Randa Kamel, Thierry Gevaert, Dirk Van den Berge, Mark De Ridder
Background
Stereotactic body radiotherapy (SBRT) for pancreatic cancer is limited by the proximity of tumors to gastrointestinal (GI) organs, increasing the risk of toxicity. Magnetic resonance-guided radiotherapy (MRgRT) offers potential advantages through superior soft tissue visualization, real-time tumor tracking, and online adaptive planning. This study aimed to quantitatively compare dosimetric outcomes of pancreatic cancer SBRT using online adaptive MRgRT versus conventional computed tomography-based image-guided radiotherapy (CT-IGRT).
Methods
A retrospective dosimetric analysis was conducted on 100 plans from 10 patients with primary (n = 3) or recurrent (n = 7) pancreatic adenocarcinoma treated between July 2021 and December 2022 at UZ Brussel. Treatment included 80 adaptive MRgRT fractions, 10 initial MR plans, and 10 CT-based volumetric-modulated arc therapy (VMAT) plans using an internal target volume (ITV) approach. All patients were treated on the MRIdian system with daily online adaptation and real-time beam gating. Dosimetric endpoints included target coverage, plan quality metrics, and organ-at-risk (OAR) doses. Statistical comparisons were performed using Wilcoxon signed-rank tests.
Results
MRgRT significantly reduced target volumes compared to CT-IGRT (median gross tumor volume (GTV): 40.65 cc vs. 62.56 cc; p = 0.005; median planning target volume (PTV): 64.4 cc vs. 94.4 cc; p = 0.005) and improved dose coverage of both GTV and PTV. Intermediate dose spillage (R50%) was also lower with MRgRT (5.18 vs. 6.56, p = 0.04). MRgRT plans provided superior sparing of critical GI OARs, with median D5cc relative dose reductions of 42% to the small bowel (p = 0.02), 23% to the duodenum (p = 0.02), and 13% to the stomach (p = 0.01). No significant differences were observed for the liver, kidneys, or large bowel. Treatment was well tolerated, with only grade I–II toxicities reported.
Conclusions
MR-guided adaptive SBRT demonstrated dosimetric superiority over CT-IGRT in pancreatic cancer, with improved target coverage and enhanced GI OAR sparing. These findings support the use of MRgRT to expand the therapeutic window for safe dose escalation. Prospective studies are warranted to confirm clinical benefits.
背景：胰腺癌的立体定向放射治疗（SBRT）由于肿瘤靠近胃肠道（GI）器官而受到限制，增加了毒性的风险。磁共振引导放射治疗（MRgRT）通过优越的软组织可视化、实时肿瘤跟踪和在线自适应规划提供了潜在的优势。本研究旨在定量比较使用在线自适应MRgRT和传统基于计算机断层扫描的图像引导放疗（CT-IGRT）的胰腺癌SBRT的剂量学结果。方法：对2021年7月至2022年12月期间在布鲁塞尔UZ治疗的10例原发性（n = 3）或复发性（n = 7）胰腺腺癌患者的100例计划进行回顾性剂量学分析。治疗包括80个自适应MRgRT分数，10个初始MR计划和10个基于ct的体积调节弧治疗（VMAT）计划，使用内部靶体积（ITV）方法。所有患者均在MRIdian系统上进行每日在线适应和实时光束门控治疗。剂量学终点包括目标覆盖率、计划质量指标和器官风险（OAR）剂量。采用Wilcoxon符号秩检验进行统计学比较。结果：与CT-IGRT相比，MRgRT显著减少了靶体积(中位总肿瘤体积（GTV）： 40.65 cc vs. 62.56 cc；p = 0.005；中位规划目标容积（PTV）： 64.4 cc vs. 94.4 cc；p = 0.005)，提高了GTV和PTV的剂量覆盖率。MRgRT的中剂量溢出（R50%）也较低（5.18 vs. 6.56, p = 0.04）。MRgRT计划提供了对严重胃肠道OARs的优越保留，小肠的中位D5cc相对剂量减少42% (p = 0.02)，十二指肠的中位D5cc相对剂量减少23% (p = 0.02)，胃的中位D5cc相对剂量减少13% （p = 0.01）。在肝脏、肾脏或大肠中未观察到显著差异。治疗耐受性良好，仅报告了I-II级毒性。结论：mr引导下的适应性SBRT在胰腺癌中的剂量学优势优于CT-IGRT，具有改善的靶标覆盖和增强的GI OAR保留。这些发现支持使用MRgRT来扩大安全剂量递增的治疗窗口。有必要进行前瞻性研究以确认临床益处。
{"title":"Online adaptive MR-guided SBRT versus CT-based planning in pancreatic cancer: A single-center dosimetric comparative study","authors":"Randa Kamel, Thierry Gevaert, Dirk Van den Berge, Mark De Ridder","doi":"10.1002/acm2.70391","DOIUrl":"10.1002/acm2.70391","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Stereotactic body radiotherapy (SBRT) for pancreatic cancer is limited by the proximity of tumors to gastrointestinal (GI) organs, increasing the risk of toxicity. Magnetic resonance-guided radiotherapy (MRgRT) offers potential advantages through superior soft tissue visualization, real-time tumor tracking, and online adaptive planning. This study aimed to quantitatively compare dosimetric outcomes of pancreatic cancer SBRT using online adaptive MRgRT versus conventional computed tomography-based image-guided radiotherapy (CT-IGRT).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective dosimetric analysis was conducted on 100 plans from 10 patients with primary (<i>n</i> = 3) or recurrent (<i>n</i> = 7) pancreatic adenocarcinoma treated between July 2021 and December 2022 at UZ Brussel. Treatment included 80 adaptive MRgRT fractions, 10 initial MR plans, and 10 CT-based volumetric-modulated arc therapy (VMAT) plans using an internal target volume (ITV) approach. All patients were treated on the MRIdian system with daily online adaptation and real-time beam gating. Dosimetric endpoints included target coverage, plan quality metrics, and organ-at-risk (OAR) doses. Statistical comparisons were performed using Wilcoxon signed-rank tests.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>MRgRT significantly reduced target volumes compared to CT-IGRT (median gross tumor volume (GTV): 40.65 cc vs. 62.56 cc; <i>p</i> = 0.005; median planning target volume (PTV): 64.4 cc vs. 94.4 cc; <i>p</i> = 0.005) and improved dose coverage of both GTV and PTV. Intermediate dose spillage (R50%) was also lower with MRgRT (5.18 vs. 6.56, <i>p</i> = 0.04). MRgRT plans provided superior sparing of critical GI OARs, with median D<sub>5cc</sub> relative dose reductions of 42% to the small bowel (<i>p</i> = 0.02), 23% to the duodenum (<i>p</i> = 0.02), and 13% to the stomach (<i>p</i> = 0.01). No significant differences were observed for the liver, kidneys, or large bowel. Treatment was well tolerated, with only grade I–II toxicities reported.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>MR-guided adaptive SBRT demonstrated dosimetric superiority over CT-IGRT in pancreatic cancer, with improved target coverage and enhanced GI OAR sparing. These findings support the use of MRgRT to expand the therapeutic window for safe dose escalation. Prospective studies are warranted to confirm clinical benefits.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12696390/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723209","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}
Emese Fodor, Zoltán Varga, Gyöngyi Kelemen, Judit Oláh, Anikó Maráz, Katalin Hideghéty
<div> <section> <h3> Introduction</h3> <p>Dental restorations using high-density materials can cause inaccuracies in target and organ-at-risk (OAR) delineation and dose calculations during radiotherapy. These materials, such as amalgam, lead to dose scattering, resulting in enhanced mucositis in adjacent tissues. Minimizing the impact of these artifacts is crucial to improve dose calculation accuracy. This study evaluates the effects of amalgam tooth fillings on dose distribution, compares two dose calculation algorithms (AAA—anisotropic analytical algorithm and AXB—Acuros XB), and assesses their impact on mucosal toxicity during head and neck radiotherapy.</p> </section> <section> <h3> Patients and methods</h3> <p>Forty-nine patients with one to five dental amalgam fillings treated with intensity-modulated radiotherapy (IMRT) for head and neck cancer between 2016 and 2021 at the Oncotherapy Department of Szeged University were included. Planning CTs with and without metal artifact reduction (MAR) were used to delineate targets and OARs. Treatment plans were optimized using the Eclipse Treatment Planning System with the AAA and AXB algorithms. In vivo dosimetry was performed using Gafchromic EBT3 films embedded in thin Styrofoam slabs during one of the first five treatment sessions. Statistical analyses, including <i>t</i>-tests, ANOVA, paired <i>t</i>-tests, and Kaplan–Meier curves, were conducted to evaluate the influence of clinical and dosimetric factors on dose perturbations and mucositis onset.</p> </section> <section> <h3> Results</h3> <p>Metal artifact reduction (MAR) correction improved contouring accuracy. Dose values calculated with AAA were higher than those with AXB for both mean and maximum dose to OARs and mucosa (Dmean: AAA > 10.57%, Dmax: AAA > 6.8% compared to AXB). Measured doses showed better agreement with AAA-calculated Dmean values (<i>p</i> = 0.341) but were significantly underestimated by AXB (<i>p</i> < 0.001). There was no difference in dose perturbation according to tumor localization, gross tumor volume, planning target volume, or the use of a tongue wedge. The number of amalgam-filled teeth correlated significantly with the earlier onset of mucositis, with each additional filling advancing mucositis appearance by 1.7 days.</p> </section> <section> <h3> Conclusion</h3> <p>High-density dental materials cause significant dose perturbations in the oral cavity during head and neck radiotherapy. In our clinical IMRT setup, the AAA algorithm demonstrated closer agreement with in vivo film measurements compared to AXB
{"title":"Impact of amalgam dental filling on radiotherapy of head and neck cancer: In vivo dosimetry and dose calculation using AAA and Acuros algorithms","authors":"Emese Fodor, Zoltán Varga, Gyöngyi Kelemen, Judit Oláh, Anikó Maráz, Katalin Hideghéty","doi":"10.1002/acm2.70378","DOIUrl":"10.1002/acm2.70378","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Dental restorations using high-density materials can cause inaccuracies in target and organ-at-risk (OAR) delineation and dose calculations during radiotherapy. These materials, such as amalgam, lead to dose scattering, resulting in enhanced mucositis in adjacent tissues. Minimizing the impact of these artifacts is crucial to improve dose calculation accuracy. This study evaluates the effects of amalgam tooth fillings on dose distribution, compares two dose calculation algorithms (AAA—anisotropic analytical algorithm and AXB—Acuros XB), and assesses their impact on mucosal toxicity during head and neck radiotherapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Patients and methods</h3>\u0000 \u0000 <p>Forty-nine patients with one to five dental amalgam fillings treated with intensity-modulated radiotherapy (IMRT) for head and neck cancer between 2016 and 2021 at the Oncotherapy Department of Szeged University were included. Planning CTs with and without metal artifact reduction (MAR) were used to delineate targets and OARs. Treatment plans were optimized using the Eclipse Treatment Planning System with the AAA and AXB algorithms. In vivo dosimetry was performed using Gafchromic EBT3 films embedded in thin Styrofoam slabs during one of the first five treatment sessions. Statistical analyses, including <i>t</i>-tests, ANOVA, paired <i>t</i>-tests, and Kaplan–Meier curves, were conducted to evaluate the influence of clinical and dosimetric factors on dose perturbations and mucositis onset.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Metal artifact reduction (MAR) correction improved contouring accuracy. Dose values calculated with AAA were higher than those with AXB for both mean and maximum dose to OARs and mucosa (Dmean: AAA > 10.57%, Dmax: AAA > 6.8% compared to AXB). Measured doses showed better agreement with AAA-calculated Dmean values (<i>p</i> = 0.341) but were significantly underestimated by AXB (<i>p</i> < 0.001). There was no difference in dose perturbation according to tumor localization, gross tumor volume, planning target volume, or the use of a tongue wedge. The number of amalgam-filled teeth correlated significantly with the earlier onset of mucositis, with each additional filling advancing mucositis appearance by 1.7 days.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>High-density dental materials cause significant dose perturbations in the oral cavity during head and neck radiotherapy. In our clinical IMRT setup, the AAA algorithm demonstrated closer agreement with in vivo film measurements compared to AXB","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70378","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723292","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}
Song Gao, Andres Cibrian, Jared Ohrt, Peter Balter
Purpose
To demonstrate the usage of a high energy electron beam symmetry measured at different collimator angles to detect jaws face angle misalignments on Varian TrueBeam linear accelerators (linac) during acceptance and commissioning processes.
Methods
During the linac acceptance, all beams were steered to a symmetric shape with the gantry and collimator at 0°. We noted that the symmetries of higher energies electrons (e.g., 16 MeV, 20 MeV) changed over 2% when measured with the collimator at 90° and/or 270° for two linacs commissioned within 5-months of each other. Misaligned applicators were ruled out as the cause of this issue. Eventually, this was traced to the X-jaw face angle not matching beam divergence. After the problem was identified and the jaws were realigned by manufacture's engineers and all beams were re-steered to a symmetric shape at collimator 0° and verified at collimator 90° and 270°.
Results
Prior to the manufacturer adjusting the jaw face angles, the maximum observed electron beam symmetry changes with 90° collimator rotation were 2.0% and 2.6% for linac 1 and linac 2, respectively. After realigning, the jaw face angles the maximum observed electron beam symmetry changes with 90° collimator rotation were within 1.0% for all beams on both linacs.
Conclusion
We have demonstrated that changes in symmetry of high energy electron beam with 90° collimator rotation can signal that the jaw face angle is not properly aligned with beam divergence.
{"title":"Detection of the Linac Jaw face angle misalignment using high energy electron beam symmetry","authors":"Song Gao, Andres Cibrian, Jared Ohrt, Peter Balter","doi":"10.1002/acm2.70419","DOIUrl":"10.1002/acm2.70419","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To demonstrate the usage of a high energy electron beam symmetry measured at different collimator angles to detect jaws face angle misalignments on Varian TrueBeam linear accelerators (linac) during acceptance and commissioning processes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>During the linac acceptance, all beams were steered to a symmetric shape with the gantry and collimator at 0°. We noted that the symmetries of higher energies electrons (e.g., 16 MeV, 20 MeV) changed over 2% when measured with the collimator at 90° and/or 270° for two linacs commissioned within 5-months of each other. Misaligned applicators were ruled out as the cause of this issue. Eventually, this was traced to the X-jaw face angle not matching beam divergence. After the problem was identified and the jaws were realigned by manufacture's engineers and all beams were re-steered to a symmetric shape at collimator 0° and verified at collimator 90° and 270°.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Prior to the manufacturer adjusting the jaw face angles, the maximum observed electron beam symmetry changes with 90° collimator rotation were 2.0% and 2.6% for linac 1 and linac 2, respectively. After realigning, the jaw face angles the maximum observed electron beam symmetry changes with 90° collimator rotation were within 1.0% for all beams on both linacs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We have demonstrated that changes in symmetry of high energy electron beam with 90° collimator rotation can signal that the jaw face angle is not properly aligned with beam divergence.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12695474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723452","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}
Sijin Zhu, Tianwen Zhang, Yutao Zhao, Jinli Peng, Jingyan Gao, Yunyan Yang, Yan Xu, Jiawen Yan, Ya Li
Background
The helical tomotherapy (HT) system can expose more normal lung tissue to low radiation doses, resulting in extensive low-dose distribution in both lungs which may induce radiation pneumonitis (RP).
Purpose
This study aims to optimize dosimetric parameters and identify a clinically feasible treatment plan by analyzing the impact of different block settings and modulation factor (MF) combinations on HT plans for lung cancer to reduce the low-dose exposure volumes in normal lung tissue.
Methods
We retrospectively reviewed 14 lung cancer patients who received radiotherapy. These cases were optimized using different modulation factors (MFs: 3, 4, 5) and block techniques (Unblocked, Directional, Complete). The impact of MF and block combinations on reducing low-dose bath (e.g., V5, V10) in lung tissue was evaluated by analyzing dose distribution maps, dose–volume histograms (DVH), homogeneity index (HI), conformity index (CI), and treatment time for each optimized HT plan combination.
Results
Block settings and higher MF exerted minimal influence on the average dose to the target volume. With stricter block constraints and higher MF, HI increased (range: 17.39%–27.54%) and CI decreased (range: 2.76%–17.43%); although both indices showed slight deterioration, they remained within acceptable clinical limits. Treatment time increased substantially (range: 15.77%–131.58%). The block technique significantly reduced V5 in the bilateral lungs and the contralateral (healthy) lung, with less impact on the ipsilateral (affected) lung. The combination of block and high MF effectively reduced V5.
Conclusions
To balance target volume coverage (high dose), dose distribution uniformity, and treatment duration while reducing low-dose irradiation to normal lung tissue, we recommend implementing Directional block with an MF range of 3–4 to optimize the HT plan for patients with unilateral lung cancer.
{"title":"Combined application of block and modulation factors to reduce the volume of the low dose area in helical tomotherapy plans for lung cancer","authors":"Sijin Zhu, Tianwen Zhang, Yutao Zhao, Jinli Peng, Jingyan Gao, Yunyan Yang, Yan Xu, Jiawen Yan, Ya Li","doi":"10.1002/acm2.70372","DOIUrl":"10.1002/acm2.70372","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The helical tomotherapy (HT) system can expose more normal lung tissue to low radiation doses, resulting in extensive low-dose distribution in both lungs which may induce radiation pneumonitis (RP).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to optimize dosimetric parameters and identify a clinically feasible treatment plan by analyzing the impact of different block settings and modulation factor (MF) combinations on HT plans for lung cancer to reduce the low-dose exposure volumes in normal lung tissue.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We retrospectively reviewed 14 lung cancer patients who received radiotherapy. These cases were optimized using different modulation factors (MFs: 3, 4, 5) and block techniques (Unblocked, Directional, Complete). The impact of MF and block combinations on reducing low-dose bath (e.g., V5, V10) in lung tissue was evaluated by analyzing dose distribution maps, dose–volume histograms (DVH), homogeneity index (HI), conformity index (CI), and treatment time for each optimized HT plan combination.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Block settings and higher MF exerted minimal influence on the average dose to the target volume. With stricter block constraints and higher MF, HI increased (range: 17.39%–27.54%) and CI decreased (range: 2.76%–17.43%); although both indices showed slight deterioration, they remained within acceptable clinical limits. Treatment time increased substantially (range: 15.77%–131.58%). The block technique significantly reduced V5 in the bilateral lungs and the contralateral (healthy) lung, with less impact on the ipsilateral (affected) lung. The combination of block and high MF effectively reduced V5.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>To balance target volume coverage (high dose), dose distribution uniformity, and treatment duration while reducing low-dose irradiation to normal lung tissue, we recommend implementing Directional block with an MF range of 3–4 to optimize the HT plan for patients with unilateral lung cancer.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70372","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723438","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}
<div> <section> <h3> Background</h3> <p>Quality control (QC) methods for computed tomography (CT) systems used in treatment planning have not been updated since the release of the Task Group (TG) 66 report by the American Association of Physicists in Medicine (AAPM) in 2003. Conventional QC methods for CT systems fail to fulfill the requirements of high-precision radiation therapy. Moreover, because the geometric accuracy of CT systems can affect the accuracy of radiation therapy, which is particularly critical in high-precision radiation therapy, a highly accurate QC method is required.</p> </section> <section> <h3> Purpose</h3> <p>This study aimed to develop a high-accuracy QC method for CT system couch tops suitable for high-precision radiation therapy by utilizing a wide-area three-dimensional (3D) coordinate measuring machine (3D-CMM), a type of laser tracker.</p> </section> <section> <h3> Methods</h3> <p>We used a 3D-CMM, which includes a wireless probe and a camera unit, focusing on a SOMATOM go.Open Pro CT system. The system was set up in accordance with the reference method outlined in the AAPM TG66 report guidelines. The initial phase verified the accuracy of 3D-CMM measurement within a CT room using a micrometer. Subsequently, a novel continuous measurement method was developed to enable the real-time tracking of the couch-top displacement during travel. This new method was evaluated against the standard manual measurement method. Measurements were performed at 0.1 s intervals at various index positions on the couch top, with and without added weight to simulate the presence of a patient. The gathered data were analyzed to assess the couch-top displacement, horizontality and orthogonality relative to the imaging plane, providing a comprehensive evaluation of the stability and alignment of the couch top.</p> </section> <section> <h3> Results</h3> <p>The difference between the micrometer and measured shifts peaked at 0.08 mm. The continuous measurements agreed with the standard measurements within one standard deviation of the three measurements. The maximum displacements of the couch top were 5.23 and 2.00 mm in the vertical axis, with and without a weight load, respectively. There were differences in the displacement at each measurement point. In the lateral axis, the maximum displacements were 2.05 and 2.09 mm with and without a weight load, respectively. The maximum displacement in the imaging plane was observed at approximately half the distance traveled by the couch top. As the couch top traveled, the horizontal angle in the imaging
{"title":"High-accuracy quality control method of CT system couch tops for treatment planning via an advanced 3D coordinate measuring machine","authors":"Ryuichi Yada, Masataka Sakamoto, Naoya Kurino, Yusuke Ueshima, Tianyuan Wang, Iori Sumida, Katsumasa Nakamura","doi":"10.1002/acm2.70409","DOIUrl":"10.1002/acm2.70409","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Quality control (QC) methods for computed tomography (CT) systems used in treatment planning have not been updated since the release of the Task Group (TG) 66 report by the American Association of Physicists in Medicine (AAPM) in 2003. Conventional QC methods for CT systems fail to fulfill the requirements of high-precision radiation therapy. Moreover, because the geometric accuracy of CT systems can affect the accuracy of radiation therapy, which is particularly critical in high-precision radiation therapy, a highly accurate QC method is required.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aimed to develop a high-accuracy QC method for CT system couch tops suitable for high-precision radiation therapy by utilizing a wide-area three-dimensional (3D) coordinate measuring machine (3D-CMM), a type of laser tracker.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We used a 3D-CMM, which includes a wireless probe and a camera unit, focusing on a SOMATOM go.Open Pro CT system. The system was set up in accordance with the reference method outlined in the AAPM TG66 report guidelines. The initial phase verified the accuracy of 3D-CMM measurement within a CT room using a micrometer. Subsequently, a novel continuous measurement method was developed to enable the real-time tracking of the couch-top displacement during travel. This new method was evaluated against the standard manual measurement method. Measurements were performed at 0.1 s intervals at various index positions on the couch top, with and without added weight to simulate the presence of a patient. The gathered data were analyzed to assess the couch-top displacement, horizontality and orthogonality relative to the imaging plane, providing a comprehensive evaluation of the stability and alignment of the couch top.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The difference between the micrometer and measured shifts peaked at 0.08 mm. The continuous measurements agreed with the standard measurements within one standard deviation of the three measurements. The maximum displacements of the couch top were 5.23 and 2.00 mm in the vertical axis, with and without a weight load, respectively. There were differences in the displacement at each measurement point. In the lateral axis, the maximum displacements were 2.05 and 2.09 mm with and without a weight load, respectively. The maximum displacement in the imaging plane was observed at approximately half the distance traveled by the couch top. As the couch top traveled, the horizontal angle in the imaging ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70409","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723208","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}
Christopher Busch, Ping Xia, Chirag Shah, Rahul Tendulkar, Young-Bin Cho
Objectives/Purposes
Whole breast 3D treatment planning with tangential fields often requires multiple manual adjustments, leading to inefficiency and variability. This study presents and evaluates an in-house developed automated script designed to improve planning efficiency and consistency for breast radiotherapy using tangential fields.
Materials/Methods
19 breast cancer patients from an IRB-approved study were selected. The automated script was developed to generate beam segments through a three-step process, (1) verification of field setup, and generation of breast planning target volume (PTV), (2) duplication of the clinical plan with open tangents and (3) automatic generation of beam segments to reduce hotspot iteratively. Plans produced by the automated script (AS) were compared to the manually optimized (MO) clinical plans using eight evaluation metrics: V16Gy of the ipsilateral lung, mean heart dose, V90%, V95% (dose coverage), V105% (hotspot) of PTV, number of segments, MU (monitor unit) weighted segment area, and total MUs. A statistical analysis was performed using the Wilcoxon signed-rank test.
Results
Four of the eight metrics showed statistical differences. For MO and AS plans, the average ± SD of ipsilateral lung 16 Gy was 15.05% ± 3.27% vs. 15.10% ± 3.26% (p = 0.04) while the mean heart dose was 0.87 Gy ± 0.52 Gy, vs. 0.87 Gy ± 0.53 Gy (p = 0.68). With regards to homogeneity and coverage, the PTV V105% were 2.0% ± 5.0% and 3.7% ± 6.4% (p = 0.03) while the PTV V90% were 98.8% ± 1.5% and 99.1% ± 0.9% (p = 0.14), V95% were 92.0% ± 4.4% and 92.4% ± 3.2% (p = 0.63) respectively. The number of segments and MU weighted segment areas were 7.3 ± 1.3 and 10.9 ± 1.9 (p < 0.001); 268.2 ± 96.6 cm2 and 262.6 ± 92.9 cm2 (p < 0.001). The total MUs was 351.7 ± 99.0 and 354.7 ± 101.2 (p = 0.05).
Conclusion
The automated script successfully generated high-quality tangential breast plans that met all clinical constraints. It significantly improved consistency while maintaining clinical acceptability, demonstrating potential for broader use in automated 3D planning.
{"title":"Development of automated whole breast 3D planning with tangential fields","authors":"Christopher Busch, Ping Xia, Chirag Shah, Rahul Tendulkar, Young-Bin Cho","doi":"10.1002/acm2.70415","DOIUrl":"10.1002/acm2.70415","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives/Purposes</h3>\u0000 \u0000 <p>Whole breast 3D treatment planning with tangential fields often requires multiple manual adjustments, leading to inefficiency and variability. This study presents and evaluates an in-house developed automated script designed to improve planning efficiency and consistency for breast radiotherapy using tangential fields.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials/Methods</h3>\u0000 \u0000 <p>19 breast cancer patients from an IRB-approved study were selected. The automated script was developed to generate beam segments through a three-step process, (1) verification of field setup, and generation of breast planning target volume (PTV), (2) duplication of the clinical plan with open tangents and (3) automatic generation of beam segments to reduce hotspot iteratively. Plans produced by the automated script (AS) were compared to the manually optimized (MO) clinical plans using eight evaluation metrics: V16Gy of the ipsilateral lung, mean heart dose, V90%, V95% (dose coverage), V105% (hotspot) of PTV, number of segments, MU (monitor unit) weighted segment area, and total MUs. A statistical analysis was performed using the Wilcoxon signed-rank test.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Four of the eight metrics showed statistical differences. For MO and AS plans, the average ± SD of ipsilateral lung 16 Gy was 15.05% ± 3.27% vs. 15.10% ± 3.26% (<i>p</i> = 0.04) while the mean heart dose was 0.87 Gy ± 0.52 Gy, vs. 0.87 Gy ± 0.53 Gy (<i>p</i> = 0.68). With regards to homogeneity and coverage, the PTV V105% were 2.0% ± 5.0% and 3.7% ± 6.4% (<i>p</i> = 0.03) while the PTV V90% were 98.8% ± 1.5% and 99.1% ± 0.9% (<i>p</i> = 0.14), V95% were 92.0% ± 4.4% and 92.4% ± 3.2% (<i>p</i> = 0.63) respectively. The number of segments and MU weighted segment areas were 7.3 ± 1.3 and 10.9 ± 1.9 (<i>p</i> < 0.001); 268.2 ± 96.6 cm<sup>2</sup> and 262.6 ± 92.9 cm<sup>2</sup> (<i>p</i> < 0.001). The total MUs was 351.7 ± 99.0 and 354.7 ± 101.2 (<i>p</i> = 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The automated script successfully generated high-quality tangential breast plans that met all clinical constraints. It significantly improved consistency while maintaining clinical acceptability, demonstrating potential for broader use in automated 3D planning.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70415","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145722240","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}
Juan Manuel Molina-Maza, David Viar-Hernandez, Blanca Rodriguez-Gonzalez, Javier Sequeiro-Gonzalez, Juan Antonio Vera-Sanchez, Alejandro Mazal, Norberto Malpica, Angel Torrado-Carvajal, Juan Maria Perez-Moreno, Borja Rodriguez-Vila
Background
Proton therapy (PT) is recognized as a superior treatment for head cancer (HC) due to its precision and minimal damage to surrounding healthy tissues, relying on computed tomography (CT) data for dose calculations. Adaptive proton therapy (APT) is crucial to address changes in patient anatomy during treatment and update dose accuracy. However, in-room cone-beam CT (CBCT) assistance is limited to assessing patient setup, with occasional constraints due to artifacts and/or lower image quality and resolution compared to a CT scan.
Purpose
Although deep learning (DL) techniques can successfully convert a CBCT into a synthetic CT (sCT), soft tissue delineation remains a challenging task. We hypothesized that, by including Magnetic Resonance Image (MRI) in CBCT-based CT synthesis, the sCT generation could more closely approximate the CT ground truth while improving tissue definition and dose calculation in PT treatment planning.
Methods
We propose a Pix2Pix-conditional generative adversarial network (cGAN) to synthesize a CT scan by combining two different input images: CBCT and T1-weighted MRI. ResUnet and SwinUnet were evaluated as the cGAN generator. Additionally, a CBCT-only-based CycleGAN was tested.
Results
Model performance improved with the inclusion of MRI data, especially in recovering soft tissue details like eyes and ventricles, with ResUnet models outperforming SwinUnet models. Our cGAN outperformed both the self-autoencoder approaches and the CycleGAN model. Pix2Pix-ResUnet (MR-based) significantly reduced average HU errors in volumes of interest and also enhanced the precision in dose values, as demonstrated in dose differences and profiles.
Conclusions
We demonstrated the promising contribution of MRI to CBCT-based CT synthesis, enhancing sCT image quality and dose calculation accuracy. Future efforts should aim to collect a larger dataset and validate the integration of MRI in APT.
{"title":"Enhancing CBCT-based CT synthesis using planning MRI in adaptive proton therapy for head cancer: A deep learning approach","authors":"Juan Manuel Molina-Maza, David Viar-Hernandez, Blanca Rodriguez-Gonzalez, Javier Sequeiro-Gonzalez, Juan Antonio Vera-Sanchez, Alejandro Mazal, Norberto Malpica, Angel Torrado-Carvajal, Juan Maria Perez-Moreno, Borja Rodriguez-Vila","doi":"10.1002/acm2.70367","DOIUrl":"10.1002/acm2.70367","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Proton therapy (PT) is recognized as a superior treatment for head cancer (HC) due to its precision and minimal damage to surrounding healthy tissues, relying on computed tomography (CT) data for dose calculations. Adaptive proton therapy (APT) is crucial to address changes in patient anatomy during treatment and update dose accuracy. However, in-room cone-beam CT (CBCT) assistance is limited to assessing patient setup, with occasional constraints due to artifacts and/or lower image quality and resolution compared to a CT scan.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Although deep learning (DL) techniques can successfully convert a CBCT into a synthetic CT (sCT), soft tissue delineation remains a challenging task. We hypothesized that, by including Magnetic Resonance Image (MRI) in CBCT-based CT synthesis, the sCT generation could more closely approximate the CT ground truth while improving tissue definition and dose calculation in PT treatment planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We propose a Pix2Pix-conditional generative adversarial network (cGAN) to synthesize a CT scan by combining two different input images: CBCT and T1-weighted MRI. ResUnet and SwinUnet were evaluated as the cGAN generator. Additionally, a CBCT-only-based CycleGAN was tested.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Model performance improved with the inclusion of MRI data, especially in recovering soft tissue details like eyes and ventricles, with ResUnet models outperforming SwinUnet models. Our cGAN outperformed both the self-autoencoder approaches and the CycleGAN model. Pix2Pix-ResUnet (MR-based) significantly reduced average HU errors in volumes of interest and also enhanced the precision in dose values, as demonstrated in dose differences and profiles.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 <p>We demonstrated the promising contribution of MRI to CBCT-based CT synthesis, enhancing sCT image quality and dose calculation accuracy. Future efforts should aim to collect a larger dataset and validate the integration of MRI in APT.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145722894","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}
Duong Thanh Tai, Luong Tien Phat, Tran Trung Kien, Duong Tuan Linh, Nguyen Ngoc Anh, Nguyen Quang Hung, Peter Sandwall, Parham Alaei, David Bradley, James C. L. Chow
<div> <section> <h3> Purpose</h3> <p>To evaluate the cumulative radiobiological impact of daily megavoltage cone-beam computed tomography (MV-CBCT) imaging dose based on normal tissue complication probability (NTCP) and excess absolute risk (EAR) of secondary malignancies among radiotherapy patients treated for breast, pelvic, and head & neck cancers. This study investigated whether MV-CBCT imaging dose warrants protocol personalization according to patient age, anatomical treatment site, and organ-specific radiosensitivity.</p> </section> <section> <h3> Methods</h3> <p>This retrospective study included cohorts of breast (<i>n</i> = 30), pelvic (<i>n</i> = 17), and head & neck (<i>n</i> = 20) cancer patients undergoing radiotherapy with daily MV-CBCT. Imaging dose distributions employing two common MV-CBCT protocols (5 and 10 MU per fraction) were analyzed. NTCP values were estimated using logistic models, while EAR were calculated using Schneider's organ equivalent dose (OED)-based model, integrating organ-specific dose, patient age, and established tissue-specific risk coefficients. Comparative statistical analyses were conducted using paired <i>t</i>-tests, and results were further stratified by patient age (< 40, 40–60, > 60 years).</p> </section> <section> <h3> Results</h3> <p>In breast cancer patients, NTCP values increased significantly for lung tissue when comparing the 10 MU protocol to the 5 MU one (<i>p</i> < 0.001), while those for heart and breast tissues showed minimal and insignificant differences. EAR estimations revealed substantial risk increases among younger breast cancer patients (< 40 years), with some exceeding 15 cases per 10 000 person-years under the 10 MU protocol. Conversely, pelvic and head & neck cohorts demonstrated consistently low NTCP and EAR values (< 1%), with no meaningful differences observed between the two imaging protocols. Across all cancer sites, younger age consistently correlated with higher secondary cancer risks.</p> </section> <section> <h3> Conclusion</h3> <p>Routine daily MV-CBCT imaging at the 10 MU protocol possesses minimal additional risk in pelvic and head & neck radiotherapy. However, among breast cancer patients, particularly those under 40 years, the 10 MU protocol significantly elevates the theoretical secondary cancer risk estimates and lung NTCP. These findings support transitioning from conventional uniform imaging approach toward personalized MV-CBCT protocols, tailored according to patient age, anatomical site, and organ radiosensitivity. A stratified ima
{"title":"From standard to stratified: Modeling NTCP and EAR to personalize daily MV-CBCT in radiotherapy","authors":"Duong Thanh Tai, Luong Tien Phat, Tran Trung Kien, Duong Tuan Linh, Nguyen Ngoc Anh, Nguyen Quang Hung, Peter Sandwall, Parham Alaei, David Bradley, James C. L. Chow","doi":"10.1002/acm2.70414","DOIUrl":"10.1002/acm2.70414","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To evaluate the cumulative radiobiological impact of daily megavoltage cone-beam computed tomography (MV-CBCT) imaging dose based on normal tissue complication probability (NTCP) and excess absolute risk (EAR) of secondary malignancies among radiotherapy patients treated for breast, pelvic, and head & neck cancers. This study investigated whether MV-CBCT imaging dose warrants protocol personalization according to patient age, anatomical treatment site, and organ-specific radiosensitivity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective study included cohorts of breast (<i>n</i> = 30), pelvic (<i>n</i> = 17), and head & neck (<i>n</i> = 20) cancer patients undergoing radiotherapy with daily MV-CBCT. Imaging dose distributions employing two common MV-CBCT protocols (5 and 10 MU per fraction) were analyzed. NTCP values were estimated using logistic models, while EAR were calculated using Schneider's organ equivalent dose (OED)-based model, integrating organ-specific dose, patient age, and established tissue-specific risk coefficients. Comparative statistical analyses were conducted using paired <i>t</i>-tests, and results were further stratified by patient age (< 40, 40–60, > 60 years).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In breast cancer patients, NTCP values increased significantly for lung tissue when comparing the 10 MU protocol to the 5 MU one (<i>p</i> < 0.001), while those for heart and breast tissues showed minimal and insignificant differences. EAR estimations revealed substantial risk increases among younger breast cancer patients (< 40 years), with some exceeding 15 cases per 10 000 person-years under the 10 MU protocol. Conversely, pelvic and head & neck cohorts demonstrated consistently low NTCP and EAR values (< 1%), with no meaningful differences observed between the two imaging protocols. Across all cancer sites, younger age consistently correlated with higher secondary cancer risks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Routine daily MV-CBCT imaging at the 10 MU protocol possesses minimal additional risk in pelvic and head & neck radiotherapy. However, among breast cancer patients, particularly those under 40 years, the 10 MU protocol significantly elevates the theoretical secondary cancer risk estimates and lung NTCP. These findings support transitioning from conventional uniform imaging approach toward personalized MV-CBCT protocols, tailored according to patient age, anatomical site, and organ radiosensitivity. A stratified ima","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70414","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723014","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}
Colleen Foote, David M McClatchy 3rd, Susu Yan, Sven Olberg, Kyla Remillard, Nathaniel Miles, Jennifer Pursley
Background
Online adaptive radiation therapy (ART) is a relatively new process, and it is recommended that institutions starting an online ART program conduct a risk analysis to identify potential hazards. While Failure Modes and Effects Analysis (FMEA) is common, Systems-Theoretic Process Analysis (STPA) has also been used to evaluate online ART workflows.
Purpose
An STPA hazard analysis was performed for a CT-guided online ART system in a multi-vendor environment. The goal was to identify potential risks and mitigations to guide the development of adaptive workflows and the quality management (QM) program.
Methods
The STPA hazard analysis was performed in four steps. First, process maps for online ART were generated to describe the interactions between users and systems. In the second step, the process maps were refined to a single control structure diagram model. In the third step, potential unsafe control actions (UCAs) were enumerated by the physicists involved in the analysis. Finally, mitigation strategies to address the UCAs were identified.
Results
A total of 496 UCAs were identified for 119 control actions, of which 239 (48.2%) were prioritized for mitigation due to having low or medium levels of detectability. The most frequent causal scenarios were accidental omission (20.1%), rushing (17.2%), and lack of training (15.9%). The most common consequences were delays (26.8%) and having to repeat work (13.5%). The two mitigation strategies considered to address the most causal scenarios were requiring trained adaptive staff (28.9%) and having physics oversight (19.9%).
Conclusions
The STPA led to valuable insights into the potential causes of unsafe control actions and various mitigation strategies that were used to develop the QM program. Notably, most UCAs were attributable to interactions between users and the system, rather than system failures. It is recommended that every institution starting an online ART program perform a risk assessment for their environment.
{"title":"Systems-theoretic process analysis of a CT-guided online adaptive radiation therapy system in a multi-vendor environment","authors":"Colleen Foote, David M McClatchy 3rd, Susu Yan, Sven Olberg, Kyla Remillard, Nathaniel Miles, Jennifer Pursley","doi":"10.1002/acm2.70330","DOIUrl":"10.1002/acm2.70330","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Online adaptive radiation therapy (ART) is a relatively new process, and it is recommended that institutions starting an online ART program conduct a risk analysis to identify potential hazards. While Failure Modes and Effects Analysis (FMEA) is common, Systems-Theoretic Process Analysis (STPA) has also been used to evaluate online ART workflows.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>An STPA hazard analysis was performed for a CT-guided online ART system in a multi-vendor environment. The goal was to identify potential risks and mitigations to guide the development of adaptive workflows and the quality management (QM) program.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The STPA hazard analysis was performed in four steps. First, process maps for online ART were generated to describe the interactions between users and systems. In the second step, the process maps were refined to a single control structure diagram model. In the third step, potential unsafe control actions (UCAs) were enumerated by the physicists involved in the analysis. Finally, mitigation strategies to address the UCAs were identified.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 496 UCAs were identified for 119 control actions, of which 239 (48.2%) were prioritized for mitigation due to having low or medium levels of detectability. The most frequent causal scenarios were accidental omission (20.1%), rushing (17.2%), and lack of training (15.9%). The most common consequences were delays (26.8%) and having to repeat work (13.5%). The two mitigation strategies considered to address the most causal scenarios were requiring trained adaptive staff (28.9%) and having physics oversight (19.9%).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The STPA led to valuable insights into the potential causes of unsafe control actions and various mitigation strategies that were used to develop the QM program. Notably, most UCAs were attributable to interactions between users and the system, rather than system failures. It is recommended that every institution starting an online ART program perform a risk assessment for their environment.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70330","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723363","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}
Ryan Truong, Lance C Moore, Casey Bojechko, Sandra M Meyers, Kelly Kisling, Xenia Ray
Background
Deep-learning models are useful for radiation therapy tasks such as 3D dose prediction, auto-contouring and auto-planning. These models require large training datasets to obtain clinically acceptable results. Currently, the process of exporting DICOM-RT data from the Eclipse treatment planning system (TPS) is often tedious and becomes unscalable when approaching the magnitude of hundreds of patients. Thus, an efficient procedure to obtain this data would be effective for downstream research applications.
Purpose
The purpose of this study was to simplify and improve the efficiency of data retrieval from the Eclipse TPS. To do so, we have created an application which exports patient treatment plans and associated images and structure sets in a parallel, streamlined process.
Methods
The application was made using C# .NET and the Prism library to create a graphical user interface (GUI). EvilDICOM was integrated within the GUI to facilitate the connection to the Eclipse patient database and obtain patient plans. Data export using our application was compared to manual export using the Eclipse Export module; specifically, timing data as a function of the number of Digital Imaging and Communications in Medicine (DICOM) files exported was assessed.
Results
Utilizing the application was faster than manually exporting via the TPS in cases with more than one patient. When attempting to perform an export of 20 patients’ treatment data (∼3 000 DICOM files, including the plan, structure set, dose, and all slices of the CT image), our application took 10.22 min while manual export took 22.93 min. Our application proved to be a linear-time process and scalable to over, but not limited to, 17 000 DICOM files.
Conclusions
We have developed an open-source application to rapidly obtain patient data from Eclipse in a scalable manner. This tool addresses the challenges of manually exporting DICOM files in large magnitudes and increases the feasibility for processes like machine learning model training.
{"title":"Batch Export: An automated framework for curated data extraction via the Eclipse treatment planning system","authors":"Ryan Truong, Lance C Moore, Casey Bojechko, Sandra M Meyers, Kelly Kisling, Xenia Ray","doi":"10.1002/acm2.70413","DOIUrl":"10.1002/acm2.70413","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Deep-learning models are useful for radiation therapy tasks such as 3D dose prediction, auto-contouring and auto-planning. These models require large training datasets to obtain clinically acceptable results. Currently, the process of exporting DICOM-RT data from the Eclipse treatment planning system (TPS) is often tedious and becomes unscalable when approaching the magnitude of hundreds of patients. Thus, an efficient procedure to obtain this data would be effective for downstream research applications.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The purpose of this study was to simplify and improve the efficiency of data retrieval from the Eclipse TPS. To do so, we have created an application which exports patient treatment plans and associated images and structure sets in a parallel, streamlined process.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The application was made using C# .NET and the Prism library to create a graphical user interface (GUI). EvilDICOM was integrated within the GUI to facilitate the connection to the Eclipse patient database and obtain patient plans. Data export using our application was compared to manual export using the Eclipse Export module; specifically, timing data as a function of the number of Digital Imaging and Communications in Medicine (DICOM) files exported was assessed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Utilizing the application was faster than manually exporting via the TPS in cases with more than one patient. When attempting to perform an export of 20 patients’ treatment data (∼3 000 DICOM files, including the plan, structure set, dose, and all slices of the CT image), our application took 10.22 min while manual export took 22.93 min. Our application proved to be a linear-time process and scalable to over, but not limited to, 17 000 DICOM files.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We have developed an open-source application to rapidly obtain patient data from Eclipse in a scalable manner. This tool addresses the challenges of manually exporting DICOM files in large magnitudes and increases the feasibility for processes like machine learning model training.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 12","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70413","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145723494","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号