Journal of Applied Clinical Medical Physics最新文献

{"title":"Diagnostic image quality of shoulder magnetic resonance imaging at 0.55T in healthy subjects and patients with rotator cuff injury: Prospective comparison with 1.5T","authors":"Jing Liu,&nbsp;Yue Gao,&nbsp;Ge Gao,&nbsp;Wei Li,&nbsp;Xiang Wang,&nbsp;Jinxia Zhu,&nbsp;Xiaoming Liu,&nbsp;Xiaoye Wang,&nbsp;Kun Zhou,&nbsp;Heng Liu,&nbsp;Jianxing Qiu","doi":"10.1002/acm2.70825","DOIUrl":"https://doi.org/10.1002/acm2.70825","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Lower‑field 0.55 T MRI scanners with large‑bore design could offer patients more comfortable feeling and flexible position. With the advances in deep‑learning reconstruction and hardware optimization, 0.55T have greatly improved their image quality and cost‑effectiveness for musculoskeletal applications. However, its feasibility for shoulder evaluation remains unstudied.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To evaluate the image quality of shoulder using 0.55T MRI in volunteers and patients with rotator cuff injury with comparison of conventional 1.5T.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Fifty participants (25 volunteers, 25 patients) were prospectively enrolled. All participants underwent shoulder MRI both at open 0.55T with contour coils and deep learning (DL) and 1.5T MR without DL. The nonparametric method was utilized to compare image quality scores and quantitative metrics (signal-to-noise ratio (SNR) and contrast-to-noise ratio (|CNR|)). Arthroscopy have been conducted in 16 patients. Kappa statistics was used to assess interobserver and interstudy agreement for lesion evaluation. Comfort feeling was also compared.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The scan time was 11′25″ for 0.55T MRI and 11′42″ for 1.5T MRI. The interobserver analyses showed high consistency (κ = 0.771–1.000, <i>P: 0.008 ∼ </i>&lt; 0.001) among 3 readers. The scores for coronal fat suppressed T2 weighted imaging (fsT2WI) and coronal T1 weighted imaging (T1WI) were significantly higher for 0.55T MRI. Most sequences at 0.55T demonstrated significantly higher SNRs (<i>P:0.04 ∼ </i>&lt; 0.001). Additionally, |CNR| values for lesions were significantly higher in fs proton weighted imaging (PDWI) and fsT2WI at 0.55T. Perfect interstudy agreement between 0.55T and 1.5T was observed between 2 readers (Kappa = 1, <i>P </i>&lt; 0.001) for lesion assessment. Agreement between MRI findings and arthroscopic results was perfect or good. The 0.55T system received higher scores in comfort ratings.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The 0.55T MRI with DL, showed comparable or better image quality in healthy subjects and patients with rotator cuff injury to 1.5T MRI without DL.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70825","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222811","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":"Filament deposition modeling quality assurance testing for the medical physicist","authors":"Benjamin T. Heggie,&nbsp;Manuel Arreola,&nbsp;Stephanie M. Leon,&nbsp;Izabella L. Barreto","doi":"10.1002/acm2.70856","DOIUrl":"https://doi.org/10.1002/acm2.70856","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Filament deposition modeling (FDM) can be a practical method for producing quality control (QC) imaging resources for the clinic. However, frequent printing may degrade print quality over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To develop a process to ensure prints for the diagnostic physicist are accurate and reproducible.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Four FDM systems were evaluated by printing a custom, novel QC model on each printer 12 times over a period of 12 months. Several tests were performed, including print resolvability (lp/cm), XYZ dimension accuracy (mm), density (g/cm3), line width (mm), XY position accuracy (mm), clearance fits (mm), and thickness uniformity (mm). Polylactic acid (PLA) samples were printed, measured, and imaged with a dual energy CT scanner. Linear regression models were then created to monitor changes in QC density measurements as a function of x-ray and material property characteristics (i.e., Hounsfield units and electron density). Between monthly prints, heat uniformity across the build plate was also tested for each printer using a NIST-certified infrared thermometer and 3D printed grids. All physical measurements were obtained using a calibrated digital caliper and milligram scale.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Mean percent error (MPE) for all tests was calculated from ground truth (CAD dimensions and filament density) and baseline values (first month of QC measurements). Among printers investigated, MPE was ± 5% of ground truth for all tests except density and thickness uniformity. Baseline MPE was also observed within ± 5% except for resolvability and clearance fit tests among printers. Subtle trend increases were presented for higher density QC prints based on DECT linear regression models. Reduced chi-squared values indicate uniform and reproducible heat bed temperature measurements.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This work offers an innovative approach toward evaluating and monitoring FDM system performance. Future work should track performance over a longer time period and across a wider variety of printers.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70856","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222809","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":"Dynamic Proton arc therapy for paediatric parameningeal rhabdomyosarcoma","authors":"Andreas Havsgård Handeland,&nbsp;Hardev Singh Grewal,&nbsp;Camilla Grindeland Boer,&nbsp;Daniel J. Indelicato,&nbsp;Kristian Smeland Ytre-Hauge,&nbsp;Helge Henjum,&nbsp;Camilla Hanquist Stokkevåg","doi":"10.1002/acm2.70867","DOIUrl":"https://doi.org/10.1002/acm2.70867","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Parameningeal rhabdomyosarcomas (PM-RMS) are pediatric tumors with a high risk of local failure and severe toxicity. Intensity modulated proton therapy (IMPT) offers improved healthy tissue sparing compared to conventional photon-based radiotherapy, and proton arc therapy (PAT) might offer further improvement in healthy tissue sparing for these patients, thus emphasizing the need for systematic studies specifically focusing on PM-RMS patients. Additionally, the relative biological effectiveness (RBE) of protons is known to vary with linear energy transfer (LET).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The aim of this study was to investigate the potential of LET-optimized PAT for PM-RMS treatment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Volumetric modulated arc therapy (VMAT) plans, IMPT and PAT plans, both with and without LET optimization were made for 13 PM-RMS patients using Raystation version 2023B. The plans were evaluated based on the achievement of clinical goals, homogeneity index, delivery time, robustness, LET and variable RBE-weighted dose within the target and selected OARs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>LET optimization increased the mean LET in the target from 2.5 keV/µm [2.1, 2.8] to 3.4 keV/µm [2.7, 4.1] for IMPT and from 2.8 keV/µm [2.5, 3.1] to 3.4 keV/µm [2.7, 4.0] for PAT with minor changes in dose distributions. Target coverage and OAR doses were comparable between IMPT and PAT, while both had an expected improvement in OAR sparing compared to VMAT. Delivery times were 134.5 [95.3, 203.7] seconds for the IMPT plans and 197.4 [138.9, 244.6] seconds for the PAT plans before LET optimization, and were for both modalities reduced by around 2–5 seconds after LET optimization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The dose distribution was similar across PAT and IMPT in this study, and superior compared to VMAT. LET optimization in the proton plans achieved LET improvements in both target and OARs without compromising dose.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70867","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222756","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":"Uncertainty-suppressed long-tailed learning with lightweight feature adaptation for multi-label chest X-ray classification","authors":"Lu Li","doi":"10.1002/acm2.70873","DOIUrl":"https://doi.org/10.1002/acm2.70873","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;Report-mined chest radiograph datasets commonly contain both long-tailed label distributions and uncertain annotations. Conventional frequency-based re-weighting can strengthen rare-label learning, but it may also amplify unreliable supervision when uncertain labels occur in minority classes.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To develop and evaluate an uncertainty-suppressed long-tailed learning method with lightweight feature adaptation for multi-label chest X-ray (CXR) classification under imbalanced and uncertain report-derived supervision.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The proposed uncertainty-suppressed long-tailed feature adaptation (USLFA) method combines a lightweight label-adaptive feature head with an uncertainty-suppressed long-tailed loss. The primary analysis used a patient-level 70%/10%/20% split of CheXpert for 14 observation labels. Robustness was further examined across two additional patient-level partitions, on the recommended MIMIC-CXR-JPG test split without retraining, and on the official radiologist-annotated CheXpert test set. Performance was assessed using macro-AUROC, macro-AUPRC, macro F1, frequency-group analysis, ablation studies, and uncertainty-handling comparisons. Ninety-five percent confidence intervals (CIs) were estimated by patient-level bootstrap resampling, and formal pairwise tests in the primary CheXpert analysis used paired permutation testing with Holm correction.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;On the primary CheXpert split, USLFA achieved a macro-AUROC of 0.864 (95% CI, 0.856–0.871), macro-AUPRC of 0.547 (95% CI, 0.532–0.560), and macro F1 of 0.501 (95% CI, 0.487–0.514). Compared with ConvNeXt-Tiny using binary cross-entropy (BCE), the gains in macro-AUPRC and macro F1 were both 0.051 and remained significant after Holm correction (both &lt;i&gt;p &lt;&lt;/i&gt; 0.001). Compared with label-distribution-aware margin (LDAM), USLFA improved macro-AUPRC by 0.018 (Holm-adjusted &lt;i&gt;p =&lt;/i&gt; 0.024) and macro F1 by 0.017 (Holm-adjusted &lt;i&gt;p =&lt;/i&gt; 0.041). The ordering was preserved across three patient-level partitions, with USLFA macro-AUPRC ranging from 0.540 to 0.555. On MIMIC-CXR-JPG, USLFA achieved a macro-AUPRC of 0.485 (95% CI, 0.467–0.502), and on the official CheXpert test set it achieved a mean AUROC of 0.920 (95% CI, 0.908–0.931) across the five competition observations.&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;USLFA improved ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70873","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222805","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":"Vision and implementation for the first U.S. carbon ion therapy center part II: Design philosophy and clinical implementation","authors":"Xiaoying Liang,&nbsp;Chris J Beltran","doi":"10.1002/acm2.70866","DOIUrl":"https://doi.org/10.1002/acm2.70866","url":null,"abstract":"<p>The anticipated clinical demand for carbon ion radiotherapy (CIRT) in the United States is expected to include a substantial proportion of clinically complex disease sites that require accurate, highly conformal, and adaptive treatment. These clinical needs, together with the unique physical and biological characteristics of carbon ion beams, form the foundation of the design philosophy for the Mayo Clinic Florida (MCF) CIRT program. The program remains under active development, with clinical deployment planned for 2028. Building upon the clinical rationale and anticipated U.S. patient population discussed in Part I of this two-part review, this Vision Article describes how MCF intends to develop an integrated CIRT treatment system. The program is guided by two overarching principles: fast, accurate, and safe beam delivery and accurate treatment planning and treatment delivery, supported by an integrated patient-specific quality assurance framework. Key elements include high-dose-rate dose-driven continuous scanning with advanced beam monitoring and irradiation control, delivery-aware treatment planning, the Monte Carlo-based BioPhys computational platform integrating physical and biological dose modeling, a hierarchical adaptive workflow, and patient-specific quality assurance spanning pretreatment, on-treatment, and post-treatment verification. This framework provides a technical roadmap for the integrated clinical implementation of CIRT at MCF.</p>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70866","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222757","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":"Image quality robustness of HyperSight-enabled versus conventional iterative cone-beam CT across patient size and imaging geometry","authors":"Nicholas Nelson,&nbsp;Sorour Hosseini,&nbsp;Geoff Nelson,&nbsp;Thomas Martin,&nbsp;Bradley Nordin,&nbsp;Jessica Huang,&nbsp;Hui Zhao","doi":"10.1002/acm2.70874","DOIUrl":"https://doi.org/10.1002/acm2.70874","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Recent advances in cone-beam computed tomography (CBCT) have led to the development of next-generation CBCT systems with enhanced image quality and quantitative imaging capabilities. These advances are particularly relevant in the context adaptive radiation therapy, where improved soft tissue visualization and Hounsfield unit (HU) stability are increasingly important for target localization and CBCT-based dose calculation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To determine how image quality and HU stability change with increasing phantom size, non-cylindrical geometries, and exposure level, and compare the robustness of Acuros-based HyperSight-enabled iterative CBCT (HS-iCBCT) and conventional iterative CBCT on a TrueBeam (TB-iCBCT) under these conditions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The CatPhan® 604 phantom, combined with custom annular extensions, was used to simulate increasing patient size and non-cylindrical imaging geometries. Three configurations (no annulus, small annulus, and large annulus) were imaged across a range of exposure levels (mAs) using HS-iCBCT and TB-iCBCT. Image evaluation metrics included noise, contrast-to-noise ratio (CNR), low-contrast visibility (LCV), image uniformity, spatial resolution, and Hounsfield unit (HU) constancy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>For the no-annulus configuration, image quality was comparable between systems, with slightly lower noise observed for TB-iCBCT. With increasing phantom size through the added annuli, TB-iCBCT exhibited substantial degradation in noise, contrast, and uniformity, whereas HS-iCBCT maintained more consistent performance. Spatial resolution was primarily dependent on field of view and was similar between systems, with smaller fields of view provided improved spatial resolution. HU constancy degraded with increasing phantom size and material density for both systems but remained substantially more stable for HS-iCBCT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>HS-iCBCT demonstrated improved robustness to patient size and imaging geometry, providing superior image quality and HU stability compared to TB-iCBCT. These improvements may support potential lower-dose imaging and more reliable performance in larger patients and non-cylindrical imaging geometries commonly encountered in clinical radiotherapy.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70874","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222755","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":"Proton arc therapy reduces the dose delivered to circulating blood compared to intensity-modulated proton therapy for head-and-neck cancer","authors":"Sebastian Tattenberg,&nbsp;Peilin Liu,&nbsp;Xiaoda Cong,&nbsp;Cornelia Hoehr,&nbsp;Xuanfeng Ding","doi":"10.1002/acm2.70864","DOIUrl":"https://doi.org/10.1002/acm2.70864","url":null,"abstract":"<div>\u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Compared to intensity-modulated proton therapy (IMPT), proton arc therapy (PAT) has various dosimetric advantages. However, questions have been raised over whether the larger low-dose bath during PAT may increase radiation-induced lymphocyte killing, which is correlated with adverse clinical outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>The purpose of this study is to quantitatively compare radiation dose delivery to circulating blood during IMPT and PAT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>For each of 10 head-and-neck cancer patients, one IMPT and one PAT treatment plan were created, and the hematological dose (HEDOS) blood dose model was used to simulate radiation dose delivery to circulating blood. HEDOS simulations utilized gantry angle-wise dose distributions (including for PAT) and considered gantry rotation and energy layer switching as well as irradiation times. Blood dose histograms as well as the mean dose to all simulation blood particles (D_mean) and the dose delivered to the 90% and 10% of blood particles receiving the highest dose (D_90% and D_10%) were then compared between IMPT and PAT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>For IMPT, blood dose metrics (in the form of mean over all patients ± one standard deviation) were (0.522 ± 0.204)Gy(RBE) for D_90%, (0.563 ± 0.212)Gy(RBE) for D_mean, and (0.605 ± 0.219)Gy(RBE) for D_10%. For PAT, D_90% was (0.430 ± 0.184)Gy(RBE), D_mean was (0.483 ± 0.195)Gy(RBE), and D_10% was (0.538 ± 0.207)Gy(RBE). The Wilcoxon signed-rank test indicated statistically significant (<i>p &lt;</i> 0.05) differences between blood dose metrics of IMPT and PAT for all patients, and IMPT did not increase the percentage of blood particles which received no radiation dose during the delivery of a single treatment fraction.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Compared to IMPT, proton arc therapy was associated with significantly lower radiation dose delivery to circulating blood across a variety of different metrics. Proton arc therapy for head-and-neck cancer is therefore not expected to result in higher radiation-induced killing of circulating lymphocytes compared to IMPT.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70864","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222806","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":"Dynamic control of carbon-ion radiation dose distribution amid respiratory motion challenges: A review of prediction research using geant4 and deep learning physics-constrained models","authors":"Jianhua Ding,&nbsp;Peng Li,&nbsp;Chai Hong Yeong","doi":"10.1002/acm2.70766","DOIUrl":"https://doi.org/10.1002/acm2.70766","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Carbon ion radiotherapy (CIRT) offers superior dose conformity and biological effectiveness; however, its precision is highly sensitive to respiratory motion, leading to dose uncertainty and interplay effects that compromise treatment accuracy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A comprehensive literature synthesis was conducted on studies employing motion-resolved imaging techniques (e.g. SMEIR), dynamic dose prediction, 4D robust planning, and hybrid adaptive methods for CIRT. The study emphasised the use of Geant4 Monte Carlo simulations combined with deep learning models, including physics-informed neural networks, to simulate and predict dose perturbations caused by respiratory motion. This review also examined clinical treatment planning systems, radiobiological modelling, and adaptive strategies to mitigate the effects of motion.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The integration of Geant4 with deep learning enabled high-fidelity, computationally efficient dose prediction under respiratory motion, improving accuracy in dose localization and adaptation. Motion management techniques such as respiratory gating, rescanning, and 4D robust optimization demonstrated enhanced tumor control and normal tissue sparing. Hybrid models combining Monte Carlo data and AI inference show promise for near-real-time adaptive therapy. Despite these advances, challenges remain, including limited motion-rich datasets, computational demands for real-time recalculations, and the complexity of incorporating variable relative biological effectiveness (RBE) into adaptive planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Combining Geant4-based Monte Carlo simulations with deep learning frameworks shows emerging promise for controlling carbon ion dose distributions amid respiratory motion, though direct clinical validation for this combination remains limited. These hybrid models may enhance the precision and adaptability of CIRT, offering improved outcomes. Future efforts should focus on clinical validation, standardization, and overcoming computational and data limitations to facilitate clinical translation of motion-adaptive CIRT. These approaches remain at Technology Readiness Levels (TRL 3–5) and require prospective clinical validation before routine implementation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70766","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222812","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":"Geometric and dosimetric effects of an automated clustering and plan optimization pipeline for multiple brain metastasis radiosurgery","authors":"Adam D. Yock,&nbsp;Guozhen Luo,&nbsp;Sean All,&nbsp;Austin N. Kirschner,&nbsp;Cornelis Kamerling","doi":"10.1002/acm2.70869","DOIUrl":"https://doi.org/10.1002/acm2.70869","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;Treating multiple brain metastases simultaneously with single-isocenter multi-target (SIMT) stereotactic radiosurgery (SRS) can streamline treatment planning and delivery. However, it can also result in targets at large distances from the isocenter, increasing sensitivity to rotational setup errors and requiring wider collimator leaves. Grouping the targets and treating each group with its own plan retains the practical benefits of SIMT SRS while mitigating the concerns of targets at large distances off-isocenter.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This work presents a prototype of a newly integrated treatment planning pipeline that automatically clusters targets into groups and subsequently optimizes a plan for each group simultaneously. Treatment scenarios featuring varying numbers of isocenters were compared.&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-nine treatment courses for patients receiving SRS for 3–15 brain metastases were retrospectively analyzed. Multiple treatment scenarios were prepared for each patient-course by grouping targets into 1–5 isocenters using k-means clustering. PTV margins were added using two methods, one with a magnitude that varied with distance to the isocenter, and a second with a constant 1-mm magnitude. A non-clinical, command-line version of the Brainlab Elements Multiple Brain Mets SRS software was used to optimize plans within each scenario simultaneously. Cumulative doses were analyzed in terms of geometric values (target distances to isocenter, total PTV volume), dosimetric values (volume of normal brain (brain-GTVs) receiving 5, 8, 10, 12, and 18 Gy (V&lt;sub&gt;5Gy&lt;/sub&gt;, V&lt;sub&gt;8Gy&lt;/sub&gt;, V&lt;sub&gt;10Gy&lt;/sub&gt;, V&lt;sub&gt;12Gy&lt;/sub&gt;, and V&lt;sub&gt;18Gy&lt;/sub&gt;)), and logistical values (number of Monitor Units (MUs)). A representative sample of 69% of plans with variable margins was reviewed by clinical SRS experts.&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 the number of isocenters increased, distances from the targets to the isocenters decreased, and the proportion of targets within a given distance increased. For example, 36%, 77%, 94%, 99%, and 100% of targets were within 4 cm of the isocenter for 1–5 isocenters, respectively. For the variable margin method, the total PTV volume relative to the single-isocenter scenario had a median decrease of 17.5, 24.3, 31.6, and 37.8% for 2–5 isocenters, respectively. Similarly, the relative change in the normal brain dose metrics decreased with increasing number of isocenters (e.g. V&lt;sub&gt;12Gy&lt;/sub&gt; decreased 20.1, 26.2, ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222740","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":"Synthetic MRI from radiotherapy planning CT images for Head-and-Neck Cancer","authors":"Prabhakar Ramachandran,&nbsp;Akshay C Dhargave,&nbsp;Catherine Jones,&nbsp;Dionee Liefman,&nbsp;Lachlan McDowell,&nbsp;Howard Liu","doi":"10.1002/acm2.70849","DOIUrl":"https://doi.org/10.1002/acm2.70849","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;Computed Tomography (CT) provides geometric accuracy and electron density information essential for radiotherapy planning; however, it offers limited soft-tissue contrast. Magnetic Resonance Imaging (MRI) improves tumor visualization but introduces registration uncertainties when acquired separately from the radiotherapy planning CT (pCT). Cross-modality image synthesis enables the generation of synthetic MRI (sMRI) directly from pCT and may combine the strengths of both modalities, reducing reliance on MRI access.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We propose a two-stage deep-learning framework for generating sMRI from pCT image-sets specifically in head-and-neck (H&amp;N) cancers, providing soft-tissue contrast comparable to ground-truth MR images (gtMRI).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study included 60 patient cases with H&amp;N cancer treated with radical radiotherapy between March 2022 and April 2024 for model development (50 for training, 10 for validation), plus 10 additional cases, independent of the development cohort for testing. All patients underwent a standard, non-contrast pCT scan followed by an MRI acquired on a 3T Siemens MR simulator. Images were deformably-registered, yielding 10,000 matched CT–MRI slice-pairs for model training. The proposed model utilizes a two-stage architecture, a Pix2Pix conditional generative adversarial network (GAN) for coarse sMRI synthesis, followed by a conditional diffusion model for refinement. To test the model's robustness, 10 patient cases with both pCT and contrast-enhanced CT (ceCT) were used to generate sMRI. Model performance was assessed using structural similarity index (SSIM), multi-scale structural similarity index (MS-SSIM), mean absolute error (MAE), and peak signal-to-noise ratio (PSNR). In addition, the geometric agreement of the primary (GTVp_70) and nodal (GTVn_70) gross tumor volumes delineated on sMRI vs. gtMRI was independently assessed by two radiation oncologists (ROs) using the Dice similarity coefficient (DSC), 95&lt;sup&gt;th&lt;/sup&gt;-percentile Hausdorff distance (HD95), and average symmetric surface distance (ASSD).&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 average MS-SSIM, SSIM, MAE and PSNR for pCT-derived sMRI were 0.82 ± 0.02, 0.70 ± 0.03, 0.05 ± 0.01, and 20.42 ± 0.66 dB, respectively. The mean MS-SSIM and SSIM values for ceCT-derived sMRI were 0.02 lower than those for the corresponding pCT-to-sMRI metrics. For the contour-based evaluation, sMRI-derived GTV contours achieved a mean DSC of 0.56 and ","PeriodicalId":14989,"journal":{"name":"Journal of Applied Clinical Medical Physics","volume":"27 11","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/acm2.70849","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149222810","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}