Wednesday, 4 November 2026: 7 new papers, 2 cross-lists and 2 replacements in Medical Physics (physics.med-ph), in arXiv's order, with full abstracts. The same papers as arXiv's own listing, set as a newspaper; every title links to arXiv.
The dielectric properties of biological tissues are used to investigate the interaction of electromagnetic (EM) fields with the human body. These properties are integrated into EM numerical simulations, such as the finite difference time domain (FDTD) method, using dielectric models such as Cole-Cole and Debye models. These computational tools are employed to study the propagation of EM waves within the human body. This paper has developed the one-pole and two-pole Cole-Cole and Debye models for the dielectric properties of normal and diseased human trabecular bone tissue at microwave frequencies (0.5-8.5 GHz). The dielectric properties of normal trabecular and cortical bone were derived based on the literature, while those of diseased human trabecular bones (osteoporotic and osteoarthritis) were acquired from a previous study conducted by the authors, which characterised the properties within the 0.5-8.5 GHz frequency range. This study has employed a weighted least squares method to optimise the one-pole and two-pole dielectric models' parameters. The accuracy of the developed dielectric models is validated by comparing the simulated results with the experimental data already published by the authors. The comparative analysis of the models demonstrated that the one-pole Cole-Cole model achieved a better fit compared to the one-pole Debye model across all bone types. Additionally, the two-pole Cole-Cole model exhibited a better fit than the two-pole Debye model. The proposed models can be used in numerical simulations to investigate the interaction of EM fields with bone tissue and develop and optimise microwave bone health monitoring and treatment techniques.
Adrenal gland-induced hypertension results from underlying adrenal gland disorders including Conn's syndrome, Cushing's syndrome, and Pheochromocytoma. Due to the limitations of existing pharmaceutical and surgical treatment methods, minimally invasive treatment options like microwave ablation (MWA) have received significant attention for treating adrenal gland disorders. A precise comprehension of the dielectric properties of human adrenal glands will help to tailor energy delivery for MWA therapy, thus offering the potential to optimise treatments and minimise damage to surrounding tissues. This study reports the ex vivo dielectric properties of human adrenal glands, including the cortex, medulla, capsule, and tumours, based on the data obtained from four patients (diagnosed with Conn's syndrome, Cushing's syndrome, and Pheochromocytoma) who underwent unilateral adrenalectomy at the University Hospital Galway, Ireland. An open-ended coaxial probe measurement technique was used to measure the dielectric properties for a frequency range of 0.5-8.5 GHz. The dielectric properties were fitted using a two-pole Debye model, and a weighted least squares method was employed to optimise the model parameters. Moreover, the dielectric properties of adrenal tissues and tumours were compared across frequencies commonly used in MWA, including 915 MHz, 2.45 GHz, and 5.8 GHz. The study found that the dielectric properties of adrenal tumours were influenced by the presence of lipid-rich adenomas, and the dielectric properties of Cushing's syndrome tumour were lowest in comparison to the tumours in patients diagnosed with Conn's syndrome and Pheochromocytoma. Furthermore, a notable difference was observed in the dielectric properties of the medulla and cortex among patients diagnosed with Conn's syndrome, Cushing's syndrome, and Pheochromocytoma.
Compton camera imaging relies on the positions and energies of multiple photon interactions recorded in the detector. In silicon detectors that resolve individual interactions, these measurements do not directly provide the causal interaction order, and in nuclear medicine applications the photon may also have scattered in the object before entering the detector. We present a probabilistic model for photon interaction chains in a silicon detector and use it for two inference tasks at the event level: interaction order inference and classification of primary versus object-scattered photons. The model combines photon transport based on Compton scattering and attenuation with a detector response model. It is evaluated on Monte Carlo data for monoenergetic point sources at 140~keV and 511~keV, with and without a cylindrical water phantom. For interaction chains of length two to four, the maximum a posteriori order estimate gives high accuracy in the case without a phantom, exceeding 0.95 for all chain lengths at 511~keV, and decreasing with increasing phantom radius. The gap between the two highest posterior order probabilities provides a confidence measure for the ordering estimate and can be used to increase accuracy at the cost of reduced retention. For scatter classification, likelihood-ratio testing yields receiver operating characteristic curves with area under the curve above 0.85 across all phantom radii considered. These results support the use of probabilistic modeling of measured interaction sequences for inference directly at the event level, and show that both interaction ordering and scatter discrimination can be treated within a common framework.
OBJECTIVE Shear wave elastography (SWE) is a recent method for evaluating soft tissue stiffness. Its application to the spinal cord is limited by the ultrasound bone barrier. Spinal dysraphism can cause neurological symptoms impairing bladder, bowel, and lower limb function due to a mechanical stress known as tethered cord syndrome. Detethering of the spinal cord is a part of surgical treatment. This study aimed to assess the feasibility of intraoperative elastography to guide surgery in patients with spinal dysraphism involving traction of the spinal cord. METHODS This single-center retrospective study included all patients who underwent surgery for spinal dysraphism between November 2023 and July 2024. SWE was performed under general anesthesia with the patient in the prone position before and after spinal cord detethering. All SWE measurements were performed using the Aixplorer system. Demographic, clinical, and radiological data (age at surgery, neurological status, and MRI findings) were collected. RESULTS Twenty-one patients with a mean $\pm$ SD (range) age of 3.7 $\pm$ 5.3 (0--17.5) years were included. Etiologies included open saccular dysraphism (n = 3), spinal cord conus lipoma (n = 6), limited dorsal myeloschisis (n = 3), and fibrolipomatous filum (n = 9). In 85% of patients, at least 1 clip was of sufficient quality for analysis both before and after release. The mean $\pm$ SD (range) spinal cord stiffness at the beginning of surgery was 25.2 $\pm$ 9.2 (12.3--39.1) kPa and 11.2 $\pm$ 3.8 (6.2--16.5) kPa at the end of release, with a significant stiffness decrease (p = 0.018). No complications attributable to SWE were observed. CONCLUSIONS SWE of the spinal cord in patients with spinal dysraphism is a safe and feasible imaging method. This technique may assist in assessing the adequacy of untethering during surgery. However, no established normative SWE values for the pediatric spinal cord currently exist. Until it does, the intraoperative interpretability and clinical utility of this technique remain limited.
Skin meshing increases graft coverage, yet the clinically achieved expansion often falls below the manufacturer's nominal meshing ratio. Previous elastic analyses have demonstrated that mesh topology and skin anisotropy strongly influence graft expansion; however, the effect of progressive damage at larger deformation remains unexplored. This study therefore investigates how progressive damage affects the expansion and mechanical response of skin meshes. The performance of auxetic mesh geometries is compared with conventional Zimmer mesher (ZM) geometry. Human back skin was modelled using a one-term Ogden ground matrix and a Gasser Ogden Holzapfel (GOH) collagen network, with separate scalar Kachanov-type continuum damage variables for each constituent. The auxetic geometries, including 1st- and 2nd-order alternative slits (AS1 and AS2), I-shaped (IS) and H-shaped (HS) re-entrant patterns, and ZM, were analysed with Langer's lines oriented either parallel or perpendicular to the loading direction. Hyperelastic and damage-based formulations were compared up to 25% strain, and the damage-based simulations were subsequently extended to 40% strain. ZM was further loaded to 155% strain; the area ratios attained by HS at 40% strain were matched by ZM at 142.1% and 124.7% strain for Langer's lines parallel and perpendicular to loading, respectively. Results indicate that HS achieves greater coverage than ZM for a given stretch, whereas its damage advantage depends on the orientation of Langer's lines.
Medical physicists turn a prescription into a delivered dose and check one another's calculations, because one error in a beam calibration or a monitor-unit (MU) calculation can affect every patient treated with it. MedPhysBench has ten seeded generators of calculation items in radiation therapy, diagnostic imaging, nuclear medicine and radiation protection, up to clinical tasks such as a TG-51 calibration worksheet. Reference answers come from code implementing the governing protocols, and a grader converts units and applies tolerance bands. From the same inputs, separate checking items test error detection, showing a colleague's worksheet or only the colleague's result, half correct and half with one planted error. On a held-out test split of 1,200 items (half for two models), 12 models scored 33.3 to 100.0% on calculation. Of the nine answers graded incorrect for the four best (99.3-100.0%), five contained model errors and four followed NCRP Report 151 on points our items misstate or leave open. Below them, most models did worst on level-3 clinical tasks, and Claude Sonnet 5.5 omitted the inverse-square correction in 19 of 20 isocentric MU items. Five models detected at least 96.7% of mostly large planted errors with at most 4% false alarms; for four of the other seven, checking only the result raised false alarms significantly. In an exploratory targeted test with 20 public cases of an omitted inverse-square correction, the three best models tested caught it in every worksheet, and three weaker models accepted 16 to 18 of 20 planted worksheets, one of them while applying the correction in most of its own calculations. Claude Opus 5.5 accepted 6 of 20 wrong results, although it applied the correction in all 20 of its own. We report the effect of two problems in our shielding items, found after the runs, and release the code, per-item outcomes and targeted-test responses.
Machine learning models in radiotherapy are commissioned by testing them on cases with known answers, which may not reveal a shortcut that the test cases share with the training data. Frontier language models have recently been reported to read and write the raw weights of small neural networks, an ability called weight-space programming. The purpose of this study was to determine whether such a model, given only a clinical protocol and a network's weights, can audit and repair the network. Networks with 433 to 4,801 parameters were trained to screen head-and-neck planning requests against four rules. Flaws were planted through the training data: confounds that hid each rule, a 3 Gy shift in the cord threshold, and a hidden trigger. Claude Opus 5.5 audited each network blind, without tools, data or code execution, and every claim and repair was tested on about 420,000 requests. The language model named the broken rule in 16 of 18 flawed networks (95% CI 67% to 97%), including all 15 with a confound or a threshold shift. It repaired each of the 16 by changing a median of 3 parameters. Fine-tuning on protocol-labeled requests also repaired every network, but changed nearly every parameter. Each confound and shift it found was visible in single units, and a simple statistic chosen for each flaw type found the same flaws. It cleared 2 of 5 healthy networks without being forced and found 1 of 3 triggers. Testing against the protocol detected every flaw, and black-box testing found the confounds and the shift faster. The results indicate that, in small networks, weight-space programming can locate and repair flaws that silence an input or shift a threshold, but cannot yet certify that a network is correct.
Optimizing continuous-variable functions on qubit-based quantum hardware requires a finite representation of the search space and a solver-compatible representation of the objective function. Fixed-grid discretizations provide a direct encoding, but restrict the search to a predefined range and resolution; at the same time, constructing a compact Hamiltonian for a general continuous-variable objective can be impractical. Here, we introduce a framework for continuous-variable optimization tailored to qubit-based quantum architectures. The method combines an adaptive discretization with an iterative local mapping of the objective function onto an effective spin-glass Hamiltonian. We assess the approach on unconstrained and constrained instances of the $n$-dimensional Gramacy-Lee benchmark, and on a proof-of-concept inverse-planning problem in intensity-modulated radiotherapy (IMRT) for cancer treatment. The results show that this framework can produce competitive solutions, supporting its use as a flexible mapping strategy for continuous-variable optimization in qubit-based quantum and quantum-inspired pipelines.
This work presents a new method for gradient-based optimization of the rhombic transposition flap and the excision it closes, which set the strain of the skin after closure. Previous studies swept at most three parameters. Here, using structural optimization methods, up to eight variables, two flap angles, two cut lengths and the size, shape and position of the rhombic excision, are optimized under up to 32 geometric and stress constraints. The skin is a pre-stretched, incompressible hyperelastic membrane that wrinkles instead of carrying compression. Smoothed level-sets on a fixed grid represent the cuts, and springs between interpolated points the sutures, so designs change without remeshing and the adjoint method gives the sensitivities. The energy the surgery adds to the skin is minimized, and the model reproduces the energies of a published 48-design sweep with a median deviation of 5%. The optimal flap angles, $(-23^\circ, 31^\circ)$, lie outside the swept range and add 63% less energy than the Limberg flap and 15% less than the best swept design. Under unequal in-vivo tension, the optimal flap turns with the direction of the tension. Fitting the excision to the lesion and its margin lowers the energy by a further 35%, and with all eight variables it is 78% below the Limberg flap. This optimum is the same for finer grids, narrower cuts and wider undermining, although wider undermining reduces its gain. Lowering its suture-line stress by 41% costs only 2.3% more energy.