Physics in medicine and biology最新文献

{"title":"Radiolytic yields and peroxyl-radical kinetics predict the LET and oxygenation dependence of FLASH radiotherapy normal-tissue sparing.","authors":"Khaoula Younous, Rajaa Sebihi, Morad El Kafhali, Amine Walia Allah","doi":"10.1088/1361-6560/aeafa6","DOIUrl":"https://doi.org/10.1088/1361-6560/aeafa6","url":null,"abstract":"<p><strong>Objective: </strong>FLASH radiotherapy spares normal tissue at ultra-high dose rates, but the dependence of this protection on linear energy transfer (LET) and tissue oxygenation is not mechanistically understood. We developed a model coupling Geant4-DNA track-structure G-values to the Labarbe peroxyl-radical (ROO•) kinetic framework to predict FLASH normal-tissue sparing as a joint function of LET and oxygenation.&#xD;&#xD;Approach. G-values for •OH, e⁻aq, H• and H₂O₂ were computed with Geant4-DNA chem6 for electrons (0.16-8.70 keV µm⁻¹) and protons (0.69-9.5 keV µm⁻¹), with 500 primary events per LET point, and taken from published Monte Carlo data for carbon ions (10-200 keV µm⁻¹). These were supplied to the Labarbe ordinary differential equation system using the published rate constants without adjustment, and integrated across dose rates of 0.03-10⁵ Gy s⁻¹, doses of 5-30 Gy and oxygen concentrations of 2-200 µM. FLASH sparing was quantified as the fractional reduction in time-integrated ROO• exposure. The mechanism was tested by removing individual reactions from the kinetic system, and predictions were compared with three independent preclinical datasets.&#xD;&#xD;Main results. Using the NTCP parameters published by Labarbe et al (2020), with no quantity fitted in the present work, the model gives a dose-modifying factor of 1.42; with the parameters refitted here it gives 1.44, against experimentally reported values of 1.30-1.40. Sparing decreases monotonically with LET, from 32.3% at 0.16 keV µm⁻¹ to 11.2% at 200 keV µm⁻¹. At matched LET, proton and electron yields converge below 2 keV µm⁻¹ but diverge by up to 19% in G(e⁻aq) at 8.7 keV µm⁻¹, setting a validity limit on LET-only parameterisation. Removing the ROO•-ROO• recombination term collapses sparing from 32.3% to 2.4%, identifying second-order peroxyl recombination as the operative mechanism. The oxygen dependence is dose- and dose-rate-gated, with the sparing difference across 2-200 µM ranging from below 1 to approximately 40 percentage points; at 30 Gy and 100 Gy s⁻¹ the model predicts 8.2 percentage points less sparing in bone osteocytes (15 µM) than in normoxic tissue, consistent with the absence of FLASH bone sparing reported in canine mandible.&#xD;&#xD;Significance. Peroxyl-radical bimolecular recombination, driven by LET-dependent track-structure yields, provides a parameter-free chemical basis for the modality dependence of the FLASH effect. The predicted dose-, dose-rate- and oxygen-gating of sparing gives testable criteria for where FLASH protection should and should not occur.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149112915","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":"Scatter-induced non-linear signal compression and SDNR loss in triple-energy photon-counting iodine imaging.","authors":"Jesse Tanguay, Kaitlyn Allison Sims","doi":"10.1088/1361-6560/aeafa4","DOIUrl":"https://doi.org/10.1088/1361-6560/aeafa4","url":null,"abstract":"<p><p>Triple-energy x-ray imaging with photon-counting detectors (PCDs) enables material decomposition, but energy-dependent scatter introduces bin-specific distortions that propagate nonlinearly through triple-energy subtraction and degrade image quality. The purpose of this work is to quantify how bin-dependent scatter alters triple-energy iodine signal formation and to determine its impact on signal-difference-to-noise ratio (SDNR). Analytical expressions for iodine signal difference, noise, and SDNR were derived incorporating energy-bin-specific scatter fractions (SF) and their nonlinear coupling with iodine areal density. Measurements were performed using a CdTe-based PCD and an image-quality phantom, with scatter varied via field of view (FOV) and quantified using the air-gap method. SDNR was evaluated over iodine areal densities of 33-140 mg/cm², SF values of ~0.2-0.8, tube voltages of 60-100 kV, and phantom thicknesses of 10-20 cm. A physics-informed empirical model was fit to the data. Simulations including charge sharing and beam hardening were used to support interpretation. Scatter fractions differed across energy bins, with the lowest-energy bin exhibiting the highest SF. Increasing scatter introduced curvature in energy-bin iodine signals as a function of areal density. When combined through triple-energy subtraction, these unequal responses produced pronounced signal compression in the triple-energy image. The model accurately predicted energy-bin and combined signal differences (R{{}^2} > 0.92) but showed reduced agreement for SDNR (R{{}^2} = 0.82-0.94), reflecting additional coupling between signal, noise, and scatter in the triple-energy combination. SDNR degradation exceeded that expected from first-order scatter scaling: for 52 mg/cm² iodine, SDNR decreased by ~20% at SF ≈ 0.2 and ~70% at SF ≈ 0.8. Simulations reproduced both linear contrast loss and the additional nonlinear compression observed experimentally. Bin-dependent scatter induces nonlinear signal compression in triple-energy imaging that directly amplifies SDNR loss with increasing iodine thickness. Because this behavior arises from the structure of triple-energy subtraction, first-order scatter scaling systematically underestimates performance degradation.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149112934","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":"Deep learning prediction of radiation-induced xerostomia and personalized outcome-driven treatment planning in head and neck cancer.","authors":"Bohua Wan, Todd McNutt, Harry Quon, Junghoon Lee","doi":"10.1088/1361-6560/aeaac0","DOIUrl":"10.1088/1361-6560/aeaac0","url":null,"abstract":"<p><p><i>Objective</i>. Radiation therapy (RT) is critical in head and neck cancer (HNC) treatment but often causes radiation-induced toxicities, such as xerostomia (RIX). While deep learning (DL)-based models show promise in predicting these toxicities, their black-box nature hinders clinical applications. This study aims to develop a robust DL model to predict RIX 12 months after RT and to leverage model interpretability techniques, specifically class activation maps (CAMs) and voxel-wise dose gradient maps (GMs), to guide personalized treatment plan optimization.<i>Approach</i>. A 3D ResNet-based model was trained using planning CTs, dose volumes, and salivary gland contours obtained from a retrospective cohort of 839 HNC patients. To address anatomical variations, we normalized each patient's volumes to a common reference frame using atlas normalization. To improve spatial correspondence between deep features and patient anatomy, we integrated blur pooling and adaptive average pooling, mitigating downsampling-induced voxel shifts. Model interpretability was achieved using Grad-CAM++ and GMs. Personalized plan optimization was performed on predicted RIX-positive cases by generating avoidance contours from both CAMs and GMs to guide dose reduction.<i>Main results</i>. The proposed model was tested on 30 independent test cases. It achieved an AUC of 0.77 with balanced sensitivity (0.71) and specificity (0.83). Among 9 predicted RIX-positive cases, GM-guided optimization converted the predictions to RIX-negative in 7 cases (77.8%), compared with 6 cases (66.7%) for CAM-guided optimization, and achieved a greater reduction in mean model-predicted RIX probability (26% versus 20%).<i>Significance</i>. The proposed atlas-normalized model achieved robust discrimination, and a 9-case plan-refinement analysis showed that CAM- and GM-derived spatial information could be translated into clinically constrained avoidance objectives that reduced the model-predicted RIX probability while preserving specified target and organs at risk dose requirements. These results demonstrate the feasibility of the proposed strategy for guiding clinical interventions.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149017764","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":"Ultrafast proton delivery with pin ridge filters (pRFs): repurposing single-energy delivery for motion management in proton therapy.","authors":"Ahmal Jawad Zafar, Xiaofeng Yang, Sunil William Dutta, Yinan Wang, Duncan Henry Bohannon, Zachary Diamond, Pretesh Patel, Sibo Tian, Jun Zhou","doi":"10.1088/1361-6560/aeaf42","DOIUrl":"https://doi.org/10.1088/1361-6560/aeaf42","url":null,"abstract":"<p><strong>Objective: </strong>Highly conformal proton stereotactic body radiation therapy (SBRT) remains vulnerable to respiratory interplay, and standard mitigation techniques are either patient-dependent or enlarge the irradiated volume. Long delivery times dominated by energy-layer switching (ELS) limit the use of breath-hold (BH). We propose using pin-ridge filters (pRF) to eliminate ELS, shorten beam-on time, and reduce margins.</p><p><strong>Approach: </strong>A monoenergetic pRF plan was constructed, with the highest clinical energy (Emax) obtained from the reference internal target volume (ITV)-based intensity modulated proton therapy (IMPT) plan. To avoid per-patient commissioning, we used a bank of pre-commissioned monoenergetic beams spanning 110-200 MeV. Each beam model enables the development of a gross tumor volume (GTV)-based downstream IMPT (IMPT-DS) plan (reduced margins in the BH setting). Next, a nested pencil-beam-direction (PBD) spot-reduction process iteratively removed low-weighted spots from each PBD and, finally, generated pRFs with coarser resolution using a single-energy. This method was validated on five liver and one lung SBRT cases (10 Gy ×5) by comparing the relative total volume receiving the prescription dose (conformity index CI(GTV+5mm) =VRx/VGTV+5mm) and the mean lung-GTV and liver-GTV doses between the conventional IMPT and pRF plans.</p><p><strong>Main results: </strong>Across five liver SBRT cases, the average CI(GTV+5mm) improves from 2.64 (IMPT) to 1.16 (IMPT-pRF). The reduced dose cloud results in ~26% reduction in Dmean to liver-GTV. The mean beam-on time per field dropped from 43.02 s (IMPT) to 7.14 s (IMPT-pRF), i.e., an average saving of 35.88 s per beam (83.4% shorter). Lung SBRT follows a similar trend for CI(GTV+5mm) (3.22 to 1.58), lung-GTV Dmean (10.3 to 6.9 Gy), and average beam-on time (decreased from 47.2 to 9.5s per beam). These dosimetric improvements are primarily due to change in the planning approach (free-breathing ITV to BH GTV), whereas the key contribution of the pRF is shortening of beam-on time, which makes BH delivery feasible and thereby allows this margin reduction.</p><p><strong>Significance: </strong>This proposed method significantly reduces delivery time and organ-at-risk dose. Future work should focus on planning quality assurance (QA) and clinical implementation in patients with limited breath-hold capacity.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113036","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":"Pulse width-dependent Monte Carlo source modeling for ultra-high dose rate electron beams.","authors":"Ángela Henao Isaza, Iván López Paz, Consuelo Guardiola, Johan Sebastián Moreno, Sophie Heinrich","doi":"10.1088/1361-6560/aea8c4","DOIUrl":"10.1088/1361-6560/aea8c4","url":null,"abstract":"<p><p><i>Objective.</i>The emergence of ultra-high dose rate (UHDR) electron beams has highlighted the need for accurate Monte Carlo (MC) source models after recent measurements revealed pulse width (PW)-dependent discrepancies in dose profiles. This work aims to develop and validate a MC source model for conventional and FLASH modes using GATE 10, including PW dependence.<i>Approach.</i>Percentage depth dose (PDD) curves and lateral dose profiles were measured in water using a flashDiamond detector for PWs of 0.5-5s. These data were used to optimize the parametric source model throughminimization and gamma analysis. Validation was performed using a mouse collimator and PMMA slabs. Relative dose distributions and cumulative dose-volume histograms were computed in a CT-based voxelised mouse, with and without bolus.<i>Main results.</i>The optimized FLASH source model features a dual-peak energy spectrum with a PW-dependent energy component (7.0-7.8 MeV for 0.5-5s) and low-energy component probability. In conventional mode, a two-component spectrum (1.51.0 and 6.81.5 MeV) was used. Simulations showed good agreement with measurements (gamma-index 2 mm/2% anddifferences for,and). Differences in the mouse lung volume receiving at least 95% of the maximum dose (V95) were 1% across FLASH PWs, increasing to 5% and 12% in CONV without and with bolus, respectively. Bolus increased V95in FLASH by 17%, indicating improved target coverage.<i>Significance.</i>A GATE 10 MC-based source model of the ElectronFLASH LINAC was developed for both UHDR (PW-dependent) and conventional modes. Despite PW-dependent energy variations, no significant dosimetric differences were observed between PWs in FLASH in the preclinical mouse model. The model provides a reliable tool for optimization of preclinical irradiation setups for FLASH biological studies in the absence of a treatment planning system.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148983405","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":"Characterizing magnetic field coupling in MRI-guided radiotherapy by solving a dirichlet problem with sparsely sampled boundary conditions.","authors":"K Vat, T Stanescu","doi":"10.1088/1361-6560/aeabe6","DOIUrl":"10.1088/1361-6560/aeabe6","url":null,"abstract":"<p><p><i>Objective.</i>Integrating medical linear accelerators and magnetic resonance imaging (MRI) scanners for MRI-guided radiotherapy (MRgRT) is complicated by mutual magnetic field coupling, making efficient field mapping crucial. This study proposes a computationally efficient methodology to characterize an MR scanner's magnetic fringe field by solving a boundary value problem (BVP) from sparsely sampled data. This approach accurately maps fields in free space and near ferromagnetic materials without requiring proprietary internal MR coil models or full-scale room simulations.<i>Approach.</i>A full-scale finite element method (FEM) model of a proximity-type MRgRT system, validated against experimental measurements, was used as the reference. A hybrid BVP methodology was developed where Laplace's equation was first solved using sparsely sampled magnetic field boundary conditions. To account for the linac, this free-space solution was subsequently used as an initial condition for a refined model that incorporated the ferromagnetic properties of the linac head and was solved using Maxwell's equations. Accuracy was assessed by comparing the BVP solutions to the full-scale FEM reference across various sampling resolutions.<i>Main results.</i>The BVP approach reconstructed the magnetic field to within 1 G of the reference using a coarse 40 cm boundary sampling. The hybrid method successfully characterized field distortions from the linac; ignoring the ferromagnetic structure led to errors of -7 G to 2 G near the component, whereas including it reduced the discrepancy to within 1 G. The methodology was efficient, reducing computation time from 2 h for the full-scale model to under 10 min, while using a fraction of the memory.<i>Significance.</i>This study presents a validated, efficient, and accessible BVP-based methodology for magnetic field characterization in MRgRT systems. By enabling accurate field mapping from sparse data, accounting for ferromagnetic components, and drastically reducing computational demands, this approach offers a robust tool for rapid engineering assessments and serves as a practical alternative to complex full-scale simulations.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149031140","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":"Decay-time correction for dual-panel in-beam PET monitoring of carbon-ion SOBP irradiation.","authors":"QingHua Zhang, Zhiqiang Liu, Tianyi Deng, Junbing Chen, Xiaodong Mo, Jiemin Zhang, Dian Guo, Peiwen Wang, Qiuning Zhang, Yongzhi Yin, Baowei Ding","doi":"10.1088/1361-6560/aeaf3f","DOIUrl":"https://doi.org/10.1088/1361-6560/aeaf3f","url":null,"abstract":"<p><strong>Objective: </strong>In-beam positron emission tomography (PET) is a promising technique for monitoring beam range and activity distribution in carbon-ion radiotherapy. However, spread-out Bragg peak (SOBP) delivery introduces a challenge because sequentially delivered energy layers experience different decay times in in-beam and off-beam PET acquisitions. This study developed a decay-time correction method to reduce temporal bias in measured PET activity distributions under SOBP irradiation.&#xD;Approach: A dual-panel LYSO-SiPM PET system in a 4 × 1 module arrangement, with an effective detection area of 21.28 × 5.32 cm², was used to acquire in-beam and off-beam PET images during homogeneous solid-water phantom irradiation. The beam was delivered in scanning mode using sequential high-to-low energy layers, with up to 11 layers ranging from 216.50 to 263.23 MeV/u. Four irradiation schemes were evaluated: physical-dose, RBE-weighted dose (RWD), full-opposing-field RWD, and half-opposing-field RWD SOBP. A Monte Carlo-based decay-time correction framework was established by incorporating beam delivery timing, radionuclide decay characteristics, and activity accumulation. Corrected PET images were compared with Monte Carlo-simulated activity distributions generated using a platform consistent with the experimental setup.&#xD;Main Results: Sequential energy-layer delivery and radionuclide decay affected measured PET activity distributions under SOBP irradiation. After correction, experimental PET profiles showed improved agreement with corresponding Monte Carlo profiles across all four SOBP schemes. Depending on the irradiation scheme and acquisition mode, the correction reduced root-mean-square error by approximately 7.7%-53.7%, reduced SOBP-region mean absolute deviation by approximately 20.8%-71.4%, and increased the Pearson correlation coefficient from 0.860-0.973 before correction to 0.941-0.978 after correction.&#xD;Significance: This study addressed temporal bias in PET activity distributions caused by decay-time differences among sequentially delivered energy layers during carbon-ion SOBP irradiation. The proposed correction improved the reliability and interpretability of dual-panel in-beam PET under sequential multi-energy carbon-ion irradiation, extending planar PET monitoring toward more treatment-relevant verification scenarios.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113666","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":"NHPVS: a nodule-aware deep learning method for high-abundance pulmonary vessel segmentation on chest CT.","authors":"Rui Zhao, Shaoze Luo, Longfei Zhao, Bing Li, Zhuangfei Ma, Ruijie Zhao, Jiaru Wang, Ran Xiao, Sirong Piao, Ying Ming, Zicheng Liao, Qiqi Xu, Wei Song","doi":"10.1088/1361-6560/aea7f2","DOIUrl":"10.1088/1361-6560/aea7f2","url":null,"abstract":"<p><p><i>Objective.</i>Deep learning-based segmentation of pulmonary vessels is challenged by vessel-nodule confusion and insufficient detection of small vessels. To address these issues, we propose a Nodule-aware High-abundance Pulmonary Vessel Segmentation (NHPVS) framework that enhances nodule differentiation and improves small vessel segmentation.<i>Approach.</i>This multi-center study retrospectively collected 477 chest CT scans comprising non-contrast and contrast scans. A 3D U-Net-based model was trained on 370 scans for pulmonary vessel segmentation. Performance metrics included Dice similarity coefficient (DSC), sensitivity, centerline DSC (cl DSC), 95% Hausdorff distance (HD95), and nodule misclassification rate (NMR). Visual and quantitative assessments were conducted on the external test set.<i>Main Results.</i>NHPVS outperformed existing methods, achieving a DSC of 89.2%, a sensitivity of 89.2%, a cl DSC of 93.2%, an HD95 of 1.4 mm, and an NMR of 1.8%. Compared with the state-of-the-art method (nnUNet-v2), NHPVS showed superior segmentation accuracy, vascular continuity, and branch abundance, with improvements of 31.1% in vessel length and 60.5% in branch counts. The volume of small pulmonary vessels (diameter <3 mm) segmented by NHPVS was significantly greater than that segmented by nnUNet-v2 (<i>p</i>< 0.001).<i>Significance.</i>By enabling the precise visualization of pulmonary arteries and veins on chest CT, NHPVS has the potential to assist radiologists in disease diagnosis and surgical planning.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148977543","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":"Comparison of proton, helium-ion, and carbon-ion CT imaging for hadron radiotherapy using Monte Carlo simulations.","authors":"Zsófia Jólesz, Gábor Bíró, G Papp, Gergely Gábor Barnaföldi","doi":"10.1088/1361-6560/aeaf40","DOIUrl":"https://doi.org/10.1088/1361-6560/aeaf40","url":null,"abstract":"<p><strong>Objective: </strong>To perform a comprehensive comparative analysis of proton, helium-ion, and carbon-ion computed tomography (CT) as direct imaging modalities for hadron therapy treatment planning, focusing on Relative Stopping Power (RSP) reconstruction accuracy and patient radiation dose.&#xD;Approach: High-fidelity Monte Carlo simulations were conducted using the GATE/Geant4 platform to model a standard CTP404 phantom. RSP maps were reconstructed using two iterative algorithms: the Simultaneous Algebraic Reconstruction Technique (SART) and the Richardson-Lucy (RL) deconvolution. Imaging performance was evaluated by comparing reconstructed RSP values against ground truth data for various tissue-equivalent inserts, while integral doses were estimated for a human head geometry using a Shepp-Logan-like phantom.&#xD;Main results: All investigated particle modalities demonstrated a significant dose reduction compared to conventional X-ray CT protocols (which are approximately 40 mGy). The estimated imaging doses were 0.5 mGy for protons, 1.3 mGy for helium ions, and 7.5 mGy for carbon ions. &#xD;In terms of accuracy, carbon-ion imaging achieved promising accuracy for soft-tissue materials (mean absolute error <0.5%). Helium ions offered a balanced performance with sub-1% errors for most materials and a dose burden significantly lower than carbon ions. Protons exhibited the widest range of RSP deviations.&#xD;Significance: Direct particle imaging eliminates the systematic uncertainties inherent in photon-to-hadron conversion, which typically introduce RSP deviations of 1.6%-3.5% in standard single-energy X-ray CT. While carbon ions provide better RSP reconstruction precision essential for complex treatment plans in heterogeneous anatomy, helium and proton imaging offer exceptional dose sparing, making them particularly advantageous for pediatric patients and frequent adaptive replanning scenarios.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149113703","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":"Effects of count rate performance on image quality in an LAFOV PET/CT system.","authors":"Nanna Overbeck, Zuzanna Czeluśniak, Søren Holm, Julie V Henriksen, Flemming Littrup Andersen, Thomas Lund Andersen","doi":"10.1088/1361-6560/aea301","DOIUrl":"10.1088/1361-6560/aea301","url":null,"abstract":"<p><p>The development of Long Axial Field-of-View positron emission tomography combined with computed tomography warrants reconsideration of the administered activity required for clinical imaging. This study investigated the relationship between body size, administered activity (¹⁸F), and image quality (IQ) using two patient-like phantoms representing normal (78.5 kg) and obese (194.3 kg) body profiles. The phantoms were scanned in selected five-minute periods within a total duration of 27 and 21 h, respectively, following the decay of the activity. Analysis of the trues, scatter, and randoms demonstrated a close to linear propagation of the trues with activity up to a point where saturation was reached. The normal body profile phantom achieved higher signal-to-noise ratios (SNRs), reaching system saturation at a lower activity (680 MBq) than the large phantom, representing the obese body profile (970 MBq). The SNR²showed a nonlinear correlation with the noise equivalent count rate, whereas SNR²had a linear correlation with the trues. The study demonstrated the count rate capabilities up to and beyond the saturation limit. Furthermore, we illustrated the possibilities of scanning patients with ultralow dose administration in the range of 0.03-0.07 MBq kg^-1body weight. However, achieving robust clinical diagnostic quality-particularly for low-contrast lesions-at these activity levels requires further clinical investigation. Utilising these ultralow activity concentrations requires extending the scan duration to compensate for IQ, especially when examining obese patients.</p>","PeriodicalId":20185,"journal":{"name":"Physics in medicine and biology","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892265","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}