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Wednesday 19 August

Medical Physics

Whole-skull acoustic transparency from a single time-reversal solve for reciprocity-based transducer placement and aperture optimization in transcranial focused ultrasound

Gianmarco Pinton

Transcranial focused ultrasound is limited by the skull, whose thickness, density and curvature aberrate and attenuate the beam in a position- and target-dependent way, making the choice of where to couple a transducer for a given deep target a central planning problem. This work shows that a single full-wave time-reversal solve resolves it. A virtual point source at the target radiates outward through a CT skull model, and by acoustic reciprocity the time-reversed field gives the transmit coupling of every point on the skull surface at once (a per-patch skull transparency map) and, in the same pass, the per-element signals of any array. For a phased array, time reversal conjugates the skull aberration, so the optimal placement maximizes the delivered energy, a surface integral over the aperture; a single element instead follows a coherent score mixing delivered energy with phase coherence, and the two optimizers select different windows. Placement, aperture size and orientation are then optimized by searching this single recorded map in seconds, with no per-candidate wave solve. The map is computed on a dry-skull micro-CT model for the left dentate nucleus with a 1 MHz heterogeneous Fullwave 2 solver at 6.16 points per wavelength with bone attenuation. A 120 degree occipital array refocuses within 0.25 mm of the dentate at 20.7 Pa per 1 Pa of per-element drive, and a 64 mm spherical transducer seated in the delivered-energy-optimal suboccipital window (27 mm from the target) refocuses at 7.9x gain; the same procedure focuses the thalamus at 15.2x and the dorsal anterior cingulate at 11.4x. The aberration correction raises the on-target peak 7.5x in pressure (56x in intensity) over geometric focusing, which mis-steers the focus by 4.3 mm. The same field measures the aberration's few-millimeter coherence length, which sets the required placement and target-localization accuracy.
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Medical Physics

A Reference System for Open Source Portable Low-Field MRI

David Schote, Helge Herthum, Umberto Zanovello et al. (+8 more)

Despite its renewed attention, the pathway to point-of-care portable low-field MRI systems remains challenging, limiting adoption across research groups. Incomplete documentation limits reproducibility, causing redesign and complicating cross-system comparison. Moreover, non-standardized testing and characterization complicates ethical approval for clinical studies. We present an open-source reference system for portable low-field MRI designed to support replication, reproducibility, benchmarking, and quantitative comparison. The system is fully open source, based on a ~50 mT permanent magnet, and integrated with a cloud-native acquisition platform. Pulseq-based calibration, characterization, and imaging sequences assessed noise level, eddy currents, image-based SNR, and geometric accuracy. Quantitative T1, T2, and B0 mapping sequences were developed and evaluated against reference values. Initial results from independent replications at two sites were compared. The system reached a noise level of 1.4 relative to the thermal noise floor and short eddy-current decay constants of 27-32 us across all gradient channels. Geometric deviations were below 2 mm over the field of view. Image-based SNR were consistent between the independent replications. Measured T1 values closely matched specified values, with an average absolute error of 3.1(1.8)%, while T2 values were overestimated by 10.4(5.8)%. Simulations showed only marginal errors for both quantities, suggesting experimental error sources for T2 mapping. The reference system combines openly documented hardware, software, calibration procedures, phantoms, quantitative MRI, and simulation tools in a reproducible ecosystem, aiming to support cross-site comparability, reproducible research, and collaborative development of future portable low-field MRI technologies.
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All authors David Schote, Helge Herthum, Umberto Zanovello, Julia Pfitzer, Ivo Jutte, Jan Gregor Frintz, Ilia Kulikov, Sebastian Littin, Frank Seifert, Christoph Kolbitsch, Lukas Winter

Medical Physics

Ultra-wideband MRE of the human liver and spleen for viscoelastic model identification in hepatic inflammation

Jakob Schattenfroh, Michael Fedders, Steffen P. Häseli et al. (+10 more)

Magnetic resonance elastography (MRE) is established for noninvasive assessment of liver fibrosis. Conventional abdominal MRE is typically limited to 40-60 Hz. Lower frequencies remain largely unexplored, particularly with regard to hepatic inflammation. We developed ultra-wideband MRE covering 5-80 Hz to investigate frequency-resolved viscoelastic dispersion of the liver and spleen and to identify biomechanical markers of hepatic inflammation. Following phantom validation, nine healthy volunteers and nine patients with inflammatory liver disease were examined at 12 frequencies. Spatiotemporal phase unwrapping and frequency-adaptive wavefield preprocessing enabled reconstruction of shear wave speed (SWS), penetration rate (PR), and loss angle ($\phi$). Six rheological models were evaluated. The largest inflammation-associated changes were observed at frequencies below 20 Hz: $\phi$ increased by 63% (p<0.001), PR decreased by 37% (p=0.003), and SWS increased by 8% (p=0.008), indicating predominantly dissipative, rather than stiffness-related, changes and a shift toward fluid-like behavior with minor stiffness changes in the lower frequency regime. The rheological springpot model with serial dashpot provided the best fit and revealed distinct dispersion functions for liver and spleen. In patients, springpot elastic modulus increased (101%, p=0.001), while viscosity and springpot power-law exponent decreased (52%, p=0.002 and 58%, p<0.001) suggesting a shift from soft-fluid to stiff-solid liver properties. Ultra-wideband MRE revealed that inflammatory liver disease is associated with property shifts toward stronger dissipation and fluid-like behavior at low frequencies while displaying solid-like behavior at higher frequencies. Ultra-low frequency MRE may provide a diagnostic window into inflammation-associated liver viscoelasticity without full rheological modeling.
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All authors Jakob Schattenfroh, Michael Fedders, Steffen P. Häseli, Tobias Puengel, Yanglei Wu, Tom Meyer, Hossein S. Aghamiry, Tim Ricken, Münevver Demir, Frank Tacke, Jing Guo, Rolf Reiter, Ingolf Sack

Tuesday 18 August

Medical Physics

Angle-domain null subtraction imaging from beamformed plane-wave data

Henri Leroy

Null subtraction imaging (NSI) narrows the apparent lateral response by combining fields produced with a zero-mean apodization and two DC-offset variants. Usually, NSI requires channel data and flexible beamformers (Receive-NSI). We investigate Angle-NSI, which operates on per-angle images during coherent plane-wave compounding. A matrix formulation was used to distinguish receive-domain and angle-domain null subtraction expressions. The method was evaluated using a simulated point target, experimental resolution phantom targets, an open microbubble (MB) traces dataset and two in vivo carotid acquisitions. Angle sampling, noise, phase jitter and target position were swept in simulation. A synchronized GPU benchmark compared the complete reconstructions. Six beamforming methods were compared: delay-and-sum (DAS), coherence-factor-weighted DAS (CF-DAS), minimum variance beamforming (MV), delay-multiply-and-sum (DMAS), Receive-NSI and Angle-NSI. Angle-NSI reduced the simulated -6 dB lateral width from 0.226 mm for DAS to 0.116 mm, compared with 0.009 mm for Receive-NSI, while the axial width was 0.720 mm for these three methods. The lateral narrowing was confirmed on an experimental resolution phantom. Angle-NSI had shorter reconstruction time than Receive-NSI and the lowest post-delay processing time among the nonlinear methods. In power Doppler, microbubble trace widths were reduced by 50.2% for Receive-NSI and 30.9% for Angle-NSI compared to DAS. On a phantom and in vivo, both NSI variants reduced generalized contrast-to-noise ratio relative to the conventional methods. Angle-NSI provides simple post-processing of per-angle beamformed images. It narrows the apparent lateral response at low computational cost, at the expense of B-mode detectability: this makes it a well-suited alternative for high-resolution power Doppler applications.
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Medical Physics · Cross-listed from eess.IV

Primitive Representation Learning for Unsupervised Dynamic Contrast Enhanced MRI Reconstruction

Veronika Spieker, Wenqi Huang, Cemre Ariyurek et al. (+5 more)

Reliable quantitative analysis of dynamic contrast-enhanced MRI requires high-quality spatiotemporal reconstructions at high undersampling rates. Scan-specific reconstructions using Gaussian and Gabor primitives have shown promising results without the need for large training datasets, but have not addressed the additional dimension of dynamic contrast. We propose a multi-dimensional, primitive based framework for dynamic contrast-enhanced MRI reconstruction that disentangles the underlying anatomy, the dynamic contrast enhancement, and residual motion into separate temporal basis functions, thereby enabling a geometrical interpretation of the representation. We show that this architecture achieves performance competitive with conventional reconstruction methods, both in reconstruction quality and in the accuracy of extracted aorta and kidney enhancement curves. The modular tier design extends naturally to additional dynamic factors and higher acceleration rates. Code available at https://github.com/compai-lab/2026-GaborDCE-spieker.
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All authors Veronika Spieker, Wenqi Huang, Cemre Ariyurek, Liam Timms, Daniel Rueckert, Onur Afacan, Julia A. Schnabel, Sila Kurugol

Medical Physics · Cross-listed from eess.IV

Harnessing Magnitude-Only and Complex Measurements for Improved Dynamic MRI Reconstruction with Learned Priors

Mahdi Saberi, Yaşar Utku Alçalar, Merve Gülle et al. (+2 more)

MRI reconstruction methods for undersampled k-space data naturally utilize complex-valued measurements. Parallel developments in sparse phase retrieval have shown that magnitude-only measurements may provide complementary information for signal recovery. However, their use in MRI reconstruction remains largely unexplored, due to lack of practical settings where informative magnitude measurements can be obtained without additional scan time. In this work, we investigate the use of auxiliary k-space magnitude information for accelerated steady-state dynamic MRI reconstruction, and demonstrate strong consistency of k-space magnitudes across time-frames. Building on this observation, we propose $\mathbb{C}+\text{Mag}$, a magnitude-informed physics-driven deep learning reconstruction method. The proposed method employs an ADMM-based unrolling framework with a novel magnitude-aware data-fidelity formulation, where quadratically smoothed optimization and momentum-based updates are introduced to address the non-differentiability and non-convexity of the magnitude constraints. Experiments on retrospectively undersampled cine MRI and phase-contrast flow MRI datasets, as well as prospectively undersampled real-time cine MRI acquisitions, demonstrate improved artifact suppression, sharper anatomical recovery, and better preservation of phase information compared to conventional PD-DL methods, which is further supported through blinded expert reader evaluations.
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All authors Mahdi Saberi, Yaşar Utku Alçalar, Merve Gülle, Chetan Shenoy, Mehmet Akçakaya

Medical Physics

Flexible Piezoresistive Yarn Pressure Sensor for Arterial Blood Pressure Waveform Measurement

Rizal Maulana, Ádám Rák, Sándor Földi et al. (+1 more)

The arterial blood pressure (ABP) waveform contains essential information concerning the hemodynamic status and its relation to the diagnosis of cardiovascular conditions. Therefore, the continuous monitoring of the ABP waveform has become important. A measurement system that offers a non-invasive approach and high accuracy in detecting morphological details of the ABP waveform is needed. In this study, we introduce a flexible piezoresistive yarn (FPY) pressure sensor for continuous non-invasive ABP waveform measurement. The sensor was experimentally validated using two scenarios: measurements on a hardware simulator and at an arterial site. The simulator measurement aimed to assess the sensor's performance in detecting consistent waveforms, while the arterial site measurements evaluated the sensor's performance in measuring ABP waveforms corresponding to the cardiovascular cycle. The simulator measurement results showed high repeatability, reproducibility, and accuracy relative to the reference signal at the upper limit of realistic force magnitude, as measured by the correlation metric: 0.9999 $\pm$ 0.0002, 0.9994 $\pm$ 0.0002, and 0.9731 $\pm$ 0.0027, respectively. The correlation value derived from measurements at the arterial site compared with measurements using a 3D force sensor as a reference sensor was 0.9880 $\pm$ 0.0035. Based on our results, the FPY pressure sensor can be used as an innovative solution for monitoring ABP waveforms and has further potential to be developed as a diagnostic device for evaluating cardiovascular conditions.
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All authors Rizal Maulana, Ádám Rák, Sándor Földi, György Cserey

Medical Physics

LV-CARE-Diff: A Conditional Anatomy-Aware Diffusion Model for Left Ventricular Shape Reconstruction and Function Quantification from Ultra-Sparse Cine Slices

Xinwang Li, Yu Lian, Bowei Liu et al. (+5 more)

Left ventricular functional quantification is an essential examination and is routinely performed using cardiovascular magnetic resonance (CMR) cine imaging. However, conventional CMR cine protocols require the acquisition of multiple short-axis (SAX) slices to cover the entire left ventricle (LV) along with two long-axis (LAX) slices, which is time-consuming and places a considerable burden on patients who are unable to sustain repeated breath-holds, limiting its suitability for large-scale early screening. In this study, a Conditional Anatomy-Aware Diffusion Model (LV-CARE-Diff) was developed using a coarse-to-fine strategy to reconstruct the complete LV shape from ultra-sparse cine slices, namely three short-axis and two long-axis slices, with the aim of accelerating CMR cine examination. LV-CARE-Diff employs a 3DUNet to generate a coarse initial shape, which is subsequently refined through a residual diffusion model. A condition-guided input incorporating imaging plane orientation and positional metadata was constructed to enable spatial awareness, and a multi-objective training strategy jointly supervising shape, function, and anatomy was incorporated to guide high-fidelity reconstruction. LV-CARE-Diff was compared against a standalone 3DUNet, a standalone diffusion model, and a 3D UNet with diffusion-based refinement. Testing results indicated that complete LV shape could be robustly reconstructed by all deep learning models, with the highest reconstruction performance achieved by the proposed LV-CARE-Diff. Deep learning models reconstructing LV shape from sparse cine slices preserved 96% of functional quantification accuracy while reducing imaging time by 73%. The LV-CARE-Diff framework established in this study enables ultra-sparse cine acquisition to shorten CMR examination duration without sacrificing quantitative functional accuracy.
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All authors Xinwang Li, Yu Lian, Bowei Liu, Yifei Jiang, Jingjing Xiao, Haiyan Ding, Xiangchuang Kong, Rui Guo

Sunday 16 August

Medical Physics

Low-rank modal endpoints from beat-resolved retinal arterial Doppler holography velocity waveforms characterize the response to flicker provocation

Sienna O'Shea, Maxime Boy Arnould, Adrien Gordon et al. (+3 more)

Conventional retinal flicker endpoints quantify changes in diameter, mean velocity, or flow but do not capture the modal concentration of the cardiac velocity waveform during neurovascular stimulation. Here, beat-resolved retinal Doppler holography and low-rank modal decomposition are combined to derive compact arterial endpoints from unfiltered arterial segment-velocity waveforms sampled across beats and vessel locations. For each acquisition, locally centered waveforms are assembled into a common matrix and decomposed by singular-value decomposition (SVD). Robust summaries quantify total pulsatile scale, modal amplitude, residual amplitude, mean-to-pulsatile balance, and singular-spectrum dimensionality; the same construction can also be applied descriptively to individual beats. We demonstrate the framework using 33 temporally ordered Baseline~1/Flicker/Baseline~2 acquisitions from one eye. Relative to the pooled baselines, 13-Hz flicker was associated with lower centered-waveform RMS scale $R_0$ and leading-mode amplitude $A_1$, and with higher robust residual-amplitude ratios $\rho_1$ and $\rho_2$, mean-to-pulsatile ratio MPR, effective rank, and participation ratio; these contrasts showed exploratory within-session separation after Holm adjustment. No evidence of differences in the absolute residual amplitudes $R_1$ and $R_2$ was detected; together, these observations are consistent with reduced concentration in the leading acquisition-specific arterial pulse mode rather than an increase in absolute residual pulsatility.
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All authors Sienna O'Shea, Maxime Boy Arnould, Adrien Gordon, Yann Fischer, Zacharie Auray, Michael Atlan

Saturday 15 August

Medical Physics

Proposal of a consistent value for the mean excitation energy of liquid water using advanced modeling, detailed simulations and precission proton Bragg curves

Pablo de Vera, Isabel Abril, Flávio Matias et al. (+3 more)

Protontherapy precision depends on accurately knowing the stopping power of liquid water, as it is the most abundant component of soft body tissues. Difficulties when working with volatile liquids have led to a long-standing debate regarding the values of the stopping power and the mean excitation energy $I$ of liquid water. The equivalence between the stopping power of liquid water and amorphous ice per unit mass density across all clinically relevant proton energies opens the possibility to obtain a reliable estimation of the $I$-value of liquid water. In this work, we employ two complementary theoretical methodologies to assess the proton stopping power of water. The MELF-GOS (Mermin Energy Loss Function - Generalized Oscillator Strengths) approach, based on the perturbative dielectric formalism, serves as an accurate reference for sufficiently high energies, while the novel non-perturbative TDDFT-Penn (time-dependent density functional theory - Penn) method ensures accuracy for energies even below the stopping maximum. These stopping-power values were incorporated into the simulation code SEICS (Simulation of Energetic Ions and Clusters through Solids) to evaluate proton Bragg curves from $1$ to $230$ MeV. Comparisons with available precise depth-dose measurements provide critical insights that help establish the consistent value $I = 79.4$ eV for liquid water, providing robust physical grounds for improving range prediction for treatment planning.
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All authors Pablo de Vera, Isabel Abril, Flávio Matias, Julian M. B. Shorto, Hélio Yoriyaz, Rafael Garcia-Molina

Medical Physics

Whole Blood-Based Point-of-Care Assay for Single-Tier Lyme Disease Testing

Mihye Lee, Rajesh Ghosh, Artem Goncharov et al. (+10 more)

Rapid point-of-care diagnostics that operate directly on whole blood can accelerate clinical decision-making by bypassing complex sample preprocessing and centralized laboratory infrastructure. However, most serologic assays still require serum or plasma, limiting near-patient deployment. This challenge is particularly evident for Lyme disease, whose diagnosis relies on centralized two-tier serology. Here, we present a whole-blood multiplexed vertical flow assay (WB-xVFA) that performs single-tier Lyme serology directly from 50 microliter of whole blood. The assay combines multilayer blood filtration with a peptide-patterned nitrocellulose membrane to separate cellular components and detect Lyme-associated IgM/IgG responses on a cartridge. Coupled with smartphone-based imaging and machine-learning analysis, the WB-xVFA provides results in 20 min. The assay remained robust across hematocrits up to 60% and sample volumes ranging from 25 to 100 microliter. In blinded testing of 62 whole-blood measurements, it achieved ~97% sensitivity and specificity, demonstrating the feasibility of rapid, near-patient whole-blood Lyme serology.
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All authors Mihye Lee, Rajesh Ghosh, Artem Goncharov, Rui-Chian Tang, Barath Palanisamy, Gyeo-Re Han, Adrian Anaya, Elizabeth J. Horn, Paul M. Arnaboldi, Raymond J. Dattwyler, Omai B. Garner, Aydogan Ozcan, Dino Di Carlo

Medical Physics · Cross-listed from physics.acc-ph

Relative and absolute dosimetric commissioning of the ELIMAIA–ELIMED laser-driven proton beamline at 23.4 MeV

G.A.P. Cirrone, G. Petringa, A. Kurmanova et al. (+12 more)

The development of laser-driven proton beamlines for biomedical and radiobiological applications requires traceable dosimetry and reliable online monitoring at the irradiation point. In this work, we report the relative and absolute dosimetric commissioning of the ELIMAIA–ELIMED laser-driven proton beamline at ELI Beamlines using an energy-selected proton beam with an average energy of about 24~MeV. Radiochromic-film measurements were used to characterize the transverse dose distribution, the depth–dose profile, and the proton energy spectrum at the irradiation point. The reconstructed spectrum was centred at $23.45~\mathrm{MeV}$ with a FWHM of $2.60~\mathrm{MeV}$, while the transverse dose distribution showed an approximately $5.5~\mathrm{mm}$ field size with a millimetre-scale homogeneous region. The Faraday Cup was used as the absolute reference detector for dose to water determination and for cross-calibrating the Dual-Gap Ionization Chamber, which was operated as the primary online dose monitor. The Integrating Current Transformer and Secondary Electron Monitor were evaluated as upstream relative beam monitors. An independent RCF–FC dose comparison performed over fifty consecutive shots yielded $30.45 \pm 3.5~\mathrm{cGy}$ from the FC and $36.46 \pm 1.8~\mathrm{cGy}$ from the EBT3 film. Dedicated G4ELIMED Monte Carlo simulations showed that the RCF positioned upstream of the FC perturbs the FC measurement through proton losses outside the FC acceptance and through an increase in the effective beam area at the FC entrance. Applying the resulting correction factor, $C_{\mathrm{MC}}=1.109$, reduced the residual difference between the FC- and RCF-derived doses to about $7\%$. These results establish the dosimetric chain of the ELIMAIA–ELIMED beamline under the present low-fluence commissioning conditions and identify the operational limits of the online monitoring system.
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All authors G.A.P. Cirrone, G. Petringa, A. Kurmanova, R. Catalano, A. Amato, A. Pappalardo, M.G. Guarrera, F. Schillaci, P. Blaha, F. Grepl, M. Tryus, A. Velyhan, L. Giuffrida, D. Margarone, G. Cuttone

Friday 14 August

Medical Physics · Cross-listed from eess.IV

UMPIRE-Net: Unrolled Magnitude-Phase Regularization Network for Accelerated MRI

Mahdi Saberi, Toygan Kiliç and Mehmet Akçakaya

MRI reconstruction from undersampled k-space measurements is an ill-posed inverse problem. Physics-driven deep learning (PD-DL) methods have shown strong performance for this task by combining the MRI forward model with learned image regularization within algorithm-unrolling frameworks. However, most existing PD-DL methods reconstruct complex-valued images directly, thereby implicitly coupling magnitude and phase within a single learned representation. This coupled regularization may be suboptimal in reconstruction settings where accurate phase modeling plays an important role, such as partial Fourier (PF) imaging, where recovery of the omitted asymmetric k-space measurements depends on the underlying image phase. In such scenarios, explicit modeling of magnitude and phase as separate components may reduce the reliance on externally estimated or predefined phase information. To this end, we propose UMPIRE-Net (Unrolled Magnitude-Phase In REgularization Network), a PD-DL method that introduces separate learned regularizers for magnitude and phase components, together with a novel data-fidelity formulation that enforces measurements consistency. We evaluate UMPIRE-Net for accelerated MRI with PF across different datasets and acceleration factors. Experimental results demonstrate that our proposed method improves reconstruction quality compared with a conventional complex-valued PD-DL baseline, yielding sharper images and reduced artifacts. Code available at: https://github.com/MahdiSaberii/UMPIRE-Net
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Medical Physics

MRI-guided cardiac radiotherapy using a 1.5 T MR-linac: surveying emerging patterns of care

O. Akdag, S. Mandija, J. Pomp et al. (+11 more)

Background: Cardiac tumours are rare and treated by surgical resections, which are complex, invasive and carry procedural risks. MRI-guided radiotherapy (MRgRT) noninvasively facilitates conformal dose deliveries using soft-tissue imaging and adaptive radiotherapy techniques. Aim: To assess the application of MRgRT for cardiac tumours, we conducted a patterns-of-care analysis with users of the 1.5T MR-linac. Materials & methods: A survey was distributed to users of the 1.5T MR-linac that treated patients with cardiac tumours. The survey included 30 questions concerning the patient cohort, imaging, treatment planning/simulation, radiotherapy treatment and treatment outcome. Results: Users from six international institutes completed the survey reporting twelve cardiac MRgRT treatments between 2021-2024. The median age[range] of the patients was 59[16-81] years with 50% of the cases concerning the treatment of primary tumours. The prescribed dose ranged between 30-60 Gy, with 30 Gy being prescribed the most (59%). In 75% of the cases, the treatment plans were delivered in five fractions with 6-8 Gy per fraction. Daily images were acquired with T1- and T2-weighted MRI and respiratory motion monitoring was performed in 92% of the cases using cine imaging. A single case was treated with intrafraction motion management using a novel vendor-provided gating solution on the MR-linac. Treatment outcomes were reported for 50% of the cases. All, but one case, attained local control using MRgRT without serious adverse events (grade$\geq$3). Conclusion: This study provides real-world insights into the feasibility and early outcomes to aid the development of cardiac MRgRT treatment recommendations and protocol harmonization.
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All authors O. Akdag, S. Mandija, J. Pomp, M.P.W. Intven, X. Chen, J. Yang, S. Oh, M. Trombetta, H. Tan, J. De Leon, M. Jameson, E. Efe, C. Önal, M.F. Fast

Medical Physics

Birth of the Coil: another Milestone towards a fully reproducible low-field MRI scanner for head-imaging

Umberto Zanovello, Julia Pfitzer, Ariane Ernst et al. (+5 more)

Low-field magnetic resonance imaging (MRI) provides an accessible, portable, and low-cost alternative to high-field scanners, expanding diagnostic imaging to point-of-care settings. However, widespread adoption is fundamentally hindered by a severely reduced signal-to-noise ratio (SNR). At low frequencies, radiofrequency (RF) coil conductor losses - rather than tissue sample losses - predominantly govern the system's total noise, making meticulous RF coil optimization critical to recovering image quality. This work presents an open-source, optimized solenoid head coil tailored for the 50 mT open-source scanner (OSII ONE v2.1). The paper validates production reproducibility across three independent international institutions and introduce an open-source connector with integrated digital circuitry for coil identification and DC or logic signals. Comprehensive benchtop measurements, Electromagnetic Interference (EMI) coupling analysis, Specific Absorption Rate (SAR) safety simulations, and phantom and human volunteer imaging confirm the design's efficacy, safety, and reproducibility. The results of the paper, when combined with the material provided in the open-source dedicated repositories, set the basis for a fully reliable and reproducible component for the open-source OSII ONE MRI scanner. In addition, the same optimization strategy and design material can be exploited for designing other RF coils for imaging of other body parts.
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All authors Umberto Zanovello, Julia Pfitzer, Ariane Ernst, Joshua Harper, Jack Hayhoe, Tri Nguyen, Lukas Winter, Nicola De Zanche

Medical Physics

Focal-point scanning for dose delivery and optimization with focused laser-accelerated very-high-energy electron beams

Zhiyuan Guo, Yifei Pi, Junwei Zhou et al. (+10 more)

Focused very-high-energy electron (VHEE) beams can produce localized dose enhancement at selected depths, but irradiation of a finite target requires coordinated control of multiple focal positions, incidence directions, and beam weights while limiting exposure of nearby organs at risk (OARs). We present Focal-Point Scanning (FPS), a dose delivery and optimization method developed for laser wakefield accelerator (LWFA)-driven VHEE beams. The method is based on a two-dipole focusing system that produces single-plane beam convergence and allows the focal position to be varied by changing the magnetic field strength. FPS distributes focal points throughout the planning target volume and determines focal-point-specific incidence sectors according to the geometry of nearby critical OARs. The method was evaluated using the AAPM TG119 C-shape benchmark and one previously treated lung radiotherapy case. At matched target coverage, FPS reduced the TG119 Core mean dose by approximately one half relative to parallel VHEE and intensity-modulated x-ray plans, approaching the single-field proton pencil-beam-scanning reference. In the lung case, FPS maintained target coverage comparable to the clinical volumetric modulated arc therapy reference while reducing the mean dose to every evaluated OAR; spinal-cord mean and maximum doses decreased by 93.2% and 87.2%, respectively. The evaluated OAR mean doses varied little across rms energy spreads of 0 to 10% and for a flat-top electron spectrum spanning 150 to 250 MeV. These results demonstrate that focal-point-specific angular selection can translate focused-beam physics into effective OAR sparing and support FPS as a planning strategy for broadband LWFA-VHEE radiotherapy.
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All authors Zhiyuan Guo, Yifei Pi, Junwei Zhou, Guoqing Liu, Wenbo Zhang, Haiyang Wang, Yaping Qi, Xiaoming Guo, Yuhan Zhang, Bo Peng, Jianfei Hua, Yang Wan, Wei Lu

Thursday 13 August

Medical Physics · Cross-listed from physics.optics

Label-Free Deep-Tissue Peripheral Nerve Detection with a Handheld Multimodal OCT Probe and NerveDetNet

Yihan Wang, Ruilin You, Shaobai Li et al. (+4 more)

Peripheral nerves buried beneath intact tissue are difficult to visualize during surgery and remain inaccessible to white light wide-field imaging and other surface optical imaging methods. Existing OCT nerve studies have largely relied on exposed nerves or polarization contrast with limited depth penetration, restricting their value for subsurface intraoperative guidance. Here, we introduce, to our knowledge, the first label-free framework for detecting peripheral nerves beneath unopened tissue and resolving their depth using intensity-based OCT structural signatures alone. The framework combines a handheld multimodal probe, integrating swept-source OCT with co-registered white light and autofluorescence imaging, with a “confirm-then-capture” workflow designed for practical surgical use. To enable efficient analysis of sparsely sampled OCT volumes, we develop NerveDetNet, a lightweight 2.5D segmentation network that recovers weak and spatially displaced nerve signals by incorporating spatial context, frame-order information, and shift-tolerant correlations across frames through a dedicated nerve feature correlation module. In ex vivo tissue experiments, NerveDetNet consistently outperformed six representative 2D baselines across all frame spacings, achieving a Dice score of 0.725 under the sparsest sampling condition while using approximately half the model parameters. End-to-end validation demonstrated localization of nerves invisible at the surface and depth-resolved detection up to 1.3–1.4~mm below the tissue surface, with OCT derived depth maps overlaid directly onto the surgical view. Together, these results establish a practical label-free approach for subsurface nerve visualization that supports intraoperative compatibility, enables efficient sparse-volume analysis, and provides depth-resolved guidance without tissue opening, contrast agents, or nerve exposure.
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All authors Yihan Wang, Ruilin You, Shaobai Li, Jiabin Chen, Bofan Song, Anh D. Le, Rongguang Liang

Medical Physics · Cross-listed from physics.optics

Fully Fiber-Integrated 3D-Printed Probes for Plug-and-Play Endoscopic Optical Coherence Tomography

Yihan Wang, Ruilin You, Jiabin Chen et al. (+5 more)

Miniature probes extend optical coherence tomography (OCT) into lumens and other confined spaces, but conventional implementations often rely on multiple distal components, fiber processing, and probe-specific interferometer matching. Here, a fully fiber-integrated OCT (F2I-OCT) architecture is demonstrated in which two-photon microfabrication defines not only the terminal imaging optic, but the complete distal optical and interferometric architecture within a single fiber-mounted element. Beam expansion, side-view redirection, common-path reference generation, and terminal imaging are physically integrated while remaining independently designable. This architecture transfers complexity from component fabrication and interferometer matching into three-dimensional optical design, reducing assembly to a print-and-bond process and enabling plug-and-play exchange on the same OCT platform. Terminal optics can be adapted to different working distances, surrounding media, and wavefront transformations without redesigning the upstream architecture. Twenty assembled probes exhibit returned-reference and side-viewing-output power standard deviations of 0.149 dB and 0.071 dB, respectively. The system achieves 93.1 dB sensitivity and enables ex vivo imaging of airway and dental structures. The combination of a common plug-and-play architecture with broad optical design freedom provides a versatile platform for endoscopic and confined-space imaging across diverse biomedical and technical environments.
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All authors Yihan Wang, Ruilin You, Jiabin Chen, Bofan Song, Zien Feng, Paula Patricia Villarreal, Gracie Vargas, Rongguang Liang

Medical Physics · Cross-listed from physics.ins-det

Scan-Coil Delay Causes Anisotropic Signal Loss in Fast 4D-STEM

Vishal Kumar, Andreas Jehle, Tizian Lorenzen et al. (+4 more)

Fast pixelated detectors are driving 4D-STEM toward microsecond dwell times, a regime in which the finite response of the scan deflection coils becomes comparable to the dwell time itself. Using direct probe imaging and sub-frame diffraction analysis, we document a significant intra-dwell scan-coil delay that systematically smears the recorded signal anisotropically along the fast scan direction, with a settling timescale of several tens of microseconds. We present a phase-correlation-based sub-frame alignment procedure that measures and corrects this smearing, and we assess its impact on focused and defocused 4D-STEM reconstructions over a range of scan step sizes. The correction restores signal across a broad range of spatial frequencies, with the largest gains at the large step sizes required for low-dose biological imaging. Because it operates on existing data with no modification to the microscope, the method offers a practical route to recovering signal that would otherwise be lost to scan-coil delay.
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All authors Vishal Kumar, Andreas Jehle, Tizian Lorenzen, Julika Radecke, Knut Müller-Caspary, Massimo Kube, Henning Stahlberg

Wednesday 12 August

Medical Physics

4$\pi$ Planning for the Reduction of Predicted Hematologic Toxicity Risk in Cervical Cancer Radiotherapy

Haotian Feng, Yan Kong, Qifan Xu et al. (+1 more)

Purpose: In conventional coplanar radiotherapy for cervical cancer, nearby pelvic bones receive high radiation doses, increasing the risk of acute hematologic toxicity (HT). This study aims to estimate the HT risk reduction achievable with non-coplanar (4$\pi$) radiotherapy. Methods: We retrospectively analyzed 114 cervical cancer patients treated with coplanar volumetric modulated arc therapy (VMAT) between 2021 and 2023. Radiomic features from planning CTs were extracted and combined with clinical and dosimetric data to train predictive machine learning models. Patients were then replanned using integrated non-coplanar beam orientation and fluence map optimization (4$\pi$ planning). The top performing model was applied to these new plans to evaluate potential HT reduction. Results: Models combined radiomics, clinical, and dosimetric features achieved the highest predictive performance (AUC = 0.79). Feature importance analysis highlighted CT radiomic and dosimetric variables as the strongest predictors. Compared to VMAT, 4$\pi$ non-coplanar planning significantly reduced doses to the bone marrow (V10Gy, V20Gy, V30Gy, and V40Gy by 28%, 52%, 47%, and 33%, respectively) while significantly reducing dose to other pelvic organs at risk (OAR). When evaluated by the model, this improved dosimetry translated into a 23% reduction in predicted HT risk (risk ratio: 0.77; 95% CI: 0.75-0.79 and odds ratio: 0.68; 95% CI:0.65-0.71). Conclusions: Non-coplanar 4$\pi$ radiotherapy significantly lowers radiation doses to major pelvic bones during cervical cancer treatment without compromising target coverage or sparing of other OARs. Based on our predictive model, this superior dosimetry should translate to a marked reduction in acute hematologic toxicity.
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All authors Haotian Feng, Yan Kong, Qifan Xu, Ke Sheng

Medical Physics

A 2D Hydrothermodynamic Analytical Model for Rapid Tumor Ablation using High-Intensity Focused Ultrasound

D. Tsiklauri

We establish a self-consistent 2D hydrothermodynamic analytical model for high-intensity focused ultrasound tumor ablation. Expanding compressible Navier-Stokes equations to second order demonstrates that a stationary cellular matrix suppresses acoustic streaming ($\mathbf{v}_2 = 0$). This constraint forces the absorbed wave momentum flux to convert entirely into localized, time-averaged static pressure gradients ($\nabla \langle p_2 \rangle = \mathbf{F}_2$), bridging non-linear hydrodynamics with thermodynamic dissipation. Solving the non-diffusive Pennes bioheat equation under a $1.0\,\text{s}$ top-hat pulse reveals that a spherically focusing geometry ($\propto 1/r^2$) overrides exponential damping past a critical geometric threshold ($r_{\text{crit}} = 2x_0$), preventing upstream skin overheating. We derive an optimization criterion where the absorption coefficient matches half the inverse target depth ($\alpha = 1/2x_0$). Solving the non-isothermal Arrhenius integral yields a sharp lesion boundary radius at $r_b = 0.75\,w_0$, where the volume average reaches $72.1^\circ\text{C}$ while the core peaks at $90.0^\circ\text{C}$. Post-pulse 2D free-space Green's function convolution confirms immediate monotonic thermal decay ($\partial \theta/\partial t' < 0$) outside this boundary. This closed-form framework provides explicit scaling laws for non-invasive wave-matter thermal confinement, bypassing computationally heavy numerical simulations.
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Medical Physics

Reducing Spectral Oscillations for Robust Reference Frequency-Based Ultrasound Attenuation Estimation in Harmonic Imaging

U-Wai Lok, Jingke Zhang, Chengwu Huang et al. (+14 more)

Ultrasound attenuation coefficient estimation (ACE) has emerged as a quantitative imaging biomarker for noninvasive assessment of hepatic steatosis. A system-independent technique based on spectral normalization, known as the reference frequency method (RFM), was previously proposed to estimate ACE without requiring a well-calibrated reference phantom. Furthermore, incorporating harmonic imaging can significantly suppress reverberation signals. In previous clinical study, RFM has achieved high correlation with MRI-PDFF, demonstrating its potential for clinical application. However, a major challenge of RFM is the presence of oscillations in the frequency power-ratio decay curves (FPDCs), which can distort the linear fitting used to estimate the attenuation coefficient and consequently degrade ACE accuracy. These oscillations arise from constructive and destructive interference among backscattered echoes, resulting in oscillatory fluctuations in the measured power spectrum that propagate into the FPDCs. We propose a transmission scheme combining multiple frequencies and steering angles to mitigate oscillations in the FPDCs. Averaging these FPDCs suppresses the interference-induced oscillations while preserving the attenuation-dependent decay trend, thereby improving linearity and the accuracy of ACE results. In in-vitro experiments using calibrated phantoms (0.5 and 0.76 dB/cm/MHz) demonstrated that the proposed method improved FPDC linearity and ACE accuracy, achieving an R2 of 0.99 and attenuation coefficient estimates of 0.51 and 0.77 dB/cm/MHz, versus an R2 of 0.89 and estimates of 0.56 and 0.70 dB/cm/MHz for conventional RFM. The proposed method also demonstrated superior performance in a pilot patient study (n=15), achieving a stronger correlation with MRI-PDFF (R = 0.89 vs. 0.83) while reducing inter-measurement variability, indicating improved robustness and clinical potential.
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All authors U-Wai Lok, Jingke Zhang, Chengwu Huang, Tao Wu, Jieyang Jin, Ryan M. DeRuiter, Jingyi Yin, Lijie Huang, Yanzhe Zhao, Kaipeng Ji, Kate M. Knoll, Dawn Boynton, Kymberly D. Watt, Kathryn A. Robinson, Joshua D. Trzasko, Matthew Callstrom, Shigao Chen

Medical Physics · Cross-listed from physics.optics

Bridging the gap: Using deep learning to reconstruct noise-reduced super-resolved OCT images from gapped spectra

Jonas Nienhaus, Thomas Schlegl, Wolfgang Drexler et al. (+2 more)

Fourier-domain (FD) optical coherence tomography (OCT) depends on broadband sources to maximize axial resolution and image quality. However, these lasers significantly drive device cost or may be unavailable at desired wavelength and bandwidth ranges. A potential solution lies in integrating multiple, more affordable sources with lower individual bandwidth into a single system. However, difficulties arise if the resulting spectrum exhibits discontinuities. In this letter, we present a method that can combine OCT images from a flexible number of spectra with arbitrary, possibly non-overlapping gaps using a neural network. Compared to low-resolution input images, reconstructed B-scans are super-resolved, preserve even fine and low-contrast details and edges, and exhibit strong noise reduction that increases with the band gap. The proposed method could thereby provide a major step towards high-quality OCT imaging using spectrally disjoint, low-bandwidth sources. In broadband settings, it can be directly applied as a Fourier-domain masked autoencoder for self-supervised image quality enhancement.
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All authors Jonas Nienhaus, Thomas Schlegl, Wolfgang Drexler, Tilman Schmoll, Rainer A. Leitgeb

Tuesday 11 August

Medical Physics

T1, T2, and complex permittivities of hydrogels, paramagnetic salt solutions, and oils at 0.35, 1.5, and 3 Tesla

H Michael Gach, Kerri Prinos and Hannah Sechaga

Approach: The T1, T2, and complex permittivities of candidate MRI phantom constituents (hydrogels, paramagnetic electrolytes, and oils) were measured at different magnetic field strengths and concentrations. Data: T1 decreased with increasing concentration except for PEG. The T1 and T2 relaxivities of polyethylene glycol (PEG), polyvinylpyrrolidone (PVP), sodium polyacrylate, and deionized water did not significantly vary with field strength. The T2 relaxivities of gelatin and sodium alginate did not significantly vary with field strength. All of the hydrogels and paramagnetic electrolyte solutions had high static dielectrics (e.g., {\epsilon}s~70) similar to water. The static electrical conductivities of Miller's LB agar, gelatin, PVA, sodium alginate, sodium polyacrylate, xanthan gum, CuSO4, NiCl2, and Mn(NO3)2 rose with concentration. However, the conductivities of PEG and PVP did not rise with concentration. Conclusions: Sodium polyacrylate, PVP, and PEG hydrogels are challenging for generating consistent phantoms. Sodium alginate, Miller's LB agar, and xanthan gum were good hydrogel candidates. Mn(NO3)2 had the highest relaxivities of the tested samples. All three oils (canola, castor, and grapeseed) are good candidates for low dielectric ({\epsilon}s<10) phantoms for high field applications) but with low conductivities.
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Medical Physics

Real-Time Requirements and Transferability in Compton Imaging: From the Detector Chain to the Application

F. Albiol, Elena Larrea Estrelles, Salvador Tortajada et al. (+4 more)

Compton cameras are proposed for tasks whose value decays with delay: verifying a range during irradiation, guiding an intervention, characterising an inaccessible volume, surveying a band no telescope covers. Whether a device can serve such a task is settled by the composition of its whole chain, while the literature that would answer the question is organised by stage – so claims made at application level routinely rest on evidence obtained at component level. This review walks that chain, asking at each stage what binds first and what a reader can determine from the published text, and then asks what governs whether a capability transfers between groups and between application domains. The evidence is of two kinds: 83 full texts scored in context against defined markers, and, for five application domains measured alike, the size of the receiving literature, of the need it states, of the incumbent and of deployment commitment. Performance is reported at one operating point in 65 of 83 full texts, with count rate swept in none: the field reports values where transfer requires gradients. An accelerator is used in 39 works and a learned model in 31, while separability is discussed in 28, a memory footprint given in 9, and the cost of a precomputation or the inference time of a model in none. Across domains, neither the size of the receiving literature, nor of the incumbent, nor of the stated need orders the domains as deployment commitment does, while whether the incumbent can serve the task at all, and how many domain boundaries the output must cross, do so consistently. The distribution of publication is close to the inverse of the distribution of deployment commitment. We give the quantities a report must contain for a third party to judge whether a method fits an application it was not built for.
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All authors F. Albiol, Elena Larrea Estrelles, Salvador Tortajada, Luis Caballero, Jose Escalante, Alberto Albiol, Jose Luis Leganes-Nieto

Medical Physics · Cross-listed from cs.CV

Lesion-Aware Adaptive Fourier Neural Operator for CT-to-PSMA PET Synthesis in Prostate Cancer

Rashmi Bhaskara, Waleed M. Almutairi, Matthew Gopaulchan et al. (+5 more)

Deep learning models that synthesize PET from CT or MRI can reduce patient dose and scanner demand, but are typically optimized with global losses such as L1 or mean squared error (MSE) that treat all voxels similarly. In whole-body PSMA-PET, tumor voxels occupy only a small fraction of the volume, yet carry the clinically relevant activity signal; as a result, models can achieve high structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) while still underestimating lesion activity or failing to preserve tumor-specific structure. Radiomics provides biologically meaningful descriptors of tumor intensity and texture, but direct radiomics conditioning is time-consuming because it requires feature extraction from delineated lesion regions. We propose LAFNO, a Lesion-Aware Adaptive Fourier Neural Operator for CT-to-PSMA-PET synthesis that replaces high-dimensional radiomics conditioning with two efficient CT-derived proxy channels. Motivated by radiomics analysis of PSMA-avid tumor core and peritumoral regions, LAFNO uses a contrast proxy for local density variation and a disorder proxy for local texture heterogeneity, both injected into the model bottleneck. LAFNO combines whole-volume reconstruction with lesion-level total lesion activity (TLA), tumor-core contrast, and peritumoral supervision. We evaluated LAFNO against four baseline architectures on the TCIA PSMA-PET-CT-Lesions dataset. LAFNO remained competitive on whole-volume image quality, achieving SSIM of 0.960 and 0.938 for 18F- and 68Ga-PSMA, respectively, while reducing per-patient TLA error to 48.3% and 64.0% for 18F- and 68Ga-PSMA, respectively, and achieving the highest tumor-core radiomics reproducibility across all feature classes for both tracers. Peritumoral reproducibility remained tracer-dependent, indicating that biological fidelity in synthetic PSMA-PET remains challenging.
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All authors Rashmi Bhaskara, Waleed M. Almutairi, Matthew Gopaulchan, Maram Musaad Alqurashi, Francis Asamoah, Alex Ocana, Clinton D. Bahler, Oluwaseyi M. Oderinde

Medical Physics · Cross-listed from cs.CV

Efficient Noise Context-Aware Representation for Low-Dose CT Denoising

Minwoo Yu, N. Robert Bennett, Jongduk Baek et al. (+1 more)

While deep learning-based denoising has become widely adopted in low-dose CT, conventional models use generic architectures designed for natural images, failing to account for non-stationary and spatially correlated CT noise characteristics. To address this, we propose an Efficient Noise COntext-aware REpresentation (ENCORE) framework that explicitly leverages CT noise characteristics and anatomical features. First, we reformulate the noise synthesis procedure based on a realistic noise distribution beyond the conventional Gaussian approximation, establishing a rigorous foundation for training pair generation. Next, we extract local noise power and correlation contexts to guide the denoising process. To fully leverage the potential of noise context, we propose a FlyingConv module, which adaptively changes convolution weights for each local image region. Notably, our approach demonstrates substantial gains in both denoising quality and computational efficiency. Furthermore, manipulating the intensity of the noise context maps at inference time enables zero-shot conditional denoising, allowing for dynamic control over the output image texture. The entire pipeline is available at https://github.com/minwoo-yu/ENCORE.git
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All authors Minwoo Yu, N. Robert Bennett, Jongduk Baek, Adam S. Wang

Monday 10 August

Medical Physics · Cross-listed from cs.CV

Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction

Mojtaba Safari, Shansong Wang, Zach Eidex et al. (+4 more)

Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantitative analysis. Existing deep learning methods for motion correction typically rely on paired clean-corrupted data or k-space acquisitions, which are rarely available in clinical settings. We propose SSRL-MAR, a motion artifact-aware unpaired representation learning framework for motion artifact reduction that requires neither paired training data nor explicit motion labels. SSRL-MAR employed a three-stage training strategy: (1) contrastive learning on 3D patches to extract motion representations by contrasting clean and synthetically corrupted images, (2) a motion artifact-aware synthesis network to generate motion artifacts from clean scans, and (3) a motion artifact-aware generator to restore clean volumes using the learned degrader for self-supervised supervision. On in-silico dataset, SSRL-MAR achieved PSNR 23.81dB, SSIM 91.55%, and NMSE 0.79%. On in-vivo MR-ART dataset, the pretrained model reduced motion distortion, and unsupervised domain adaptation further improved anatomical fidelity. Against a source-only supervised model trained on the same simulated pairs, SSRL-MAR improved PSNR by up to 2.0 dB on MR-ART after unsupervised domain adaptation, and remained within 0.25-0.47 dB of an oracle supervised model that requires real paired data unavailable in practice. At the milder motion level, volumetric error in structures such as the corpus callosum and ventricular system decreased by more than 50%, confirming improved neuroanatomical consistency. These results indicate that SSRL-MAR provides a robust and scalable image-domain solution for 3D brain MRI motion correction, enabling reliable structural quantification in large-scale neuroimaging studies without requiring prospectively acquired pairs or acquisition-specific calibration.
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All authors Mojtaba Safari, Shansong Wang, Zach Eidex, Matthew Goette, Tonghe Wang, Zhen Tian, Xiaofeng Yang

Medical Physics · Cross-listed from eess.IV

Lost in k-Space: An Open-Source MR-Physics Escape Room

Sabine Melanie Räuber, Marta Brigid Maggioni and Francesco Santini

Introduction. Operating an MR scanner for technical and clinical research requires multidisciplinary competencies beyond MR physics, including safety management and teamwork. Gamification, particularly educational escape rooms, have been associated with improved motivation, engagement and knowledge retention in health professional education. Materials and Methods. We developed an MR-physics-themed educational escape room for the 41st Annual Meeting of the ESMRMB. Designed for teams of four with a time limit of 25 minutes, the room reproduced the atmosphere of an MR control room. The five puzzles covered the Larmor equation, sequence composition, MR safety and acoustical identification of MR sequences. Custom ESP32 electronics allowed the puzzles to communicate in real time with each other and with the game master Results. The room ran without technical interruptions and was played by 39 teams (approximately 160 participants); 12 solved it (escape rate 31%), with a median solution time of 21 minutes and 53 seconds. Early-career researchers acted as game masters. Discussion. The escape rate aligns with comparable activities targeting scientific audiences. Difficulty can be tuned by adjusting puzzle obscurity, component availability, required prior knowledge and mental leaps. A modified version could usefully supplement mandatory MR safety training. Code, schematics, machining files and documentation are released as open source.
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Medical Physics · Cross-listed from physics.ins-det

Openable Force-Balanced Halbach Magnets: From Fibonacci Sphere Simulations to Icosahedral Realizations

Ingo Rehberg, Helmut Soltner and Peter Blümler

A long-standing goal in magnet design is to completely surround a volume of highly homogeneous magnetic field with permanent magnets while maintaining practical access to that volume. In this work, we present a theoretical and experimental investigation of mechanically accessible spherical magnets in Halbach configuration that can be opened with minimal or vanishing force. Focusing on dipolar Halbach spheres composed of discrete magnetic subunits, we derive conditions for force-free opening along specific cutting planes. These conditions define a continuous set of geometries for which tensile magnetic forces cancel, leaving only shear components, enabling mechanically effortless opening. The theoretical predictions are validated experimentally using icosahedral approximations of the Halbach sphere, for which both opening forces and magnetic field properties are measured. The results demonstrate that excellent field homogeneity can be preserved while reducing opening forces by orders of magnitude. Although discussed in detail for the dipolar case, the theoretical framework is general and applicable to higher-order multipole Halbach systems. Finally, the concepts are extended to spherocylindrical Halbach configurations, highlighting their potential for large-volume, highly homogeneous, and mechanically accessible permanent-magnet systems for magnetic resonance
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