Physics in medicine and biology最新文献

{"title":"IG-BiReg: implicit-guided bidirectional residual registration framework for cardiac cine MRI images.","authors":"Shuangshuang Jia, Yi Yang, Qing Chang","doi":"10.1088/1361-6560/aeb060","DOIUrl":"10.1088/1361-6560/aeb060","url":null,"abstract":"<p><p><i>Objective</i>.To achieve accurate registration of cardiac cine magnetic resonance imaging sequences by addressing the challenges of large non-rigid deformations during the cyclic movement of the heart.<i>Approach</i>. We propose a new collaborative framework built on the key idea of 'explicit motion generation combined with implicit global verification'. To capture the continuous dynamics of the heart, the explicit approach utilizes a bidirectional residual fusion network to generate deformation fields based on local spatiotemporal context. To ensure global structural consistency, the implicit supervision is proposed: the warped sequences are mapped into mean intensity and principal component feature spaces. This dual-space constraint acts as a global feedback mechanism to enforce anatomical plausibility and suppress non-anatomical deformations across the entire sequence.<i>Main results</i>. The method achieved average Dice coefficients of 0.843 and 0.842 on the ACDC and M&Ms datasets, respectively. Furthermore, it demonstrated highly accurate contour alignment, yielding average 95% Hausdorff distance and average symmetric surface (ASSD) distance values of 4.837 and 1.768 on the ACDC dataset, and 4.918 and 1.899 on the M&Ms dataset.<i>Significance</i>. The proposed method successfully addresses the inadequate handling of boundary frames in bidirectional temporal modeling and overcomes the limitations of groupwise registration by adapting to sequences of different lengths. By effectively tracking complex non-rigid cardiac deformations, it provides a robust solution that facilitates reliable quantitative clinical analysis.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GPT-assisted radiomic modeling for predicting pathological complete response to neoadjuvant chemoimmunotherapy in head and neck squamous cell carcinoma.","authors":"Huaxian Shi, Tianjun Lan, Xiaoling Gao, Hanxiao Song, Ying Li, Yu Wang, Lingjie Yang, Xiaohua Ban, Xi Zhong, Chaobin Pan, Xiaohui Duan, Yu Peng, Zhaoyu Lin, Dong Zeng","doi":"10.1088/1361-6560/aea735","DOIUrl":"10.1088/1361-6560/aea735","url":null,"abstract":"<p><p><i>Objective</i>. To evaluate whether GPT can assist in automating radiomics modeling for predicting pathological complete response to neoadjuvant chemoimmunotherapy in head and neck squamous cell carcinoma.<i>Methods.</i>The study included a training cohort (TC;<i>n</i>= 186), a validation cohort (VC;<i>n</i>= 116), and a prospective multicenter validation cohort (PVC;<i>n</i>= 269). Radiomic and supervised deep learning features were extracted from pretreatment T2-weighted magnetic resonance imaging. logistic regression (LR) was first evaluated using radiomic, deep learning, and fused features. Support vector machine, naïve Bayes, random forest, and extreme gradient boosting models were subsequently compared using fused features. GPT was not used as the classifier but assisted with preprocessing, feature selection, hyperparameter optimization, code generation and execution, model training, and probability output. Each GPT-assisted workflow was independently repeated five times.<i>Results.</i>Fused features achieved the highest area under the receiver operating characteristic curve for both manually developed and GPT-assisted LR models. Their AUCs were 0.759 versus 0.763 ± 0.003 in the TC, 0.714 versus 0.741 ± 0.008 in the VC, and 0.700 versus 0.706 ± 0.004 in the PVC. Across five classifiers, GPT-assisted workflows achieved performance broadly comparable to manually developed models. Repeated GPT-assisted runs showed limited variability, with AUC standard deviations ranging from 0.001 to 0.019.<i>Conclusion.</i>Under expert supervision, GPT can automate key radiomics modeling procedures while achieving performance comparable to conventional machine learning workflows, potentially reducing technical workload and facilitating integrated model development.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148970751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical considerations in measuring out-of-field neutron dose for pulsed and gantry-mounted proton therapy machines.","authors":"Hailei Zhang, Thomas R Mazur, Gabriele Zorloni, Arash Darafsheh","doi":"10.1088/1361-6560/aeaf3e","DOIUrl":"https://doi.org/10.1088/1361-6560/aeaf3e","url":null,"abstract":"<p><p><i>Objective.</i>Synchrocyclotrons deliver radiation in distinct macro pulses with high instantaneous dose rate that distinguish them from isochronous cyclotrons and synchrotrons. The relatively high instantaneous dose rates associated with synchrocyclotrons require special consideration in measurement of the neutron dose. The objective of this work is to measure the out-of-field neutron ambient dose equivalent (H*(10)) as a conservative operational surrogate to assess the fetal dose due to secondary neutrons for a gantry-mounted synchrocyclotron proton therapy system when an intensity modulated proton therapy (IMPT) brain treatment is delivered with the dynamic aperture (DA), static aperture (SA), and no aperture (NA).<i>Approach.</i>A pencil beam scanning (PBS) gantry-mounted synchrocyclotron was used for beam delivery. IMPT plans employing the DA, SA, and NA, each with 3 fields (vertex, lateral, and posterior-anterior (PA)) were optimized using the treatment planning system to treat a left-sided spherical brain target with 6 cm diameter to a total dose of 66 Gy (weighted by radiobiological effectiveness [RBE] 1.1) in 33 fractions. The plans were delivered to an anthropomorphic phantom and the neutron H*(10) was measured using two commercial rem-meters, a WENDI-II and a LUPIN-BF3-NP counter at 43, 53, 61, and 71 cm distance from the isocenter intended to mimic distances to a fetus at various gestational periods. To investigate the influence of the couch angle for the PA field, the neutron dose from the PA field was measured at several couch angles including 0°, 180°, and 270°.<i>Main results.</i>WENDI-II suffers from dead-time associated issues and underestimated the dose by a factor of ∼1.7-2.7 compared to LUPIN-BF3-NP. H*(10) showed dependence on the measurement location and the use of field shaping system. The total H*(10) for 66 Gy-equivalent proton dose was estimated to be 10.7 mSv (9.7 mSv) and 4.9 mSv (4.5 mSv) at 43 and 71 cm distance from the isocenter, respectively, when the SA (DA) was used. Without an aperture the corresponding values were 11.8 mSv and 5.3 mSv. The 270°-couch-angle resulted in the highest neutron dose from the PA field by ∼15% relative to the 0°-couch-angle, resulting in an increase in the neutron dose by ∼5% for the whole treatment.<i>Significance.</i>WENDI-II is not a reliable device for in-room neutron dose measurement for synchrocyclotrons with high instantaneous dose rates. Employing appropriate use of the aperture system as well as avoiding the 270° couch angle for the PA field can minimize the neutron dose in the gantry-mounted system studied in this work.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":"71 20","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient Chebyshev reconstruction for the anisotropic equilibrium model in magnetic particle imaging.","authors":"Christine Droigk, Daniel Hernández Durán, Marco Maass, Tobias Knopp, Konrad Scheffler","doi":"10.1088/1361-6560/aeaf3c","DOIUrl":"10.1088/1361-6560/aeaf3c","url":null,"abstract":"<p><p><i>Objective.</i>Magnetic particle imaging (MPI) is a tomographic imaging modality capable of real-time, high-sensitivity mapping of superparamagnetic iron oxide nanoparticles. Model-based image reconstruction provides an alternative to conventional methods that rely on a measured system matrix, eliminating the need for laborious calibration measurements. Nevertheless, model-based approaches must account for the complexities of the imaging chain to maintain high image quality. This work investigates and accelerates an adapted direct Chebyshev reconstruction (DCR) method that accounts for the physical effect of magnetic nanoparticle anisotropy.<i>Approach.</i>The adapted DCR method employs weighted Chebyshev polynomials in the frequency domain and incorporates a spatially variant deconvolution step to compensate for magnetic anisotropy effects. The method is evaluated on five experimental phantoms and compared with model-based and measured system matrix reconstructions. In addition, an efficient approximation of the spatially variant deconvolution is introduced to reduce computational runtime and memory consumption while maintaining reconstruction accuracy. The proposed approach is further investigated on simulated three-dimensional data to assess its scalability to volumetric MPI.<i>Main results.</i>The adapted DCR method significantly improves reconstruction quality in real measurements and achieves image fidelity comparable to that of the measured system matrix reconstruction and superior to that of the model-based system matrix reconstruction. The proposed approximation of the spatially variant deconvolution preserves the reconstruction accuracy while reducing computational and memory requirements. Its computational complexity is reduced to. The method also successfully reconstructs simulated 3D data, demonstrating its applicability to volumetric MPI.<i>Significance.</i>The results demonstrate the potential of the adapted DCR approach to improve model-based MPI reconstruction while avoiding the need for a system matrix. The efficient deconvolution approximation makes the method particularly attractive for high-resolution and three-dimensional imaging by substantially improving its computational efficiency and scalability.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection and correction of rigid patient motion in SPECT with exponential data consistency conditions.","authors":"My Hoang Hoa Bui, Antoine Robert, Jean-Noël Badel, Ane Etxebeste, Simon Rit","doi":"10.1088/1361-6560/aeadeb","DOIUrl":"10.1088/1361-6560/aeadeb","url":null,"abstract":"<p><p><i>Objective</i>. Rigid patient motion during single photon emission computed tomography (SPECT) can introduce artifacts in the reconstructed images. Patient translation can be estimated using various data-driven methods, e.g. those based on exponential data consistency conditions (eDCCs). eDCCs are mathematical equations that characterize the small redundancy between pairs of exponential projections derived from the application of the attenuated Radon transform. However, rigid motion typically involves both translational and rotational components. This study aimed to develop and evaluate an eDCCs-based approach for detecting and estimating any rigid patient motion during a SPECT acquisition.<i>Approach</i>. We calculated exponential projections from SPECT measurements, assuming that the photon emission was confined to a known convex region<i>K</i>with constant attenuation, and evaluated their pairwise consistency with eDCCs. The rigid motion was characterized by six parameters, three translations and three rotations, and the index indicating when the motion occurred. The six parameters and the motion index were estimated by minimizing the inconsistency between pairs of exponential projections after compensating for the estimated rigid motion in the projection domain. The method was evaluated on several datasets of a simulated liver patient and on experimentally acquired data of a NEMA IEC phantom.<i>Main results</i>. The proposed method accurately estimated the ground truth motion parameters when the SPECT projections were ideally modeled by the attenuated Radon transform, but was affected by degrading physical effects, mainly by the system spatial resolution (intrinsic and collimator spatial resolution) and the scatter. Despite these physical effects, eDCCs recovered the source center position within a two-pixel offset and substantially improved reconstructed image quality. Specifically, the method achieved a relative activity recovery coefficient (rARC) of around 101% relative to images reconstructed from motion-free projections, compared with an rARC of 87% without correction for the studied liver patient's rigid motion occurring at the beginning of the acquisition.<i>Significance</i>. A fully data-driven method with eDCCs was able to estimate and correct for a rigid patient motion during a SPECT acquisition.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149081895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A harmonisation framework for multi-centre preclinical PET imaging across a national research infrastructure.","authors":"Georgios I Angelis, Gary Cowin, Tzong Hung, Ingrid J Burvenich, Michael De Veer, Kelly Smart, Yaser Hadi Gholami, Karine Mardon, David Zahra, Hasar Hamze, Andrew Scott, Steven R Meikle","doi":"10.1088/1361-6560/aeb46a","DOIUrl":"https://doi.org/10.1088/1361-6560/aeb46a","url":null,"abstract":"<p><strong>Objective: </strong>Quantitative preclinical positron emission tomography (PET) &#xD;imaging plays an important role in translational research, yet variability &#xD;across scanners, sites, and analysis workflows remains a major barrier &#xD;to robust multi-centre studies. In this work, we developed and evaluated &#xD;a harmonisation framework across a national network of preclinical PET &#xD;facilities. &#xD;&#xD;Approach. Six identical NEMA NU~4-2008 image quality phantoms were &#xD;manufactured and distributed to six sites, where they were imaged using &#xD;local acquisition and reconstruction protocols across multiple scanner &#xD;platforms.&#xD;&#xD;Main Results. Substantial variability in contrast recovery, uniformity, &#xD;and spill-over ratios was observed under site-specific conditions. &#xD;Centralised automated re-analysis produced only minor reductions &#xD;in variability, indicating that inter-user effects were relatively small, &#xD;compared to site-specific protocol variations. In contrast, optimisation &#xD;of reconstruction parameters led to a marked reduction in inter-scanner &#xD;variability (an average of 60% reduction across larger rods), particularly &#xD;for voxel-wise maximum contrast recovery coefficients (CRC_max^vox), &#xD;which are more sensitive to noise and reconstruction settings than the &#xD;standard axial averaging NEMA CRC metric. Following harmonisation, &#xD;the variability of CRC_max^vox approached and was lower that of &#xD;conventional axial-averaged NEMA analysis (CRC_max^avg), with &#xD;reductions ranging 7--33% across the 1--5 mm rods, demonstrating &#xD;improved quantitative consistency even at the voxel level.&#xD;&#xD;Significance. These findings show that scanner and site-specific &#xD;protocol variations are the dominant factors for harmonisation in preclinical &#xD;PET. By systematically evaluating acquisition, image reconstruction &#xD;and analysis related sources of variability across a national network of &#xD;heterogeneous preclinical PET systems, this work provides a practical &#xD;framework for harmonisation. The proposed framework is conceptually &#xD;aligned with clinical harmonisation initiatives such as EARL and provides a &#xD;practical basis for the future development of harmonised performance &#xD;ranges across preclinical scanners. This enables more reliable multi-centre &#xD;studies and supports the use of quantitative, voxel-wise imaging biomarkers &#xD;in translational research.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-scanner validation and time-stability analysis of STARE, a blood-free quantification tool for brain imaging with irreversible PET tracers.","authors":"Gjertrud Louise Laurell, Elizabeth A Bartlett, Mike F Schmidt, Sergey Anishchenko, Ilia Shkolnik, Todd Ogden, J John Mann, David Beylin, Jeffrey M Miller, Francesca Zanderigo","doi":"10.1088/1361-6560/aeb469","DOIUrl":"https://doi.org/10.1088/1361-6560/aeb469","url":null,"abstract":"<p><strong>Objective: </strong>\"Gold standard\" blood-based quantification of dynamic 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) data has limited practical clinical applications due to cost and complexity of data collection and analysis. We previously presented a blood-free quantification alternative, STARE (Source-to-Target Automatic Rotating Estimation), that was validated on 18F-FDG data acquired on an ECAT EXACT HR+ scanner. Here, we extend that initial work by applying STARE to within-subject data acquired with both a Siemens Biograph mCT scanner and a portable Brain Biosciences CerePET scanner. &#xD;Approach: Performance was assessed by comparing regional net influx rates (Ki) estimated using STARE and the standard blood-based Patlak approach. Twenty participants underwent 60-minute brain 18F-FDG scans, on two different days, once in each scanner. The time-stability of both STARE- and Patlak-based Ki estimates was evaluated by applying each method to the first 20 (STARE only), 30, 40, and 50 minutes of data. &#xD;Main results: STARE demonstrated high correlation with Patlak Ki estimates, particularly in the Biograph mCT (r = 0.82-0.93 (within-region)), with lower correlation in the CerePET (r = 0.27-0.62 (within-region)). In the Biograph dataset, STARE showed small deviations from the 60-min estimates across all evaluated durations (20 min and above), whereas deviations increased with shorter durations in CerePET data. The Patlak approach showed smaller changes across abbreviated scan durations in both datasets. &#xD;Significance: STARE shows potential as a noninvasive alternative to traditional blood-based quantification of dynamic 18F-FDG PET brain data, facilitating shorter, blood-free acquisition. This advancement could make dynamic 18F-FDG PET brain imaging more accessible and comfortable for patients, potentially facilitating broader clinical adoption. &#xD.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DiscoTSNet: a phase-guided temporal-spatial network for discontinuous respiratory motion prediction.","authors":"Yifan Zhu, Jinmei He, Xiaohe Li, Miao Liao, Yuqian Zhao","doi":"10.1088/1361-6560/aeaf3d","DOIUrl":"10.1088/1361-6560/aeaf3d","url":null,"abstract":"<p><p><i>Objective.</i>Respiratory motion introduces positional uncertainties in radiotherapy for thoracic and abdominal tumors, and system latencies between respiratory signal acquisition and beam adjustment further increase targeting errors. This study aims to develop a precise real-time prediction method for discontinuous respiratory motion under prolonged latency conditions.<i>Approach.</i>We propose DiscoTSNet, a phase-guided temporal-spatial network for discontinuous respiratory motion prediction. The model combines a phase-guided respiratory decomposition module for separating respiratory signals into aperiodic, inhalation, and exhalation components; a Disco2D mechanism for organizing historical sequences according to known system latency; and a spatial feature extraction module for modeling relationships among the coordinate channels of the surface markers.<i>Main results.</i>DiscoTSNet was evaluated on a publicly available CyberKnife respiratory motion dataset and achieved the lowest mean absolute error (MAE) and mean squared error (MSE) and the highest coefficient of determination () and correlation coefficient (CORR) among the compared models across the evaluated latency conditions from 200 ms to 1000 ms. At 1000 ms latency, its MAE, MSE,, and CORR were 0.186, 0.107, 0.688, and 0.831, respectively.<i>Significance.</i>The proposed latency-guided discontinuous respiratory motion prediction method is tailored to radiotherapy motion compensation and has potential to improve real-time tumor tracking and enhance radiotherapy precision.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial sampling for triaxial OPM-MEG: understanding neurodevelopmental trajectory.","authors":"Lukas Rier, Niall Holmes, Ryan Michael Hill, Matthew J Brookes","doi":"10.1088/1361-6560/aeb468","DOIUrl":"https://doi.org/10.1088/1361-6560/aeb468","url":null,"abstract":"<p><strong>Objective: </strong>&#xD;Magnetoencephalography (MEG) measures magnetic fields generated by current flow in neural assemblies, providing a non-invasive means to track brain function. In recent years, the MEG field has been revolutionised by a new class of field sensor called an Optically Pumped Magnetometer (OPM). OPMs are small, lightweight, and allow construction of wearable and reconfigurable arrays of 'triaxial' field sensors (that measure magnetic fields along three axes simultaneously). These systems can be used to capture MEG data across the life span, from infancy to adulthood. With such multi-axis sensing arrays coming into routine use, here we aimed determine how dense a sensor array is required to adequately capture the spatial variation of neuromagnetic fields across the scalp.&#xD;Approach: &#xD;We simulated neuromagnetic fields based on realistic head geometries of individuals aged 15 months to 34 years. We then used two independent approaches to determine the sensor spacing required to capture the highest spatial variation of the field across the scalp surface: one method was based on spherical harmonic decomposition of neuromagnetic fields, and the other based on evaluating sensor redundancy in densely sampled arrays.&#xD;Main results: &#xD;Both methods agree in showing that the required sensor separation increases with age, from ~40 mm in a 1-year-old to ~55 mm in an adult.&#xD;Significance: &#xD;The sensor spacings obtained in our simulations represent upper bounds in the required values: separations above these bounds will not adequately capture spatial field variation; however, continuing to reduce sensor separation below these limits will continue to improve performance. These findings are important for the future development of OPM-MEG technology, particularly the construction of systems for neurodevelopmental applications.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>In silico</i>modeling of radiobiological effects using tumor spheroids.","authors":"Tiago A Azevedo, Diogo Estêvão, Ana M Abrantes, Rui D Travasso, Tânia Cruz, Maria José Oliveira, João Carvalho","doi":"10.1088/1361-6560/aeafa3","DOIUrl":"10.1088/1361-6560/aeafa3","url":null,"abstract":"<p><p><i>Objective.</i>Radiotherapy remains one of the most widely used cancer treatments. However, optimizing its effectiveness requires a deeper understanding of the tumor architecture and its influence on radiation response. Three-dimensional spheroid cultures offer a more physiologically relevant model than traditional 2D assays, and their integration with<i>in silico</i>techniques enable the simulation of both growth dynamics and radiobiological response across multiple scales.<i>Approach.</i>In this study, we developed a multi-scale<i>in silico</i>framework capable of simulating tumor spheroid growth, using a cellular potts model, and transferring that information to OpenTOPAS to simulate irradiation with any given particle type, where in this work we apply it specifically to a 6 MV photon beam. The dose deposited at each cell was used to determine cell fate via a two-lesion kinetic model (TLKM), which accounts for cellular oxygen concentration, the number of radiation-induced double-strand breaks, their type (simple or complex), and their origin (direct or indirect). The model was applied to two rectal cancer cell lines (SW837 and SW1463) subjected to a short-course radiotherapy regimen of 5 Gy/fraction over 5 consecutive days, replicating the fractionation schedule used in short-course radiotherapy for rectal cancer patients.<i>Main results.</i>The calibrated model reproduces experimental spheroid growth and viability data across fractionated treatment, with oxygen dynamics and hypoxic and necrotic zonation behaving as expected under the model's consumption-diffusion coupling, consistent with, though not independently validated, against spatially-resolved measurements. To our knowledge, this is also the first practical application of the oxygen fixation parameter within the TLKM.<i>Significance.</i>This framework provides a flexible platform for investigating alternative treatment regimens, combination therapies, and particle-based modalities. Expanding the experimental dataset, particularly with spatially resolved measurements of proliferative, hypoxic, and necrotic zones, will be essential to further constrain and validate the model. Incorporating subcellular damage mechanisms and explicit dose-rate effects into the TLKM formulation represents key directions for future development.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}