Medical physics最新文献

{"title":"Interpretable graph-conditioned CNNs for dose-volume histogram prediction in radiotherapy","authors":"Xiaoling Zhu,&nbsp;Chifang Ling,&nbsp;Hao Xu,&nbsp;Kuo Men,&nbsp;Jianrong Dai,&nbsp;Weigang Hu,&nbsp;Zhiqiang Liu,&nbsp;Jiawei Fan","doi":"10.1002/mp.70663","DOIUrl":"10.1002/mp.70663","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Accurate dose-volume histogram (DVH) prediction is essential for high-quality and automated radiotherapy (RT) planning. However, existing deep learning methods primarily focus on voxel-level dose prediction followed by post-processing to extract DVHs, a workflow that can introduce cumulative errors and limit clinical interpretability.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>In this study, we propose a novel deep learning framework that directly predicts full DVHs for multiple organs-at-risk (OARs) from computed tomography (CT) and structure contours.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Our method combines a three-dimensional convolutional neural network (CNN) for anatomical feature extraction with a graph neural network (GNN) that models each DVH as a structured graph, enabling sequential dose-volume dependencies to be learned explicitly. The model was extensively validated on nasopharyngeal cancer cases from an external institute and rectal cancer cases from our affiliated hospital, encompassing treatments with TomoTherapy and volumetric modulated arc therapy (VMAT). We additionally conducted a model-guided clinical DVH assessment on suboptimal cases to demonstrate the method's clinical utility</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The proposed method achieved low dose-wise prediction errors and outperformed previous approach. Specifically, it reduced the mean dose error for the brain stem from 1.24 Gy to 0.66 Gy and for the larynx from 1.53 Gy to 0.78 Gy, with notable improvements also observed in the parotid glands and temporal lobes. Statistical analysis of clinical indices demonstrated non-inferiority to ground-truth plans (<i>p</i> &gt; 0.05). Moreover, the predicted DVHs effectively guided plan revision and improved plan quality.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Our results suggest that direct DVH prediction using a CNN-GNN framework offers a robust and clinically interpretable solution for treatment planning and quality assurance.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A neighborhood attention transformer network for enhanced 3D segmentation of the left anterior descending artery","authors":"Rafi Ibn Sultan,&nbsp;Chengyin Li,&nbsp;Yiannos Demetriou,&nbsp;Ahmed I. Ghanem,&nbsp;Joshua P. Kim,&nbsp;Justine Cunningham,&nbsp;Hassan Bagher-Ebadian,&nbsp;Dongxiao Zhu,&nbsp;Kundan S. Thind","doi":"10.1002/mp.70653","DOIUrl":"10.1002/mp.70653","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Accurate segmentation of the left anterior descending (LAD) artery in 3D free-breathing, non-contrast CT is critical for cardiac dose sparing in thoracic radiotherapy. The task is inherently difficult because the LAD is extremely small, exhibits poor soft-tissue contrast, and varies substantially across patients. Even manual contours show limited inter-observer agreement on non-contrast CT, underscoring the ambiguity of the vessel boundaries.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To develop a transformer-based segmentation framework that enhances LAD delineation in low-contrast, imbalanced CT using local-global context modeling and uncertainty-guided optimization.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We propose &lt;b&gt;NA-UNETR&lt;/b&gt;, a 3D transformer-based segmentation model with neighborhood attention (NA) and Dilated NA (DiNA) blocks that jointly capture fine structural detail and long-range context. To address the limited availability of annotated LAD artery data, the model is pretrained on 1000 CTA volumes representing general coronary anatomy and then fine-tuned using a parameter-efficient adaptation strategy on 20 free-breathing institutional CT scans of the LAD artery. A composite Dice–Focal and Hausdorff loss, dynamically balanced via homoscedastic uncertainty, improves overlap and boundary accuracy. Preprocessing included intensity clipping, contrast enhancement, and artery-centric sampling, and postprocessing refined morphology.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;NA-UNETR achieved comparable performance to SOTA with improved efficiency and boundary properties. It reached 45.64% Dice, 38.16 mm HD95, and 10.01 mm ASD, improving Dice by 3.10 percentage points over nnU-Net and reducing HD95 by 2.96 mm relative to Swin UNETR, while showing the strongest boundary accuracy among all models and demonstrating improved geometric and centerline stability. On ImageCAS, it achieved 79.49% Dice, 8.89 mm HD95, and 1.02 mm ASD. Ablations confirmed that residual blocks, variable kernels, and uncertainty-weighted loss each contributed to performance stability and boundary precision.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;NA-UNETR effectively balances local precision and global context, enabling accurate segmentation of thin, low-contrast LAD structures. Its integration of NA, uncertainty-weighted loss, and LoRA-based fine-tuning demonstrates a robust and computationally efficient framework for substructure-level cardiac segmentation in radiotherapy planning.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of motion quantification in dynamic CT images of the wrist joint across multiple CT vendors: A phantom study","authors":"Hanne Vries,&nbsp;Brigitte van der Heijden,&nbsp;Stefan Hummelink,&nbsp;Iwan Dobbe,&nbsp;Ioannis Sechopoulos,&nbsp;Geert Streekstra","doi":"10.1002/mp.70667","DOIUrl":"10.1002/mp.70667","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Four-dimensional computed tomography (4D CT) allows dynamic assessment of wrist kinematics and offers a non-invasive alternative for evaluating ligament instability. However, insufficient temporal resolution and differences in acquisition or reconstruction protocols may introduce motion-related artifacts that affect quantitative analysis. As these artifacts can mimic pathological carpal motion, measurement error must be quantified to distinguish true pathology from methodological error. Therefore, systematic evaluation of motion quantification across different CT systems and acquisition protocols is required.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To evaluate the errors in motion quantification across acquisition and reconstruction protocols of different CT systems in 4D CT imaging of wrist bones.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A rotating wrist phantom with three 3D-printed bones (scaphoid, lunate, capitate) was scanned on five CT systems from three manufacturers (Aquilion ONE PRISM and ONE Vision, Canon Medical; Revolution Apex, GE HealthCare; single-source and dual-source SOMATOM Force, Siemens Healthcare). One static 3D scan and multiple 4D scans were acquired at different phantom rotation speeds, each lasting 10 s. Single-source covered 0.050–0.300 phantom rotations per second (rps), and dual-source 0.100–0.600 rps. Dose dependence was evaluated on two systems (80 kV/40 mA and 120 kV/100 mA). Images were reconstructed in full and partial modes, segmented, and registered using point-to-image registration. Motion quantification error was calculated for translation and rotation of the scaphoid and capitate relative to the lunate, referenced to the static scan, and reported per rotation cycle. Motion quantification error was additionally expressed as a function of normalized motion per reconstructed frame to relate the error to the amount of motion occurring during image acquisition. Effects of CT system, bone type, reconstruction method, and rotation speed were analyzed using a linear mixed model. Statistical significance was defined as &lt;i&gt;p&lt;/i&gt; &lt; 0.05.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The motion quantification error was hardly affected by dose. For 0.100 rps, the errors of the best single-source system were median 0.29 mm (interquartile range: 0.21–0.36 mm) and 1.37° (0.82°–2.18°) for full and 0.21 mm (0.16–0.25 mm) and 0.70° (0.52°–0.95°) for partial reconstructions for the capitate; the dual-source system showed the lowest errors (0.14 mm (0.12–0.17 mm) and 0.48° (0.39°–0.62°)). M","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13542767/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anatomy-aware fusion attention network for high-precision prostate MRI segmentation","authors":"Yulong Wang,&nbsp;Hui Huang,&nbsp;Yan Ma,&nbsp;Hongqing Zhu,&nbsp;Chunlin Wen,&nbsp;Feiniu Yuan,&nbsp;Bingcang Huang","doi":"10.1002/mp.70669","DOIUrl":"10.1002/mp.70669","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Accurate prostate segmentation in Magnetic Resonance Imaging (MRI) is crucial for clinical diagnosis and treatment. However, it remains a challenging task due to low soft-tissue contrast and structural ambiguity in the gland's appearance. While recent deep learning methods have focused on refining network structures, they often neglect the inherent anatomical consistency of the prostate.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To address this limitation, a novel segmentation framework integrating an Anatomy-Aware Fusion Attention (AAFA) module is proposed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>By leveraging anatomical templates, our approach establishes a multilevel feature cross-attention mechanism that enhances global contextual modeling of prostate regions. Additionally, we introduce a Phased Learning strategy that progressively trains the model to mitigate the adverse effects of invalid or noisy samples commonly found in clinical MRI data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Extensive ablation studies on the PROMISE12 dataset validate the contribution of each component to overall performance. Comparison experiments on both PROMISE12 and MSD Prostate datasets show that our method consistently outperforms existing approaches across key metrics, such as Dice similarity coefficient (DSC), Intersection over Union (IoU), Precision and 95% Hausdorff distance (HD95).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These results confirm the robustness and strong generalization capability of the proposed framework in challenging clinical segmentation tasks.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Megavoltage photon minibeam production through the embedded multi-leaf collimator of a clinical linac: A dosimetric characterization","authors":"Stefania Linsalata,&nbsp;Jake Harold Pensavalle,&nbsp;Fabiola Paiar,&nbsp;Francesco Romano,&nbsp;Antonio Claudio Traino,&nbsp;Fabio Di Martino","doi":"10.1002/mp.70597","DOIUrl":"10.1002/mp.70597","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Although spatially-fractionated radiation therapy (SFRT) has been receiving increasing clinical interest, its complete and optimized clinical transfer requires several technological and radiobiological issues to be addressed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The aim of this work is to setup and dosimetrically characterize an experimental platform generating planar megavoltage photon minibeams to exploit quantitative radiobiological SFRT experiments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Minibeam patterns were generated on a Varian TrueBeam™ linear accelerator equipped with a high definition (HD) MLC, which consists of 60 tungsten leaf pairs, whom the 32 inner ones project a thickness of 2.5 mm at the isocenter plane (i.e., 100 cm distance from the radiation source) and the 28 outers of 5 mm. Each pattern was obtained alternating opening one leaf after closing one, two, or three of the smallest MLC leaves. Measurements were performed with a PTW microdiamond detector in edge-on orientation in a water phantom over depths from 1 to 30 cm, varying the beam energy and the source to surface distance (SSD) in different sessions. A Python-based in-house automated fitting procedure was used to obtain from the measured profiles all the minibeam parameters: peak widths (PWs), distance between consecutive peaks (CTCs), peak to valley dose ratios (PVDRs) and depth doses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The best performances were obtained at SSD = 70 cm and 6 MV, where PWs and PVDRs respectively range from 1.2 to 2.4 mm and from 2 to 7. For all patterns the average dose varies in depth analogously to the reference field, PVDRs show an almost steady decrease except at shallower depths, while PWs and CTCs widen linearly with the depths. Moreover, their variation over different sessions was within the estimated uncertainty of the single measurement.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We are claiming that a Varian TrueBeam™ equipped with an HD-MLC represents a practical, stable, reproducible and accessible platform that might be suitable for radiobiological studies on SFRT and for the investigation of the relative underlying mechanisms.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13542783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148889863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation study of wedge-shaped light guide for compensating depth-of-interaction induced timing uncertainty in Cherenkov radiator","authors":"Hyungu Kang,&nbsp;Hyeong Seok Shim,&nbsp;Minseok Yi,&nbsp;Juhwan Kim,&nbsp;Yoonchan Jeong,&nbsp;Jae Sung Lee","doi":"10.1002/mp.70655","DOIUrl":"10.1002/mp.70655","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Coincidence timing resolution (CTR) is a key performance factor in PET systems. Cherenkov radiation, due to its ultrafast emission on the femtosecond scale, offers potential for achieving improved timing resolution compared to traditional scintillation-based detectors. However, the inherently low photon yield in pure Cherenkov radiators makes depth-of-interaction (DOI) estimation and its associated timing uncertainty a significant challenge, especially when trying to achieve sub-30 ps CTR.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to reduce DOI-induced timing uncertainty in Cherenkov-based PET detectors by proposing a novel wedge-shaped light guide design. The goal is to improve the CTR performance by compensating for optical path differences resulting from varying interaction depths.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A Monte Carlo simulation framework was developed to model gamma-ray interactions within a Cherenkov radiator, incorporating electron scattering and Cherenkov photon generation. Two detector geometries were compared: one with a conventional planar light guide and another with the proposed wedge-shaped light guide. The wedge design was tailored to delay early-arriving photons and synchronize photon transit times, thereby reducing time spread. The simulation tracked photon paths through the wedge and evaluated performance using metrics such as spatial resolution, timing spread, and sensitivity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Simulations demonstrated that the wedge-shaped light guide significantly reduced DOI-induced timing uncertainty—by 26.3% in a 3 mm-thick Cherenkov radiator—compared to the conventional configuration. The wedge geometry also enabled improved spatial resolution in multi-layer detector configurations. However, a trade-off with reduced sensitivity was observed. To address this, strategies such as utilizing discarded photons via refractive index manipulation and cascade detector structures were proposed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The wedge-shaped light guide effectively compensates for DOI-related path length differences and enhances CTR in Cherenkov-based PET detectors. This approach opens avenues for more accurate event localization without increasing photon yield, and could serve as a building block for advanced PET systems requiring ultrafast timing performance.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-angle fluoroscopic lung perfusion imaging using x-ray pulsatility index: A pilot study in healthy subjects","authors":"Matthew R. Smith,&nbsp;Bradley W. Richmond,&nbsp;Savannah Gregory,&nbsp;Maggie Cartwright,&nbsp;Andreas Fouras,&nbsp;Greg T. Mogel,&nbsp;Charles R. Hatt,&nbsp;Gary T. Smith,&nbsp;Jared V. Grice","doi":"10.1002/mp.70666","DOIUrl":"10.1002/mp.70666","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;X-ray pulsatility index (XPI) quantifies cardiac-synchronous attenuation changes as a surrogate for regional lung perfusion, but current implementations are limited by projectional overlap and the lack of reference values in healthy individuals.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To characterize regional XPI patterns and establish preliminary reference values in healthy participants using a novel multi-angle fluoroscopic imaging system.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Nineteen healthy participants underwent an 8 s breath-hold during fluoroscopic imaging using 15 fps at four simultaneous projections (LPO, AP caudal, RPO, AP cranial) using a novel scanner. Frames were cropped to exclude initial x-ray tube stabilization and bulk motion. Spectral analysis exploited the periodic signal attenuation in the lungs to create XPI maps, as previously described. To focus on the clinically important regions of lung perfusion, the peripheral 3 cm of lung was manually segmented and divided into upper, middle, and lower lung zones. XPI values from these regions were compared to evaluate laterality and cranial–caudal differences using paired &lt;i&gt;t&lt;/i&gt;-tests corrected with the Benjamini-Hochberg procedure to control the False Discovery Rate (FDR). Peripheral XPI contrast-to-noise (pCNR) was calculated in the AP caudal projection to quantify signal-to-background separation. Data were retrospectively resampled to assess the effect of reduced frame rate (7.5, 5 fps) and shorter acquisition time using multiple regression analysis. Radiation dose was estimated using phantom measurements and simulation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;All participants performed the breath-hold without difficulty. XPI maps demonstrated bilateral lung perfusion across all four views, enabling multi-projection assessment of regional perfusion. No focal defects were observed; however, one participant demonstrated globally reduced XPI. Significant cranial–caudal gradients in XPI were observed across projection angles, consistent with known gravity-dependent physiology. Following FDR adjustment (&lt;i&gt;Q&lt;/i&gt; = 0.05), the lower zones continued to demonstrate significantly higher values than the upper zones in 3 of 4 projections (all &lt;i&gt;q&lt;/i&gt; &lt; 0.05). There were no significant laterality differences (&lt;i&gt;q&lt;/i&gt; &gt; 0.05). XPI values remained stable across acquisition lengths and frame rates, indicating robustness of the metric. CNR increased with longer acquisitions and higher frame rates, reflecting reduced noise and impr","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13535757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving portability of knowledge-based planning using an LLM-driven plan refinement framework in lung radiotherapy","authors":"Zipai Wang,&nbsp;Hao Guo,&nbsp;Yang Lei,&nbsp;Robert Samstein,&nbsp;Kenneth E Rosenzweig,&nbsp;Ming Chao,&nbsp;Tian Liu,&nbsp;Junyi Xia,&nbsp;Jiahan Zhang","doi":"10.1002/mp.70657","DOIUrl":"10.1002/mp.70657","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Knowledge-based planning (KBP) has improved the quality and efficiency of radiotherapy treatment planning. However, its broader clinical adoption remains limited because effective deployment often requires institution-specific model training and tuning. Publicly available KBP models provide a convenient starting point but may not consistently meet local clinical objectives across institutions.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We developed and evaluated the Planning Copilot, a large language model (LLM)-guided plan refinement framework designed to operate as a model-agnostic post-processing layer for KBP.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The Planning Copilot is a closed-loop, multi-agent system that iteratively refines KBP-generated plans through structured dosimetric feedback and the selection of clinically validated optimization actions within a treatment planning system. For each case, an initial step-and-shoot IMRT plan was generated with each of three RapidPlan models, including a publicly available model and two institutional models with different optimization constraints. To assess whether the refinement depends on KBP, we additionally evaluated PlanningCopilot starting from a non-KBP fixed objective template applied identically to all cases. The PlanningCopilot was applied without model-specific tuning to 62 retrospective locally advanced NSCLC cases. Clinical goal achievement rates and clinically relevant dose–volume metrics were compared between the initial KBP plans and the refined plans.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Across all three KBP models, the PlanningCopilot substantially improved plan quality. Clinical goal achievement increased from 79% to 98% for the UCSD model, from 73% to 97% for Institutional T1, and from 69% to 98% for Institutional T2. Starting from the non-KBP fixed template, the achievement rate increased from 68% to 97%, comparable to the KBP initializations. Significant reductions were observed in key lung dose metrics, including lung Dmean across all models and lung V20 in the Institutional T1 model and template initializations, while target coverage and doses to critical structures were maintained. Notably, the KBP model that prioritized OAR sparing, which exhibited the lowest initial pass rate, showed the highest rescue rate after refinement.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;An LLM-guided refinement layer can improve the success rate and portability of KBP across heterogeneous models without retraining the underlying KBP ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and performance evaluation of an upright dedicated cone-beam breast CT system","authors":"Thomas C. Larsen,&nbsp;Hsin Wu Tseng,&nbsp;William Ross,&nbsp;Stephen Araujo,&nbsp;Pengwei Wu,&nbsp;Eri Haneda,&nbsp;Cynthia Davis,&nbsp;Andrew Karellas,&nbsp;Srinivasan Vedantham","doi":"10.1002/mp.70664","DOIUrl":"10.1002/mp.70664","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Dedicated breast CT is an emerging breast X-ray imaging modality. While current commercial breast CT systems use prone-patient, pendant-breast geometry, the system described here uses upright patient geometry with the uncompressed breast supported by a cup.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The purpose of this work is to describe the development of a newly designed, upright geometry, dedicated cone-beam breast CT system and to evaluate its imaging performance using objective metrics.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The prototype system uses a tungsten-target, mammography-format, X-ray tube operating at 60 kV with 0.25 mm Cu and 1 mm Al added filtration, and a complementary metal-oxide semiconductor (CMOS) detector with 0.152 mm pixel pitch coupled to 500 microns thick CsI:Tl scintillator. During short scan acquisition, the X-ray source moves inferior to the breast, and 210 projections are acquired over an angular range of 210 degrees. The projections are reconstructed to an isotropic voxel pitch of 0.22 mm using Feldkamp-Davis-Kress (FDK) algorithm with Parker weights. Quantitative performance measures including linearity, modulation transfer function (MTF), and noise power spectrum (NPS) were evaluated. Phantom studies were conducted at various X-ray tube current (mA) and pulse-width (ms) combinations with the objective of determining the minimum detectable size of low-contrast targets and calcium carbonate spheres representing soft tissue lesions and microcalcification clusters, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The measured 1st HVL was 4.23 ± 0.01 mm of Al. The limiting resolution (10% MTF) was 2.18 mm⁻¹ in the coronal (cross-sectional) plane near the axis of rotation. In the coronal plane, the peak of the NPS occurred at 0.5 mm⁻¹. Phantom studies at a mean glandular dose of 3–5.7 mGy showed the ability to visualize 2–3 mm low-contrast targets and 0.27–0.29 mm calcium carbonate spheres.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The developed upright breast CT system showed the ability to achieve high spatial resolution and low contrast resolution. The excellent technical performance of the breast CT system reported here suggests that further investigations using patient imaging are warranted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PlanningCopilot: An agentic framework integrating ESAPI modules for autonomous treatment planning in lung radiotherapy","authors":"Hao Guo,&nbsp;Zipai Wang,&nbsp;Tenzin Kunkyab,&nbsp;Yang Lei,&nbsp;Robert Samstein,&nbsp;Kenneth E. Rosenzweig,&nbsp;Ming Chao,&nbsp;Tian Liu,&nbsp;Jiahan Zhang,&nbsp;Junyi Xia","doi":"10.1002/mp.70665","DOIUrl":"10.1002/mp.70665","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Consistently generating clinically acceptable plans without human intervention remains a challenge in radiotherapy. Rule-based automation provides deterministic execution, and knowledge-based planning (KBP) provides statistical dose estimation, but both often require manual refinement. Large language models (LLMs) offer clinical reasoning capability, but effective autonomous planning also requires a mechanism to execute complex planning actions within the treatment planning system (TPS).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To develop and evaluate PlanningCopilot, an agentic system that utilizes the reasoning capability of LLM and a validated Eclipse Scripting API (ESAPI) optimization module integrating KBP initialization (“PlanAct”) to autonomously generate treatment plans. This study evaluates the system's ability to produce clinically acceptable plans for locally advanced non-small cell lung cancer (LA-NSCLC) and assesses its potential to refine performance by self-learning.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;PlanningCopilot was implemented as a multi-agent framework linked to the TPS through PlanAct API. It comprises four specialized GPT-4.1 agents that iteratively interact with the TPS: (1) an Evaluator agent that accesses the plan and generates plan quality reports, (2) a Supervisor agent that validates these reports before passing them to a Planner agent, (3) the Planner agent that executes initialization and optimization tasks through PlanAct API and planning guidelines, and (4) an optional Learner agent that synthesizes optimization history into Planner-facing prompt addendums. We retrospectively analyzed 62 patients with conventionally fractionated LA-NSCLC and compared original clinical plans with autonomous plans with and without the Learner agent. Measurement-based patient-specific quality assurance (PSQA) was performed on the first 21 autonomous IMRT plans in planning order.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;All autonomous plans met clinical dosimetric requirements, including those not achieved in the clinical plans and KBP (RapidPlan) plans. Paired Wilcoxon signed-rank tests showed no significant differences between autonomous and clinical plans for Lungs D&lt;sub&gt;mean&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.371), Lungs V&lt;sub&gt;20Gy&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.449), Lungs V&lt;sub&gt;5Gy&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.309), Heart D&lt;sub&gt;50%&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.175), Esophagus D&lt;sub&gt;mean&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.750), Spinal Cord D&lt;sub&gt;0.03cc&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.422), and Plan D&lt;sub&gt;0.03cc&lt;/sub&gt; (&lt;i&gt;p&lt;/i&gt; = 0.941). Furthermore, autonomous plans achieved significantly lower Esophagus D&lt;sub&gt;0.03cc&lt;/sub&gt;","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}