LETd-based approach to support the comparison of RBE-weighted dose between LEM1- and mMKM-based clinical dose systems. The results may aid the interpretation of RBE-weighted dose in carbon-ion radiotherapy and support consistent evaluation of treatment plans.

Introduction
In particle therapy the biological absorbed dose ist the product of physical dose and relative biological effectiveness (RBE). For carbon ions, RBE can be derived using either the Local Effect Model-I (LEM-I) or the modified Microdosi-metric Kinetic Model (mMKM). Our clinic uses a bi-model approach, prescribing and optimizing doses in LEM-I, and subsequent mMKM recalculation may trigger LEM re-optimization. Recently, dose-averaged linear energy transfer (LETd) has been introduced, aiming to increase LETd inside the target, while minimizing it to adjacent organs at risk (OARs). This study summarizes the preparatory steps for implementing clinical LETd painting with carbon ions.
Methods
Seven sacral chordoma patients with large targets (GTV>150cc) were re-optimized using different LETd functions to assess their impact on routine clinical treatment planning (RayStation v2025, RaySearch Laboratories, Stockholm). All patients received 73.6 Gy(RBE)/16 fractions in LEM-I; mMKM dose distributions were recalculated. Robustness eval-uation was performed with (5 mm, 3.5%) and doses were recomputed on control CT scans acquired during treatment. Minimum LETd values of 40, 50 and 60 keV/um were tested, along with varying maximum LETd functions on OARs. Remaining optimization parameters were adjusted to maintain LEM dose quality comparable to the initial plans.
Results
LETd optimization increased minimum LETd (compare Figure1) and produced higher, more homogeneous mMKM doses, but reduced plan robustness (compare Figure2). Maximum LETd constraints directly impact dose conformity in both, LEM and mMKM. To balance these effects, LETd optimization was introduced with 40 keV/um and the use of maximum LETd functions was limited whenever possible. Currently, only maximum LETd values for sacral nerves have been defined and may be applied when necessary.
Conclusions
Clinical LETd optimization was implemented using a minimum LETd of 40 keV/um for the high-dose CTV only, to achieve an increased LETd in the GTV, but maintain dosimetric plan quality and plan robustness.

Ziel

Die Robustheit von HDR-Brachytherapieplänen für Zervixkarzinompatientinnen soll durch simulierte Organbewegungen mittels MRT-Bilddeformation bewertet werden.

Methoden

10 intrakavitär-interstitielle Behandlungspläne von 5 Patientinnen wurden retrospektiv analysiert. Die MRT-gesteuerte adaptive Brachytherapiebehandlung umfasste vier Fraktionen mit einer Dosis-Volumen-Parameter-basierten Vorschreibung gemäß ICRU-89, entsprechend dem EMBRACE-II Protokoll (doi:10.1016/j.ctro.2018.01.001). Klinische Pläne wurden mithilfe manueller Optimierung und der Einhaltung einfacher Prinzipien zur robusten Planung von Beladungsmustern erstellt und retrospektiv mit einer Forschungsversion des RayStation Bestrahlungsplanungssystems analysiert.
Die relative Bewegung der Risikoorgane (OARs) zwischen oder während einzelner Fraktionen wurde unter Verwendung mehrerer deformierter Patientenbilder simuliert, welche durch Deformationsfelder - abhängig von der Bewegung jeweils eines OAR - erzeugt wurden. Applikator, Katheter und primäre Tumor-Zielvolumina wurden bei der Verformung ausgeschlossen, um ein starres, fixiertes Implantat zu simulieren. Organbewegungen für Blase, Rektum und Darm wurden simuliert, indem diese in diskrete Richtungen – superior, inferior, anterior, posterior, links und rechts – um einen Betrag von ±0,5, ±1 und ±2 cm verschoben wurden (Abbildung 1). Für jedes Szenario wurde die dosimetrische Auswirkung auf die OAR D2cm3 (Gy) durch Berechnung der absoluten prozentualen Differenz pro Millimeter (ΔD%/mm) zwischen klinischem und verschobenem Szenario bewertet.

Ergebnisse

Verformungen von 10 mm in P-A-Richtung führten zu Mittelwerten (und Standardabweichungen) der ΔD%/mm von 8.0 (4.0), 5.9 (2.3) und 4.4 (3.1) % für Blase, Rektum und Darm, was mit Literaturwerten übereinstimmt (doi:10.1016/j.radonc.2008.06.010).
Unter der Annahme, dass diese Werte für alle vier HDR-Fraktionen gelten, würden bei einer Teletherapie von 45 Gy und einem Brachytherapie-Plan, der alle EMBRACE-II-Dosisziele erreicht, die Gesamtdosen, D2cm3 in Gy EQD2α/β=3Gy, im Falle ungünstiger Organverschiebungen für Blase, Rektum und Darm um 5%, 3% bzw. 2% pro mm Organbewegung ansteigen. ΔD%/mm für andere Richtungen lag in den durchgeführten Simulationen zwischen 1 und 4 %.

Schlussfolgerungen

MRT-basierte Organbewegungssimulation könnte ein wertvolles Instrument zur Robustheitsbewertung von HDR-Brachytherapie-Bestrahlungsplänen bei Gebärmutterhalskrebs darstellen und in zukünftige Studien zur Robustheit der Beladungsstrategie einbezogen werden.

Establishing reliable asynchronous brain-computer interfaces (BCIs) for communication remains a challenging task due due to differences in electroencephalography (EEG) signal characteristics between calibration and online use. In this work, we investigate cue-aligned decoding of movement-related cortical potentials (MRCPs) combined with online retraining in an EEG-based BCI speller. 21 healthy participants completed an offline calibration phase followed by two online sessions with a row-wise scanner speller paradigm. The first online session used the offline calibration data, while the second online session employed a classifier trained on data from the previous online session. By comparing the five best and five worst performers in the initial session, we analysed differences in MRCP characteristics, movement timing, and classifier feature relevance. Our results also indicate that retraining based on the speller substantially improves performance and reduces group differences, suggesting that learning effects, classifier feedback and user engagement may play an important role in MRCP-based BCI control.

Latest developments in the Technical Quality Assurance (TQA) for the Austrian Breast Cancer Screening Programme (BKFP)

Ana Adensamer, Reference Center for the TQA in the BKPF (RZQS), Austrian Agency for Health and Food Safety (AGES), Vienna, Austria, ana.adensamer@ages.at
Susanne Menhart, RZQS, AGES, Vienna, Austria, susanne.menhart@ages.at
Horst Schödl, RZQS, AGES, Vienna, Austria, horst-alexander.schoedl@ages.at
Introduction
Mammography systems from six different manufacturers are used in the BKFP. A minimal quality standard is ensured by means of regular quality checks. The systems are further optimized in cooperation with the respective manufactur-ers in line with the instructions of the RZQS.
Methods
The optimal image parameters are determined for every mammography system type, and then gradually applied to all the other systems of the same type. The outcome is monitored by means of subsequent quality tests. One established tool used is the determination of the threshold thicknesses by means of the CDMAM phantom. The goal is to attain threshold thicknesses below the achievable reference values as determined by the EFOMP group.
Results
Since the start of the optimisation process, a clear improvement in the image quality has been observed and confirmed. As of year-end 2025, only 12% of the mammography systems have a threshold thickness which is beyond the achiev-able value of 1,1 µm for the 0,1 mm diameter gold plate of the CDMAM. Before the optimisation, around 38% of the mammography systems failed to comply with the achievable values.
Conclusion
Further improvement is still possible in the overall quality of the diverse mammography systems used in the BKFP. Op-timisation of the CDMAM results is a good measurable method to determine the image quality of 2D-mammography images. Further optimisations in the future are under development, as is the establishment of similar methods for the Tomosynthesis mode.

Non-stationarity of EEG signals poses a major challenge for motor decoding for brain-computer interface BCI applications, as shifts in feature distributions between source and target domains degrade decoding performance. We propose a conditional domain-adversarial neural network that integrates an EEGNet-based feature extractor with a task classifier and a domain discriminator operating on class-conditioned features to encourage domain-invariant representations. We evaluate the proposed model on a multi-session hand-gesture EEG dataset, observing consistently higher test accuracies with statistically significance compared to standard sLDA and EEGNet baselines. These results demonstrate the effectiveness of domain-adversarial training to achieve more robust BCI decoding.

The evaluation of performance for continuous cursor control brain-computer interfaces (BCIs) is problematic especially in motor-impaired patients. For such patients, a movement trajectory cannot be evaluated with regards to a ground truth, since they oftentimes cannot volitionally move their muscles. Our work proposes the evaluation of such BCIs based on move-and-select tasks in which participants move their cursor towards a target and select the target at the final position. A conditional randomization test to estimate a baseline of random performance based on the observed movement tasks is proposed and its applicability in this context is verified through simulation. The proposed method can aid in the comparability of continuous cursor control BCIs in the future.

Introduction:
A novel iterative reconstruction method with AI-based scatter correction (IRIS) has recently become available on a commercial CBCT-based image guidance system (XVI v5.1, Elekta AB, Sweden). The reconstruction model is currently approved for the pelvic region and can replace conventional Feldkamp-David-Kress (FDK) back-projection.
Methods:
Using an anthropomorphic pelvic phantom (Exactrac pelvis phantom, Brainlab SE, Germany) and three identical XVI-CBCT systems, Hounsfield unit (HU) accuracy and inter-scanner variability were evaluated for the IRIS reconstruction. A CT scan (Siemens Somatom Definition) was used as benchmarking imaging set. To test HU values, spherical regions of interest (ROI) with 1 cm radius were distributed over the scan volume of the phantom (9 in soft tissue, 5 in bone) and averaged grey values in each ROI were calculated. Target and organ structures relevant for prostate cancer treatment were mimicked on the phantom CT. A 10 MV photon volumetric arc treatment plan was generated on the CT and recalculated on the IRIS-CBCT images using the same HU-to-density curve. Dose-volume metrics (D50%, D2%, D98%) for the planning target volume (PTV) were determined on all images.
Results:
The median grey values over all soft tissue ROIs were 36 HU (IQR:70) on IRIS-CBCTs, -38 HU (IQR:293) on FDK-CBCTs and 16 HU (IQR:10) on the planning CT. For bone ROIs the median values were 921/573/774 HU on IRIS/FDK/CT, respectively. Only minor grey value variability between the three IRIS-CBCT systems was observed with median differences for individual ROIs of 13 HU (IQR:14) for soft tissue and 21 HU (IQR:32) for bone. Dose distributions in the PTV calculated on the CT and on all IRIS-CBCTs agreed within 0.6%.
Conclusion:
IRIS reconstruction produces CBCT images of anthropomorphic phantoms with enhanced HU fidelity compared to FDK reconstructions, potentially enabling online dose calculations for adaptive radiotherapy.

Introduction
Cardiovascular diseases are among the leading causes of morbidity and mortality worldwide, highlighting the need for continuous and early detection of pathological cardiac events. Electrocardiography (ECG) as the clinical gold standard is typically limited to short-term and obtrusive measurements. Ballistocardiography (BCG) enables unobtrusive, long-term cardiovascular monitoring using sensors embedded in everyday environments such as bed or chairs. However, clin-ical adoption of BCG remains limited due to strong signal variability, motion artifacts, less standardized acquisition protocols, and limited availability of labelled pathological data. Robust automated anomaly detection methods for real-world BCG signals are therefore still lacking.

Methods
This work proposes a robust AI-based framework for anomaly detection in BCG signals under real-world conditions. The approach relies on unsupervised and self-supervised generative modelling, trained primarily on healthy physiologi-cal data. Anomalies are detected as deviations from learned normal signal representations using different methods to calculate anomaly scores (reconstruction, forecasting, likelihood). The scarcity of pathological BCG recordings is ad-dressed by simulating physiologically plausible anomalies through controlled modifications of waveform morphology and temporal structure of recordings and/or artificially created BCG signals. Transfer learning strategies will be em-ployed to adapt models pretrained on large-scale ECG datasets to the BCG domain. We will leverage shared cardiac physiology while accounting for modality-specific signal characteristics.

Results
At this early stage, no experimental results are available. The project is designed to systematically study the impact of inter-subject variability, motion artifacts, and domain shifts across acquisition settings, explicitly separating physiolo-gy-related anomalies from measurement artifacts. Evaluation strategies focusing on generalization under weakly labelled conditions and clinically meaningful performance metrics are planned.

Conclusion
This project aims to establish a methodological foundation for robust anomaly detection in ballistocardiography. By combining self-supervised representations learning, generative augmentation and transfer learning, it seeks to enable re-liable detection of clinically relevant anomalies in unobtrusive long-term monitoring scenarios.

Introduction
Rapid eye movement (REM) sleep behavior disorder (RBD) is characterized by abnormal muscle activity during REM sleep, commonly referred to as REM sleep without atonia (RWA). RBD is considered an early marker of neurodegener-ative disorders such as Parkinson’s disease. Current approaches for RWA quantification rely primarily on manual scoring according to internationally recommended criteria (SINBAR criteria in 3-second mini-epochs), which are time-consum-ing, prone to subjective interpretation, and require artifacts identification and rejection from RWA scoring. Rule-based automatic implementations still require manual identification of 3-s mini-epochs and artefact correction. Therefore, there is a need for a fully automated and robust method to quantify RWA.

Methods
In this study, machine learning will be investigated as a data-driven approach to implement the internationally recom-mended SINBAR method for RWA scoring in an automated manner. Around 200 polysomnographic recordings from the Center for Sleep Medicine (Department of Neurology, Medical University of Innsbruck), together with the corresponding manual annotations of muscle activity according to the SINBAR criteria, are used to develop, validate and test the algo-rithm. Muscle signals undergo extensive preprocessing, including filtering and downsampling. A convolutional neural network (CNN) is trained to detect RWA (“any” activity in the chin, and “phasic” activity in the arm) on 3-second mini-epochs, according to the SINBAR standards. Starting from a basic CNN architecture, extensions including a muscle baseline and regularization techniques will be explored.

Results
The performance of the CNN-based models will be evaluated on their ability to detect muscle activity during REM sleep in comparison to human annotations. The impact of including baseline information and regulatiozation on model behavior will be analyzed.

Conclusion
This study aims to demonstrate that CNN-based models can automatically detect RWA and, thus, help identifying patients with RBD in an objective and automated manner.

Introduction
Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a leading cause of chronic liver disease and can progress to cirrhosis or hepatocellular carcinoma (HCC). This work focuses on identifying gut-resident and liver-resident microbes that may contribute to liver tumorigenesis. These complex relationships within metabolomic profiles may en-able the discovery of new, noninvasive biomarkers.

Methods
16S rRNA gene–based microbiome profiles from patients with noncirrhotic MASLD (n=39), nonmalignant cirrhosis (n=34), and HCC (n=186) were collected across fecal, blood, and liver-tissue compartments. The dataset was analyzed using linear and nonlinear feature-filtering methods, followed by machine-learning approaches.

Results
Preliminary linear and nonlinear filtering of the dataset revealed no single dominant marker capable of separating the three patient groups, indicating that multi-marker signatures are required. Subsequent machine-learning analyses showed that classification of the three groups is feasible, with the best performance achieved by combining microbi-ome features from blood and liver tissue.

Conclusion
Our results suggest that microbiomes may support biomarker-based classification of noncirrhotic MASLD, nonmalig-nant cirrhosis, and HCC using gradient boosting.

Introduction
Motor imagery (MI)-based brain-computer interfaces (BCI) are a beneficial addition to conventional neurorehabilitation therapies and have been successfully applied to provide functional movement after spinal cord injury and in post-stroke motor training. However, classification of lower-limb MI has been less studied compared to upper extremity motor tasks and studies using lower-limb motor tasks have mostly classified them against a resting state or other body parts. In this study, we investigated classification of two different lower-limb movement tasks from EEG measurements.
Methods
EEG during lower-limb MI was recorded from five healthy participants (2 male, 3 female, 4 at age 25-35, 1 age >75) in one session using a 64-channel EEG-system at 1024Hz sampling rate. Participants performed cue-based imagination of four classes (left/right ankle, left/right legpress-motion) during six runs, yielding 240 trials in total. All processing was performed in Matlab using FieldTrip and EEGLAB toolboxes. Signals were bandpass filtered between 0.5-40Hz, re-referenced to common average reference, and corrected for artifacts using independent component analysis. Pairwise two-class classification was performed to distinguish between movement type (leg vs. ankle on each side) and body sides (left vs. right for each task) using filter bank common spatial patterns linear discriminant analysis (FBCSP-LDA).
Results
Although, not all participants showed clear motor event-related synchronization and desynchronization patterns (ERDS) over the motor cortex, good classification accuracies were achieved for most subjects. Four out of five subjects showed accuracies of over 89% in all four comparisons. For one participant, the accuracies ranged from 64 to 73%.
Conclusion
Investigating not only upper extremity but also lower-limb movement classification is of interest for the application of BCI in neurorehabilitation. The results indicate that lower-limb movements can be distinguished from EEG recordings despite their deeper representation area within the brain, encouraging further investigation into the use of BCIs in lower-limb rehabilitation.

Background
AI has increasingly been integrated into radiation therapy planning to automate tasks such as tumour and organ-at-risk (OAR) segmentation, thereby reducing contouring time. Despite the availability of established performance metrics for AI models, standardized quality assurance (QA) protocols to ensure reproducibility and traceability in clinical settings remain lacking, potentially impacting treatment outcomes and regulatory compliance.

Materials and Methods
Robust QA protocols were developed to assess performance changes and ensure the reliability of TheraPanacea ART-Plan/Annotate, an AI-based tool for automated segmentation of OARs, following its clinical workflow integration at MedAustron. Forty OARs were selected based on an initial evaluation of ART-Plan version 2.1.0. Baseline and tolerance thresholds were established using the dice similarity index (DSI) and dose–volume histogram (DVH) parameters. Automated pipelines and a dedicated graphical user interface (GUI) were also designed for seamless integration into the treatment planning system (TPS) and to generate structured reports for traceability.

Results
Efficient evaluation and documentation within the clinical workflow using this framework, enabled a comparison between ART-Plan v2.1.0 and v2.2.1. The updated model demonstrated (DSI-based): (i) improved performance in 10/40 OARs, (ii) comparable performance in 20/40 OARs, and (iii) reduced performance relative to the previously available model in 10/40 OARs (see left side of table 1, with a tolerance of 0.01±1SD form baseline). For dosimetric evaluation, the unsigned relative differences between baseline and ART-Plan AI-generated contours were analysed using the near-maximum dose indicator D2, expressed as a percentage deviation (D2[ %]) with a tolerance of 1% difference with respect to the baseline (comparison is presented on the right side of table 1.

Conclusion
AI model upgrades should not be adopted blindly; they should undergo appropriate qualification and monitoring protocols, as the claimed improvements were not consistently reflected in the clinical data.

Introduction
Helium ions combine reduced lateral scattering compared to protons with lower fragmentation tail than carbon ions, enabling sharp dose gradients and improved normal tissue sparing. These characteristics make helium ions particularly attractive for anatomically challenging indications requiring high conformality. This work aims to commission a scanned helium pencil beam line and implement and validate a corresponding beam model for clinical treatment planning at MedAustron.

Methods
Synchrotron-based helium ion beams covering energies from 54.6 to 402.8 MeV/u were commissioned. Depth–dose curves were measured, and beam optics (spot size, position, and intraspill stability) were evaluated for different spill lengths (1, 5, and 10 s). The collected data were used to generate a clinical beam model covering the full energy range. A beam model was implemented in the treatment planning system (TPS) (RayStation v2024A) and validated with 2D absolute dose measurements and 3D measurements of cubic spread-out Bragg peak fields using an ionization chamber array. Gamma-index analysis (3%/1.5mm and 5%/1.5mm) and Monte Carlo simulations (GATE/Geant4) were used for benchmarking.

Results
Measured ranges agreed with Monte Carlo simulations within ±0.3 mm. Spot sizes decreased with energy and were independent of spill length, while spot positions remained within ±0.5 mm; intraspill variations were ≤0.2 mm (position) and ≤5.4% (size). TPS-predicted doses agreed within 0.1%. For 3D validations, dose differences were generally within 2%, with larger deviations limited to high-gradient regions and range shifter configurations. Gamma pass rates exceeded 95% for 5%/1.5 mm and 90% for 3%/1.5 mm.

Conclusion
The helium pencil beam line was successfully commissioned and validated. The strong agreement between measurements, TPS calculations, and Monte Carlo simulations demonstrates the robustness and accuracy of the implemented beam model across the clinical energy range. These results establish the physical basis required for routine clinical use and further translational research in helium ion therapy.

Einleitung
Die Jahrestests zur technischen Qualitätssicherung im Brustkrebsfrüherkennungsprogramm werden, von verschiedenen Personen mit verschiedenen Röntgenmultimetern (XMM) durchgeführt. Ungenauigkeiten in der Postionierung, Abdeckungen des Detektors oder die Position der Kompressionsplatte (KP) können das Messergebnis beeinflussen. In dieser Arbeit sollen mögliche Einfluss-faktoren der Messungen von Luftkerma und Halbwertsschichtdicke (HWS) systematisch untersucht werden, um die Messunsicherheit abzuschätzen zu können.
Methoden
Ein X2 (Unfors) XMM wurde auf einem Mammomat 3000 (Siemens) für die Anode/Filterkombinationen Mo/Mo und W/Rh untersucht. Es wurden 4 Einflussfaktoren getestet: 1: Positionierung auf der Brustauflage. Zusätzlich zum Referenzpunkt, 6 cm von der Brustwandseite, zentriert wurden Messungen jeweils 0,5 cm und 1 cm an 4 Positionen um den Referenzpunkt durchgeführt. 2: Ein-fluss der seitlichen Streustrahlung einer PMMA Schablone zur Positionierung. 3: Abdeckung des Bilddetektors durch Stahl-, Aluminium- oder Bleiplatten. 4: Position KP. Dafür wurden Messungen ohne KP und mit der KP im Kontakt mit dem X2 als auch mit 5 cm, 10 cm und 15 cm Abstand gemacht.
Resultate
Sowohl Luftkerma als auch HWS ändern sich um bis zu 3% mit zunehmendem Abstand der KP vom XMM (Luftkerma: W/Rh, 25 kV, HWS: Mo/Mo, 35 kV). Bei der Positionierung um den Refe-renzpunkt zeigen sich Abweichungen von bis zu 2% (Mo/Mo, 28 kV) für die Luftkerma- und bis zu 1% für die HWS Messung (Mo/Mo, 28 kV). Der Einfluss der seitlichen Streustrahlung der PMMA Schablone sowie die Abdeckung des Bilddetektors auf die Luftkerma- und HWS Messung ist < 1%.
Fazit
Verschiedene Einflussfaktoren auf die Messung mit XMM auf Mammographiesystemen wurden getestet. Die Position der KP und die Positionierung auf der Brustauflage liefern die größten Bei-träge. Die Studie wird noch mit weiteren XMMs ergänzt. Ziel ist eine ausführliche Analyse der Messunsicherheit der für den Jahrestest verwendeten XMMs.

Einführung
Seit 2024 wird in der Strahlentherapie Innsbruck ein IQM Detektor für die Prüfung komplexer Bestrahlungspläne (Pre Treatment PlanQA) eingesetzt. Parallel dazu wurde begonnen, das System hinsichtlich seines Potenzials für die geforderten Konstanzprüfungen (MaschinenQA) gemäß ÖNORM S 5290 (1+2) zu evaluieren. Ziel dieser Arbeit ist es, die bisherigen Erfahrungen aus Routine und Testmessungen darzustellen und das Einsatzpotenzial des IQM als ergänzendes Werkzeug in der Konstanzprüfung zu bewerten.
Material und Methoden
Für die Messungen mit dem IQM wurden gemeinsam mit dem Hersteller iRT spezifische Abfolgen von Bestrahlungsfeldern entwickelt, um folgende Qualitätsmerkmale zu überprüfen: Dosis Output, Dosis Output in Abhängigkeit vom Gantrywinkel, Symmetry, Flatness, Linearität der Monitor Units sowie die Proportionalität der Dosisrate. Die Auswertung erfolgt seit Oktober 2024 mit der automatisierten Machine QA Extension von iRT. Zusätzlich wurde zur Bewertung der Positionsgenauigkeit von Leaves und Jaws eine umfangreiche Messreihe mit einem speziell adaptierten Picket Fence Test durchgeführt.
Ergebnisse
Die IQM Messungen zeigen eine hohe Reproduzierbarkeit und eine zuverlässige Erkennung von Abweichungen im Rahmen der oben erwähnten Konstanzprüfungen gemäß ÖNORM 5290. Der rasche Aufbau und die automatisierte Auswertung reduzieren den zeitlichen Aufwand deutlich. Die Ergebnisse des Picket Fence Tests belegen eine hohe Positionsempfindlichkeit von Leafbank (0,3 mm) und Jaws (0,2 mm), was eine Identifikation von Positionsänderungen ermöglicht. Die Integration dieser Methodik in die Maschine QA Extension von iRT ist geplant.
Schlussfolgerung
Der IQM Detektor erweist sich als effizientes und schnell einsatzbereites Werkzeug für ausgewählte Bereiche der Maschinen QA. Die Methode ergänzt etablierte Verfahren, insbesondere für regelmäßige Konstanzprüfungen und die frühzeitige Erkennung von Abweichungen. Das System zeigt somit Potenzial, bestehende QA Prozesse effektiv zu unterstützen und weiterzuentwickeln.

Introduction (14 pt bold)
Surface guided radiation therapy (SGRT) is routinely used for patient positioning and intrafractional motion monitor-ing. In clinical practice, however, surface scanner systems are commonly reduced to rigid transformations or region-of-interest–based metrics, while the full three-dimensional (3D) sur-face information remains largely unused. In parallel, thermal surface information is typically limited to qualitative assessment. This work presents one of the first clinical implementations that exploits the complete 3D surface point cloud together with 3D thermal image data from the Brainlab Ex-acTrac Dynamic (ETD) system to calculate live surface shifts.
Methods (14 pt bold)
Live 3D surface point clouds and co-registered thermal image clouds were continuously acquired from the ETD system during controlled motion experiments and clinical test scenarios. Rigid and non-rigid surface registrations were per-formed using iterative closest point–based algorithms to estimate translational and rotational shifts in real time. Ther-mal surface data were incorporated to assess temperature-dependent surface stability and potential drift effects. Cal-culated shifts were synchronized with known reference motions.
Results (14 pt bold)
The proposed framework enabled real-time extraction and processing of full 3D surface and thermal data without in-terfering with clinical workflows. Calculated surface shifts showed sub-millimeter agreement with reference motions and demonstrated stable performance over extended acquisition times. Thermal data revealed measurable tempera-ture-related surface variations, which could be quantified and separated from true geometric motion. The combined geometric-thermal approach improved robustness of surface registration under changing environmental conditions.
Conclusion (14 pt bold)
This work demonstrates the feasibility of using the complete 3D surface and thermal data provided by the Brainlab ETD system for live motion and shift calculation. Using the full information content of SGRT systems opens new pos-sibilities for advanced motion modeling, drift detection, and future digital-twin–based patient monitoring without addi-tional imaging dose.

Introduction
Magnetorelaxometry imaging (MRXI) allows spatially resolved and quantitative detection of magnetic nanoparticles (MNPs), which is crucial for magnetic hyperthermia therapy monitoring and other biomedical applications. However, in realistic scenarios, reliable quantification remains challenging, as the reconstruction problem is ill-posed because the sensor measurements do not uniquely resolve the voxel-scale MNP distribution. In this work, we aim at improving MRXI imaging by incorporating a-priori knowledge on the MNP distribution.

Methods
A 3D voxelized phantom of size (100×100×50mm³) with a spatial resolution of 5mm was employed to simulate the MRXI experiment. Four capsule regions with a size of 10×10×20mm³ were defined within the phantom, containing iron amounts of 0.2125, 0.425, 0.85, and 1.7 mg per capsule. A single excitation coil and sensor were positioned with a distances of 15mm, and 5.6mm from the phantom respectively. A coil current of 25A generates a magnetic field of ~10mT at the phantom center, inducing nonlinear MNP magnetization. A total of 24 coil–sensor configurations were arranged around the phantom to acquire the measurements. The system matrix defining the spatial sensitivity is used in the forward model to generate relaxation signals. Reconstruction of the MNP distribution was formulated as an inverse problem and solved using Elastic Net regularization with a non-negativity constraint. Spatial masks based on prior knowledge of the capsule locations were applied to restrict the solution to regions of interest. In addition, experimental MRXI measurements were performed using the same geometric phantom and coil–sensor configurations to validate the proposed reconstruction approach.

Results
Both simulated and experimentally measured relaxation amplitudes showed the expected proportional relationship with MNP mass. The reconstructed MNP distributions showed good quantitative agreement with the known capsule locations.

Conclusion
These results highlight that combining multiple measurement configurations with mask-based prior knowledge enables reliable quantitative MNP reconstruction in MRXI under realistic conditions.

Introduction
Single isocenter multiple target radiosurgery demands exceptional geometric accuracy to ensure the accurate high dose delivery, especially off-isocenter. An off-isocenter Winston-Lutz (WL) test is a suitable method to evaluate the geomet-rical accuracy of the linear acclerator (linac). Phantoms with off-center targets are used for these measurements, such as the MultiMet-WL cube (MM-Cube) from SunNuclear. As can be found in literature, the initial MultiMet-WL cube positioning is crucial for the test outcome. Therefore, we performed the test at various setup and repositioning methods to identify a robust and meaningful procedure for our clinical use.

Methods
The off-isocenter WL test was performed with different initial positioning methods of the MM-Cube with regard to the linac MV-isocenter: cross-hair, kV-kV, CBCT, MV-MV and Exac-Trac-Dynamic (ETD). ETD was also used to reposi-tion the MM-Cube at couch angles different from 0° to mimic a real patient-workflow. In doing so, several matching possibilities within ETD were tested. Additionally, to account for a real patient on the couch, tests with weight on the couch were performed.

Results
It was shown that the outcome of the off-isocenter WL test depends highly on the initial setup of the MM-Cube. Excel-lent results are obtained with high precion matching in kV-kV and CBCT setup procedures. Another promisising candi-date is MV-MV imaging, directly using the treatment beam for imaging. Unfortunately initial setup and/or repositioning at extended couch position with ETD does not work as accurately as expected due to limitations of the matching work-flow for the phantom structures.

Conclusion
The off-isocenter WL test was implemented successfully with easy-to-use kV-kV or CBCT initial positioning of the MM-Cube as our method of choice for the clinical routine. Therefore a precisely matched kV-imaging and MV isocen-ter is inevitable, requiring special attention in quality assurance.

Motivation
Die technische Qualitätssicherung im Brustkrebs-Früherkennungsprogramm (koordiniert vom Referenzzentrum in der AGES) wird nach den Europäischen Leitlinien für Mammografie-Screening durchgeführt. In diesen Leitlinien wird emp-fohlen, dass mit den Geräten die im Protokoll angegebenen Wunschwerte („achievable values“) erreicht werden. Bei den Mammographie-Geräten eines Herstellers wurde 2024 nach Absprache mit dem Referenzzentrum die Dosis an-gepasst, um die Bildgüte gemäß diesen Leitlinien zu verbessern. Die beiden Mammographie-Geräte, die im Universitätsklinikum AKH Wien aufgestellt sind, wurden im Oktober 2024 dosismäßig angepasst. Die Abteilung Medizinphysik begleitete diese Dosisanhebung mit Messungen und präsentierte die Ergebnisse mit einem Poster bei der ÖGMP-Jahrestagung 2025. Diese erste Dosisanpassung erreichte nicht den erwarteten Grad an Verbesserung der Bildqualität. Deshalb wurden im Mai 2025 verfeinerte Einstellungen an beiden Geräten im AKH Wien vorgenommen.

Material & Methoden
Erneut begleitete die Abteilung Medizinphysik diese Dosisanhebung mit Phantommessungen, um festzustellen, ob die Verbesserung der Bildqualität erreicht wurde. Es wurden Aufnahmen mit dem CDMAM-Phantom gemäß den relevanten Prüfpunkten nach dem EUREF-Ö-Protokoll durchgeführt und mit den Ergebnissen vor der ursprünglichen Dosisanhebung verglichen (2D-Modus und Tomosynthese). Außerdem bewerteten erfahrene Radiolog*innen die Aufnahmen von ausgesuchten wiederkehrenden Patientinnen hin-sichtlich einer Verbesserung der Bildqualität für die Befundung. Die Auswertung der CDMAM-Aufnahmen erfolgte automatisiert mit der im Referenzzentrum verwendeten Software. Die Auswirkungen der Dosisanhebung auf die verabreichte Organdosis (ESE und AGD) wurde anhand der in das Dosis-managementsystem übertragenen Daten untersucht.

Ergebnisse
Die Ergebnisse der Auswirkungen der modifizierten Anhebung der Grundeinstellungen der Mammographie-Geräte auf die Organdosis und die Bildqualität werden präsentiert und diskutiert.

Schlussfolgerungen
Als Schlussfolgerung werden wir erläutern, ob der mit der Dosisanhebung unweigerlich einhergehende Anstieg der durch-schnittlich verabreichten Organdosen durch die Verbesserung in der Bildqualität der Befundung gerechtfertigt werden kann.

Einleitung
Die Photon-Counting-Computertomographie (PCCT) stellt eine innovative Weiterentwicklung der konven-tionellen Computertomographie dar. Durch die direkte Detektion einzelner Photonen ermöglicht sie eine verbesserte Bildqualität bei potenziell reduzierter Strahlendosis, was insbesondere für pädiatrische Patientinnen und Patienten von hoher klinischer Relevanz ist. Ziel dieser Studie ist die Optimierung pädiatrischer Kopf-CT-Protokolle am PCCT im Vergleich zu konventionellen Energy-Integrating-Detector-CT-Systemen (EID-CT) am Allgemeinen Krankenhaus (AKH) in Wien.

Methoden
Die Untersuchung umfasst sowohl quantitative als auch qualitative Analysen. Zu den quantitativen Parametern zählen die Signal-to-Noise-Ratio (SNR) sowie dosimetrische Messwerte. Die qualitative Bildbewertung erfolgt durch erfahrene Radiologinnen und Radiologen. Basierend auf Erkenntnissen aus Vorstudien und Phanto-muntersuchungen werden zentrale Scanparameter, darunter Bildqualitätslevel, Röhrenspannung und Rekon-struktionsalgorithmen, systematisch variiert, um eine Reduktion der Strahlenexposition bei erhaltener diagnos-tischer Bildqualität zu erreichen.

Ergebnisse
Die Ergebnisse befinden sich derzeit in der Auswertung. Basierend auf bisherigen Studien ist zu erwarten, dass PCCT-Systeme im pädiatrischen Kopfbereich eine signifikante Verbesserung der SNR bei gleichzeitiger Dosis-reduktion im Vergleich zu EID-CT ermöglichen. Insbesondere Phantomstudien deuten darauf hin, dass bei ver-gleichbarem Bildqualitätsniveau niedrigere Dosiswerte erzielt werden können, vor allem bei altersabhängigen Protokollanpassungen.

Schlussfolgerung
Die Studie zielt darauf ab, altersgerechte und strahlenschutzoptimierte PCCT-Protokolle für pädiatrische Kop-funtersuchungen zu entwickeln. Die erwarteten Ergebnisse sollen die klinische Implementierung der PCCT-Technologie unterstützen und einen wichtigen Beitrag zur evidenzbasierten Verbesserung der Bildqualität bei minimaler Strahlenbelastung im Kindesalter leisten.

Introduction
Reliable detection of the acoustic stapedius reflex is essential for cochlear implant fitting, yet in routine clinical practice it remains largely a manual procedure performed by expert audiologists. This process is time-consuming, subjective and particularly challenging in pediatric patients. Although automated detection methods have been proposed, their dependence on fully annotated datasets has limited their scalability and clinical adoption. Here, we investigate whether semi-supervised learning can reduce the need for expert annotation while preserving clinically relevant performance in stapedius reflex detection.

Methods
We analyzed 4,167 stapedius reflex measurements from adult and adolescent cochlear implant users and evaluated two semi-supervised learning strategies. In a wrapper-based pseudo-labeling approach, classifiers were trained on only 10% of the labeled data and then used to infer labels for the remaining measurements before retraining on the combined dataset. In a second approach, self-training was applied, in which pseudo-labels were iteratively updated based on prediction confidence. Multiple conventional machine learning classifiers were assessed. Models were trained on adult data and evaluated on an independent adolescent cohort to examine their generalizability.

Results
The wrapper-based approach achieved a maximum test accuracy of 90.0% on the independent adolescent test set, indicating that high classification performance can be obtained with minimal expert annotation. Self-training reached a peak accuracy of 88.2% while enabling a fully automated refinement process. Models trained on adult data achieved high performance when applied to adolescent measurements, indicating that cross-age application is feasible.

Conclusion
These results show that semi-supervised learning can substantially reduce expert labeling requirements without compromising classification performance. This approach offers a practical route toward more scalable, efficient and objective cochlear implant fitting and may be particularly valuable in adolescent audiology, where expert time is limited and measurements are difficult to obtain.

Introduction
Magnetic nanoparticles (MNP) are promising constituents for various biomedical applications, such as magnetic drug targeting and magnetic hyperthermia. Preclinical phantom studies are typically performed with immobilized MNP to mimic their binding to tissue and to work with more realistic magnetic conditions. However, most studies use only one reference sample. Until now, no analysis has been carried out on how reproducible the magnetic properties of such samples are in dependence on the immobilization method.
Methods
Perimag plain MNP (micromod Partikeltechnologie GmbH, Germany) were immobilized with five different immobilization methods, namely crystallization by freeze drying and gypsum addition, polymerization in a polyacrylamide matrix, and drying on filter paper and cotton wool. Five replicas were prepared for each immobilization method. Magnetic particle spectroscopy (MPS) and magnetorelaxomery (MRX) were used to assess and compare the magnetic properties in form of normalized third-harmonic amplitude and harmonic ratio for MPS, and relaxation amplitude and relaxation time extracted from MRX measurements. For each parameter and immobilization method, the mean value, standard deviation and coefficient of variation were calculated.
Results
For all parameters, immobilization methods based on crystallization (freeze drying, gypsum) and polymerization (polyacrylamide) showed lower variability than evaporation based methods (filter paper, cotton). An explanation could be the less defined spatial arrangement of MNP and an increased probability for particle interactions during the evaporation. In addition to the underlying evaporation mechanism as the main factor, the complexity and number of preparation steps affected the parameter variability. Overall, MNP amount dependent parameters varied more than MNP amount independent parameters.
Conclusion
The immobilization procedure has significant influence on the magnetic properties of MNP. Consequently, we recommend the use of immobilization methods based on controlled immobilization mechanisms with few preparation steps. The production of replicas is mandatory if MNP quantity dependent magnetic properties shall be accurately investigated.

Background: Risk stratification after ischemic stroke (IS) or transient ischemic attack (TIA) remains challenging due to heterogeneous patient profiles and complex interactions between clinical, physiological, and imaging-derived parameters. While structured care programs such as STROKE-CARD care improve outcomes at the population level, there is a need for data-driven methods that enable individualized risk estimation and decision support.

Objective: The SPRINT project aims to design and implement an explainable artificial intelligence (AI) framework for predicting (i) major cardiovascular events and (ii) functional outcome at 12 months after IS or TIA. The project focuses on robust data engineering, model development, and clinical integration.

Methods: SPRINT leverages a structured longitudinal dataset of approximately 1,700 IS and TIA patients collected within the STROKE-CARD care program at the Medical University of Innsbruck. The project emphasizes reproducible data preprocessing pipelines, feature harmonization, and temporal alignment of follow-up information. Multiple modeling paradigms will be explored, including gradient boosting machines, random survival forests, and deep learning architectures optimized for tabular and multimodal data. Model development prioritizes stability under limited event rates, external validation, and interpretability through feature importance and attribution methods. A modular software architecture will enable seamless evaluation, comparison, and deployment of models.

Expected impact: SPRINT is expected to deliver a scalable and transparent AI-based risk prediction framework that can be integrated into clinical research workflows. By bridging biomedical engineering methodology and clinical stroke care, the project aims to facilitate personalized secondary prevention strategies and serve as a blueprint for AI-enabled outcome prediction in cardiovascular medicine.

Introduction
Pretreatment plan quality assurance (QA) is an essential component of modern radiotherapy, particularly for highly modulated IMRT and VMAT techniques. Conventional pretreatment plan QA systems, such as phantom-based detector arrays, assess delivery accuracy using dose comparison metrics like the gamma index. Transmission detector systems offer an alternative approach by monitoring beam fluence during delivery. This work reports the first clinical implementation in Austria of the IQM transmission detector and its validation as a standalone pretreatment plan QA system. Simultaneous measurements with the established Delta⁴ system were performed to assess agreement between both approaches.

Methods
Clinical IMRT and VMAT treatment plans were selected for pretreatment plan QA. Each plan was delivered once, while measurements were acquired simultaneously using the IQM transmission detector and the Delta⁴ phantom. Delta⁴ measurements were evaluated using standard gamma index criteria, whereas IQM data were analyzed using plan-specific signal deviation metrics. Simultaneous measurements were used exclusively for comparative validation. Correlations between Delta⁴ gamma pass rates and IQM deviation metrics were investigated to assess agreement.

Results
Simultaneous measurements enabled direct comparison of both QA systems under identical delivery conditions. Delta⁴ measurements showed clinically acceptable gamma pass rates, while IQM signals demonstrated stable and reproducible plan-specific behavior. A correspondence between Delta⁴ pass rates and IQM deviation metrics was observed across evaluated plans. Despite fundamentally different measurement principles, both systems showed comparable plan acceptance trends.

Conclusion
The analysis demonstrated that IQM provides pretreatment plan QA results consistent with established phantom-based gamma evaluation. Agreement between Delta⁴ pass rates and IQM signal deviation metrics supports the use of IQM as a reliable standalone pretreatment plan QA system. Following validation, IQM enables an efficient and workflow-friendly QA approach without phantom-based measurements.

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that has been used successfully in treating psychiatric and neurological disorders. By inducing focal electric fields (E-fields) in the brain, TMS can modulate neural activity in targeted brain regions. However, small deviations in coil placement, e.g. during extended stimulation sessions, can substantially influence the distribution and magnitude of the induced cortical E-field. This creates a source of considerable dose variability and thus may result in reduced clinical outcomes. To address this dosimetric variability, we analysed typical motion patterns during TMS treatments and their impact on delivered E-field. In addition, we developed a framework which allows for real time compensation of E-field variations caused by motion.

Motion tracking data of 200 individual TMS treatment sessions was analysed in terms of dominant axes of movement and corresponding E-field variability. E-field simulations were calculated based on individual-specific MRI scans and tissue segmentations using finite element modelling implemented in the SimNIBS toolbox. To reduce motion-induced variability, we developed a real-time compensation mechanism, which adjusts stimulator output continuously using an interpolation algorithm based on precomputed E-field simulations.

E-field variability during clinical sessions was primarily driven by displacement along the scalp-normal. Importantly, this motion could be successfully compensated by the proposed intensity-adjustment method. The developed method is associated with minimal additional computation time, creating an important tool for research as well as clinical applications.

Within this work, we present a quantitative characterization of motion-induced dose variability in TMS treatments and demonstrate a practical approach for real-time compensation. Stabilizing the induced E-field will contribute to higher reliability in TMS treatments, especially in patients prone to movement, potentially enhancing clinical outcomes in non-invasive brain stimulation.This framework allows for adaptive TMS dosing with minimum computational effort, and thus simple integration in clinical workflows.

The inter-individual variation of head tissue conductivities and especially of the skull conductivity leads to a significant uncertainty in the results of EEG/MEG source analysis. To reduce this uncertainty, individual skull conductivity estimation based on combined EEG/MEG measurements of evoked brain activity has been proposed. However, the accuracy of source analysis based on estimated skull conductivities and how much the skull conductivity estimate is influenced by uncertainties of other head tissue conductivities has not been investigated in detail so far.
We simulated EEG and MEG measurements of evoked brain activity (somatosensory, visual) and of interictal epileptic discharges (IED) for randomly assigned tissue conductivities and performed skull conductivity estimation based on the simulated evoked brain activity. Following, we performed EEG, MEG, and combined EEG/MEG source analysis of the simulated IEDs with and without skull conductivity estimation.
We find that EEG/MEG skull conductivity estimation is more accurate than EEG skull conductivity estimation, especially when considering realistic noise levels. Both EEG and EEG/MEG skull conductivity estimation clearly improve source analysis accuracy for EEG and combined EEG/MEG source analysis, reducing the uncertainty of the source localization from a few centimeters to less than one centimeter for most sources. However, we find that the effect of the conductivity estimation is less pronounced for sources at the base of the brain.
We conclude that EEG and EEG/MEG conductivity estimation exploiting evoked potentials and fields has the potential to become a valuable tool to reduce uncertainty in source analysis, especially also of IEDs, while it only requires little additional measurement effort in practice.

Establishing a brain-computer interface (BCI) system for communication in patients and especially at their home is a non-trivial task. The Graz BCI has a long history on the development of a variety of BCI systems. In this work, we highlight the history of BCIs for communication and draw the line from our first applications to the current project INTRECOM, which involves implanting a BCI in a patient with amyotrophic lateral sclerosis (ALS). Besides the development of paradigms and pipelines, we also discuss the steps necessary for such a clinical study.

Kathrin Sterk, Institute of Neural Engineering, Graz University of Technology, Graz, Austria
Thomas Mueck, Sigmund Freud Private University, Vienna, Austria
Steffen Franz, AUVA Rehabiliation Center Weißer Hof, Klosterneuburg, Austria
Gerfried Peternell, AUVA Rehabiliation Clinic Tobelbad, Austria
Kyriaki Kostoglou, Gernot R. Müller-Putz, Institute of Neural Engineering, Graz University of Technology, Graz, Austria, gernot.mueller@tugraz.at

Introduction
NeuroGrasp aims to develop an AI-powered, non-invasive brain–computer interface (BCI) for individuals with upper-limb amputation or spinal cord injury. By addressing key challenges of current electroencephalography (EEG)-based BCIs, such as difficulties in the discrimination of hand movements, the need for extensive user training, and limited real-world usability, the project focuses on enabling intuitive, real-time control of neuroprosthetic devices with in-creased degrees of freedom. Using advanced machine learning and deep learning methods, NeuroGrasp seeks to de-code user intentions more accurately, allowing more natural and functional prosthetic control.

Methods
The proposed BCI framework consists of an offline calibration phase and an online control phase. In the offline phase, a large-scale EEG dataset of motor-related hand and arm activity, acquired from healthy participants and collected at the institute over several years, enables the application of modern deep learning methods to automatically learn dis-criminative spatial, spectral, and temporal motor-related brain activity patterns. These data are used to train a general-ized movement-decoding model. EEG data newly recorded from motor-impaired users in collaboration with the AUVA Rehabilitation Clinic Tobelbad and the AUVA Rehabilitation Center Weißer Hof are then used for model re-finement and individualization via transfer learning. In the online phase, the adapted models will be employed to de-code user intentions in real time, enabling intuitive (neuro)prosthetic control with increased degrees of freedom.

Conclusion
NeuroGrasp brings together long-term EEG research and clinical recordings to improve non-invasive BCI systems, establishing a proof of concept for prosthetic control through individualized model adaptation.

Introduction
Human motor activity has been studied in various ways both at the brain level and at neuromuscular level in e.g., the extremities. However, there may be many hidden processes along the pathways from the brain to the extremities and vice versa. Especially in the upper extremities, we are highly interested in studying the spinal activity to learn about corticospinal processing in both, afferent and efferent pathways.

Methods
From 2024 to 2025, we established the Graz Brain-Spine Lab. It investigates the neurophysiology of the spinal cord in healthy, as well as in paralyzed people. Furthermore, it develops imaging methods based on non-invasive measurements and connects findings directly with brain activity. The lab is equipped with high resolution EEG amplifiers as well as a stimulation unit for sensory stimulation of the nervous system. Furthermore, several devices are available for functional electrical stimulation aimed at restoring movement in paralyzed people. Additionally, we have easy access to a 3T MRI scanner which enables us to study brain and spine anatomy and combine this information with electrophysiological measurements.

Results
So far, the lab has been equipped and first studies have taken place. To date, we were able to study the initial components of the cervical electrospinogram (ESG) after sensory stimulation. These evoked peaks are at 9, 13 and 22 ms af-ter the stimulus reflecting successive stages of afferent and corticospinal processing. Furthermore, we are working in a forward model of the head-brain-cervial-spine area to allow inverse functional spinal mapping from non-invasive high-density ESG recordings.
Conclusion
After two years of setup and first initial studies, we are able to present the first results on ESG recordings and the corresponding measurement and analysis methods. From now on, we are able to start studying this promising new field and to research the under-investigated part of cortico-spinal processing.

Ziel
Ziel dieses Beitrags ist die Darstellung der Implementierung eines Ethos™-Strahlentherapiesystems (Varian) mit HyperSight™-Bildgebung und Identify™-Oberflächenüberwachung. Neben der Projekt-Timeline von der Planung bis zur klinischen Anwendung werden insbesondere die medizinphysikalischen Herausforderungen beleuchtet, die sich aus den konzeptionellen Eigenschaften des Systems sowie aus dessen Integration in die vorhandene technische Infrastruktur ergeben.
Material & Methoden
Nach Entscheidungsfindung und Bestellung erfolgten Vorbereitung, Installation und Abnahme des Systems. Das Ethos™-System weist mehrere grundlegende Besonderheiten auf, darunter ein Bore-Design, ein Dual-Stack-MLC, nur eine Photonenenergie (X6FFF) sowie das Fehlen von Kollimatorblenden, SSD-Anzeige und Lichtfeld, die angepasste Messstrategien erforderten.
Die Abnahme umfasste Messungen der Beamdaten, Abnahmeprüfung des Planungssystems gemäß ÖNORM 5295-1, Konstanzprüfungen gemäß ÖNORM 5290 und ÖNORM 5295-2 sowie End-to-End-Tests. Zur Aufnahme der Kalibrierkurven der HyperSight™-Bildgebung wurden Messungen mit dem Advanced Electron Density Phantom (CIRS) durchgeführt. Ergänzend wurden DoseCHECK bzw. AdaptCHECK (Sun Nuclear) zur Verifikation von IGRT- und oART-Patientenplänen eingeführt. SunCHECK Machine wurde zur Dokumentation der Konstanzprüfungen des Beschleunigers und des Planungssystems implementiert.
Im Rahmen der sogenannten Aria-Koexistenz wurde das Zusammenspiel der Planungssysteme Ethos™ und Eclipse™ evaluiert, wobei Einschränkungen in der Interoperabilität berücksichtigt werden mussten. Nach Schulungen und begleitetem Go-Live begann der klinische Betrieb.
Ergebnisse
Alle Abnahme- und QA-Messungen erfüllten die normativen Anforderungen. Die ersten Patient:innen wurden erfolgreich klinisch behandelt, wobei etwa 75 % der Behandlungszeit für IGRT-Patient:innen und 25 % für oART-Patient:innen genutzt wurden. In der initialen klinischen Phase erfolgte die patientenspezifische Qualitätssicherung mittels ArcCHECK für die ersten Patient:innen, alle Ergebnisse waren innerhalb der klinikinternen Toleranzen. Die QA für die online neu berechneten Bestrahlungspläne erfolgt mit AdaptCHECK (Sun Nuclear).
Schlussfolgerungen
Die Implementierung des Ethos™-Systems zeigte, dass das zugrunde liegende Systemkonzept angepasste Mess- und QA-Strategien erfordert. Darüber hinaus stellen die Aria-Koexistenz, insbesondere die eingeschränkte Interoperabilität zwischen Ethos™ und Eclipse™ relevante organisatorische und medizinphysikalische Herausforderungen im klinischen Betrieb dar.

Introduction
The treatment of head and neck squamous cell carcinoma (HNSCC) results in long-term adverse events (AEs). Previous clinical deintensification trials failed to improve AEs without compromising efficacy. However, novel imaging modalities, biomarkers and adaptive treatment strategies offer new opportunities.
This prospective study aims to evaluate the clinical benefit of MRI-based mid-treatment adaptation by assessing dose differences to organs of interest (OOIs).

Methods
The study includes patients with localized primary HNSCC (1976/2024). Participants underwent initial CT (CT_ini) (Somatom Definition AS, Siemens Healthineers) and MRI (1.5T Ingenia Ambition X, Philips Healthcare) followed by MRI after 30-40Gy. Synthetic CTs (sCTs), generated using the dedicated MRCAT sequence, served as planning images for the adaptive phase (sCT_ada). Primary tumor (GTV_T), nodal volumes (GTV_N), and high-dose PTVs were delineated utilizing MRI at both time points. Volume shrinkage was calculated as relative percentage change. Adaptive plans were optimized on sCT_ada using identical planning settings as the initial plans. Two dose accumulation strategies applying deformable image registration (ANACONDA, RaySearch) were performed on CT_ini: accDose_ini combining the initial plan with a recomputed dose on sCT_ada; and accDose_ada combining the initial plan with a target-driven reoptimized plan on sCT_ada. Mean, and maximum relative OOIs dose differences were analyzed.

Results
Six of 30 enrolled patients were included in this preliminary analysis. At the adaptation time
point, significant median shrinkage of 79% (IQR 43%) for GTV_T, 53% (IQR 22%) for GTV_N, and 48% (IQR 21%) for PTV was observed. While target coverage was maintained, all evaluated OOIs showed reduced dose-volume parameters. The median relative difference across OOIs was 2.7% (IQR 1.2%). Notably, the parotid gland showed a relative dose reduction up to 15.7%.

Conclusion
MR-based adaptation demonstrated dose reduction to adjacent OOIs, suggesting its potential to minimize AEs in HNSCC. Ongoing analysis includes the full cohort and focuses on organ/AE-driven optimization.

Introduction
In real-time image-guided lung cancer radiotherapy, tumor localization on stereoscopic X-ray images remains challenging, particularly for small lesions. We investigated a novel anatomical surrogate („Correlation Object“), formed by the gross tumor volume (GTV) and surrounding bronchial structures moving similarly to the GTV. Our aim was to assess the impact of this surrogate on the registration accuracy.
Methods
Four-dimensional computed tomography scans (4DCTs) of 59 T1-staged lung cancer patients were retrospectively collected (IRB:1359/2025). Stereoscopic X-rays were simulated for inspiration and expiration CT phases using standard clinical lung imaging settings of an ExacTrac Dynamic System (BrainLab SE, Germany).
For these phases, the motion amplitude of each voxel in the ipsilateral lung contour was estimated via deformable image registration between the 4DCT phases. The Correlation Object was defined using Brainlab's pilot software Motion Analysis by grouping tissue moving similarly to the GTV within a tolerance threshold. The size of this Correlation Object depended on this threshold, ranging from 0mm (GTV-only) to the maximum, covering all bronchial structures. Digitally reconstructed radiographs of the Correlation Objects were 6D-registered to the simulated X-rays of the same 4DCT phase. Registration accuracy was quantified by the absolute distance between original and registered GTV center-of-mass.
Results
At 0mm tolerance threshold (GTV-only), median absolute registration errors (IQR) over all patients were 3.4(1.4-7.0)mm for inspiration and 2.8(1.5-7.2)mm for expiration. Increasing the tolerance threshold to 5mm expanded the registration object’s size, such that the bronchial structures included in the Correlation Object covered major parts of the lung. This expansion resulted in decreased median absolute registration errors to 0.3(0.2-0.3)mm for inspiration and 0.2(0.1-0.3)mm for expiration.
Conclusion
Correlation Object based registration yielded improved accuracy compared to GTV-only registration. Results showed the approach’s lesion localization potential. Further investigation is required to translate these findings to more clinically realistic settings and finding optimal tolerance thresholds.

Das medizinische Leistungsspektrum befindet sich in einem raschen und kontinuierlichen Wandel, dessen sichere und effiziente Umsetzung die zentrale Einbindung von Medizinphysikerinnen erfordert. Für den Bereich ionisierender Strahlung sind aktuell nur minimale Erfordernisse an Medizinphysikerinnen sowie deren Tätigkeitsbereiche in der Medizinischen Strahlenschutzverordnung geregelt. Technologische Innovationen – etwa KI-basierte Anwendungen wie automatische Konturierungsalgorithmen in der Radioonkologie – erweitern das Einsatzspektrum der Medizinphysik erheblich und stellen zugleich neue Anforderungen an Qualitätssicherung und Validierung. Parallel dazu führen Automatisierung und Standardisierung zu einer Reduktion des Zeitaufwands bestimmter Tätigkeiten.

Im Jahr 2018 veröffentlichte die Österreichische Gesellschaft für Medizinische Physik (ÖGMP) eine Personalbedarfsempfehlung für die Strahlentherapie/Radioonkologie, die nun angesichts der fortschreitenden Entwicklungen – insbesondere in der Präzisionsradiotherapie – einer Aktualisierung bedurfte. Darüber hinaus wurden erstmals Empfehlungen für die Radiologie sowie die Nuklearmedizin, einschließlich Hybridbildgebung, erarbeitet. Im Rahmen dieser Aktualisierung wurden zudem europäische und internationale Modelle (u. a. der DGMP, EFOMP, EU, IAEA) eingehend evaluiert, validiert und im Hinblick auf nationale Rahmenbedingungen miteinander verglichen.

Für den Personalbedarf von Medizinphysiker:innen wurden zusätzlich Anwendungen nichtionisierender Strahlung, Beratungstätigkeiten, Ausbildung sowie potenzielle Synergieeffekte zentraler und überregionaler Strukturen ergänzt.

Das vorgestellte Modell basiert auf einer Excel-basierten Berechnung, die den Bedarf an medizinphysikalischen Vollzeitäquivalenten unter Berücksichtigung abteilungsspezifischer Faktoren ermittelt.

Einleitung
Cochlea Implantate (CIs) werden heute weltweit zur Versorgung von Patienten mit hochgradiger, an Taubheit grenzender Schwerhörigkeit eingesetzt, die nicht von konventionellen Hörgeräten profitieren können. Neben der korrekten Indikationsstellung und Implantation ist eine individuelle Anpassung des Sprachprozessors für den Erfolg mit CI entscheidend. Eine prinzipielle Herausforderung bei der Anpassung besteht darin, dass die elektrische Stimulation des Hörnervs durch das CI für den Audiologen nicht hörbar und der Audiologe daher auf die subjektive Rückmeldung des Patienten angewiesen ist.
Methoden
Bei erwachsenen CI-Trägern werden zur Anpassung meist psychoakustische Verfahren eingesetzt, um den „elektrischen Dynamikbereich“ zwischen minimal wahrnehmbarer und maximal angenehm empfundener Stimulation zu bestimmen. Bei Säuglingen, Kleinkindern und nicht kooperationsfähigen Patienten sind objektive Methoden, bei denen physiologische Vorgänge entlang der Hörbahn durch Messungen nachgewiesen werden, erforderlich. Neben elektrisch evozierten Potentialen (eCAP, eBERA etc.) spielt insbesondere der Nachweis des durch das CI ausgelösten Stapediusreflexes eine zentrale Rolle.
Bereits in der Pionierphase der CI-Versorgung wurde an der Innsbrucker Klinik untersucht, ob der über den Hirnstamm verlaufende Reflexbogen bei tauben Patienten funktionsfähig ist und ob ein Zusammenhang zwischen Stimulationsstärke an der Reflexschwelle und der Lautheitswahrnehmung besteht. Der Stapediusreflex wurde dabei mittels Messung der akustischen Impedanz nachgewiesen.
Ergebnisse
Die Untersuchungen an erfahrenen erwachsenen CI-Trägern zeigten, dass der Reflexbogen in der Regel intakt ist und eine hohe Korrelation zwischen der Stapediusreflexschwelle (ESRT) und der maximal angenehm empfundenen Lautheit (MCL) besteht. Eine auf ESRT-Werten basierende Anpassung des Sprachprozessors führte zudem zu gutem Sprachverstehen.
Diskussion
Auf Basis dieser Erkenntnisse wurde ein klinisch einsetzbares Messsystem entwickelt, das die Reflexauslösung in Echtzeit während der CI-Anpassung darstellt. Das ESRT-Verfahren hat sich insbesondere bei Kindern und nicht kooperationsfähigen Patienten bewährt, sofern Mittelohr und Reflexbogen intakt sind.
Zusammenfassung
Mit der Entwicklung des ESRT-Verfahrens steht heute eine Methode zur objektiven Anpassung von Cochlea Implantaten zur Verfügung, die auch international in etlichen Zentren erfolgreich angewandt wird.

Ziel: Die Pulsphasendauer ist eine von vielen Größen, die die Hörwahrnehmung via Cochleaimplantat maßgeblich beeinflussen. Ladungsäquivalente Stimulationspulse werden mit steigender Phasendauer als weniger laut wahrgenommen. Das Ausmaß dieser phasendauerinduzierten Lautheitsverluste ist individuell sehr unterschiedlich und kann mittels verschiedener subjektiver und objektiver Methoden festgestellt werden. Hier soll eine subjektive Methode vorgestellt werden, mit der die Lautheitsverluste im klinischen Alltag ohne größeren Aufwand bestimmt werden können.

Material und Methoden: Bei fünf Teilnehmer:innen (sieben Ohren), die mit einem Cochleaimplantat der Firma MED-EL versorgt sind, wurden auf Basis des individuellen Alltagsprogrammes drei Programme mit fixen Phasendauern von 50, 100 und 150 µs erstellt. Sämtliche Signalvorverarbeitungsalgorithmen wurden deaktiviert. Mit allen drei Programmen wurde jeweils eine Kategoriale Lautheitsskalierung bei den Frequenzen 250Hz, 1kHz und 4kHz durchgeführt und auf Basis der Messergebnisse die phasendauerinduzierten Lautheitsverluste bestimmt.

Ergebnisse: Das Messprozedere konnte bei allen Teilnehmer:innen problemlos durchgeführt werden. Die Lautheitswachstumsfunktion bleibt für alle Teilnehmer:innen und Frequenzen entweder annähernd konstant oder verschiebt sich mit steigender Phasendauer hin zu geringerer Lautheit. Es zeigt sich dabei kein Hinweis auf einen Zusammenhang zwischen Stimulationsfrequenz und Ausmaß der Lautheitsverluste.

Schlussfolgerungen: Die vorgestellte Methode stellt ein geeignetes Mittel zur Bestimmung von phasendauerinduzierten Lautheitsverlusten im klinischen Alltag dar. Ein optimiertes Messprozedere würde es potenziell erlauben, die Lautheitsverluste für die gezielte Deaktivierung von Stimulationskanälen heranzuziehen, um Klangerlebnis und Sprachverstehen zu optimieren. Die Ergebnisse zeigen, wie wichtig es ist, die Phasendauer im Blick zu behalten, insbesondere bei steigenden Elektrodenimpedanzen.

Introduction
Previous studies have shown that the sound localization ability of users of a cochlear implant (CI) in combination with a conventional hearing aid (HA) on the opposite side (bimodal users) improves when the constant interaural time delay caused by the different devices and stimulation sites is minimized using the same delay across frequency [1,2]. However, excitation propagation in the cochlea is actually frequency-dependent and increases at low frequencies.
Methods
In our current study, we use frequency-specific delay values for each CI electrode depending on their position in the cochlea.
Results
In over 50% of the included bimodal users, frequency-specific delays led to a further improvement in sound localization (RMS error and signed bias).
Conclusions
Frequency-specific delay of CI stimulation to improve temporal synchronization of the modalities is a promising approach to further improve sound localization in bimodal users.

References:
[1] Angermeier, Hemmert, and Zirn (2023). Clinical Feasibility and Familiarization Effects of Device Delay Mismatch Compensation in Bimodal CI/HA Users. Trends in Hearing, 27, https://doi.org/10.1177/23312165231171987
[2] Felsheim, Hochmuth, Kleinow, Radeloff, and Dietz (2025). Bimodal Cochlear Implants: Measurement of the Localization Performance as a Function of Device Latency Difference. Trends in Hearing. https://doi.org/10.1177/23312165251396658

Einleitung
Das menschliche Gehör kann Zeitunterschiede im Bereich von Mikrosekunden zwischen den akustischen Signalen, die von beiden Ohren aufgenommen werden, erkennen. Dies ist insbesondere für die Ortung von Schallquellen im Raum erforderlich. Auch Patienten die beidseits mit Cochlea Implantaten versorgt sind, welche die neuralen Strukturen direkt elektrisch stimulieren, können ein räumliches Hören entwickeln. Bei solchen Patienten mit künstlichen Hörprothesen kann die zeitliche Synchronisation zwischen der Stimulation an beiden Cochlea Implantaten beeinflusst werden. Daraus ergibt sich eine Möglichkeit die Grundlagen der Schalllokalisation bei diesen Patienten zu studieren. In der vorliegenden Studie wurde bei diesen Patienten die Stimulation an einem ihrer Implantate etwas verzögert und untersucht ob und wie sich das auf die Schalllokalisationsfähigkeit auswirkt.
Methoden
Die Studiengruppe umfasste 11 Probanden, welche beidseits mit Cochlea Implantaten der Fa. MedEl versorgt waren. Die Testungen zur Schalllokalisation wurden in einem reflexionsfreien Raum (Camera Silens) durchgeführt, wobei sich der Restgeräuschpegel in diesem Raum unterhalb der menschlichen Hörschwelle befand. Vor dem Probanden war ein Ring mit 7 Lautsprechern montiert, worüber die Stimuli randomisiert dargeboten wurden. Die Schalllokalisationstests wurden für 4 verschiedene Bedingungen durchgeführt, insbesondere wurden die Signale am rechten Sprachprozessor um 0, 4, 7 und 10ms verzögert. In unverzögerter Bedingung erreichten die Probanden einen Winkelfehler von 29°, welcher bei aktivierter Signalverzögerung von 10ms auf 45° anstieg. The Schalllokalisationsbias war gering in unverzögereter Bedingung, und zwar 6°, und ist auf 20° angestiegen für eine Signalverzögerung von 10ms.
Schlussfolgerung
Die Verzögerung des Signals an nur einem Hörimplantate bei bilateral mit Cochlea Implantat versorgten Patienten beeinflusst insbesondere die Fähigkeit der Schalllokalisation. Die zeitliche Abstimmung von Hörprothesen sollte bei deren Anpassung berücksichtigt werden.

Einleitung

Das Sprachverstehen im Beisein von Lärm ist beim Menschen sehr ausgeprägt. Der Schallpegel von Sprache kann deutlich niedriger sein als umgebender Störschall, um das Gesprochene noch verstehen zu können. In der Audiologie ist das Sprachverstehen im Störschall ein Maß für die Hörfähigkeit. Ein einfacher Sprachtest ist der Ziffern-Tripel-Test, bei dem eine Folge von drei Zahlen versteckt in einem definierten Rauschen meist über Kopfhörer präsentiert werden. Dabei wird die Sprachverständlichkeitsschwelle bestimmt: diese entspricht jenem Signal-Rausch-Verhältnis, bei dem 50% des Sprachmaterials verstanden wird. Der Ziffern-Tripel-Test kann an jedem Ohr einzeln, oder bei beiden Ohren gleichzeitig präsentiert werden. Letztere Darbietung wird diotisch genannt, wenn dasselbe Signal an beiden Ohren anliegt. Auch eine antiphasische Darbietung der Zahlen im Störschall ist möglich, wobei die Sensitivität für Hörstörungen bei dieser Art der Testung höher scheint. In der vorliegenden Studie werden die Ergebnisse des Ziffern-Tripel-Tests bei diotischer und antiphasicher Darbietung an Probanden mit normalem Gehör verglichen.

Methoden

Den Ziffern-Tripel-Test wurde in der Deutschen Version bei einer Probandengruppe von Normalhörenden und Teilnehmern mit mittelgradigen Hörstörungen (N =100) in vier Bedingungen getestet: Darbietung von Sprache und Rauschen am linken und rechten Ohr, sowie beidohrige Darbietung in diotischer und antiphasicher Art. Zusätzlich wurden bei den Probanden für vier audiometrische Testfrequenzen (1.5, 2, 4 und 6 kHz) die Hörschwellen mit der Methode der Distorsionsprodukt-Otoakustischen-Emissionen bestimmt um ein normales Gehör zu bestätigen.

Schlussfolgerung

Bei allen Probanden mit bekannter mittelgradiger Hörstörung zeigten sich signifikante Unterschiede in den Ergebnissen des Ziffern-Tripel-Tests entweder bei diotischer oder antphasischer Darbietung. Bei sequentieller Anwendung scheinen der diotische und der antiphasiche Ziffern-Tripel-Test ausreichend genau um eine Hörstörung zu erkennen bzw. ein normales Gehör zu bestätigen.

Synaptische und neuralbedingte Hörverluste stellen in der klinischen Diagnostik eine besondere Herausforderung dar, da morphologische Bildgebung und funktionelle Einschränkungen häufig nicht kongruent sind. Ziel dieses Beitrags ist es, den Stellenwert objektiver audiometrischer Verfahren bei Verdacht auf eine auditorische Neuropathie sowie bei retrocochleären Pathologien wie Vestibularisschwannomen – einschließlich Patienten mit Neurofibromatose Typ 2 (NF2) – einzuordnen und deren komplementäre Rolle zur Bildgebung herauszustellen.

Im Vortrag werden zentrale objektive audiometrische Verfahren wie otoakustische Emissionen (OAE), Hirnstammaudiometrie (BERA), Elektrocochleographie (ECochG) sowie die präoperative Ableitung elektrisch evozierter Hirnstammpotenziale (E-BERA) konzeptionell dargestellt. Anhand typischer klinischer Befundkonstellationen wird erläutert, welche funktionellen Hinweise diese Methoden liefern und wie sie zur Differenzierung cochleärer, synaptischer und neuraler Schädigungen beitragen können. Die Verfahren werden dabei bewusst im Kontext der Magnetresonanztomographie (MRT) und Computertomographie (CT) betrachtet, ohne diese zu ersetzen.

Objektive audiometrische Messungen ermöglichen häufig frühzeitige funktionelle Hinweise auf eine gestörte neuronale Signalübertragung, auch wenn die Bildgebung unauffällig ist oder morphologische Befunde nicht mit der klinischen Symptomatik korrelieren. Insbesondere bei auditorischer Neuropathie sowie bei Vestibularisschwannomen – auch im Rahmen von NF2 – liefern sie entscheidende Zusatzinformationen zur funktionellen Integrität des auditorischen Systems und zur klinischen Entscheidungsfindung. Die E-BERA gewinnt in diesem Zusammenhang zunehmend an Bedeutung, da sie vor einer möglichen Cochlea-Implantat-Versorgung Hinweise auf die elektrische Stimulierbarkeit der Hörbahn liefern kann.

Objektive audiometrische Verfahren stellen damit ein zentrales Instrument zur funktionellen Charakterisierung neuralbedingter Hörstörungen dar und ergänzen subjektive Testverfahren sowie bildgebende Diagnostik auf sinnvolle Weise, insbesondere in komplexen oder diskrepanten Befundkonstellationen.

Introduction
Reliable diagnosis of rapid eye movement (REM) sleep behavior disorder (RBD) often relies on expert visual analysis of video-polysomnography (v-PSG) recordings in specialized sleep laboratories, making detection time-consuming and costly. Building on our previous work demonstrating the feasibility of using a small, portable, depth camera for RBD detection in a small cohort (10 patients with RBD and 15 clinical controls), this study extends the evaluation to a larger, multicenter, and more diverse population.

Methods
We included 96 participants from five European sleep laboratories comprising 36 patients with RBD and 60 clinical controls (mean ages 67.3±8.3 and 45.4±17.9 years, respectively). All participants underwent in-lab v-PSG with simulta-neous, time-synchronized video recording using a portable depth camera (pico flexx2). Sleep experts visually annotated all observable movements in the infrared videos. Depth data were preprocessed through automatic bed cropping and removal of low-confidence pixels. Movements were automatically detected by computing frame-to-frame depth differ-ences, discarding changes below 1% of the larger depth value, and aggregating spatially and temporally connected acti-vations. Using both manual and automatic movement annotations, we derived features including the ratio of time spent moving during REM sleep and the average number of movements/REM hour, stratified by duration (0.1–2s, 2–15s, 15–300s, and unrestricted). A logistic regression classifier with leave-one-subject-out cross-validation was used to distinguish RBD from controls.

Results
Using automatically detected movements, RBD patients were identified with an F1-score of 0.794 when restricting move-ments to 0.1–2 s. Expert-scored movements without duration restriction yielded an F1-score of 0.806. Comparisons re-vealed occasional over-identification by the camera, primarily due to artifacts and reflective surfaces.

Conclusion
This multicenter study demonstrates that a small, portable depth camera can automatically detect movements and support RBD identification with performance comparable to expert visual scoring, highlighting its potential as a scalable and cost-effective screening aid.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and remains widely underdiagnosed. Smartphone-based photoplethysmography (PPG) enables large-scale AF screening and underpins the Austrian Digital Heart Program (ADHP), a nationwide, randomized, centerless clinical trial targeting nearly 100,000 participants. As PPG may not be feasible for all subgroups, collecting complementary biosignals offers an opportunity to improve data coverage and robustness. In this work, two additional submodules were developed for the ADHP mobile application and seamlessly integrated into the existing platform. One submodule captures self-reported physical activity, while the other records cardiac-related vibrations using the smartphone’s inertial measurement unit, including accelerometer and gyroscope sensors. Collected data are transmitted to a dedicated backend service using FHIR DiagnosticReport resources. To ensure data integrity, a local synchronization workflow was implemented, allowing data to be securely stored on the device and automatically re-uploaded if initial transmission fails.

Key Results and Significance: The device integrates a metal core alloy with a nanoparticle-doped polymer sheath, engineered for surgical familiarity and a controlled 12–18-month resorption profile with fibrous tissue replacement to restore heart valve functions as primary mode. In vitro data show sustained antibacterial activity as a secondary mode against Staphylococcus aureus and Escherichia coli. Due to its novelty and lack of predicate devices, de novo clinical evidence is essential. The thesis delivers a regulatory roadmap spanning EU MDR and U.S. FDA (5,6) pathways, mapping risk management, GSPR conformity, hazard traceability and a FMEA analysis, including ISO-10993 biocompatibility, mechanical properties, and degradation testing, which are aligned to applicable standards and agency expectations (1, 2). The Center’s cardiovascular tissue-engineering expertise and preclinical models support translational relevance and test selection (3), while GLP infrastructure enables non-clinical study credibility and acceptance (4).
Future Outlook: Next steps are early regulator engagement (Notified Body pre-subs; FDA Q-Sub/TAP if applicable), and a first-in-human clinical investigation under MDR Annex XV and FDA IDE. The resulting package is intended to streamline CE marking and subsequent U.S. submissions for this high-risk, Class III implant.

Ziel
Das Brustkrebsfrüherkennungsprogramm (BKFP) startete mit Jänner 2014. Der Brust-Ultraschall ist in Österreich eine klärende Zusatzuntersuchung als Teil der Primärdiagnostik. Testkonzept und -methoden zur technischen Qualitätssi-cherung (TQS) wurden dafür eigens entwickelt. Das Hauptaugenmerk liegt auf der frühen Detektion von defekten Schallköpfen, die als häufigste Fehlerquelle des Ultraschallsystems gelten.
Ziel war es eine für Anwender einfache, leicht durchzuführende und effiziente TQS zu etablieren.

Material und Methoden
Die Daten wurden in einem Beobachtungszeitraum von über 10 Jahren erhoben und ausgewertet: die Anzahl der am BKFP teilnehmenden Institute, Ultraschallgeräte, Schallköpfe, sowie die Anzahl defekter Schallköpfe.

Ergebnisse
Im BKFP nehmen aktuell 195 Institute mit 249 Ultraschallgeräten und 266 Schallköpfen teil. Die Anzahl der defekten bzw. ausgetauschten Schallköpfe beträgt 13,1%. Dieser Wert hat sich über die Jahre hinweg bei diesem Prozentsatz ein-gependelt.
Betrachtet man die Anfänge des BKFP, lag die Quote der defekten Schallköpfe bei 23,5%.

Schlussfolgerungen
Mit der regelmäßigen Durchführung einer einfachen TQS, kann mit wenig Aufwand schon eine große Wirkung erzielt werden. Schon einfachste visuelle Methoden können dabei helfen frühzeitig defekte Schallköpfe zu erkennen. Das Einpendeln der Anzahl defekter Schallköpfe ist unter anderem auch auf ein gesteigertes Qualitätsbewusstsein des Anwenders zurückzuführen.

Einleitung
Bei interventionellen radiologischen Untersuchungen können bei höheren Dosen deterministische Strahlenschäden auf-treten. Patientinnen haben ein Recht auf Information und Betreuung.
Der wichtigste Aspekt ist, dass Strahlenschäden (hauptsächlich an Haut, evtl. auch an Knochen) erst mit einer zeitlichen Verzögerung von einigen Wochen bis Monaten auftreten. Dadurch ist der Zusammenhang mit der Strahlenbehandlung unter Umständen für dendie Patientin nicht klar. Auch ein Besuch bei einerm Dermatologin ist ohne dieses Wissen nicht hilfreich. Dermatologinnen ohne Spezialwissen betreffend Strahlenschädigung können dendie Patientin nicht entsprechend behandeln.
In der Strahlentherapie ist dieses Problem schon lang präsent, da einerseits im Normalfall eine deutlich höhere Dosisbe-lastung auftritt, und andererseits die Patientinnen über einen längeren Zeitraum hinweg mit der Klinik in Kontakt sind. Bei interventionelle radiologischen Untersuchungen werden die Patientinnen eintweder zeitnah entlassen oder nach der Behandlung auf einer anderen Station weiterversorgt.

Methoden
Durch eine proaktive Vorgangsweise erkennt man die Mündigkeit der Patientinnen an und kann Verunsicherung und Unzufriedenheit abfedern. Durch Überwachung der Dosisdaten im Dosismanagementsystem des Universitätsklinikums AKH Wien können bei Überschreitung von geeignet gewählten Schwellwerten die Patientinnen zeitgerecht informiert und gegebenenfalls weiterverwiesen werden.

Ergebnisse
Ein abteilungs- und klinikübergreifender Prozess wurde entwickelt und wird derzeit implementiert. Dabei war es wich-tig, auf bereits vorhandene Ressourcen z.B. der Strahlentherapie zurückzugreifen.

Schlussfolgerungen
Aufgrund der Größe und Struktur des Universitätsklinikums AKH Wien ist es nicht einfach, einen neuen Prozess zu implementieren – man spürt Skepsis und Unwillen gegenüber Veränderung. Auch ist es nicht leicht, Gelegenheiten zur Nutzung von Synergien zu finden. Im Sinne des Patient*innenwohls sehen wir hier aber Verantwortung der Medizin-physik, da wir durch unseren Aufgabenbereich einen anderen Blickwinkel auf die Prozesse haben.

Introduction
National and international recommendations for quality assurance (QA) of treatment planning systems (TPS) using the TG-43 dose algorithm in brachytherapy were recently updated. Methods and results of dosimetric checks are compared.

Methods
National Austrian regulations ÖNORM 5295-2 (Austrian Standards International, 2025) and GEC-ESTRO guidelines (doi:10.1016/j.radonc.2025.111008) were compared. Moreover, results of the AKH/MedUni Wien QA programme are summarized.

Results
To check dose calculation, ÖNORM 5295-2 states that a reference plan should be evaluated. The GEC-ESTRO guidelines recommend checking the dose distribution of a single source and summations of multiple sources by evaluating various dose points. The TPS dose can be compared to the published AAPM/GEC-ESTRO consensus data spreadsheets (www.estro.org) . Special care needs to be taken to select the applicable source model. In our clinic, this approach has resulted in maximum deviations of 0,2% and 0,3% for a single source plan and a multiple source plan, respectively using the GEC-ESTRO recommendations geometries, and less than 2% deviations for any other complex geometry.
Contrasting international guidelines, the ÖNORM 5295-2 proposes an end-to-end test including dosimetric measurement. This poses severe challenges on calibrated equipment with suitable detector size and energy sensitivity, and on achieving an extremely stable measurement setup, thus making the procedure error-prone and highly experimental. Proper transfer of the treatment plan to the afterloader in our clinic is checked by monitoring the total reference air kerma (TRAK) of every treatment plan, during patient-specific QA. Combined with machine QA, this ensures proper application of radiation. Additionally, it serves as an easy metric to compare to similar treatment plans and avoid severe errors during planning and treatment.

Conclusion
Dosimetric TPS QA in brachytherapy was successfully performed based on published data of the TG-43 algorithm and monitoring of TRAK values.

Ziel
Ziel dieser Arbeit ist die kritische Bewertung von Remote-Scanning-Modellen für MRT und CT unter Berücksichtigung der aktuellen wissenschaftlichen Publikationen, der österreichischen Rechtslage sowie den berufs- und strahlenschutz-rechtlichen Anforderungen. Unter Remote-Scanning wird die fernbediente Steuerung und Überwachung bildgebender Systeme über eine räumlich getrennte Bedienoberfläche verstanden. Besonderes Augenmerk liegt auf Patientensicherheit, Verantwortlichkeit und den technischen sowie organisatorischen Voraussetzungen für einen sicheren Betrieb.

Material und Methoden
Es wurde eine Analyse der verfügbaren Literatur und Rechtsgrundlagen durchgeführt, darunter das ÖGRT-Whitepaper zu Remote-MRT (2024), ESR-Whitepaper zur Rolle der Radiologie (2022), die Stellungnahme des Bundesumweltministeriums Hessen zum Tele-MTRA-Modell bei CT (2023), die EU-MDR, die Strahlenschutzgesetzgebung sowie die wissenschaftlichen Arbeiten von Deistung et al. (2024), Hudson et al. (2022) und Quinsten et al. (2023). Die Inhalte wurden hinsichtlich technischer Machbarkeit, rechtlicher Zulässigkeit und klinischer Risiken ausgewertet.

Ergebnisse
Die Literaturrecherche zeigt, dass Remote-Scanning im MRT technisch realisierbar ist, jedoch stabile Netzwerkverbindungen, verlässliche Kommunikation und qualifiziertes Personal vor Ort voraussetzt. Gleichzeitig wird beschrieben, dass Latenzen, reduzierte Patienteninteraktion und eine erhöhte kognitive Belastung des Bedienpersonals die praktische Umsetzung spürbar einschränken. Weiters wird betont, dass für einen sicheren und effizienten Betrieb klar definierte Prozesse, Rollen sowie umfassende Schulungen und Kommunikationsstrukturen unabdinglich sind. Risiken wie Verbindungsabbrüche, fehlende Ausfallsicherheit und hoher Dokumentationsaufwand bleiben jedoch bestehende Herausforderungen.

Schlussfolgerungen
Insgesamt zeigen die vorliegenden Studien und Stellungnahmen, dass Remote-Scanning die Möglichkeit schafft hoch-qualifiziertes Fachpersonal standortübergreifend einzusetzen und Versorgungsstrukturen gezielt zu unterstützen. Dieses Modell kann zur Entlastung beitragen, ist jedoch mit sicherheits-, qualitäts- und rechtsrelevanten Risiken verbunden.

Transcranial focused ultrasound stimulation (TUS) offers the unique capability of non-invasively modulating neuronal activity in deep brain structures with millimeter-scale spatial precision. TUS also requires precise planning and continuous monitoring to maintain spatial accuracy. While sound wave propagation is simulated numerically, uncertainties in skull properties and transducer positioning can lead to deviations between simulated and actual stimulation targets. Magnetic Resonance Acoustic Radiation Force Imaging (MR-ARFI) enables in vivo validation of TUS focal spots by visualizing submillimeter tissue displacements induced by sound waves.
CITRUS is a collaborative PATHFINDER project funded by the European Innovation Council involving eight partners from academia and industry. Within the CITRUS project, we have developed the specific hard- and software for a novel TUS-MRI approach: (1) 256-element steerable transducers, (2) 16-channel receive coil array, (3) accelerated MR-ARFI sequence, (4) tailored neuronavigation software suite. During the experimental session, neuronavigation ensures accurate positioning of the transducers. MR-ARFI is used to localize the actual sonication focus in the brain. Any deviations from the intended target are compensated by using the electronically steerable transducers without any mechanical repositioning. MR-ARFI is then used to validate the correct focus position using the updated sonication parameters. The dedicated CITRUS hardware setup allows for robust transducer placement and yields high-sensitivity MR-ARFI and fMRI data.
The CITRUS system enables integration of focused ultrasound hardware within the MR environment, most importantly, it supports an imaging-guided replanning step, where stimulation parameters can be updated based on MR-ARFI feedback. Following focus validation, the platform allows concurrent TUS-fMRI to assess stimulation-induced brain responses. Currently, this CITRUS system is being used in a first study assessing TUS-fMRI in healthy human volunteers. The CITRUS approach establishes a foundation for validated, image-guided neuromodulation and physics-based quality assurance in the emerging field of ultrasound brain stimulation.

Introduction
Quantifying brain microstructure using magnetic resonance imaging (MRI) is essential for a wide range of medical applications. Although transverse relaxation and Larmor frequency shifts provide access to magnetic microstructure, their interpretation is still largely empirical. Obtaining precise biophysical models is challenging due to the complexity of biological tissue and the involvement of physical processes across multiple length scales.

In this work, we employ a biophysical model that explicitly links magnetic microstructure to measurable macroscopic MRI parameters. We use this model to study tissue microstructure in patients with aceruloplasminemia (ACP), a rare pathology characterized by extreme iron accumulation and enlarged iron-loaded cells.

Methods
Quantitative brain MRI of three patients with ACP and three matched healthy controls was acquired in vivo on a $3~$Tesla system. Transverse relaxation rates ($R^*_2$, $R_2$) and magnetic susceptibility maps (QSM) were derived from the measured data and interpreted within a biophysical framework supported by theoretical considerations and Monte-Carlo simulations.

Results
Across deep gray matter brain regions, patients exhibited higher $R^*_2$ and $R_2$ values compared to controls, accompanied by markedly increased $R^*_2/R_2$. Monte Carlo simulations of spherical magnetic inclusions predicted the same behavior, showing an increase of the $R^*_2/R_2$ ratio with inclusion size. Analysis of the relationship between $R^*_2$ and bulk magnetic susceptibility further revealed a substantially steeper susceptibility-dependent relaxation slope in patients ($295.93~$Hz/ppm) compared to controls ($162.25~$Hz/ppm). Theory predicts a slope of $324.4~$Hz/ppm.

Conclusion
The observed in vivo relaxation and susceptibility behavior is consistent with theoretical predictions and Monte Carlo simulations. The inferred microstructural characteristics are in agreement with reported histopathological findings in ACP. Together, these results demonstrate that a multiparametric quantitative MRI approach combining relaxometry and QSM enables a detailed assessment of tissue magnetic microstructure and provides sensitivity not only to increases in iron concentration but also to size differences of magnetic inclusions in vivo.

Goal
MRI-based myelin quantification can non-invasively evaluate demyelinating diseases and allow 3D virtual microscopy, but is confounded by varied element concentrations and microstructural alterations.[1] To explore this, we compared multi-modal myelin-sensitive MRI to myelin-specific small-angle x-ray scattering tensor tomography (SAXS-TT)[2].

Materials and Methods
Formalin-fixed human brain specimens from a 52yo multiple sclerosis (MS) patient were scanned on a 7T Bruker BioSpec scanner. Diffusion kurtosis imaging (DKI) allowed calculation of axonal water fraction (AWF) maps and fiber orientation distributions (FODs); multi-gradient echo yielded R2*; FLASH, magnetization transfer ratio (MTR); and RARE, T1 and T2 maps. SAXS-TT of the same specimen, acquired in the DESY synchrotron, provided 3D myelin quantifications, which were registered to AWF. This was followed by sectioning and iron and glial histology staining. Correlation coefficients between SAXS and MRI were calculated over voxels in automatically clustered subregions.

Results
Multi-modal MRI allowed rich tissue characterization. FA/FOD maps were relatively contiguous over WM bundles, facilitating identification, while other contrasts indicated intra- and inter-bundle myelin level variations. Intensity-based clustering captured such variations, separating the WM into largely contiguous subregions varying in SAXS-MRI covariance. Despite histology-implied glial activation, with potentially varied effects on diffusion MRI, some clusters showed high SAXS-AWF correlation (ρ~0.6-0.8). A different cluster showed similar SAXS-AWF correlation (ρ=0.7), but much lower SAXS-R2* and SAXS-MTR correlations (ρ<0.1), potentially explained by iron content variations indicated by histology.[3]

Conclusions
Correlating high-resolution multi-contrast MRI to SAXS myelin levels indicated spatially varying relationships in multiple sclerosis tissue. DKI-derived AWF showed localized strong correlations, while iron-confounded R2* and MTR correlated more weakly. Our results highlight the dependence of quantification accuracy on local (subregional) variations in microenvironment, but also how multi-modal imaging can help characterize such variations.

References
[1] Van Der Weijden et al., Brain,vol.146,no.4,pp.1243–1266,2023.
[2] Georgiadis et al., Nat. Commun.,vol.12,no.1,p.2941,2021.
[3] Birkl et al., NeuroImage,vol.220,p.117080,2020.

Introduction
In vivo proton magnetic resonance spectroscopy (¹H-MRS) enables non-invasive assessment of tissue metabolism. In pancreatic ductal adenocarcinoma (PDAC), MRS can reveal disease-related metabolic alterations, including changes in fatty acids (FA) lipids and metabolites (e.g. choline-containing-compounds, lactate), reflecting tumor-driven metabolic reprogramming. Although MRS is well established for brain, muscle, and liver, pancreatic applications remain limited by technical challenges, lack of standardization, and the absence of dedicated prepocessing/analysis pipelines. Robust metabolic characterization of healthy and diseased pancreatic tissue remains an unmet need.
This study aimed to establish a pancreas-specific MRS framework aligned with consensus guidelines and state-of-the-art methodologies and apply it to a PDAC mouse model to characterize cancer metabolism and effects of cysteinase-based therapy.

Methods
Eight PDAC genetically engineered mouse models were examined using an MRI system. Animals were assigned to vehicle or cysteinase-treated groups and scanned before and after placebo/treatment administration. Tumors were identified using anatomical MRI, followed by localized MRS acquisition. A pancreas-dedicated preprocessing and analysis pipeline was developed and optimized to ensure robust spectral quality. The metabolites and lipids evaluated were selected based on prior preclinical and clinical evidence. Quantitative analysis used linear-combination modeling with simulated reference spectra. Compound concentrations were statistically compared to assess group differences.

Results
Saturated and unsaturated FA lipid resonances, glycerol and metabolites such as lactate, taurine, and glutathione, were detected in vivo. These findings were consistent with cancer-associated metabolic reprogramming and aligned with prior in vivo and ex vivo spectroscopic observations. Several unsaturated lipid signals differed significantly following cysteinase treatment.

Conclusion
This MRS pipeline improves metabolic characterization of PDAC. It expands the limited panel of MR-detectable pancreatic compounds to seven lipids and twelve metabolites, including signals not previously reported in pancreatic ¹H-MRS studies (unsaturated FA lipids, glycerol, lactate). These results support the use of ¹H-MRS to study PDAC metabolism and treatment effects.

Flexible radio frequency coils increase signal-to-noise ratio (SNR) in MRI due to closer positioning to the patient. This study evaluates the performance of two flexible 4-channel receive arrays: a stranded wire coil (SWC) utilizing stranded copper wire and a coil based on coaxial cables used as transmission line resonators (“ModFlex”). The primary objective was to validate the SWC as a simplified, easy-to-manufacture production method that maintains SNR comparable to traditional designs. The coils were characterized on the bench, and tested in a 3 T MR scanner (Prisma Fit, Siemens Healthineers, Germany).
Bench measurements demonstrated robust geometric decoupling and impedance matching, with all individual loop elements achieving a return loss (Sii) better than -14.2 dB and inter-element isolation (Sij) due to geometric decoupling below -14.2 dB. Active detuning provided isolation of better than -23 dB for all channels during the transmit phase. Additionally, preamplifier decoupling was effective in minimizing noise correlation, achieving isolation values of better than -21 dB. The unloaded-to-loaded Q-ratio (Qu/Ql) of ~ 2.5 for each individual loop demonstrated sample loss dominance.
From noise-only measurements in the MR scanner, noise correlation coefficients below 0.2 were determined. SNR maps were acquired with a 3D gradient echo sequence on a canister phantom filled with H20+9 g/l NaCl and calculated using the pseudo multiple replica method. Average SNR over a cuboid ROI (12 x 12 x 12) cm³ under the arrays was found to be 8% higher for the SWC. Decoupling from the transmit coil was tested by acquiring flip angle maps with and without the coils present on the phantom. The maximum deviation was below 15% for SWC and 12% for ModFlex, demonstrating efficient transmit decoupling.
These results confirm that the flexible SWC array performs slightly better than the flexible coaxial coil array, and offers a simpler manufacturing alternative.

Introduction

Solid polymers are generally not visible in MRI. However, MRI-visible solid materials would be highly beneficial for radiation oncology applications, allowing for more accurate patient positioning, improved image registration between MRI and (CB)CT images and improve brachytherapy workflows with positive contrast catheters and surface moulds.
In this work, we present initial results of a novel MRI-visible solid composite material consisting of paraffin oil containing microcapsules enclosed in a matrix of UV-curable polymer.

Methods

The material was prepared by encapsulating paraffin oil via a double emulsion process in UV-curable resin. The resulting capsules were mixed with UV-curable resin as matrix material and cured in bulk. Imaging was performed on a 1.5 T MR scanner (Ingenia Ambition X, Philips). T1 and T2 times were measured using an inversion recovery- and a multi-echo turbo spin sequence respectively. For the T1 data a biexponential fit with both T1 times set to predetermined values of pure paraffin oil and water was performed. The uncertainty of the fitting parameters T1 and T2 reflect the noise and heterogeneity of the sample rather than repeated measurements.

Results

Our material showed clear positive contrast in DIXON-, inversion recovery-, turbo spin-echo- and gradient-echo sequences. Fitting a biexponential model with both T1 times set to the predetermined values of paraffin oil and water resulted in an R2 of 0.991. The determined T2 time of the material was 129±13ms (R2=0.989), pure paraffin oil had a T2 time of 118±2ms (R2=0.996).

Conclusion

We were able to successfully prepare a solid composite material which produces well visible positive contrast in MRI. Therefore, paraffin oil filled microcapsules are a suitable additive to render polymers MRI-visible. T1 analysis revealed that our fabrication process also incorporates water into the material.