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Physics Physics Medical Physics

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Wednesday 14 October · still arriving

Medical Physics

A single radiation hard pixel detector for proton dosimetry, imaging, energy resolution and beam monitoring

Nico Frederic Brosda, Stephane Higueret, Nicolas Arbor et al. (+7 more)

Proton therapy enables highly conformal tumour irradiation by exploiting the Bragg peak. Clinical precision relies on detector systems that provide linearity, spatial resolution, radiation hardness, and, for ultra-high-dose-rate (FLASH) therapy, high dynamic range with sufficient temporal response. No compact all-in-one solution currently fulfils all these requirements. Here, we present pixelated gallium nitride (GaN) arrays as a multifunctional platform. These detectors exhibit high linearity (proton currents from 70 to 1700 pA cm-2) and signal uniformity below 2% across 128 pixels. To probe GaN radiation hardness, we applied cumulative doses up to 6.7 MGy at energies from 25 MeV down to the Bragg-peak regime. Locally deposited dose dictates long-term signal loss, yet devices preserve linearity and spatial response. We demonstrate 0.25 mm effective spatial resolution, validated against radiochromic film. Proton radiography resolves fine tissue structures, with the dose extrapolated to 7 mGy per 1 ms frame in a prospective single-shot configuration. Energy-dependent responses match GATE/Geant4 simulations, and wedge measurements enable Bragg-peak tracking with an energy resolution below 10 keV in an optimised geometry. Real-time ms-scale beam monitoring enables live dose verification.These results establish GaN pixel detectors as a scalable and radiation-hard platform, enabling dosimetry, beam monitoring and energy verification in one device.
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All authors Nico Frederic Brosda, Stephane Higueret, Nicolas Arbor, Matilde Siviero, Maxime Hugues, Eric Frayssinet, Luisa Parschat, Christian Baumer, Andreas Dirk Wieck, Jean Yves Duboz

Tuesday 13 October · still arriving

Medical Physics · Cross-listed from physics.optics

High-resolution retinal matrix imaging via computational motion and aberration correction

Aymeric Melt, Léo Puyo, Victor Barolle et al. (+3 more)

High-resolution optical imaging of the human retina is essential for diagnosing ophthalmic and neurodegenerative diseases. While adaptive optics combined with coherence gating can resolve retinal structures at the cellular scale, it requires complex, costly, and cumbersome hardware to physically correct for ocular aberrations and motion. Matrix imaging offers a powerful digital alternative by leveraging wave linearity to undo aberrations and multiple scattering; however, its in vivo deployment has been hindered by continuous, involuntary eye movements that destroy phase coherence during acquisition. Here, we overcome this fundamental barrier and demonstrate the first in vivo reflection matrix imaging of the human retina using an ultra-simplified optical setup without physical correctors. We introduce a fully computational framework that tracks and compensates for multi-axial ocular motion directly from raw interferometric data, thereby restoring the phase coherence of a multi-spectral distortion matrix. This enables local, high-order aberration correction to achieve diffraction-limited, volumetric imaging of retinal tissues. By shifting the hardware burden to physics-guided numerical computation, this paradigm opens the way for accessible, non-invasive, and high-resolution digital ophthalmology.
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All authors Aymeric Melt, Léo Puyo, Victor Barolle, Claude Boccara, Gereon Hüttmann, Alexandre Aubry

Medical Physics · Cross-listed from eess.IV

DoReMe: Dual optimization of Reconstruction and Motion estimation for self-navigated free-breathing abdominal MRI using Gaussian Splatting

Majd Helo, Dominik Nickel and Thomas Kuestner

Purpose: Free-breathing abdominal MRI is limited by respiratory motion, which introduces image artifacts and k-space inconsistencies. Existing reconstruction approaches often depend on pre-estimated motion fields or external respiratory surrogate signals. We propose a coupled reconstruction-motion estimation algorithm for self-navigated free-breathing acquisition, in which motion is represented by compact Gaussian primitives and jointly refined with the image estimates during iterative reconstruction. Methods: An iterative reconstruction that alternates between data consistency updates and motion modelling was proposed. Respiratory motion was represented using Gaussian primitives. A Gaussian splatting was integrated into the reconstruction algorithm. The method was evaluated on self-navigated free-breathing Cartesian gradient-echo (GRE) acquisition in four healthy volunteers, including retrospective scan shortening experiments, and was compared with regularized compressed sensing (CS) reconstruction. Results: Respiratory motion states were reconstructed in approximately 1.5 min. Compared with CS, the proposed method improved visual image quality, particularly in coronal liver views, and better preserved anatomical structures in retrospectively shortened acquisitions. These findings provide proof of concept for the proposed method. Conclusion: The proposed coupled reconstruction-motion estimation algorithm improved visual image quality compared with CS alone. Gaussian primitives provided a compact and sufficiently flexible representation of nonrigid respiratory motion with practical runtime, supporting further scanner integration and validation in larger cohorts.
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Medical Physics

Can $^{225}$Ac be imaged on a long axial field-of-view PET/CT with standard clinical settings?

Lorenzo Mercolli

Purpose: The $^{225}$Ac decay chain includes $^{209}$Tl, whose prominent 1567 keV gamma line can create electron-positron pairs. We investigated whether a long axial field-of-view (LAFOV) PET/CT can image $^{225}$Ac using standard clinical acquisition and reconstruction methods. Methods: A syringe placed next to a vial (5.89 and 10.29 MBq of $^{225}$Ac activity) and a NEMA IEC body phantom (sphere activity concentration 4.56 kBq mL$^{-1}$) were scanned for 45 and 60 min, respectively, on a Biograph Vision Quadra (Siemens Healthineers). To support our findings, FLUKA simulations scored the annihilation locations around a $^{225}$Ac point source. Results: The contours of the syringe and vial were visible despite high noise, but the NEMA spheres could not be distinguished from the background. As illustrated by the FLUKA simulations, the number of annihilation events decreases exponentially according to the mean free path of the 1567 keV photon in the surrounding medium. Conclusion: A LAFOV PET/CT can detect positrons created by pair production of the main $^{209}$Tl gamma line. However, these positrons are created where the photons interact with the surrounding medium rather than at the location of the $^{209}$Tl decays, which rules out standard PET imaging of $^{225}$Ac.
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Medical Physics

Direct correlation of intravoxel incoherent motion imaging based on implicit neural representations and histopathology in pediatric Wilms tumors: can it differentiate between subtypes?

G.C. Arends, M. Fitski, J. Harbers et al. (+8 more)

Wilms tumor (WT) is a heterogeneous pediatric renal malignancy. Invasive procedures to establish histology prior to pre operative treatment are not recommended by the International Society of Pediatric (SIOP) Oncology Renal Tumor Study Group, yet different tissue components are associated with different responses to therapy (SIOP Umbrella protocol). Intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) may improve subtype differentiation before surgery as a noninvasive radiographic biomarker by capturing both diffusion and perfusion characteristics, as opposed to the conventionally used apparent diffusion coefficient (ADC). The objective of this study is to evaluate the discriminative performance of IVIM MRI in differentiating WT subtypes. IVIM provides quantitative parameters that disentangle the diffusion coefficient (D), incoherent blood flow (pseudodiffusion Dstar) and perfusion fraction (f). This retrospective study included thirthy children with WT. Standardized 1.5T MRI with 10 b value diffusion weighted imaging (DWI) was performed. IVIM parameters were estimated using a selfsupervised implicit neural representations network and were correlated with histopathology via a patient specific 3D printed cutting guide. Statistical analyses included mixed models, receiver operating curve analysis, and logistic regression. Thirty lesions were MRI histopathology correlated on slice level. Significant subtype differences were observed for Dstar stromal versus epithelial (p = 0.024), regressive tumors (p = 0.031) and mixed WT tumors (p = 0.043). ADC showed no significant subtype differences. Direct MRI histopathology correlation enabled differentiation between stromal subtype and epithelial, mixed and regressive subtype on macroscopic slice level using Dstar.
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All authors G.C. Arends, M. Fitski, J. Harbers, J.N. van der Beek, R.R. de Krijger, M.M. van den Heuvel-Eibrink, A.F.W. van der Steeg, F.F.J. Simonis, E. Versteeg, A.S. Littooij, C.M.W. Tax

Medical Physics · Cross-listed from math.NA

Hyperelastic Modeling of Cardiac Tissue Deformation for Data Registration

Joyce Ghantous, Yves Coudiere and Michael Leguèbe

This work proposes a biomechanical registration framework designed to combine functional optical-mapping data with structural high-resolution MRI of cardiac tissue. The two acquisitions are performed in different mechanical configurations: optical mapping is obtained after stretching the sample, whereas MRI is acquired in a fixed resting state. To estimate the deformation between these configurations, the tissue is modeled as a nearly incompressible transversely isotropic hyperelastic material, and the traction amplitude is identified from optical-map marker positions through an inverse problem. Two-and threedimensional simulations show physically admissible deformations and provide a first proof of concept for the proposed strategy.
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Medical Physics · Cross-listed from math.NA

Numerical simulation of biological capsules based on interface-fitted polygonal meshes

Daniele A. Di Pietro, Simon Mendez and Aurelio E. Spadotto

In this work we introduce a numerical framework for the simulation of biological capsules based on meshes that adapt iteration-wise to the shape of the membrane. The discretization leverages a Hybrid High Order method (HHO) to solve a Stokes problem with a source term distributed on the interface between the internal and the external phases. The HHO discretization supports meshes composed of general polygons, permitting to use fitted meshes that can be easily generated by cutting the elements intersected by the interface. Moreover, polygonal meshes allow arbitrarily accurate interface discretizations without introducing bulk degrees of freedom. The presentation of the simulation algorithm is completed with a proof-of-concept numerical test on a well-established benchmark: the deformation of an elastic capsule immersed in a shear flow.
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Medical Physics

Photoacoustic imaging of human brain function through intact adult skulls

Yilin Luo, Rui Cao, Manxiu Cui et al. (+12 more)

Blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has revolutionized noninvasive imaging of human brain function, but it indirectly senses deoxyhemoglobin through water-proton relaxation and relies on bulky, costly, noisy, enclosed, superconducting-magnet scanners. In contrast, photoacoustic computed tomography (PACT) directly probes hemoglobin absorption using a more compact, lower-cost, quieter, open, magnet-free system. However, functional PACT of the adult human brain has so far been demonstrated only after surgical skull removal, because the skull strongly attenuates optical and acoustic signals. Here, we demonstrate non-invasive transcranial functional PACT (T-fPACT) through the intact adult skull. A densely packed, high-channel-count (3,072-element) hemispherical ultrasonic array provides near-$2\pi$-steradian simultaneous acquisition, enabling high sensitivity and single-shot three-dimensional imaging at 20 Hz that eliminates motion blurring. Participant-specific stabilization further enables measurement of small task-evoked hemodynamic responses over the entire task duration. In healthy adults, T-fPACT localized responses to expected sensorimotor regions, distinguished task-specific motor representations, and yielded consistent localizations across repeated task runs and visits. Comparison with high-field (7 T) fMRI showed spatially corresponding functional regions, while dual-wavelength imaging revealed distinct hemoglobin-weighted responses. These findings overcome the long-standing skull barrier in human brain PACT and establish non-invasive, rapid volumetric photoacoustic imaging of brain function.
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All authors Yilin Luo, Rui Cao, Manxiu Cui, Karteekeya Sastry, Kay Jann, Yousuf Aborahama, Geng Ku, Jinhua Xu, Xiaofei Luo, Shuai Na, Samuel Davis, Konstantin Maslov, Yang Zhang, Danny J. Wang, Lihong V. Wang

Monday 12 October

Medical Physics · Cross-listed from hep-ex

Experimental Demonstration of Soft-Tissue Muon Scattering Tomography

Dipanwita Banerjee, Benjamin Banto Oberhauser, Paolo Crivelli et al. (+1 more)

Muons have fascinated physicists since their discovery in cosmic rays almost a century ago. Their large mass and relatively long lifetime allow relativistic muons to traverse large amounts of matter, a property that has been exploited to probe otherwise inaccessible structures, from volcanoes and archaeological monuments to shielded nuclear materials. Here, we experimentally demonstrate for the first time that muon scattering tomography can be extended to biological soft tissue. We image an anthropomorphic thorax phantom using a 2 GeV/c muon beam at the CERN Proton Synchrotron and reconstruct its three-dimensional scattering density from the measured deflections of individual muons. Despite the weak scattering produced by tissue-equivalent materials, the reconstructed density agrees with the expectation from simulation at the percent level. Our results extend muon imaging into a previously unexplored regime and open the possibility of using muons as a complementary probe for medical imaging.
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All authors Dipanwita Banerjee, Benjamin Banto Oberhauser, Paolo Crivelli, Laura Molina Bueno

Sunday 11 October

Medical Physics

BOLD PSF: Impact of k-space trajectories and timing on the depiction of T2* contrast

Maria Engel, Lars Kasper and Klaas P Pruessmann

The timing of BOLD-fMRI is typically chosen such that TE matches T2*. This assumes contrast being exclusively elicited by signal differences at TE. While sensible for short or TE-symmetric readouts, such as EPIs, it oversimplifies contrast generation for longer or TE-asymmetric trajectories, such as spirals. We propose the concept of a BOLD PSF for a more comprehensive perspective on the imaging characteristics of a functional experiment. Our findings indicate that TE can be reduced for spiral-out without sacrificing BOLD-sensitivity when compared to EPI. Furthermore, we characterize the intrinsic trade-off between specificity and resolution of the BOLD response under varying TE.
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Medical Physics

Personalized Physiological-Model-Based Neural Network for Glucose Forecasting in Type 1 Diabetes

Yaowen Zhang, Shuhao Que and Ying Wang

Accurate, physiologically consistent glucose forecasts could help people with type 1 diabetes respond to impending excursions. We applied our physiological-model-based neural network (PMB–NN) framework to glucose forecasting. A temporal convolutional network (TCN) used 180 min of history, constrained during training by a personalized four-parameter physiological model. The main PMB–NN combined forecast and neural–physiological agreement losses; a three-term variant additionally fitted physiological predictions to measured glucose. Data comprised 6–8 weeks of continuous glucose monitoring, pump, and meal records from 25 AZT1D participants. Person-specific models used chronological 70/10/20 train/validation/test splits and 30-, 60-, and 120-min horizons. Median mean absolute errors were 16.24, 25.00, and 30.20 mg/dL with basal insulin records and 15.38, 24.21, and 31.79 mg/dL before these records became available. In the latter setting, PMB–NN had the lowest median error at 30 and 60 min; it outperformed the physiological model alone in all six settings. In input-increase tests, glucose predictions changed in the expected direction for 85% of correction boluses and 100% of carbohydrate rescues, versus 57% for active insulin and 56% for active carbohydrates. Most standalone physiological fits showed locally distinguishable parameter effects, with glucose-related coefficients more stable under resampling than insulin- or carbohydrate-related coefficients. The three-term variant improved hyperglycaemia accuracy with basal records, but did not significantly change overall MAE and reduced directional plausibility in three tests. PMB–NN combines personalized forecasting with an explicit physiological model, allowing assessment of predictive accuracy, physiological response behavior, and participant-specific coefficients.
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Medical Physics

Automated carotid artery atherosclerotic inflammation segmentation in PET using MSR-Net

Ran Li, Abhinav K. Jha, Jie Zheng et al. (+8 more)

Objective. To develop an automated method for segmentation and uptake quantification of carotid atherosclerotic inflammation on 64Cu-CANF-comb PET while accounting for partial-volume and tissue-fraction effects. Approach. Synthetic carotid PET images with known fractional-volume ground truth were generated by combining MR-derived high-resolution activity maps with GATE Monte Carlo simulation incorporating major PET physical processes and matched to the Biograph mMR acquisition and reconstruction. A two-stage network first localized the carotid vessel wall from T1-weighted MR and then estimated voxel-wise inflammation fraction from masked PET. Both stages used a multiscale residual (MSR) convolutional backbone. Performance was compared with U-Net, Transformer U-Net, DUCK-Net, and iterative Yang partial-volume correction. Main results. In a two-alternative forced-choice study, five nuclear-medicine physicians identified real images with 54% accuracy (54/100; Wilson 95% CI 0.44-0.63; exact binomial p = 0.48). On 184 simulated test slices from five held-out patients, the proposed method achieved a weighted DSC of 0.79, compared with 0.73 for U-Net, 0.69 for Transformer U-Net, and 0.75 for DUCK-Net, with corresponding HD values of 1.85, 2.29, 2.32, and 2.23 voxels. Patient-cluster bootstrap comparisons favored the proposed method for DSC and HD against all three baselines (Holm-corrected p <= 0.031). Overall ENRMSE was 0.24 versus 0.59, 0.68, and 0.59 for the three DL baselines and 0.57 for iterative Yang. In seven patients, corrected SUV showed a positive association with MR-derived lipid-rich/necrotic core with hemorrhage. Significance. The proposed framework improved carotid PET segmentation and uptake quantification under simulated conditions. The patient analysis is preliminary and requires external validation with biological reference standards before clinical deployment.
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All authors Ran Li, Abhinav K. Jha, Jie Zheng, Richard Laforest, Yongjian Liu, Mohamed Zayed, Tyler J. Fraum, Barry A. Siegel, Malak Itani, Joyce C. Mhlanga, Pamela K. Woodard

Friday 9 October

Medical Physics

Separating active irradiation from passive outcome learning in radiotherapy: a finite-model computational benchmark

Yuntao Wang

Apparent gains from informative irradiation may reflect treatment reoptimization or better use of outcomes from static treatment. We tested whether changing irradiation adds value beyond optimized static treatment, passive outcome learning, and data-dependent stopping. Three synthetic three-dimensional geometries supplied 51 parent fluences. Four known response scenarios generated Bernoulli risks from normalized organ-dose contrasts at uncalibrated slopes of 0, 4, 16, and 64; one unknown scenario applied to all 2,816 hypothetical uses. Loss included acquisition and deployment. We compared fixed passive and locally selected fixed active sampling, passive optimal stopping, and a restricted one-checkpoint, one-switch active policy with a shared terminal menu. Fixed active sampling improved on fixed passive sampling in three of nine nonzero-slope conditions, but never on passive stopping. One-switch adaptation added at most 4.00625e-5 expected model events avoided. With the policies held fixed, two of four increments above the numerical reporting threshold reversed sign under alternative integration; all four became negative at some allowed prior weighting. Adding three generated probes changed none of 72 paired policy values, and none was used on a positive-probability path. The tested probes did not demonstrate stable incremental value beyond optimized passive stopping. Treatment opportunities, stopping permissions, acquisition costs, and input sensitivity must be separated when attributing benefits to active irradiation. These are restricted finite-model results, not evidence about unrestricted active learning or clinical safety and effectiveness.
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Medical Physics · Cross-listed from math.OC

Warm-IP: A Path-Following ADMM Warm Start for Interior-Point Quadratic Programming

Babak Aslani, Mojtaba Tefagh, Gourav Jhanwar et al. (+1 more)

Interior-point (IP) methods are powerful second-order optimization algorithms but can make slow progress during early iterations. We propose Warm-IP, a hybrid framework that combines a path-following variant of the alternating direction method of multipliers (ADMM) with a primal–dual IP method. The ADMM phase generates a warm start that remains close to the central path, enabling the subsequent IP phase to rapidly refine the solution to high accuracy. We evaluate Warm-IP on a diverse collection of real-world and synthetic quadratic programming (QP) instances and compare it with leading commercial solvers (MOSEK and Gurobi) and open-source solvers (Clarabel, PIQP, and OSQP). We also curate and release a new benchmark of large-scale QPs from cancer radiotherapy treatment planning, built from real patient data and provided in canonical QP form, with instances containing hundreds of thousands of constraints. Warm-IP substantially outperforms existing solvers on large-scale problems. On the large-scale radiotherapy benchmark comprising 60 lung cancer cases, for example, Warm-IP solves an instance in 47 seconds on average with no failures, while the strongest competitors, MOSEK and Gurobi, average 55 seconds with failures on 23% of the cases and roughly 240 seconds with no failures, respectively. To support reproducibility and future benchmarking, we publicly release the implementation and benchmark data through a \href{https://github.com/Radiotherapy-Optimization/Warm-IP}{GitHub repository}. These results demonstrate that appropriately warm-started IP methods can combine the rapid initial progress of first-order methods with the high-accuracy convergence of second-order methods.
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All authors Babak Aslani, Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh

Thursday 8 October

Medical Physics

An anatomically grounded human-scale dynamic model of contraction-driven lymphatic pumping

Chia-Feng Chang, Ayemon Baraka, Egor Sidorov et al. (+1 more)

Lymphangions, the valved muscular segments of lymphatic vessels, pump lymph against an adverse pressure gradient. Current models resolve this pumping in one vessel, a short chain or a regional network, and whole-body human models are passive. We extend the passive whole-body network of a companion static study to the active regime on the same anatomical graph, with intrinsic contraction, dynamic valves and a respiration-gated venous outlet on every vessel. Without fitting the waveform or the contraction amplitude, the network settles into a bounded pumping cycle at the lymphovenous junction, at a clinical pressure of 7.5 to 12.3 mmHg and a drainage of 35 to 50 mm^3/s. Respiration adds a swing of 1 to 2.5 mmHg at the junction and contraction about 1 mmHg inside the duct. Pressure generation is limited more by load than by drive, and no single contraction amplitude fits every vessel. Raising the subclavian venous pressure from 3 to 15 mmHg lifts the deep cervical node from 8.6 to 21.1 mmHg at the weakest drive, a transmission of 1.04 that falls to 0.78 at the strongest, so contraction buffers cervical drainage against venous pressure. The same solver gives the human cervical outlet pressure that cerebrospinal-fluid drainage models prescribe.
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All authors Chia-Feng Chang, Ayemon Baraka, Egor Sidorov, Sabee Molloi

Medical Physics

An anatomically grounded human-scale steady hydraulic model of the lymphatic network

Chia-Feng Chang, Ayemon Baraka, Egor Sidorov et al. (+1 more)

The lymphatic system returns 2 to 3 L of interstitial fluid per day to the venous circulation and drains the central nervous system. Most models of lymph transport describe one lymphangion or a short chain, so they cannot show how body-wide topology, calibre hierarchy and the venous outlet set pressure and flow. We build a passive steady hydraulic model on an anatomically derived graph of the human lymphatic system, with 1010 vertices and 1126 edges expanded to 89,060 sub-edges. Radii follow a Murray cube law, derived both from minimum work and from wall-shear-stress homeostasis. Pressure and flow follow from nodal hydraulic balance over Hagen-Poiseuille conductances, with an exponential wall law, hysteretic valves, Starling leak, node retention and a Windkessel outlet. Active contraction is off, and only the inflow scale is calibrated. Two quantities that are not fitted land in clinical range at the same operating point. Radii fall inside the vessel-class range, from 1.50 mm in the thoracic duct to 0.16 mm in the cervical collectors, and pressures stay below the 50 mmHg cuff scale on all sub-edges. About 49% of the gross load is removed before the outlet, nearly independent of the outflow scale and of the outlet parameters. On the route that drains the central nervous system, 30% of the superficial cervical load reaches the vein, at 10 to 18 mmHg along a segment that cervical-scale models replace with a prescribed outlet pressure. The model is a passive whole-body baseline for contraction-driven and clinical extensions.
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All authors Chia-Feng Chang, Ayemon Baraka, Egor Sidorov, Sabee Molloi

Medical Physics · Cross-listed from cs.LG

Expert-level detection of low-voltage intervals in EEG as a robust biomarker of neonatal encephalopathy

John M. O'Toole, Sean R. Mathieson, Aurel Luca et al. (+4 more)

Background: Discontinuity in neonatal EEG is a critical marker of brain dysfunction but can be difficult to quantify visually. Inter-burst intervals (IBIs) are a key characteristic of discontinuity, yet their definition does not easily translate to AI detection. Objectives: To introduce low-voltage intervals (LVIs), defined exclusively by amplitude and duration, as a context-independent alternative to IBIs, develop an AI detection method for LVIs, and assess their clinical utility as a marker of brain injury. Methods: We developed a ConvNeXt model to detect LVIs and compared its performance with existing methods. We then tested the clinical relevance of detected LVIs across four applications: 1) grading background EEG abnormalities on an open benchmark dataset, 2) classifying clinical hypoxic-ischaemic encephalopathy (HIE) grades and comparing with a normal EEG dataset, 3) seizure prediction, and 4) association with seizure burden. Results: For training and validation, 654 hours of per-channel EEG from 123 neonates were reviewed and 51,162 LVIs were annotated. On held-out validation, ConvNeXt had an AUC of 0.996 and a Matthews correlation coefficient of 0.926. Model-reader agreement exceeded inter-reader agreement ($\Delta \kappa = 0.025$, 95% CI: 0.007 to 0.045, $p<0.001$), attaining expert-level equivalence. On a combined dataset of 444 neonates, percentage LVI showed a strong association with EEG grades (Spearman's $\rho=0.801$), a moderate association with HIE grades ($\rho=0.384$), a weaker association with seizure burden ($\rho=0.244$), and a strong seizure prediction capacity (AUC $=0.872$). Conclusion: AI detection of LVIs achieves expert-level equivalence, whereas quantitative features do not. Automated LVI quantification provides a robust clinical biomarker of neonatal encephalopathy associated with background EEG activity, HIE severity, and seizure risk.
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All authors John M. O'Toole, Sean R. Mathieson, Aurel Luca, Soraia Ventura, Sean Griffin, Geraldine B. Boylan, Robert Hogan

Medical Physics

Deep preferential evolution guided by pairwise comparisons enables motion correction in photoacoustic tomography

Karteekeya Sastry, Yousuf Aborahama, Junhao Zhu et al. (+2 more)

Motion artifacts in three-dimensional photoacoustic tomography (PAT), caused by extended mechanical scanning of sparse arrays, degrade image quality. Since sparse sampling results in low-quality sub-reconstructions, tracking motion directly is challenging. While final image quality could in principle guide artifact correction, conventional regularizers do not accurately reflect photoacoustic image quality. Here, we introduce deep preferential evolution (DPE), a derivative-free optimization framework where a learned image comparator guides evolutionary search over reconstruction parameters. By learning relative quality differences between same-target image pairs rather than absolute quality scores, the comparator generalized more robustly from simulation to in-vivo images (after unlabeled domain calibration) than an absolute scorer. Comparator-based DPE successfully corrected synthetic motion across diverse anatomies and backgrounds, and it mitigated artifacts from natural, unconstrained motion in human palm images. These results demonstrate that pairwise learned comparison can provide a transferable optimization objective for high-dimensional image restoration when labeled experimental training data are scarce.
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All authors Karteekeya Sastry, Yousuf Aborahama, Junhao Zhu, Manxiu Cui, Lihong V. Wang

Wednesday 7 October

Medical Physics

Technical Preparations for the First Carbon-Ion Therapy Facility in the United States

Jun Tan, Xiaoying Liang, Keith M Furutani et al. (+4 more)

Carbon ion radiotherapy (CIRT) provides greater biological effectiveness than conventional photon therapy because of its high linear energy transfer and its ability to induce complex DNA damage. Mayo Clinic Florida is developing the first CIRT facility in the United States, using a synchrotron-based system with dose-driven continuous scanning (DDCS). Although DDCS improves delivery efficiency by keeping the beam on during spot transitions, it also creates the challenge of accurately modeling the dose delivered during beam motion (move dose), which is not fully addressed in current treatment planning systems. In this work, we present a method for accurate simulation of move dose to support Monte Carlo (MC) dose calculations. The method models realistic beam trajectories, including the characteristic hockey stick motion caused by different scanning speeds in the X and Y directions, and accounts for time-dependent beam intensity with linear ramp-up behavior. The beam path is divided into small segments, each represented by a move source with analytically determined position, intensity, and monitor units. Beam intensity fluctuations are also included using a stochastic model based on measurements. Validation using TOPAS simulations for a 430 MeV/u carbon ion beam in a water phantom showed accurate modeling of move dose and the resulting dose distributions. This method provides a practical framework for MC-based dose calculation in clinical CIRT.
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All authors Jun Tan, Xiaoying Liang, Keith M Furutani, Justin Park, Sridhar Yaddanapudi, Bo Lu, Chris J. Beltran

Medical Physics

How Can Technology Improve Acetabular and Pelvic Fractures Management in the Operating Room? A Systematic Review

Marie Le Baron, Martine Pithioux, Stéphane Candoni et al. (+1 more)

In recent years, there has been a proliferation of literature describing new technologies increasingly integrated into the surgical management of pelvic fractures. However, the available data are heterogeneous, scattered, and sometimes limited to small series or single-center studies. This review aims to present new technologies in the field of pelvic and acetabular fractures and explore their potential benefits for surgeons and patients. The goal is to describe current concepts, advantages, and limitations and to open a discussion about future use and development. The search was conducted through Medline, Central and Embase databases from inception to January 2025 following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol. A total of 841 records were reviewed and 115 studies were included according to the inclusion and exclusion criteria. Technologies such as robotics, navigation, patient-specific management, and 3D printing are being developed for the management of pelvic injuries. These technologies demonstrate greater surgical accuracy without increasing complications. In pelvic and acetabular fractures surgery, new technologies are very attractive and are a promising help for management of these complex injuries and need to be improved before being included in routine care.
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All authors Marie Le Baron, Martine Pithioux, Stéphane Candoni, Xavier Flecher

Tuesday 6 October

Medical Physics · Cross-listed from physics.data-an

Data geometry preserves prediction but reshapes explanation

Nicola Amoroso, Mario Caruso, Marianna La Rocca et al. (+8 more)

Across scientific domains, empirical data often give rise to positive semidefinite matrices that encode similarities, couplings or interactions and induce natural geometries. We investigate whether changing the geometry used to compare the same empirical representations preserves subject-level performance and the local structures from which explanations are derived, a question we term the prediction explanation invariance problem. We address this problem across morphometric MRI, fMRI and EEG data by comparing Frobenius and trace geometries applied to the same empirical matrices. Predictive performance was broadly preserved across geometries, but comparable performance did not imply agreement in subject-level decision scores or predicted labels. Predictive similarity also masked geometry-dependent differences in local neighbourhoods, perturbation sensitivities and explanatory rankings. Dimensionality reduction made the two subject-space geometries progressively more concordant, while classification performance and decision-level agreement declined. These results identify data geometry as a hidden degree of freedom in explainability: similar performance does not guarantee invariant decisions or explanations.
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All authors Nicola Amoroso, Mario Caruso, Marianna La Rocca, Loredana Bellantuono, Tommaso Maggipinto, Michele Morelli, Sabina Tangaro, Marco Tatullo, Roberto Bellotti, Ester Pantaleo, Alfonso Monaco

Medical Physics

Laplace-Domain Beamforming for Ultrafast Plane-Wave Imaging

Martin F. Schiffner

Fourier-domain beamforming methods, such as filtered backpropagation (FBP), are beneficial in ultrafast plane-wave imaging due to their computational efficiency and high image quality. These methods use the Fourier diffraction theorem (FDT) for steered plane waves to exactly invert linear scattering models. However, these models rely on simplifying assumptions that degrade image quality. The use of linear transducer arrays, in particular, requires: (i) a two-dimensional space, and (ii) lossless tissues. Herein, Laplace-domain beamforming is proposed. This method retains the computational efficiency of the Fourier-domain methods while improving image quality for linear arrays. Specifically, the method uses a generalization of the FDT, here called Laplace diffraction theorem, to account for three spatial dimensions, finite array element heights, and lossy tissues. A phantom experiment showed that the proposed method improves image uniformity, spatial resolution, and contrast compared to FBP. Using three steering angles, the lateral and axial -6 dB-widths of wires reduced by up to 12% and 25%, respectively, while the contrast of anechoic regions improved by up to 9%.
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Medical Physics

Gold nanorod radioenhancement: interpreting Monte Carlo dose enhancement across geometry, composition, coating, and localization

Ali Taheri, Hans Rabus, Mayeen Uddin Khandaker et al. (+2 more)

Nanoparticle radiosensitization depends on interconnected NP properties, yet geometry, elemental composition, surface coating, and localization are typically studied separately, with their combined biological impact rarely assessed in one framework. Drawing on TOPAS Monte Carlo simulations from PhD research, we consolidated four investigations of metallic nanorods, mainly gold nanorods (AuNRs), examining these parameters across closely linked studies. The findings reveal that each parameter can influence over a distinct spatial range. Nanorod geometry primarily alters the spectrum and distribution of low-energy Auger-Meitner electrons emitted within tens of nanometers. Elemental composition induces significant near-field dose enhancement that rapidly attenuates and becomes negligible beyond roughly 1 um. Surface coatings reduce the fluence of secondary electrons below 3.5 keV, absorbed within about 150 nm of the surface, lowering physical dose contribution by 1-7%. Since coatings predominantly remove low-energy electrons, radiolytic yield changes through a shift in the electron energy spectrum, not directly following dose response. At the vascular scale, the enhanced dose region extends to approximately 10 um from the vessel wall, meaning NP localization determines where the biological target sits relative to radiation sources. Collectively, no single design parameter serves as a universal predictor of radiosensitization. Translating physical radioenhancement into biological effect depends on whether the target lies within each parameter's effective range. Furthermore, charged-particle equilibrium (CPE) correction, applied where beam confinement necessitated it, substantially alters calculated dose enhancement ratios. Consequently, scoring distance and CPE-corrected values should be explicitly reported to ensure comparability across studies.
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All authors Ali Taheri, Hans Rabus, Mayeen Uddin Khandaker, Farhad Moradi, David Andrew Bradley

Medical Physics

A Multimodal Hyperspectral and Laser Speckle Imaging Platform for Simultaneous Monitoring of Spinal Cord Oxygenation, Perfusion and Metabolism

Junda Wang, Luca Giannoni, Ayse Gertrude Yenicelik et al. (+3 more)

Hyperspectral imaging (HSI) enables spatial mapping of haemoglobin oxygenation and cytochrome-c-oxidase (CCO) redox changes in exposed neural tissue. In this study, we present a technical upgrade of an existing HSI platform by the integration of laser speckle contrast imaging (LSCI), enabling contemporaneous assessment of oxygenation, oxidative metabolism, relative perfusion and a derived relative oxygen metabolic index in exposed spinal cord in a rat preclinical model. The upgraded system (hNIR+) uses a shared optical path and a single camera to acquire HSI and LSCI images from the same field of view using a sequential acquisition workflow. Hyperspectral images are acquired at 11 discrete wavelengths (600, 630, 665, 784, 800, 818, 835, 851, 868, 881, and 894 nm) to estimate changes in oxygenated haemoglobin (HbO2), deoxygenated haemoglobin (HHb) and oxidized CCO (oxCCO). LSCI is implemented using 632.8-nm coherent illumination to generate relative blood-flow index (rBFI) maps. The LSCI subsystem was validated using a controlled blood-flow phantom, where the LSCI-derived inverse speckle contrast index showed a strong positive linear relationship with pump-controlled flow. The upgraded platform was then evaluated in proof-of-concept observations of the rat spinal cord under normoxia, hypoxia and recovery conditions. Representative multimodal maps and ROI-based time-course analysis showed clear dynamic responses in HbO2, HHb, oxCCO and rBFI during oxygen challenges that were consistent with the expected physiological responses of the spinal cord during hypoxia, hyperoxia and subsequent recoveries. Overall, these results demonstrate that integrating LSCI into HSI extends the platform to multimodal and simultaneous monitoring of haemodynamic-metabolic coupling.
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All authors Junda Wang, Luca Giannoni, Ayse Gertrude Yenicelik, Eleni Giama, Frederic Lange, Ilias Tachtsidis

Medical Physics

A No-Go Framework for Coarse-Grained Effect Prediction in Boron Neutron Capture Therapy: Structural Identifiability Limits and Microscopic Coverage

Atsushi Fujimura, Shuichi Furuya and Yasuaki Ichikawa

We establish when coarse-grained observables uniquely determine an expectation-based biological response in boron neutron capture therapy (BNCT). Microscopic target populations are represented by probability distributions, while retained observables are finitely many population-averaged linear descriptors. For an admissible class containing all finitely supported microscopic distributions, exact distribution-free identification holds if and only if the single-target response kernel lies in the span of the constant function and retained descriptors. Thus mean dose, mixed-field component means, and finite moment sets are not generally sufficient under unrestricted microscopic heterogeneity. We also derive irreducible ambiguity and approximation bounds, sharp partial-identification intervals for bounded non-increasing convex survival kernels, a treatment-ranking criterion, and lower-tail and high-exposure bounds. A fixed-total-exposure temporal model distinguishes transient re-sampling from persistent target-specific underexposure, and a marked-Poisson model shows that separate frequency and event-quality marginals need not determine survival. The framework clarifies which microscopic information is lost through BNCT coarse-graining while leaving room for approximation, partial identification, and prediction under independently justified model restrictions.
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Monday 5 October

Medical Physics · Cross-listed from physics.optics

Digital confocal imaging in holographic optical coherence tomography at high space-bandwidth product

N. P. Klooster, S. A. Thakur, F. Zeisberger et al. (+4 more)

Full-field Fourier-domain optical coherence tomography (FF-FD-OCT) enables rapid volumetric imaging but lacks the confocal gating inherent to point-scanning OCT. By acquiring volumes under multiple oblique illuminations, a digital confocal volume can be synthesized in post-processing, a technique originally developed within the framework of reflection matrix imaging (RMI). Existing implementations, however, are often time-domain, off-axis, or use a Michelson interferometer, which reduces sensitivity, speed and the usable space-bandwidth product (SBP). Here, we present an oblique-illumination FF-FD-OCT system in a Mach-Zehnder configuration. This setup enables optimal use of SBP, providing up to a fourfold increase in effective acquisition throughput. In addition, we pose the scattering and aberrations as an overdetermined system, allowing a closed-form solution of an alternating least squares problem. The resulting iterative optimization is equivalent to the state-of-the-art closed-loop accumulation of single scattering (CLASS) algorithm. We demonstrate the setup and reconstruction method in lens tissue, a PSF phantom, a USAF target, and a model eye. The resulting digital confocal volumes provide locally optimized focusing and detection quality, and show improved resolution and signal-to-noise ratio (SNR) compared to conventional FF-FD-OCT. The technique combines the advantages of FF-FD-OCT and confocal OCT while mitigating the limitations of both approaches.
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All authors N. P. Klooster, S. A. Thakur, F. Zeisberger, J. R. Hagen, S. Eggert, U. Najar, D. Hillmann

Medical Physics

A software tool for parametric collimator creation for linac-based preclinical irradiation studies

Joseph B. Schulz, Dixin Chen, Lloyd Emmanuel Kamole Ghomsi et al. (+5 more)

Designing custom Cerrobend collimators for linac-based preclinical electron irradiation is labor intensive and susceptible to design inconsistencies. We developed Collimator Creator (CC), an open source parametric workflow that converts aperture dimensions and jig offsets into printable STL models for a collimator mold, collimator shell, Cerrobend holder, and beam degrader. Two designs were fabricated and characterized: a 4.0 x 1.5 cm$^2$ bilateral lung collimator centered on the central axis and a 1.5 x 1.5 cm$^2$ unilateral lung collimator with a 7.5 mm jig offset, each with a 15 mm thick Cerrobend collimator and a 10 mm PLA degrader. Kilovoltage planar images were used to assess aperture geometry and casting uniformity. Radiochromic film was used to measure full width at half maximum (FWHM) and 80%-20% penumbra under conventional and ultra high dose rate (UHDR) electron delivery on a Varian TrueBeam, and off axis leakage was measured with an ionization chamber at conventional dose rate. The cast Cerrobend apertures deviated by less than 0.2 mm from their specified designs. FWHM values were within 3% of the nominal field dimensions, and penumbra ranged from 0.73 to 1.05 mm under conventional and UHDR delivery. Crossline leakage 2 cm beyond the collimator edge was below 2% for both collimators at conventional dose rate. Parametric collimator generation standardized digital design inputs for the two evaluated rectangular linac-based electron fields. Further work will assess specimen-level dosimetry, additional aperture geometries, and Monte Carlo integration.
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All authors Joseph B. Schulz, Dixin Chen, Lloyd Emmanuel Kamole Ghomsi, M. Ramish Ashraf, Lawrie Skinner, Edward Elliot Graves, Billy W. Loo Jr, Stavros Melemenidis

Medical Physics

A Differentiable Brain Tumor Mass Effect Solver

Marco L. Wittrich, Michal Balcerak, Lucas Zimmer et al. (+6 more)

A growing brain tumor mechanically deforms the surrounding healthy brain through mass effect. This compression and displacement of tissue affects both patient prognosis and treatment planning, so biophysical models of tumor growth must account for this deformation. Established mass-effect models are partial differential equation (PDE) solvers that couple growth to elasticity and calibrate parameters per patient, at substantial implementation, runtime, and calibration cost. We ask how much of this deformation a fully differentiable energy-based model can recover, and introduce a potential-spring model: a regular grid over the brain is driven outward by a tumor-concentration potential and held by an elastic spring lattice with tissue-specific stiffness. It shares the tumor-gradient driving force of continuum elasticity but uses a single global parameter and no per-patient inversion, minimized end-to-end by gradient descent. We benchmark it against established solvers by applying each displacement field to a healthy atlas and measuring tissue overlap with the patient's own segmentation on 134 BraTS patients. Our model yields the largest overall local overlap improvement at up to 100$\times$ shorter computation time, establishing a lightweight, differentiable solver for tumor mass effect. Because our model obeys mechanical laws and reflects the tumor-induced tissue loading, it remains physically plausible, a prerequisite for clinical use.
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All authors Marco L. Wittrich, Michal Balcerak, Lucas Zimmer, Ivan Ezhov, Björn Menze, Marie-Christin Metz, Nicole Tueni, Benedikt Wiestler, Jonas Weidner

Medical Physics

The FetalSenseM V2: a wearable and wireless, multi-wavelength NIRS device for continuous monitoring of placental oxygenation and metabolism

Luca Giannoni, Frederic Lange, Musa Talati et al. (+9 more)

We present here the FetalSenseM V2 (FSM V2), a wireless and wearable, multi-wavelength, NIRS device, based on LED illumination at six NIR wavelengths (782, 800, 818, 830, 848 and 888 nm). It utilises two sources located on the flexible wings of the sensor body, and three photodiodes placed symmetrically in its centre at 1 cm from each other. The configuration provides two sets of three source-to-detector distances (SDS) at 3, 4 and 5 cm. FSM V2 allows estimation of dynamic, relative changes in placental concentrations of HbO2, HHb and oxCCO. At the same time, the dual set of SDS also enables the use of multi-distance algorithms, such as spatially-resolved spectroscopy (SRS) and Dual Slope (DS), for estimating placental oxygen saturation (PlO2). FSM V2 is the first example of a new generation of wearable NIRS devices, paving the way for smart and advanced monitoring of placental health at bedside. The FSM V2 was successfully validated on a bench-testing, metrological platform based on optical phantoms, as well as against a gold-standard, time-domain (TD) NIRS system, before moving to preliminary examples of clinical application and usability on pregnancy monitoring trials at University College Lon-don Hospital (UCLH), conducted as part of an in vivo proof-of-concept study.
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All authors Luca Giannoni, Frederic Lange, Musa Talati, Uzair Hakim, Darshana Gopal, Angelos Artemiou, Niccole Ranaei-Zamani, Olivia Newth, Sarah Johnson, Maeve McGaughey, Subhabrata Mitra, Ilias Tachtsidis

Sunday 4 October

Medical Physics

MRI-Free CT-to-Ultrasound Skull Registration in Transcranial Focused Ultrasound using CMUT based Integrated Therapeutic and Imaging Arrays

Reza Pakdaman Zangabad, Sai Vikas Satyanarayana, Costas D. Arvanitis et al. (+1 more)

Accurate skull-to-array registration is essential for transcranial focused ultrasound (tFUS) because CT-derived skull models must be aligned with the physical-array coordinate system to support patient-specific aberration correction. Current workflows typically use MRI and/or external tracking to establish this spatial relationship, adding imaging infrastructure and coordinate transformations to the treatment workflow. Here, we describe an MRI-free CT-to-ultrasound registration framework using a hybrid hemispherical CMUT tFUS array that combines a sparse therapeutic array with an integrated CMUT US-Cross imaging array. The therapeutic array provides pulse-echo measurements of skull location, while the US-Cross array provides local high-resolution images of the skull surface. The approach was evaluated using a CT-derived outer cortical skull surface across a 25-pose matrix with 10-mm lateral offsets between the skull and array centers and +/-5 degree angular perturbations. Five randomized radial-noise seeds were applied to therapeutic pulse-echo measurements to model measurement or element-placement errors, yielding 125 pose-seed realizations per noise and active-element setting. US-Cross imaging features were generated using Field II and delay-multiply-and-sum plane-wave compounding. Four registration modes were evaluated: Therapeutic only, US-imaging only, Sequential, and Fused registration. Fused registration yielded the best overall performance, with a median total displacement error of 0.271 mm [0.169-0.420] and a median rotation error of 0.904 degrees [0.432-1.639]. These results support an all-ultrasound-based approach using a hybrid CMUT tFUS array for MRI-free CT-US skull registration.
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All authors Reza Pakdaman Zangabad, Sai Vikas Satyanarayana, Costas D. Arvanitis, F. Levent Degertekin