Journal of Applied Clinical Medical Physics最新文献

{"title":"Dosimetric evaluation of systematic source position uncertainty along the source path and robust planning during MRI-only cervical HDR brachytherapy","authors":"Amritpal Singh, Raffi Karshafian, Ananth Ravi, Moti Raj Paudel","doi":"10.1002/acm2.70810","DOIUrl":"10.1002/acm2.70810","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The knowledge of the dosimetric impact of systematic source position uncertainty and the use of a methodology for robust treatment planning against such uncertainty can help improve the quality of treatment plans, during MR-only cervical brachytherapy treatment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To assess the dosimetric impact of systematic source position uncertainty along the source path and evaluate strategies to minimize it during MRI-only cervical high-dose-rate (HDR) brachytherapy treatment planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Treatment plans from 22 cervical cancer patients (FIGO stages IB2–IVA; 11 intracavitary brachytherapy (ICBT), 11 interstitial brachytherapy (ISBT)) were retrospectively analyzed. Positional uncertainty was modeled by systematically shifting the source position (± 1 to ± 5 mm with 0 mm as the reference position) within applicators along the source path in the original plans. Dosimetric parameters, HRCTV_D90 and D<sub>2cc</sub> for organs at risk (OARs), were computed for each source position. Statistical significance was assessed via paired t-test and Wilcoxon signed-rank test. Targeted plans exceeding dosimetric limits for OARs were re-optimized by modifying dwell times or gradients within 1 cm of the targeted OAR to improve the variability and overall OAR dosimetry.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Significant dosimetric changes were observed for bladder, sigmoid (all shift positions; <i>p </i>≤ 0.001) and rectum (1 to 5 mm; <i>p</i> ≤ 0.04) in ICBT, and for all OARs (all shift positions; <i>p</i> ≤ 0.003) in ISBT. HRCTV_D90 was significantly affected in ICBT from -2 to -5 mm (<i>p</i> ≤ 0.042) and at all shifts (<i>p</i> ≤ 0.033) except at -1 and -2 mm in ISBT. Within ± 5 mm shift range, the mean (maximum) drop in HRCTV_D90 and increase in OARs (bladder, bowel, rectum and sigmoid) D<sub>2cc</sub> were up to −2.0 ± 1.9(−5.4)% and (6.0 ± 3.4(13.6)%, 0.5 ± 2.5(5.5)%, 2.2 ± 2.7(7.4)% and 1.8 ± 1.2(4.2)%) for ICBT, and -6.2 ± 1.4(-11.9)% and (5.2 ± 4.6(17.2)%, 1.3 ± 0.9(3.0)%, 4.6 ± 2.5(7.6)% and 6.6 ± 3.6(13.8)%) for ISBT, respectively. Re-optimized plans showed improved robustness of dosimetry against source positional uncertainty for the targeted OAR with the same or better dosimetry for other OARs and HRCTV. The strategies to obtain this robustness were patient and applicator-type dependent.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13598937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149024934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volumetric Modulated Arc Therapy for lung cancer: Correlation between dose and volume","authors":"Yu Wang,&nbsp;Deying Xu,&nbsp;Yunfeng Liu,&nbsp;Xiaofeng Zhang,&nbsp;Liang Yu","doi":"10.1002/acm2.70781","DOIUrl":"10.1002/acm2.70781","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In lung cancer radiotherapy, the volume of the lung receiving a dose above 20 Gy (V_20Gy) and the mean lung dose are widely recognized dosimetric indicators for predicting radiation pneumonitis. However, there is currently no unified model to predict the minimum achievable values of V_20Gy and mean lung dose. In modern radiotherapy, the most advanced and widely used technology in mainstream medical linear accelerators is volumetric modulated arc therapy (VMAT). This article describes, based on linear accelerator VMAT, the clinical dependency of achievable dose-to-volume ratios.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To investigate the predictive effect of the ratio of the planning target volume (PTV) to lung volume (r) on lung V_20Gy and mean lung dose (MLD) in volumetric modulated arc therapy (VMAT) for lung cancer, with the aim of optimizing radiotherapy plans for lung cancer.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 197 samples were used, including VMAT plans covering primary lung lesions and lymphatic drainage areas, of which 149 were used for training and 48 for testing. A retrospective analysis was conducted on the relationship between the r and MLD or V_20Gy in the plans, and function fitting was performed using the least squares method.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The r ranged from 0.0112 to 0.2811. The R² values of the power function and logarithmic function of MLD versus r were 0.820 and 0.805, respectively, while the <i>R</i>² values of the power function and logarithmic function of V_20Gy versus r were 0.822 and 0.816, respectively. The residual of MLD is ± 200, and the residual of V_20Gy is ± 4%, with residuals distributed randomly.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The r showed good fitting results with the power and logarithmic functions of MLD or V_20Gy. During treatment plan creation and evaluation, the power or logarithmic function relationships can be used to predict MLD and V_20Gy in the treatment plan, thereby achieving the lowest possible lung dose while conforming to radiation principles.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13598815/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149024885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated decision support tool for static angle modulated ports configuration in VMAT with dynamic collimator rotation for head and neck cancer","authors":"Hideaki Hirashima,&nbsp;Takahiro Iwai,&nbsp;Shinya Hiraoka,&nbsp;Mitsuhiro Nakamura,&nbsp;Ryota Nakashima,&nbsp;Takashi Mizowaki","doi":"10.1002/acm2.70813","DOIUrl":"10.1002/acm2.70813","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;RapidArc Dynamic (RAD; Varian Medical Systems, Palo Alto, CA) is a novel volumetric modulated arc therapy (VMAT) technique that features dynamic collimator rotation synchronized with gantry rotation. RAD enables the use of static angle-modulated ports (STAMPs) defined by user selected gantry and collimator angles. However, the determination of STAMP configurations currently relies on manual trial-and-error procedures based on planner experience, which limits the efficient clinical implementation of this functionality.&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;This study aimed to develop an automated decision support tool using an Eclipse Scripting Application Programming Interface (ESAPI; Varian Medical Systems) to identify cost-optimized STAMP configurations and evaluate its clinical utility in complex head and neck cancer planning.&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;Twenty patients with nasopharyngeal or sinonasal cancer who had previously received radiotherapy at our institution were retrospectively analyzed. Four treatment plans were generated for each patient: conventional VMAT using RapidArc (RA, Varian Medical Systems), RAD with manually defined STAMPs (RADm) by an expert radiation oncologist, RAD with a vendor-provided automatic collimator rotation algorithm (RADa), and RAD using the proposed decision support tool (RADdst). The developed algorithm determined the STAMP configurations in three phases: (1) generation of a two-dimensional geometric cost map across the gantry and collimator angles by integrating planning target volume-fit and organ-at-risk (OAR)-avoidance terms, (2) extraction of a cost-minimizing collimator trajectory, and (3) identification of cost-optimized STAMP positions in geometrically critical regions that require substantial collimator rotation while satisfying machine-specific rotation-speed constraints. The dosimetric indices of the targets and OARs, optimization calculation times, and estimated beam delivery times were evaluated.&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 ESAPI-based tool successfully generated dosimetrically feasible RADdst plans for all patients, automatically selecting between two and ten STAMPs according to anatomical complexity. All planning techniques achieved clinically acceptable target coverage and OAR sparing. In nasopharyngeal cancer cases, all RAD approaches significantly reduced the oral cavity dose compared with RA (RADm, &lt;i&gt;p&lt;/i&gt; = 0.02; RADa, &lt;i&gt;p&lt;/i&gt; = 0.002; RADdst, &lt;i&gt;p&lt;/i&gt; = 0.002), and RADdst additionally achieved a si","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13598925/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149024898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging TG-116 and TG-232: A retrospective multi-vendor evaluation of deviation index re-centering and process control in digital radiography","authors":"Ezzat AbuAzzah,&nbsp;Faisal Alrehily,&nbsp;Moawia Gameraddin,&nbsp;Sultan Alshoabi,&nbsp;Walaa Alsharif,&nbsp;Kamal Dahan Alsultan,&nbsp;Abdullah Alshamrani,&nbsp;Khaled Al-Radadi,&nbsp;Ramy Badawy,&nbsp;Samer Al-Jabri,&nbsp;Turki Al-Harbi,&nbsp;Nawaf Al-Hazme","doi":"10.1002/acm2.70820","DOIUrl":"10.1002/acm2.70820","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;The deviation index (DI) is a vendor-neutral indicator of detector exposure relative to the configured target exposure index (TEI). Because TEI is a protocol value rather than a calibrated physical quantity, poorly aligned TEI settings can create systematic DI offsets, obscure protocol problems, and prevent meaningful statistical process control.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This retrospective multi-vendor study evaluated whether routine DICOM metadata can identify biased DI distributions, separate fixed TEI-setting offsets from protocol-adherence variation, estimate candidate TEI updates, and support TG-232-aligned standard deviation-based monitoring after DI re-centering.&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 retrospectively analyzed 38 916 digital radiography examinations performed from January 1, 2024 through August 27, 2024 using three vendor platforms at a tertiary hospital. DICOM metadata were benchmarked against published technical standards using a composite adherence index (CAI) for SID, kVp, mAs, grid use, and AEC use. A secondary gradient-boosting/SHAP analysis was retained as a non-causal variance discovery to rank the metadata patterns used to predict DI. Candidate TEI updates were estimated within the vendor-region-projection groups by algebraically re-centering the observed mean DI (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mover&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;D&lt;/mi&gt;\u0000 &lt;mi&gt;I&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;¯&lt;/mo&gt;\u0000 &lt;/mover&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$overline {DI} )$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; to 0.0. Robustness was assessed using sensitivity analyses restricted by automatic exposure control, beam energy, and patient habitus proxy measures.&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 baseline &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mover&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;D&lt;/mi&gt;\u0000 &lt;mi&gt;I&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;¯&lt;/mo&gt;\u0000 &lt;/mover&gt;\u0000 &lt;annotation&gt;$overline {DI} $&lt;/annotation&gt;\u0000 ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149030175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative evaluation of VoxelMorpand conventional deformable image registration algorithms for thoracic 4D-CT in radiotherapy","authors":"Mizuha Sakai,&nbsp;Megumi Nakao,&nbsp;Hideaki Hirashima,&nbsp;Masahiro Yoneyama,&nbsp;Noriko Kishi,&nbsp;Takashi Mizowaki,&nbsp;Mitsuhiro Nakamura","doi":"10.1002/acm2.70816","DOIUrl":"10.1002/acm2.70816","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Deformable image registration (DIR) is essential for thoracic four-dimensional computed tomography (4D-CT)-based radiotherapy applications. Recently, deep learning-based DIR methods such as VoxelMorph have been proposed; however, their performance relative to clinically used DIR algorithms remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aimed to evaluate the DIR accuracy of VoxelMorph for thoracic 4D-CT and to compare it with conventional clinical and research-oriented DIR methods.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and methods</h3>\u0000 \u0000 <p>Thoracic 4D-CT data from 64 lung cancer patients were retrospectively analyzed. End-inhalation and end-exhalation phase images were used for DIR. VoxelMorph was trained using 50 cases, with 4 for validation and 10 for testing. DIR performance on the test dataset was compared with Demons (SimpleITK), modified Demons (Eclipse), and ANACONDA (RayStation). Accuracy was evaluated by mean absolute error (MAE) of CT values computed within the body region, whereas Dice similarity coefficient (DSC) and 95th percentile of Hausdorff distance (HD95) were evaluated within the lung label.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The median MAE decreased from 67.56 HU before DIR to 52.32 HU with modified Demons, 37.39 HU with Demons, 36.18 HU with ANACONDA, and 36.83 HU with VoxelMorph. The median DSC increased from 0.91 to 0.95 for modified Demons, 0.97 for Demons and ANACONDA, and 0.98 for VoxelMorph. The median HD95 was 3.0 mm for modified Demons, 3.1 mm for Demons, 2.0 mm for ANACONDA, and 2.5 mm for VoxelMorph. Overall, VoxelMorph demonstrated competitive accuracy, significantly outperforming modified Demons (adjusted <i>p &lt;</i> 0.05), while showing smaller inter-case variability and markedly reduced processing time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>VoxelMorph demonstrated DIR performance comparable to that of clinically used algorithms for thoracic 4D-CT, with high overlap accuracy, relatively low inter-case variability and shorter processing times under the evaluated implementation conditions. These findings suggest its potential as research-oriented DIR framework, although further validation under standardized conditions is required before routine clinical implementation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13598922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149024967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical evaluation and regression test of a commercial deep-learning auto-segmentation model","authors":"Roya Barati,&nbsp;Jingwei Duan,&nbsp;Song Gao,&nbsp;Yao Zhao,&nbsp;Xinru Chen,&nbsp;Cenji Yu,&nbsp;Zhan Xu,&nbsp;Moghadaseh Khaleghibizaki,&nbsp;Fredrik Lofman,&nbsp;Jared Ohrt,&nbsp;Laurence Court,&nbsp;Peter Balter,&nbsp;Jinzhong Yang","doi":"10.1002/acm2.70824","DOIUrl":"10.1002/acm2.70824","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;Commercial deep-learning segmentation (DLS) tools are increasingly used in clinical practice. Software updates may alter segmentation performance, highlighting the need for systematic clinical evaluation before implementation.&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;This study presents our experience in clinically evaluating and regression-testing a RayStation DLS model with the aim of guiding commissioning and routine quality assurance of commercial DLS tools in clinical environments.&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;U-Net DLS model for normal-tissue structures, originally commissioned in RayStation version 11B, was regression-tested after upgrading to 2024A. Previously commissioned CT datasets for head and neck (&lt;i&gt;n&lt;/i&gt; = 18), thorax (&lt;i&gt;n&lt;/i&gt; = 18), male pelvis (&lt;i&gt;n&lt;/i&gt; = 18), and breast (&lt;i&gt;n&lt;/i&gt; = 21) were re-evaluated in RayStation 2024A for regression testing following the software upgrade, while 20 new abdominal cases were included for initial commissioning. Clinical segmentations served as the reference standard. Geometric performance was evaluated using Dice Similarity Coefficient (DSC), 95% Hausdorff Distance (HD95), and Mean Surface Distance (MSD). Dosimetric evaluation used the original clinical treatment plans to compare Dmean and Dmax between DLS and clinical contours, normalized to prescription dose; breast was excluded from dosimetric analysis because its DLS model was not commissioned for clinical use.&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;Regression testing showed that, in comparison with the previously commissioned data, mean [± standard deviation (SD)] DSC values were 0.81 ± 0.09 for the head and neck, 0.84 ± 0.13 for the thorax, and 0.89 ± 0.06 for male pelvis. Corresponding MSD values were 0.83 ± 0.34 mm, 2.47 ± 1.81 mm, and 1.76 ± 0.68 mm; and HD95 values were 4.75 ± 2.38 mm, 8.45 ± 3.38 mm, and 13.21 ± 7.05 mm. Significant paired differences between versions were limited to selected structures, including the mandible, cochlea, and eye in head and neck; lungs and esophagus in thorax; and prostate in the male pelvis (&lt;i&gt;p&lt;/i&gt; &lt; 0.05). Breast segmentation results showed low performance (DSC 0.66 ± 0.15, MSD 4.8 ± 1.93 mm, and HD95 22.2 ± 9.6 mm) compared to clinical reference, so the breast structure models are not recommended for clinical use. Abdominal structures (RayStation 2024A vs clinical) had DSC 0.95 ± 0.014; MSD 0.82 ± 0.32 mm; and HD95 5.4 ± 2.9 mm. The mean dose differences between DLS and clinical segmentations were 0.03 Gy for the head and nec","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70824","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149030238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing diagnostic precision for BI-RADS 4a breast nodules: A multimodal AI model integrating ultrasound radiomics, hemodynamic signatures, and clinical profiles","authors":"Jun Yang,&nbsp;Longman Long,&nbsp;Guang Li,&nbsp;Jian Zeng,&nbsp;Caixiao Peng,&nbsp;Jingting Yan","doi":"10.1002/acm2.70800","DOIUrl":"10.1002/acm2.70800","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;Breast Imaging Reporting and Data System (BI-RADS) 4a nodules represent a diagnostic dilemma, with a malignancy rate ranging from 2% to 10%. The majority of these nodules prove benign after biopsy, leading to unnecessary invasive procedures, patient anxiety, and healthcare costs. Current clinical practice lacks a reliable, noninvasive tool to accurately distinguish benign from malignant BI-RADS 4a lesions. Emerging evidence suggests that integrating multiparametric ultrasound data with clinical factors through artificial intelligence may improve diagnostic precision, but a validated multimodal model specifically for this ambiguous category is lacking.&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 validate a multimodal artificial intelligence model that integrates ultrasound radiomics, hemodynamic features, and clinical data for the accurate differentiation of benign and malignant BI-RADS 4a breast nodules, with the ultimate goal of supporting clinical decisionmaking and safely reducing unnecessary biopsies.&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;This prospective, multicenter study enrolled 350 pathologically confirmed BI-RADS 4a nodules from 331 patients in one tertiary hospital and two secondary hospitals. Clinical data, grayscale ultrasound images, and hemodynamic parameters were collected for each nodule. Radiomics features were extracted from the ultrasound images. A multimodal fusion model was constructed using the Light Gradient Boosting Machine (LightGBM) algorithm following feature selection via Least Absolute Shrinkage and Selection Operator (LASSO) regression. The model was developed and hyperparameter-tuned on a training set (&lt;i&gt;n&lt;/i&gt; = 260) using nested cross-validation and was evaluated on a temporally independent test set (&lt;i&gt;n&lt;/i&gt; = 90). Model interpretability was enhanced using SHapley Additive exPlanations (SHAP).&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;On the independent test set, the multimodal LightGBM model demonstrated excellent diagnostic performance, achieving an area under the receiver operating characteristic curve (AUC) of 0.95 (95% CI: 0.91–0.99), with a sensitivity of 100% (95% CI: 81.5%–100%) and a specificity of 86.1% (95% CI: 75.8%–93.1%). Its performance was significantly superior to baseline classifiers including Logistic Regression, Support Vector Machine, and Random Forest (all &lt;i&gt;p&lt;/i&gt; &lt; 0.05). SHAP analysis identified wavelet-transformed texture features, the presence of a penetrating vessel, and BRCA mutation status as the top predictors of","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13594395/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149017080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calibration and count rate performance of NaI(Tl) gamma counters for quantifying the activity 89Zr radiopharmaceuticals","authors":"Michael Silosky","doi":"10.1002/acm2.70788","DOIUrl":"https://doi.org/10.1002/acm2.70788","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Quantification of low activity samples using gamma counters is a common technique when investigating the biodistribution of experimental radiopharmaceuticals. Several human and pre-clinical trials have investigated ⁸⁹Zr labeled compounds, utilizing gamma counter to quantify activity in blood or animal samples. While the performance of gamma counters has been investigated for other positron emitting radionuclides, the more complex spectrum, including a 909 keV gamma emission, and low positron fraction of ⁸⁹Zr may reduce both counting efficiency while increasing the severity of count rate losses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The purpose of this study is to evaluate both the counting efficiency and the effect of count rate losses on the quantitation of activity for ⁸⁹Zr using NaI(Tl) gamma counters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Sources of known activity (initially 78.3 kBq) were measured in a gamma counter as they decayed over approximately 15 days. Observed count rates were fit with a paralyzable detector model for two separate energy windows, 511 keV ± 10% and 909 keV ± 10%, as well as their sum. Counting efficiency in the absence of losses as well as the effective deadtime for each dataset were calculated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Count rates for each energy window were well fit with a paralyzable model with <i>R</i>² &gt; 0.999. Counting efficiency (mean ± 95% confidence interval) was 10.07% ± 0.07%, 17.38% ± 0.13%, and 27.46% ± 0.16% for the 511 keV, 909 keV, and summed energy windows respectively. Effective dead time (mean, 95% confidence interval) was 14.31 µs, (13.30 µs–15.30 µs), 7.11 µs (6.68 µs–7.55 µs), and 4.77 µs (4.48 µs–5.06 µs) for the 511 keV, 909 keV, and summed energy windows respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Counting efficiency and count rate performance for ⁸⁹Zr are poorer than for other positron emitting radionuclides. Count rate losses follow the paralyzable model and are correctible.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70788","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of interfractional shift corrections in Gamma Knife radiosurgery","authors":"Edward A. Opalko,&nbsp;Dheerendra Prasad,&nbsp;Matthew B. Podgorsak","doi":"10.1002/acm2.70787","DOIUrl":"https://doi.org/10.1002/acm2.70787","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The purpose of this study was to evaluate the ability of the GammaPlan treatment planning system used in the Gamma Knife Icon and Esprit machines to automatically correct large interfractional shifts in hypofractionated frameless treatments using a custom 3D printed phantom.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A custom 3D printed insert was created to modify a commercial head phantom. The water equivalence of polylactic acid (PLA) was determined by comparing optical densities of film using solid water and PLA as buildup. Lesions of varying size, shape and location were created on images of the phantom to replicate several clinical scenarios. Seven 5-fraction plans were generated using typical dose objectives. Six combinations of headrests/masks were created to simulate different setup positions. Masks were changed between fraction measurements to simulate interfractional shifts. The composite dose distributions of the corrected plans were measured using Gafchromic film and compared to the original dose distribution using Gamma Analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The average deviation for Coverage, Paddick Conformity Index and Gradient Index across all plans remained unchanged between the corrected plan and the original plan. No deviation was greater than 0.01 between the three metrics. Compared to the original plans, the measured dose distributions produced an average Gamma Passing Rate of 98.3% for 3%/1mm, 99.6% for 2%2mm, 96.3% for 2%1mm and 92.7% for 1%/1mm. All but two dose distributions produced passing rates above 90%. For the dosimetric analysis of PLA, the optical densities at various MU values were found to be equivalent for solid water and PLA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The correction algorithm was able to produce a corrected plan almost identical to the original plan in terms of plan statistics and dose distributions. The algorithm could accurately correct for extreme interfractional shifts beyond what is seen clinically. The results of this study also show the potential for PLA phantoms to be used as dosimetry tools.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70787","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Commissioning and end-to-end validation of a combined surface-guided and triggered kV imaging workflow for breath-hold SBRT on a Varian TrueBeam","authors":"Offormata E. Osunkwor,&nbsp;Alois Ndlovu,&nbsp;Roland F. Teboh","doi":"10.1002/acm2.70812","DOIUrl":"https://doi.org/10.1002/acm2.70812","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Respiratory motion introduces significant geometric uncertainty in Stereotactic Body Radiotherapy (SBRT) for thoracic and abdominal tumors. Deep Inspiration Breath-Hold (DIBH) mitigates this, but the surface signal alone may not reflect internal target position, supporting the need for real-time internal-anatomy verification during delivery.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p> To commission a Surface-Guided Radiation Therapy (SGRT) system and validate an integrated SGRT + Image-Guided Radiation Therapy (IGRT) + triggered kV imaging (SITI) workflow for DIBH SBRT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials &amp; Methods</h3>\u0000 \u0000 <p>The LAP LUNA 3D SGRT system was commissioned per AAPM TG-302 using phantom-based assessment of static and dynamic localization accuracy, reproducibility, and latency. An end-to-end test using a dynamic phantom validated the SITI workflow. Point dose was measured with an ion chamber under four scenarios: SGRT-only delivery, full SITI delivery, and SITI with induced 1 and 2 mm uncorrected 3D shifts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Static localization accuracy was better than 0.5 mm / 0.3°, with reproducibility within 0.2 mm / 0.1°. Dynamic testing confirmed sub-millimeter spatial accuracy and a 31.6 ms latency, well below the AAPM TG-302 100 ms tolerance. The 1 and 2 mm uncorrected shifts produced point-dose reductions of 0.9% and 2.2% relative to the SITI reference, consistent with the ∼1%/mm local dose gradient. Both shifts were clearly visualized on triggered kV images, confirming detection of sub-tolerance residual displacements undetected by surface guidance alone.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The LAP LUNA 3D system meets the technical requirements for SBRT. The SITI workflow is technically feasible and provides real-time visualization of internal target position during delivery, offering a robust motion-management strategy for DIBH SBRT of mobile thoracic and abdominal targets.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 10","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70812","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}