Med Phys [JOURNAL]
Sun
200 papers
Correction to "On the shape of the radiation survival curve in tumor spheroids: The role of oxygen heterogeneity".
Med Phys · 2026 Jul · PMID 42384576 · Publisher ↗
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Multi-view constrained semi-supervised vertebra detection for 3D ultrasound spine volume.
Gao Y, Zhao J, Mao Y … +4 more , Song X, Zhang M, Zheng R, Zeng H
Med Phys · 2026 Jul · PMID 42384571 · Publisher ↗
BACKGROUND: Scoliosis is a spinal disorder characterized by a three-dimensional (3D) deformity of the vertebral column. 3D ultrasound imaging has been used for scoliosis assessment, and automatic vertebra detection is im...
BACKGROUND: Scoliosis is a spinal disorder characterized by a three-dimensional (3D) deformity of the vertebral column. 3D ultrasound imaging has been used for scoliosis assessment, and automatic vertebra detection is important for objective evaluation of spinal deformity. However, existing automatic assessment methods are mainly based on two-dimensional (2D) projection images and require large amounts of labeled data, leading to incomplete use of volumetric ultrasound information and substantial annotation effort. PURPOSE: To develop a multi-view constrained semi-supervised learning (SSL) method for vertebra detection that reduces annotation requirements and facilitates fully automatic 3D spinal deformity assessment. METHODS: The proposed framework integrated maximum intensity projection (MIP) images in the coronal view with ultrasound slices in the transverse view to exploit complementary multi-view information from 3D ultrasound volumes. A semi-supervised training strategy was adopted, in which coronal bounding boxes were incorporated into pseudo-label generation for the transverse lamina detector. The resulting 3D lamina positions were used for spinal curve fitting, curvature estimation, and 3D visualization. The training set comprised 83 593 unlabeled transverse ultrasound slices from 180 subjects and 856 labeled slices from 10 subjects, whereas the testing set included 2163 slices from 163 patients. To evaluate label efficiency, not all labeled slices were used for training; instead, subsets of different sizes were sampled from the labeled training set to analyze the effect of labeled training set size on detection performance. The proposed method was compared with supervised learning and several SSL benchmarks, including Pseudo-Labeling, FixMatch, MeanTeacher, Uncertainty-Aware Mean Teacher (UA-MT), and Vertmatch. Detection performance was evaluated using accuracy, precision, recall, and F1 score, whereas scoliosis angle estimation in 30 ultrasound subjects was assessed against the radiographic Cobb angle and manually labeled ultrasound spine curvature using mean absolute difference (MAD) and standard deviation (STD). Statistical analysis was performed using the Wilcoxon signed-rank test at a significance level of , with Bonferroni correction for multiplicity, Cohen's d effect-size analysis, and 95% confidence intervals estimated from 1000 bootstrap resamples. RESULTS: On the vertebra detection task, the proposed method achieved an accuracy of 91.19%, a precision of 93.02%, a recall of 97.89%, and an F1 score of 95.39% using a subset of 400 labeled training slices. Compared to all SSL methods, the proposed method improved accuracy by 0.22% to 10.34% and precision by 1.71% - 9.03%. These comparisons were statistically significant ( ), and effect-size analysis showed large effects for most metrics, except for Recall versus FixMatch (Cohen's d = 0.26). Ablation experiments showed that the multi-view constraint increased accuracy from 83.87% to 91.19%. On the clinical dataset, both manual and automatic ultrasound-based measurements showed good agreement with the radiographic measurements (automatic MAD: , SD: ; manual MAD: , SD: ). The difference was not statistically significant ( ). CONCLUSIONS: The proposed method reduces annotation workload and improves vertebra detection performance, providing a promising non-radiative approach for scoliosis assessment.
Accuracy of quantitative Lu SPECT/CT imaging: A systematic review.
van Oorschodt JCJ, Eslick GD, Ugander M … +2 more , van Pul C, Eslick EM
Med Phys · 2026 Jul · PMID 42384560 · Publisher ↗
Accurate quantification of lutetium-177 (Lu) activity in SPECT/CT imaging is essential for a further development of Lu-based peptide receptor radionuclide therapy (PRRT) in establishing absorbed dose-effect relationships...
Accurate quantification of lutetium-177 (Lu) activity in SPECT/CT imaging is essential for a further development of Lu-based peptide receptor radionuclide therapy (PRRT) in establishing absorbed dose-effect relationships. This review summarizes the reported accuracy of quantitative Lu SPECT/CT imaging and highlights key sources of variability, including partial-volume effect (PVE) in small volumes. A systematic review was conducted according to PRISMA guidelines. MEDLINE, EMBASE, and Web of Science databases were searched with no language restrictions. Original studies explicitly reporting on the accuracy of Lu activity quantifications in physical SPECT/CT measurements were included. Reported percentage error/deviation and recovery coefficient (RC) were extracted and compiled, with studies grouped by object type (geometric phantoms, anthropomorphic phantoms, and patient data). The literature search identified 630 records, of which 46 studies were included for analysis. Percentage errors of quantifications were found to constitute a large range (-102% to 285%). The recovery of Lu activity from small volumes is inherently limited by PVE. The application of PVC has led to improvements in the accuracy and precision of quantifications on small volumes in phantom imaging. The accuracy of Lu activity quantifications in SPECT/CT imaging remains heterogenous across literature, is subject to large variability and will be degraded by PVE when imaging small volumes. The data suggests that the implementation of standardized procedures including standardization of calibration, reconstruction, segmentation, and PVC assumptions may lead to an improved accuracy and precision of quantitative Lu SPECT/CT imaging in clinical practice, thereby allowing the further development of Lu-based PRRT.
Physics-constrained dual-domain network for CBCT reconstruction from orthogonal X-rays in gynecologic radiotherapy.
Gao Y, Hu M, Pan S … +10 more , Peng J, Xie H, Chang CW, Remick J, Bradshaw B, Kapoor P, Qiu RLJ, Roper J, Tian Z, Yang X
Med Phys · 2026 Jul · PMID 42384553 · Publisher ↗
BACKGROUND: Daily cone-beam computed tomography (CBCT) is widely used for image-guided radiotherapy (IGRT) in gynecologic (GYN) cancer to verify patient setup and visualize inter-fraction pelvic anatomical variations, wh...
BACKGROUND: Daily cone-beam computed tomography (CBCT) is widely used for image-guided radiotherapy (IGRT) in gynecologic (GYN) cancer to verify patient setup and visualize inter-fraction pelvic anatomical variations, where volumetric soft-tissue information is critical due to substantial organ motion and deformation. However, routine CBCT acquisition increases treatment time and cumulative imaging dose over multi-week treatment courses. In clinical practice, orthogonal two-dimensional (2D) kilovoltage (kV) X-ray imaging is often used for rapid setup verification but provides limited soft-tissue information and cannot adequately capture internal anatomical changes relevant to pelvic radiotherapy. Recent deep learning approaches have shown promises for reconstructing three-dimensional (3D) images from sparse projections, yet many methods lack explicit physical constraints or fail to fully exploit the geometric coupling between projection data and volumetric anatomy, particularly in patient-specific GYN radiotherapy settings. PURPOSE: The purpose of this study is to develop and evaluate a patient-specific framework that reconstructs volumetric CBCT images from orthogonal anterior-posterior (AP) and lateral (LAT) X-ray projections, enabling recovery of clinically relevant three-dimensional (3D) anatomical information while reducing reliance on daily CBCT acquisition. METHODS: We propose a physics-constrained dual-domain network (PCD-Net) for CBCT reconstruction from ultra-sparse orthogonal projections. The framework integrates three key components: (1) a Projection Restoration Network that estimates missing angular information in the projection domain, (2) a differentiable analytic geometry transformation operator that enforces physical consistency between projection and image domains, and (3) a Volumetric Refinement Network that enhances reconstructed CBCT image quality. The method was evaluated on 360 CBCT datasets acquired from 15 GYN cancer patients, with 24 fractions per patient used for patient-specific training and testing. Reconstructed volumes were quantitatively compared with reference CBCT using peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and mean absolute error (MAE) within a body mask. Performance was benchmarked against a conditional generative adversarial network (C-GAN) and a standard volumetric denoising diffusion probabilistic model (DDPM). RESULTS: PCD-Net achieved improved reconstruction performance compared with baseline methods, yielding an average PSNR of 48.02 dB, SSIM of 0.9880, and masked MAE of 24.89 HU. In comparison, the conditional GAN achieved a PSNR of 37.94 dB, SSIM of 0.9546, and MAE of 48.45 HU, while the standard DDPM achieved a PSNR of 38.89 dB, SSIM of 0.9634, and MAE of 46.29 HU. Qualitative evaluation demonstrated reduced reconstruction artifacts and improved anatomical consistency relative to the comparison methods. CONCLUSION: The proposed PCD-Net enables geometry-consistent volumetric CBCT reconstruction from ultra-sparse orthogonal 2D kV projections. This approach has the potential to reduce imaging dose and treatment time in daily IGRT workflows while preserving clinically meaningful volumetric information, making it particularly suitable for GYN radiotherapy where frequent image guidance is required.
Decomposition-based harmonization for quantitative PET imaging across scanners and radiotracers.
Zhao S, Huang Q, Nie B … +5 more , Zhang T, Zuo C, Zhang G, Mao G, Shan B
Med Phys · 2026 Jul · PMID 42381155 · Publisher ↗
BACKGROUND: Quantitative positron emission tomography (PET) is widely applied in oncology, neuroscience, and clinical practice. However, its quantitative accuracy is often compromised by systematic variability arising fr...
BACKGROUND: Quantitative positron emission tomography (PET) is widely applied in oncology, neuroscience, and clinical practice. However, its quantitative accuracy is often compromised by systematic variability arising from differences in scanners, acquisition protocols, and radiotracers, which limits the reliability of multicenter studies. PURPOSE: To develop and validate PETHarmony, a novel voxel-level harmonization framework for minimizing inter-scanner and inter-tracer variability. METHODS: PETHarmony utilizes a linear neural network to model covariates and singular value decomposition to isolate and remove variability in voxel space. Its performance was assessed in four scenarios: (i) using paired -FBB PET/CT and PET/MR scans (N = 25, Huashan Hospital) to test the removal of scanner variability; (ii) using 20 repeated PET acquisitions of a NEMA NU-2 IQ phantom to validate absolute quantitative accuracy; (iii) using paired -FBP and -PiB scans from GAAIN (N = 46); and OASIS (N = 84) to evaluate cross-tracer consistency of cortical SUVR; and (iv) using unpaired multicenter data from ADNI (N = 471; -FBP, -FTP, -FDG) to assess the impact on Alzheimer's disease (AD) classification. All harmonization procedures were conducted using leave-one-out cross-validation or by training on unpaired data and applying the learned transformations to paired data. RESULTS: PETHarmony effectively eliminated voxel-level discrepancies between PET/CT and PET/MR images ( reduced to n.s.). Phantom validation demonstrated that recovery coefficient curves were restored and closely aligned with the reference line, indicating improved quantitative accuracy. For cross-tracer consistency, linear regression between -FBP and -PiB was markedly improved toward the line of identity (y = x, R = 1). Specifically, in the GAAIN cohort, the regression line improved from y = 0.52x + 0.52, = 0.89 to y = 0.93x + 0.13, R = 0.97. In the OASIS cohort, it improved from y = 0.51x + 0.55, = 0.87 to y = 0.95x + 0.06, = 0.95. Furthermore, PETHarmony improved multicenter AD classification accuracy by 15.3% ( -FBP), 18.3% ( -FTP), and 21.7% ( -FDG). CONCLUSIONS: PETHarmony achieves robust voxel-level harmonization of multicenter PET data, significantly improving cross-scanner and cross-tracer consistency and enhancing diagnostic accuracy. It provides a practical solution for standardizing quantitative PET in multicenter oncology, neuroscience, and other clinical trials.
Development and evaluation of an in vivo dose-based monitoring system for electron FLASH radiation therapy.
DeFrancisco J, Richeson M, Javidtash T … +3 more , Bartee C, Ma T, Kim S
Med Phys · 2026 Jul · PMID 42381116 · Full text
BACKGROUND: FLASH radiotherapy requires further preclinical and clinical investigation to establish its biological effectiveness and define optimal beam parameters. In conventional (CONV) radiotherapy, redundant beam ter...
BACKGROUND: FLASH radiotherapy requires further preclinical and clinical investigation to establish its biological effectiveness and define optimal beam parameters. In conventional (CONV) radiotherapy, redundant beam termination systems are a cornerstone ensuring patient safety, yet analogous safeguards for FLASH delivery are not well established, creating a critical barrier to safely enabling such studies. PURPOSE: To develop and evaluate a real-time, in vivo, point-dose monitoring system capable of terminating electron FLASH beam delivery as an additional monitoring system on a modified medical linear accelerator (LINAC). METHODS: A decommissioned LINAC was modified to deliver electron FLASH beams with stable dose per pulse (DPP) at 300 Hz pulse frequency. A commercial plastic scintillation detector system was adapted through hardware and firmware modifications to enable pulse-based and dose-based beam termination via the LINAC MLC interface. The detector was cross-calibrated against radiochromic film under FLASH conditions. System performance was evaluated through measurements of control accuracy, and detector response as a function of DPP. RESULTS: Stable electron FLASH delivery was achieved with an average dose rate of 127.5 14.91 Gy/s and an approximate beam energy of 5.2 MeV. Pulse-based control terminated delivery within +3 pulses of the requested value (requested 1-20 pulses), with overshoot attributable to downstream circuitry latency. Dose-based control agreed with film measurements within 1.11 0.81 Gy for surface-based control (in vivo setup) and -1.45 0.38 Gy at depth (stable dosimetry) (tested dose deliveries between 2-15 Gy). The detector response versus DPP in the FLASH range (0.11-0.78 Gy/p) could be roughly approximated as linear before detector saturation, with only marginal improvement seen when using quadratic fitting. CONCLUSION: A modified scintillation-based system was implemented as a real-time in vivo beam termination mechanism for electron FLASH radiotherapy under stable DPP and specific experimental conditions. While not intended for primary beam control, the system may provide a practical redundant safety layer for mitigating gross delivery errors in experimental and translational FLASH applications.
A novel optical respiratory gating system with a hybrid phase-amplitude algorithm for spot-scanning proton therapy.
Belikhin MA, Shemyakov AE, Zavestovskaya IN … +1 more , Pryanichnikov AA
Med Phys · 2026 Jul · PMID 42376887 · Publisher ↗
BACKGROUND: Respiratory motion remains a major challenge in thoracic and abdominal proton treatments, causing interplay effects and dose distortions. In synchrotron-based systems, conventional gating significantly prolon...
BACKGROUND: Respiratory motion remains a major challenge in thoracic and abdominal proton treatments, causing interplay effects and dose distortions. In synchrotron-based systems, conventional gating significantly prolongs beam delivery and overall treatment time, which limits its clinical applicability and patient suitability. PURPOSE: The present study was aimed to investigation of the gating system with the novel hybrid phase-amplitude algorithm specified for synchrotron-based proton therapy systems with spot-scanning beam delivery in the phantom test. This system was experimentally evaluated for robustness to target motion irregularities in terms of dose distortion and irradiation time. METHODS: A dynamic phantom simulated the free-breathing motion using a radiochromic film immersed in water. The film was irradiated in a single fraction with gating for regular and irregular motion patterns. The phase-amplitude gating algorithm was implemented to provide two-signal control of the synchrotron for beam injection and extraction. The measured dose distributions were analyzed using gamma index calculation with a 5%/3 mm criterion. RESULTS: Gating mitigated the interplay effect, resulting in a gamma passing rate (GPR) of 98.5 ± 0.1% (mean ± SD) at regular motion, but the irradiation time was increased from 155 ± 2 s (mean ± SD) to 209 ± 9 s compared to no gating. The GPR fluctuated unsystematically as a function of motion irregularity (p = 0.111), resulting in a median GPR of 96.0% (range 89.2%-98.6%), and the irradiation time increased from 209 ± 9 s to 238 ± 8 s compared to regular motion (p = 0.002). Robustness to random motion irregularities up to 30% resulted in 67% acceptable dose distributions and 14% increase in irradiation time. CONCLUSIONS: The algorithm ensured full synchronization of beam injection and extraction with the respiratory cycle, which allowed a significant reduction in treatment time. The phase-amplitude gating together with fractionation and rescanning can be potentially effective in the treatment of thoracic and abdominal tumors using synchrotron-based systems with scanning beams. The introduction of a system-specific quantitative threshold for patient respiratory irregularity is mandatory for deciding to use gated treatment or not.
Gamma Knife treatment planning using knowledge-based reinforcement learning.
Huynh C, Ahlgren B, Zhang B … +3 more , Fay D, Nordström H, Ruschin M
Med Phys · 2026 Jul · PMID 42376877 · Full text
BACKGROUND: Inverse planning is often used for Gamma Knife radiosurgery, allowing clinicians to mathematically specify desired clinical objectives and dose limits. The objectives are controlled by weights that are manual...
BACKGROUND: Inverse planning is often used for Gamma Knife radiosurgery, allowing clinicians to mathematically specify desired clinical objectives and dose limits. The objectives are controlled by weights that are manually tuned to find the desired trade-off, which varies from case to case. Automation of this process can reduce clinical workload and improve consistency in plan quality. PURPOSE: To train a deep reinforcement learning agent using a reward function that incorporates the clinical metrics from past plans into its scoring criteria. The metric trade-off from the clinical plan is scored higher than all others, guiding the agent to produce plans with similar trade-offs. METHODS: An agent was trained to adjust the two priority weights (i.e., digital slider bars) in the clinical inverse planner. The agent consists of a neural network that receives the metrics and dose distribution of the current plan and the target and organ-at-risk masks as inputs. These methods were demonstrated on a dataset of 204 single-target metastases and a dataset of 71 acoustic neuroma cases. The cases were split into training, validation, and testing sets of size 123/41/40 and 42/14/15 for the metastases and acoustic neuromas, respectively. RESULTS: On the metastases test dataset, the agent achieved a significantly higher (p = 0.0136) average plan score (3.925 ± 0.130) compared to the default slider plans (3.874 ± 0.147). On the acoustic neuromas test dataset, the agent achieved a higher (p = 0.4493) average plan score (4.035 ± 0.177) compared to the default slider plans (3.995 ± 0.365). The higher plan scores are reflected in the four plan quality metrics: the agent's plans, on average, had metrics more similar to the clinical plans, compared to the default slider plans, for both test datasets. CONCLUSIONS: The proposed reward function enabled the agent to learn to find plans that aligned with historical planning decisions. Future work will investigate providing the agent with additional inputs that can explain the variability in planning decisions, which would further improve its performance.
Development and characterization of a novel, small animal external beam irradiator using a clinical high dose rate brachytherapy source.
Cecchi D, Freeman S, Warren G … +4 more , Gill B, Johnstone C, Chithrani DB, Lloyd SAM
Med Phys · 2026 Jul · PMID 42376807 · Full text
BACKGROUND: Pre-clinical in vivo characterization is a necessary step in the translation of novel radiotherapeutic interventions to clinical application. In vivo irradiations using a radioactive source like Ir-192 are ch...
BACKGROUND: Pre-clinical in vivo characterization is a necessary step in the translation of novel radiotherapeutic interventions to clinical application. In vivo irradiations using a radioactive source like Ir-192 are challenging due to steep dose gradients and absence of universally available applicators that do not require physical contact or interstitial insertion. PURPOSE: To develop a novel external beam radiotherapy (EBRT) jig for accurate and reproducible radiotherapy treatments delivered using an Ir-192 source for in vivo studies. METHODS: An irradiation jig was constructed as a flat treatment bed and upright 6 cm diameter semi-circle with eight peripheral catheter positions encompassing the lateral side of a mouse. A CT scan was acquired of the jig along with a silicone phantom of a mouse with flank tumor. The scan was imported into Oncentra® for planning using 500 cGy prescribed to the tumor and calculated using TG43 and collapsed cone. EBT4 film and OSLD measurements verified dose distributions in the axial and coronal directions along with the entrance and exit dose to the tumor. Monte Carlo simulations using TOPAS™ were used to observe the 3D dose distribution within the tumor itself. Five female immunodeficient mice inoculated with HEC-1A cervical cancer tumors were irradiated and monitored for 3 weeks for tumor growth, body weight, and signs of toxicity. RESULTS: Dosimetry measurements agreed within 2%-15% of the tumor's entrance and exit dose as reported by Oncentra® using both computational formalisms. Monte Carlo simulations confirmed a uniform dose distribution within the tumor of ± 10%. Compared to unirradiated mice, a significant reduction in tumor growth post-irradiation was observed in all irradiated mice with no observable signs of toxicity. CONCLUSION: We have successfully developed an EBRT platform for in vivo irradiations with an Ir-192 source. The platform can be adapted for various tumor and sample sizes and other radioactive sources.
Deep learning-based dose prediction for MR-guided prostate SIB: Supporting rapid feasibility assessment and adaptive editing margin selection.
Cheng HW, Tseng WC, Yan G … +2 more , Li J, Liu C
Med Phys · 2026 Jul · PMID 42376806 · Publisher ↗
BACKGROUND: The template-based treatment planning workflow in the Unity magnetic resonance-guided linear accelerator (MR-Linac) helps facilitate the treatment planning process; however, dose optimization and calculation...
BACKGROUND: The template-based treatment planning workflow in the Unity magnetic resonance-guided linear accelerator (MR-Linac) helps facilitate the treatment planning process; however, dose optimization and calculation remain time-consuming in complex cases. In addition, the deformable image registration (DIR) algorithm used during adaptive planning may produce inaccurate results, thereby making efficient contour editing essential for online adaptation, especially in cases involving multiple organs at risk adjacent to the target. PURPOSE: This study aims to resolve key clinical challenges in treatment planning and online adaptive planning for prostate simultaneous integrated boost (SIB) treatment on the MR-Linac using deep learning (DL)-based dose prediction. Multiple DL-based dose prediction models are developed and evaluated for rapid dosimetric feasibility assessment, and the top-performing model is used to guide the development of a novel contouring strategy to streamline the adaptive planning workflow. METHODS: Six DL models were developed and evaluated for 3D dose prediction using 80 reference and adaptive plans from 20 patients previously treated with SIB intensity-modulated radiation therapy (SIB-IMRT) on the Unity MR-Linac. To address DIR-introduced contour inaccuracies during adaptation, a contour editing strategy based on a minimal manual editing margin (MMEM) around the target structures was introduced. The MMEM was determined using six margin sizes (5-30 mm, in 5-mm increments) evaluated by the top-performing DL model. Twenty adaptive plans with DIR inaccuracies in bladder, rectum, and bowel bag from 12 patients were analyzed for MMEM determination, and 10 adaptive plans were further evaluated for feasibility in the Monaco treatment planning system. RESULTS: The dosimetric differences between model predictions and the treatment planning system-calculated ground truth were small for most models (≤1.5 Gy or 2%), and the average Dice Similarity Coefficients across the 10-100% isodose volumes exceeded 0.9, demonstrating strong spatial agreement. Among the evaluated models, the attention-gated (AG) U-Net achieved the best overall performance and was used for the MMEM determination. Based on the MMEM and feasibility analyses, a 10-mm editing margin is recommended for the rectum, with the use of the semi-automatic segmentation tool for the bladder and no manual edits for the bowel bag. CONCLUSION: The AG U-Net enabled accurate dose prediction for rapid dosimetric feasibility assessment in prostate SIB treatment on the Unity MR-Linac. Leveraging this model, an MMEM-based contouring strategy was developed to guide contour modification and improve the efficiency of online adaptive planning.
Surface-guided analysis of breast shape changes during postoperative radiotherapy by using a functional map framework.
Galmiche P, Seo H, Pin Y … +3 more , Meyer P, Noël G, De Mathelin M
Med Phys · 2026 Jul · PMID 42376805 · Full text
BACKGROUND: While positioning errors during radiotherapy are increasingly well-characterized and accounted for in the Planning Target Volume (PTV), little is known about the shape and volume changes of the breast in the...
BACKGROUND: While positioning errors during radiotherapy are increasingly well-characterized and accounted for in the Planning Target Volume (PTV), little is known about the shape and volume changes of the breast in the course of radiotherapy. Yet they represent an unknown factor that may impact treatment effectiveness, highlighting the need to analyze inter-fractional breast deformations to enable promising approaches such as patient-specific adaptive irradiation planning. PURPOSE: In this study, we develop a geometric approach to analyze inter-fractional breast deformation throughout the radiotherapy treatment, based on a dataset of 3D surface scans of patients' frontal torso acquired during radiotherapy sessions. METHODS: We used a handheld 3D range scanner to collect surface scans of 22 patients prior to, during, and after radiotherapy sessions following breast-conserving surgery (lumpectomy). We begin by adapting functional map framework to compute inter- and intra-patient nonrigid correspondences. To study shape changes during radiotherapy, we then perform both intrinsic and extrinsic analyses of the collected breast surface shapes, by leveraging the intra- and inter-patient correspondences. These analysis provide complementary insights into how the breast changes over time: The intrinsic analysis evaluates deformation patterns directly on the shape manifolds, enabling the identification of regions exhibiting high conformal (bending) or area distortions (stretching). We also perform extrinsic analysis, where we align surface acquisitions of the treated breast with the CT-derived skin surface to assess pointwise surface displacements and volume changes in the treated area, thereby producing quantitative measures such as displacement amplitudes (in mm) and relative volume changes (in percentage). RESULTS: The qualitative shape collection analysis highlight deformations in the contra-lateral breast and armpit areas, along with positioning shifts on the head or abdominal regions. On average, displacements within the treated breast exhibit amplitudes of 1-2 mm across sessions, with higher values observed at the time of the 25th irradiation session. Volume changes, inferred from surface variations, reached up to 10% over the course of treatment, with the majority of values ranging between 2% and 5%. CONCLUSIONS: A -based geometric approach has been proposed for analyzing breast shape changes over the course of radiotherapy from surface data acquisitions. Based on a functional map framework, we develop a shape matching specialized for the breast data as well as a shape variability analysis within a unified space. Analysis across multiple patient datasets revealed a wide spectrum of breast changes despite a clinically acceptable quantitative average, demonstrating the power of our method to perform both quantitative and qualitative analysis of deformation patterns both on the individual and group level. TRIAL REGISTRATION: The clinical trial data used in this paper is registered under the ClinicalTrials.gov ID NCT03801850.
Monte Carlo assessment of a treatment planning system for intraoperative radiotherapy in the presence of tissue heterogeneities.
Corso A, Jimenez-Albericio FJ, Avanzo M … +5 more , Ortega-Pardina P, Cirio R, Vera-Tena D, Gonzalez-Gonzalez E, Garcia-Romero A
Med Phys · 2026 Jul · PMID 42365440 · Full text
BACKGROUND: Radiance is a Monte Carlo-based treatment planning software integrated into the Intrabeam system for 50-kVp X-rays intraoperative radiotherapy (IORT). PURPOSE: This study evaluates Radiance accuracy in calcul...
BACKGROUND: Radiance is a Monte Carlo-based treatment planning software integrated into the Intrabeam system for 50-kVp X-rays intraoperative radiotherapy (IORT). PURPOSE: This study evaluates Radiance accuracy in calculating absorbed dose in IORT of the breast including the effect of tissue heterogeneities. METHODS: Dose distributions from IORT were calculated in 88 virtual phantoms of different tissue-equivalent materials. Dose was calculated independently using the penEasy code for the PENELOPE Monte Carlo engine and compared to Radiance. Depth dose curves (DDCs) were compared through gamma analysis using 5%/0.5 mm and 3%/0.5 mm criteria. RESULTS: When comparing Radiance vs penEasy all passing rates were above 95%. Notable differences from dose to water emerged for some tissues: cortical bone absorbed about four times more than water, while adipose tissue received about 45% less. These variations were affected by atomic number more than density. CONCLUSION: Radiance results show strong agreement with penEasy simulations. Furthermore, it was observed that IORT absorbed doses can fluctuate by ± 50% due to heterogeneities surrounding the applicator. This highlights that the prescribed dose and the absorbed dose in the applicator surface do not necessarily coincide in non-water tissues, emphasizing the critical need to account for specific tissue characteristics during treatment planning.
Medical image local augmentation via text- and mask-guided diffusion model.
Cao P, Li D, Li X … +2 more , Yan Y, Li Y
Med Phys · 2026 Jul · PMID 42347908 · Publisher ↗
BACKGROUND: Medical images serve as the core basis for precision diagnosis and treatment, yet their scarcity severely hampers the advancement of intelligent medical image analysis. Data augmentation for medical images re...
BACKGROUND: Medical images serve as the core basis for precision diagnosis and treatment, yet their scarcity severely hampers the advancement of intelligent medical image analysis. Data augmentation for medical images represents a key pathway to overcoming this data bottleneck. However, existing methods primarily focus on global image transformations and exhibiting limited control over local regional details. PURPOSE: In order to enhance image diversity, this paper proposes a text- and mask-guided local augmentation method for medical images. METHODS: Aiming at the problem of insufficient diversity of medical synthesized images, this paper designs a text- and mask-guided local augmentation method for medical images (MILA-TMGDiff). This method first employs a pre-trained MedSAM model to segment target regions within input medical images, yielding precise masks. Subsequently, text prompts with semantic relevance and task-specificity are designed for different types of medical imaging data. Finally, the mask and text prompts are jointly input as local guidance conditions into a diffusion generative model. By applying controlled perturbations to the local noise distribution, fine-grained generation control over specific anatomical regions is achieved, ultimately producing synthetic medical images of high quality in both visual realism and diversity. RESULTS: The method in this paper has been tested on x-ray, MRI, and CT images for local augmentation experiments, and the quantitative analysis results show that the local structural similarity of the images generated by this paper in the Mask region exhibits a significant change: a reduction of 97.9%, 103.3%, and 42.2% on chest x-ray, pelvic CT, and brain CT data, respectively. This phenomenon confirms that the local feature enhancement mechanism proposed in this paper can effectively modulate the distribution of structural features in the Mask region while maintaining the global texture consistency. CONCLUSIONS: This provides a new technical pathway for controlled data augmentation in medical imaging, helping to advance the development of intelligent medical image analysis and laying the foundation for future research on fine-grained medical image generation.
Physics-informed patient-specific calibration for monocular visual-based dose reconstruction in breast cancer radiotherapy.
Deng Y, Wang X, Chen R
Med Phys · 2026 Jul · PMID 42347841 · Publisher ↗
BACKGROUND: Interfractional anatomical variations during breast cancer radiotherapy can significantly deviate the delivered dose from the treatment plan. Standard image guidance via Cone-Beam CT (CBCT) is typically spars...
BACKGROUND: Interfractional anatomical variations during breast cancer radiotherapy can significantly deviate the delivered dose from the treatment plan. Standard image guidance via Cone-Beam CT (CBCT) is typically sparse due to radiation and workflow constraints, leaving daily geometric changes unmonitored. PURPOSE: To bridge this gap, we propose a physics-informed framework that utilizes monocular surface vision for continuous, non-ionizing 3D dose reconstruction. METHODS: The system utilizes the weekly CBCT scans from the first 2 weeks of treatment (Week 1 and Week 2) for patient-specific calibration. Surface features are extracted via a hybrid HOG-CNN descriptor, while 3D deformation vector fields (DVFs) are compressed into a low-dimensional latent space via Principal Component Analysis (PCA). A linear mapping from surface topography to PCA coefficients is optimized using physics-informed Tikhonov regularization, incorporating an eigenvalue-based penalty matrix to suppress high-order non-physical modes. Post-calibration, the model reconstructs 3D dose distributions for subsequent fractions in real time using only monocular input. RESULTS: Validated on 29 patients (87 fractions), the framework achieved a deformation coefficient correlation of R = 0.796. Reconstructed doses yielded a mean Gamma passing rate (3%/3 mm) of 93.8% ± 3.1% and a dose correlation of 0.940 ± 0.037. Ablation studies demonstrated that removing physics constraints or PCA reduction significantly degraded performance (ΔGPR = -8.5% and -22.1%, respectively; p < 0.001). End-to-end latency was 42 ± 5 ms per fraction, representing a ∼124-fold acceleration over commercial deformable registration solutions. CONCLUSIONS: This framework transforms routine weekly CBCTs into robust "calibration anchors" for continuous visual dose monitoring. It provides clinical-grade accuracy with negligible computational overhead and no additional ionizing dose, offering a practical solution for real-time adaptive radiotherapy.
Experimental and simulated in pure water under conventional and ultra-high dose rates for single pulse proton irradiation.
Kwon D, Fiegel V, Blain G … +11 more , Chiavassa S, Anh LT, Tran HN, Terfas S, Evin M, Craff E, Incerti S, Delpon G, Haddad F, Koumeir C, Maigne L
Med Phys · 2026 Jul · PMID 42347839 · Publisher ↗
BACKGROUND: Despite the remarkable sparing of normal tissue by FLASH radiotherapy, the fundamental mechanisms that link physics to biological outcomes remain unclear. Among water radiolysis species produced after irradia...
BACKGROUND: Despite the remarkable sparing of normal tissue by FLASH radiotherapy, the fundamental mechanisms that link physics to biological outcomes remain unclear. Among water radiolysis species produced after irradiation, hydrogen peroxide ( ) is a final product resulting from hydroxyl radical ( and reactive oxygen species / ) reactions, sources of biological damage. Many experiments have shown that increasing the dose rate, reduces yields, supporting hypotheses related to a transient hypoxia during irradiation. Reproducing experimental data using Monte Carlo simulations can be challenging due to incomplete or ambiguous information about the actual experimental conditions, such as the thorough measurement of oxygen or pH levels. PURPOSE: Through water radiolysis experiments and simulations, we propose to understand the fundamental mechanisms responsible for the production of under varying oxygen and dose rate conditions. A new Geant4-DNA chemistry module, managing pulse duration, is specifically tested. METHODS: The purified water samples were irradiated with a 67.5 MeV proton beam delivered by the ARRONAX isochronous cyclotron (IBA Cyclone 70XP) at dose rates ranging from a conventional dose rate (CDR, 0.2 Gy/s) to ultra-high dose rates (UHDR, ∼6 kGy/s). The concentration of , used as a final endpoint providing insight into earlier processes, was quantified using the Ghormley triiodide protocol. We reproduced irradiation conditions using the GATE and Geant4-DNA Monte Carlo libraries. Beam alignment and dose homogeneity were verified using a gamma-index method. A Geant4-DNA chemistry module (Geant4 11.4-beta version) was used to calculate the time-dependent evolution of radiolytic yields for , , , species until 15 min post irradiation, taking into account the oxygen concentration, pH, absorbed dose, and pulse duration. RESULTS: Under aerated conditions, for CDR, the simulated (2.18) and experimental (2.13) G( ) are in close agreement. At higher dose rates, the decrease of G( ) is very similar between experiments and simulations. Under deaerated conditions, simulated G( ) decreased from 1.56 at 0.26 Gy/s to 1.22 at 42 Gy/s, with relative differences of 1.3% and 0.8 % compared to the experiment. The impact of content is evaluated through simulation studies and discussed. CONCLUSIONS: The Geant4-DNA chemistry module reproduces with a good agreement experimental yields measured under different oxygen levels and dose rates. Both experiments and simulations show an oxygen dependent decrease in G( ) under UHDR conditions. Simulations indicate an impact of the content at physiological level. As perspectives, we aim at studying the role of hydrated electron associated to the understanding of and effects through time resolved radicals' measurement.
Should reference beam data be used for beam modeling during linear accelerator commissioning?
Gayou O, Zhu TC, Das IJ
Med Phys · 2026 Jul · PMID 42347802 · Publisher ↗
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Study of prompt gamma and neutron emission for real-time range verification in proton and carbon-ion therapy.
Bellotti ES, Mazzucconi D, Bortot D … +4 more , Pola A, Fiorini C, Urban K, Agosteo S
Med Phys · 2026 Jul · PMID 42347753 · Full text
BACKGROUND: Accurate range verification is crucial in hadrontherapy to fully exploit the ballistic advantages of charged particles and prevent damage to healthy tissues. Among the proposed approaches, prompt gamma imagin...
BACKGROUND: Accurate range verification is crucial in hadrontherapy to fully exploit the ballistic advantages of charged particles and prevent damage to healthy tissues. Among the proposed approaches, prompt gamma imaging (PGI) has emerged as an effective technique for real-time monitoring, but its performance is limited by the intense neutron background generated during irradiation, especially with carbon-ions. PURPOSE: This work presents a Monte Carlo study performed with the FLUKA code to investigate prompt gamma and neutron emission in proton and carbon-ion therapy. A prototype detection system based on a knife-edge collimator coupled to a pixelated LYSO scintillator was simulated to evaluate its capability for range verification. The aim is to quantify how neutron fields and neutron induced signals bias or degrade range related quantities, and how these effects differ between proton and carbon-ion beams. METHODS: The analysis includes the characterization of prompt gamma energy spectra and spatial profiles, the assessment of neutron fields within a treatment room, and the decomposition of the detector signal into primary gammas, secondary gammas, and neutrons. RESULTS: Results show that prompt gamma profiles correlate well with the Bragg peak position, particularly within the 3-7 MeV energy window, while carbon ions exhibit higher prompt gamma yields but also significantly stronger neutron backgrounds compared to protons. Detector simulations highlight the impact of neutron capture on lutetium, producing distinct peaks that must be accounted for in the detector signal analysis. The fall-off retrieval precision (FRP) analysis indicates that the distal fall-off of prompt gamma profiles can be used to estimate the Bragg peak position, while secondary radiation components introduce additional fluctuations that affect the achievable precision, particularly for carbon-ion beams. CONCLUSIONS: The study provides a detailed characterization of prompt gamma and neutron contributions in proton and carbon-ion therapy and highlights the main physical factors affecting PGI-based range monitoring, particularly in the presence of neutron-induced backgrounds. These results provide useful insights for the design and optimization of prompt gamma detection systems in clinical applications.
Cerebral arteries segmentation based on projection domain in single exposure computed tomographic angiography.
Seo KH, Kim H, Shim J … +3 more , Battaglia C, Kim K, Lee Y
Med Phys · 2026 Jul · PMID 42347746 · Publisher ↗
BACKGROUND: Cerebrovascular diseases are major causes of death and disability worldwide, highlighting the critical importance of early diagnosis and accurate acquisition of vascular information. However, conventional ima...
BACKGROUND: Cerebrovascular diseases are major causes of death and disability worldwide, highlighting the critical importance of early diagnosis and accurate acquisition of vascular information. However, conventional imaging techniques using direct subtraction computed tomography (CT) and dual energy CT have limitations, including invasiveness, radiation exposure, and artifacts caused by metal and bone. PURPOSE: This study investigated the feasibility of cerebral artery segmentation in single-exposure CT angiography (CTA) using a projection-domain framework derived from patient-based CTA data. METHODS: The proposed method employs the DeepLab V3+ model to segment brain vessels directly in the projection. A total of 103 patients were included in the dataset, and 61, 17, and 25 patients were allocated to the training, validation, and test sets, respectively. This approach eliminates the risk of double exposure and motion artifacts while preserving clinical information. Additionally, this approach minimizes beam-hardening artifacts from high-density materials and reduces the operator's workload. RESULTS: The cerebral artery images reconstructed using the proposed method were quantitatively compared to those of the labeled images, and the intersection over union, Dice similarity coefficient, bidirectional Hausdorff distance, bfscore, F1-score, and precision were measured to be approximately 0.89 [95% CI, 0.87-0.91], 0.90 [0.88-0.91], 219.12 pixels [201.54-236.70], 0.90 [0.89-0.92], 0.90 [0.89-0.92], and 0.89 [0.88-0.91], respectively. Performance metrics consistently demonstrated high agreement between reconstructed vessel maps and reference labels. In addition, the proposed method confirmed that reconstructing cerebral arteries and metallic implant components may yield clinically relevant vascular image information with limited information loss. CONCLUSIONS: These results support the feasibility of the proposed method for generating cerebral arterial 3D images in CTA systems and suggest potential utility for improved vascular visualization and image quality, pending further clinical validation.
Experimentally determined proton discrete spot scanning time structures for an improved synchrotron-based PBS spot delivery time model.
Lee JKH, Chua CGA, Lew KS … +11 more , Koh CWY, Yagi M, Lee KH, Gan JK, Fu K, Master Z, Lee JCL, Bettiol AA, Furutani KM, Park SY, Tan HQ
Med Phys · 2026 Jul · PMID 42347740 · Publisher ↗
BACKGROUND: An accurate discrete spot scanning (DSS) beam delivery time (BDT) model is essential, particularly as 4D dynamic dose accumulation calculations rely on machine-specific time models for reliable interplay eval...
BACKGROUND: An accurate discrete spot scanning (DSS) beam delivery time (BDT) model is essential, particularly as 4D dynamic dose accumulation calculations rely on machine-specific time models for reliable interplay evaluation. PURPOSE: To derive a BDT model for a synchrotron-based Hitachi Probeat PBS proton system from oscilloscope measurements of key BDT structures, including multi-energy extraction (MEE) characteristics. METHODS: Key BDT structures were characterized using oscilloscope measurements, supplemented by delivery log files where appropriate. Spot-to-spot scanning trajectories were visualized using a CROSSmini 2D strip ionization chamber (Liverage Biomedical Inc, Taiwan) via the dose-driven continuous scanning (DDCS) mode. The MEE design and MEE charge recapture efficiencies were also characterized. In addition, the impact of the number of delivered spots on both the extractable fraction of charge and MEE recapture efficiency was investigated. RESULTS: An improved synchrotron-based BDT model was derived that incorporates dead times between radiofrequency knockout (RFK) and high-speed steering magnet (HSST) signals. Spot-to-spot movement follows a "hockey-stick"-like behavior where the effective spot-to-spot move time is governed by the slower axis. An energy-dependent variation in the number of MEE layers deliverable per spill was also observed, with fewer MEE layers per spill (1-3) was observed in low and high energy ranges compared to the mid-energy range (4-5), deviating from the nominal vendor value of five MEE layers per spill per block. A reduction in the extractable fraction of charge was observed with an increasing number of spots per spill, while increasing the number of delivered spots in the preceding layer significantly reduced the MEE recapture efficiency. CONCLUSION: MEE characteristics should be incorporated into synchrotron-based time models for accurate beam delivery modeling. The methodology presented here also provides a framework for centers seeking to derive machine-specific delivery time models for their proton systems.
Diffusion-based novel view synthesis for X-ray imaging.
Wang M, Cai H, Li Y … +4 more , Kabika T, Dai L, Yan M, Hou W
Med Phys · 2026 Jul · PMID 42347736 · Publisher ↗
BACKGROUND: X-ray imaging is extensively used in clinical practice due to its low cost, accessibility, and relatively low radiation dose. However, its intrinsic two-dimensional (2D) projection mechanism inevitably leads...
BACKGROUND: X-ray imaging is extensively used in clinical practice due to its low cost, accessibility, and relatively low radiation dose. However, its intrinsic two-dimensional (2D) projection mechanism inevitably leads to severe structural overlap and lesion occlusion in single-view acquisitions, substantially limiting the completeness and reliability of anatomical interpretation. PURPOSE: To overcome the loss of spatial information caused by limited viewing angles, this study proposes a diffusion-based novel view synthesis framework for X-ray imaging that directly generates target-view X-ray images from a small number of reference views, without relying on explicit three-dimensional reconstruction. METHODS: Built upon the Stable Diffusion framework, the proposed method introduces a lightweight and physically interpretable angular-difference conditioning mechanism to explicitly model cross-view geometric relationships. By embedding the relative angular offset between reference and target views into the attention-based feature interaction process, the model effectively captures view-dependent structural transformations and synthesizes anatomically consistent novel-view X-ray images. RESULTS: Extensive experiments on a synthesized multi-view X-ray dataset demonstrate that the proposed approach achieves robust and stable performance under sparse-view input conditions, significantly outperforming existing methods in terms of view generalization and structural preservation. In particular, for target view offsets of , , and , the proposed method achieves PSNR values of dB, dB, and dB, respectively, together with consistently improved SSIM and LPIPS scores. CONCLUSIONS: These results indicate that the proposed framework provides an efficient and flexible solution for supplementing missing X-ray views in clinically constrained imaging scenarios.
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