Journal of Applied Clinical Medical Physics最新文献

{"title":"Investigation on the efficacy of a tissue equivalent material bolus for BNCT","authors":"Akinori Sasaki,&nbsp;Naonori Hu,&nbsp;Ryo Kakino,&nbsp;Mai Nojiri,&nbsp;Keiji Nihei,&nbsp;Teruhito Aihara,&nbsp;Satoshi Takeno,&nbsp;Yuki Yoshino,&nbsp;Hiroki Tanaka,&nbsp;Koji Ono","doi":"10.1002/acm2.70287","DOIUrl":"https://doi.org/10.1002/acm2.70287","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>In radiation therapy, the use of bolus is an effective technique for improving the surface dose. This irradiation technique is also used in BNCT. However, since BNCT uses neutron irradiation, it is important to evaluate both the neutron moderation characteristic and the radioactivation of the bolus.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aimed to evaluate the tissue equivalence and activation of commercially available boluses for use in BNCT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two types of commercially available boluses were evaluated. The boluses were placed on a water phantom and irradiated using the NeuCure BNCT system. Firstly, the tissue equivalency of the boluses was evaluated by comparing the experimentally measured thermal neutron flux and gamma-ray distribution within the phantom, and the results were compared with simulation results. Secondly, the neutron activation of the boluses was assessed using an ionization chamber survey meter and an HP-Ge semiconductor detector to identify the produced radionuclides.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The thermal neutron flux and gamma ray distribution in the water phantom agreed well between the measured and simulated results. The study revealed that both boluses became radioactive after neutron irradiation, primarily due to the production of radionuclides such as ²⁴Na and ³⁸Cl.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>While boluses are effective in improving surface dose in BNCT, their use also introduces the risk of patient exposure to radiation from radioactivated bolus materials. Therefore, careful selection of bolus materials with minimal radioactivation is crucial to ensure patient safety.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70287","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272387","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":"Evaluating the Ethos automated planning system for spatially fractionated radiotherapy","authors":"A Aziz Sait,&nbsp;Yoganathan SA,&nbsp;Amine Khemissi,&nbsp;Umang Patel,&nbsp;Sunil Mani,&nbsp;Satheesh Paloor,&nbsp;Rabih Hammoud","doi":"10.1002/acm2.70306","DOIUrl":"https://doi.org/10.1002/acm2.70306","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Lattice radiotherapy (LRT), a form of spatially fractionated radiation therapy (SFRT), has emerged as a promising approach for treating massive tumors. By delivering high-dose regions within the tumor while sparing surrounding healthy tissue, LRT offers distinct advantages over conventional radiotherapy. Recent advancements in treatment planning systems (TPS), particularly the integration of intelligent optimization engines (IOEs) with automated planning capabilities, have the potential to further refine and expand the clinical utility of LRT. This study aimed to comparatively evaluate the planning quality and clinical feasibility of lattice SFRT treatment plans generated using the Ethos planning system, equipped with an IOE and O-ring linear accelerator, versus the Eclipse planning system paired with a conventional C-arm TrueBeam linac, in patients with stage III non-small cell lung cancer (NSCLC).&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 retrospective stage III NSCLC cases (GTV &gt; 200 cc) with available PET-CT imaging were selected. A total of 40 plans (20 Eclipse, 20 Ethos) were compared, incorporating lattice spheres (1 cm diameter, 2 cm spacing between spheres) placed in the tumor, FDG-PET/CT-informed intratumoral heterogeneity, prioritizing viable perinecrotic subregions while avoiding critical OARs. Plans aimed to deliver 15 Gy to lattice spheres, limit Valley (PTV minus spheres) doses to 2 Gy, and restrict doses to organs at risk (OARs) to ≤ 3 Gy. Dose conformity, OAR sparing, dose gradient parameters (PEDR, PVDR), planning time, and deliverability, which was evaluated using ArcCheck, EPID gamma analysis, and MLC log-file verification.&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;Ethos demonstrated statistically significant improvements compared to Eclipse in lattice sphere mean dose (17.2 Gy vs. 15.83 Gy, &lt;i&gt;p&lt;/i&gt; &lt; 0.001), V15 Gy coverage (98.2 % vs. 91.74 %, &lt;i&gt;p&lt;/i&gt; &lt; 0.001), and dose gradient metrics (PEDR: 6.42 vs. 5.80; PVDR: 3.70 vs. 3.29; both &lt;i&gt;p&lt;/i&gt; &lt; 0.001, and VPDR: 0.131 vs. 0.135; PVDR&lt;sub&gt;DVH&lt;/sub&gt;: 7.62 vs. 7.41). For the valley target, Ethos plans demonstrated a lower mean dose (Dmean: 4.72 Gy vs. 4.91 Gy, &lt;i&gt;p&lt;/i&gt; = 0.064), although not statistically significant, and achieved significantly improved dose gradient at V7.5 Gy (14.5% vs. 16.35%, &lt;i&gt;p&lt;/i&gt; = 0.019), V5Gy (30.77% vs. 34.84%, &lt;i&gt;p&lt;/i&gt; = 0.006), and V2Gy (99.77% vs. 97.79%, &lt;i&gt;p&lt;/i&gt; &lt; 0.001) compared to Eclipse. Ethos achieved significantly better OAR sparing, particularly for the bronchial tree, heart, spinal cord, esophagus, and great vessels (all &lt;i&gt;p&lt;/i&gt; &lt; 0.01). Furthermore, Ethos substantial","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272317","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 radiotherapy planning for volumetric modulated arc therapy in lung cancer","authors":"Johann Brand,&nbsp;Juliane Szkitsak,&nbsp;Bernd-Niklas Axer,&nbsp;Lucas Pieper,&nbsp;Oliver J. Ott,&nbsp;Marlen Haderlein,&nbsp;Florian Putz,&nbsp;Rainer Fietkau,&nbsp;Christoph Bert,&nbsp;Stefan Speer","doi":"10.1002/acm2.70297","DOIUrl":"https://doi.org/10.1002/acm2.70297","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;Volumetric-modulated arc therapy (VMAT) treatment planning balances the need for adequate coverage of the planning target volume (PTV) and the sparing of organs-at-risk (OARs). However, this time-consuming iterative process is influenced by the planner's experience, personal preferences, and the time devoted to create the plan. This often leads to a considerable variability in plan quality.&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;For lung tumors, where PTV size and the relative location between OARs and PTV vary widely, these challenges are particularly pronounced. This work aims to develop an automated treatment planning solution for lung tumors, standardizing the process and ensuring consistent, high-quality plans while significantly reducing the planner's active workload and time investment&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;An automated treatment planning software, named Uniklinikum Erlangen-Automated Treatment Planning (UKER-ATP), developed within the RayStation (RaySearch, Stockholm, Sweden, Version 12A) treatment planning system using its Python interface, was employed to automate the entire planning process. This software combines both scripted and knowledge-based methods; for the latter, overlap-z-histogram (OZH) and overlap volume histogram (OVH) were used to predict dose volume histograms (DVHs). This study included 15 clinical lung cancer patients with manually created VMAT treatment plans as part of their therapy. For each patient, an automated plan (AP) was generated and compared with the manual plan (MP) created by physicists in our institute. Dosimetric parameters and plan quality indices were evaluated. Furthermore, four board-certified physicians conducted a direct comparison of the plans to assess quality.&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 APs achieved comparable coverage of the PTV while demonstrating improved dose conformity and uniformity compared with the MPs. Mean dose and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;V&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;20&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mi&gt;Gy&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;annotation&gt;${V_{20 {rm Gy}}}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; of the total lung were significantly lower in the APs compared with those in the MPs (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70297","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272340","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":"Robust deep learning-based patient-specific quality assurance prediction models for novel dual-layer MLC linac","authors":"Qizhen Zhu,&nbsp;Xiaoyang Zeng,&nbsp;Zhiqun Wang,&nbsp;Heling Zhu,&nbsp;Yongguang Liang,&nbsp;Awais Ahmed,&nbsp;Bo Yang,&nbsp;Jie Qiu","doi":"10.1002/acm2.70286","DOIUrl":"https://doi.org/10.1002/acm2.70286","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study investigates the feasibility of utilizing deep learning models to robustly predict patient-specific quality assurance (PSQA) outcomes in fixed field intensity-modulated radiation therapy (FF-IMRT) plans on the Halcyon linear accelerator equipped with a novel dual-layer multi-leaf collimator (MLC). The study explores the integration of Shuffle Attention (SA) mechanisms and deep imbalance regression techniques to enhance the precision and robustness of deep learning-based PSQA predictions. It ensures relative prediction robustness in the extreme imbalance distribution of gamma passing rate (GPR) values.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data from 214 FF-IMRT treatment plans covering various treatment sites comprising 1394 beam orientations and corresponding Portal Dosimetry verification data were collected. Fluence maps calculated for each beam orientation served as inputs for the ResNet model. First, the SA module was introduced to improve the prediction accuracy of ResNet, resulting in the proposed Att-ResNet model. Furthermore, to ensure prediction robustness in the GPR values with extreme imbalance distribution, we incorporated the Label Distribution Smoothing (LDS) technique, ultimately forming the ALDS-ResNet method.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>ALDS-ResNet exhibited smaller mean absolute error (MAE) values than ResNet across all gamma criteria (1%/1 mm: 2.035 vs. 1.824, 2%/2 mm: 1.416 vs. 1.178, 3%/3 mm: 0.951 vs. 0.787). ALDS-ResNet also demonstrated lower MAE values than ResNet for complex but important plan samples (GPR &lt; 85, 1%/1 mm: 10.163 vs. 4.985, 2%/2 mm: 7.443 vs. 3.272, 3%/3 mm: 5.031 vs. 2.940). Compared to ResNet, ALDS-ResNet achieved higher Pearson correlation coefficient (CC) values at 2%/2 mm and 3%/3 mm gamma criteria, measuring 0.7864 and 0.7852, respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The deep learning model based on ResNet shows promise for predicting GPR values in linacs with dual-layer MLC. Integrating attention mechanisms with deep learning networks enhances the accuracy of PSQA predictions. The LDS technique is attributed to the substantial improvement in failed plan GPR prediction accuracy and robustness. Specifically, the deep learning model tailored for dual-layer MLC linacs can be an auxiliary tool for physicists in identifying PSQA failure plans.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272316","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":"A case study on SSD to SAD linear acceleartor calibration transition","authors":"Sharareh Koufigar,&nbsp;Eric Ford,&nbsp;Yulun He,&nbsp;Soren Olsen,&nbsp;Jessica M. Fagerstrom","doi":"10.1002/acm2.70298","DOIUrl":"https://doi.org/10.1002/acm2.70298","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Modifying calibration conditions of linear accelerators is infrequent and potentially a high-risk procedure. This study outlines a systematic approach used to transition a linear accelerator's calibration condition in an active clinical environment from source-to-surface (SSD) to source-to-axis (SAD), while maintaining treatment accuracy and avoiding interruption of clinical operations.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A satellite clinic within a university radiation oncology service operated an Elekta Versa HD linear accelerator with SSD calibration, while other system C-arm accelerators used SAD. With a single installation of the treatment planning system used across all sites, it was decided to convert the machine to SAD calibration. Representative plans with diverse delivery techniques were comprehensively evaluated in advance. Over a single weekend, beams were recommissioned in the treatment planning system (TPS), and output was adjusted per AAPM's TG-51 protocol. Monitor units (MUs) for on-treatment patients were scaled manually in the oncology information system, MOSAIQ. Quality assurance (QA) checks, as well as independent peer-reviewing of each field, were performed to ensure safety and quality for this high-risk procedure. A retrospective failure modes and effects analysis (FMEA) was subsequently conducted. To evaluate the clinical relevance and broader impact of this work, a targeted survey was conducted via the Wayne State MedPhysUSA LISTSERV.&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;As a result of the change in output calibration condition, field MU required scaling, ranging from 2.7% to 6.4%. Patient-specific QA measurements demonstrated consistent gamma pass rates, and both solid-water phantom and external audit results verified machine output accuracy within 2%. No patient treatments were interrupted during the process. The FMEA identified insufficient expertise and staffing as the highest-risk failure mode. Survey results indicated that 80% of respondents had never personally performed a calibration transition with patients on treatment, and the majority of respondents characterized the procedure as extremely rare and of higher risk than standard TG-51 annual QA.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The absolute output calibration condition was successfully transitioned from SSD to SAD without interruptions of patient treatments. Multiple verification steps were implemented to ensure quality and safety. This project contributed to improved standardization across mu","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272389","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":"Evaluating dosimetric parameters with a plastic scintillator for megavoltage photon beam quality assurance","authors":"Gregory Penoncello,&nbsp;Bernard L. Jones,&nbsp;David A. P. Dunkerley,&nbsp;Adam Mahl,&nbsp;Moyed Miften,&nbsp;Cem Altunbas,&nbsp;C-K Chris Wang,&nbsp;Daniel G. Robertson","doi":"10.1002/acm2.70276","DOIUrl":"https://doi.org/10.1002/acm2.70276","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Linear accelerators require a large amount of data to be collected daily, monthly and annually to verify safe deliveries for patients. Different detectors have been utilized to improve the simplicity, efficiency and accuracy of the various experimental setups required to collect the necessary data resulting in reduced data collection and evaluation time. Plastic scintillators are stable and energy independent radiation detectors with high spatial resolution that emit light proportional to the amount of radiation incident on them. With an appropriate photodetector and technique to measure and analyze the light that is emitted, scintillators can be utilized to measure dosimetric parameters necessary for various monthly quality assurance requirements.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A uniform cylindrical plastic scintillator imaged by a complementary metal oxide semiconductor (CMOS) camera is designed to act as a radiation detector to measure 2D projections of linear accelerator beams. Beams were delivered to the detector to evaluate machine quality assurance (QA) parameters, including beam energy, output, profile consistency and reproducibility as described by TG-198. These measurements were compared to calculations from the Eclipse treatment planning system (TPS). Typical monthly quality assurance (QA) beams were delivered and 2D projections of the scintillation light were measured to validate the accuracy and reproducibility of this detector system for monthly QA.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The plastic scintillator was able to accurately characterize the radiation beam. Energy and profile measurements were reproducible and within 2%/2mm of calculations in the TPS. Output measurements had maximum variations of up to 1.3% and average differences of 0.5%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A simple cylindrical plastic scintillator and CMOS camera radiation detector setup was designed and tested for measuring monthly QA dosimetric parameters specified by TG-198 with accurate and reproducible output, energy and profiles measurements. This method reduces the number of measurements required, allowing multiple parameters to be evaluated in a single beam delivery.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70276","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272407","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":"Performance evaluation and quantitative comparison of two 4DCT imaging respiratory systems using deformable image registration","authors":"Ali Al-Zein,&nbsp;Rawan H. Naim,&nbsp;Wassim Jalbout,&nbsp;Bilal H. Shahine","doi":"10.1002/acm2.70279","DOIUrl":"https://doi.org/10.1002/acm2.70279","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Improved accuracy in 4DCT imaging and precise targeting of tumors contribute to more effective and targeted radiation therapy. This study focuses on evaluating the accuracy of utilizing the GateCT (VisionRT Ltd, London, United Kingdom) in comparison with a pressure sensor system (ANZAI Medical Co., Ltd., Shinagawa, Tokyo) to provide 4DCT with respiratory information.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A dynamic breathing phantom enclosing three spheres (A, P, and R) of different densities was enrolled to produce breathing patterns tracked by the two systems. Image sets for three breathing phases obtained based on GateCT and ANZAI systems were analyzed using deformable registration by deforming the three-phase image sets with the static image sets. Our deformable registration approach revealed how far different phase image sets were from the quantified by various metrics, such as dice similarity coefficient (DSC), mean surface distance (MSD), absolute volume estimation, mean Jacobian, and Warp.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Results indicated DSC values greater than 0.90 across all phases and spheres for both respiratory systems, with mean DSC values for spheres A, P, and R of 0.980 versus 0.977, 0.977 versus 0.976, and 0.977 versus 0.976 for GateCT and ANZAI systems, respectively. MSDs for both systems were consistently less than 2 mm across all spheres and phases. Furthermore, the mean volume estimation error for both systems, relative to the static, exhibited statistical insignificance (<i>p</i> &gt; 0.05). Friedman test revealed significant differences in median Jacobian, and median Warping between the two systems (<i>p</i> &lt; 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In addition to the effectiveness of deformable image registration in the quantification of respiratory system performance, both systems exhibited comparable performance in providing 4DCT with respiratory information.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70279","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272511","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":"Impact of extended source-to-surface distances and respiratory motion on the precision of electron beam therapy","authors":"Takaaki Ito,&nbsp;Hiroyuki Kosaka,&nbsp;Yuya Yanagi,&nbsp;Yusuke Sakai,&nbsp;Hajime Monzen","doi":"10.1002/acm2.70301","DOIUrl":"https://doi.org/10.1002/acm2.70301","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>In electron beam therapy targeting superficial thoracic and abdominal lesions, the source-to-surface distance (SSD) varies due to patient respiration. This study aimed to investigate the percentage depth dose (PDD) and off-center ratio (OCR) of 6, 9, and 12 MeV electron beams at extended SSDs; and to assess the variations in dose caused by respiratory motion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>PDDs and OCRs for 6, 9, and 12 MeV electron beams were measured using a Blue Phantom 2 with 5 cm circular aperture and 10 × 10 cm² fields at SSDs ranging from 98 to 105 cm. The dose differences at the maximum depth (<i>d</i>_max) were calculated relative to an SSD of 100 cm. We simulated patient respiratory motion of 0–4 cm during irradiation with 5 cm circular aperture and 10 × 10 cm² fields by placing a water-equivalent phantom with a parallel-plate ionization chamber on a QUASAR Platform. The gantry angle was set to 270°, and the SSD was set to 100 cm. The dose differences at <i>d</i>_max were calculated relative to a motion amplitude of 0 cm.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Extending the SSD by 3 cm reduced the dose by &gt; 5% for all energies. For a 6 MeV electron beam with a 5 cm circular aperture, extending the SSD to 105 cm resulted in a dose reduction of 13.42% and expansions of the field size by 2.0 mm and the penumbra by 4.2 mm. A respiratory motion amplitude of 3 cm resulted in dose variations of &gt; 3% for all energies and field sizes. The largest dose difference of 5.36% was observed for a 6 MeV electron beam with a 5 cm circular aperture.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The results demonstrate that extending the SSD by 3 cm reduced the dose by &gt;5% for all energies, providing a useful quantitative benchmark for quality assurance in superficial electron therapy. Respiratory motion management may be warranted for electron beam therapy when respiratory-induced SSD variations exceed 3 cm.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70301","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272388","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":"Comparison of two dosimetric systems for quality assurance in a clinical treatment scenario for brain radiotherapy: Diode array and polymer gel dosimetry","authors":"Angeliki Ntouli,&nbsp;Georgios Kalaitzakis,&nbsp;John Stratakis,&nbsp;Kostas Perisinakis,&nbsp;Stefanos Kachris,&nbsp;Maria Tolia,&nbsp;Michalis Mazonakis,&nbsp;Thomas G. Maris","doi":"10.1002/acm2.70272","DOIUrl":"https://doi.org/10.1002/acm2.70272","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Advanced radiotherapy techniques such as single-isocenter volumetric modulated arc therapy (VMAT) and simultaneous integrated boost (SIB-VMAT) require precise quality assurance (QA) due to their complexity and sensitivity to geometric and dosimetric uncertainties, especially for multi-target configurations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To evaluate and compare two dosimetric systems—a diode array and a polymer gel dosimeter—for quality assurance in single-isocenter multi-target VMAT and SIB-VMAT plans through 3D gamma index and statistical agreement analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A diode array system (Delta⁴—Scandidos, Uppsala, Sweden) and a 3D printed phantom (Prime—RTsafe, Athens, Greece) embedded with in-house polymer gel were utilized. The treatment plans for VMAT and SIB-VMAT were created using the Monaco treatment planning system (TPS) and irradiations were performed with the Elekta Infinity linear accelerator with a 6-MV photon beam on both Prime and Delta⁴. Analyses of the irradiated gels were performed using a 1.5T clinical MRI system. Additionally, 3D gamma indexes and Bland-Altman analyses were conducted to evaluate the agreement between relative doses from MRI-derived gel data and diode array's detector measurements.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Diode array system achieved gamma passing rates (GPRs) &gt;99%, while polymer gel showed &gt;95% GPR for both irradiation plans. Bland–Altman analysis indicated minimal bias (mean difference: 0.1%) and narrow limits of agreement (−1.9% to 2.2%), confirming good consistency between the two dosimetric methods for both plans delivered.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Acceptable agreement between the two systems was observed. Both demonstrated complementary capabilities, making both essential tools for ensuring precision in advanced radiotherapy techniques. The polymer gel system offers more detailed insights compared to the diode array method, showing increased sensitivity in challenging cases that involve small targets at greater distances from the isocenter.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145272263","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":"A computer-aided diagnosis (CAD) system based on convolutional neural networks for lung cancer diagnosis from 2D [18F]- PET/CT images","authors":"Mohammad Karimpour,&nbsp;Neda Taghinezhad,&nbsp;Alireza Mehdizadeh,&nbsp;Mehrosadat Alavi,&nbsp;Tahereh Mahmoudi","doi":"10.1002/acm2.70285","DOIUrl":"10.1002/acm2.70285","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>This study aims to automatically classify lung conditions into normal, non-small cell lung cancer (NSCLC), and small cell lung cancer (SCLC) using [¹⁸F] FDG PET/CT images and deep learning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>PET/CT scans from 146 patients (1974 scans) were retrospectively analyzed using two strategies: (1) transfer learning with pre-trained CNNs, and (2) a custom CNN (Res-SE Net) incorporating residual and squeeze-and-excitation (SE) modules. A patient-based data splitting approach was used to avoid data leakage. Models were trained and validated at the scan level and evaluated at the patient level using majority voting. Grad-CAM was employed to generate lesion-localization heatmaps.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among the seven evaluated CNN models, the proposed Res-SE Net demonstrated superior performance, achieving an accuracy of 91.67% and a sensitivity of 92.00% in detecting NSCLC, and an accuracy of 90.14% with a sensitivity of 90.00% for distinguishing SCLC cases. When tested on an external dataset, the model attained an accuracy of 98.00% in binary classification (Normal vs. Cancer). In the three-class classification task, the model achieved an accuracy of 73.02% for NSCLC and 66.26% for SCLC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>These findings demonstrate the potential of Res-SE Net architecture for accurate multi-class lung cancer classification using [18F] FDG PET/CT images.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"26 10","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://aapm.onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145251154","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}