Medical physics最新文献

{"title":"Dose modeling of superficial brachytherapy applicator geometries using multiple radioisotopes","authors":"Jin Jegal, HyeoungWoo Park, Seonghee Kang, Jung-in Kim, Chang Heon Choi, Siyong Kim","doi":"10.1002/mp.70641","DOIUrl":"https://doi.org/10.1002/mp.70641","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Superficial brachytherapy enables localized dose delivery for superficial cutaneous lesions, but conventional applicators may be limited in treating extended, irregular, or curved surfaces. Geometric constraints, gaps or overlaps between adjacent applicators, and placement-related uncertainties can reduce dose uniformity, underscoring the need to optimize applicator geometry and deployment strategy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>To enhance the efficacy of superficial brachytherapy for irregular or curved cutaneous surfaces, we conducted a dosimetric analysis of beta and photon sources utilizing modular circular and hexagonal applicator geometries. The study emphasizes dose uniformity, the impact of applicator dimensional variations, and the evaluation of alternative deployment strategies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Monte Carlo simulations were performed for beta sources (P-32, Sr/Y-90, and Ho-166) and photon sources (I-125, Pd-103, and Yb-169). Applicator models incorporating a zirconia absorber with ceramic and tungsten shielding were constructed, and dose distributions were scored in a water-equivalent medium. Percent depth–dose (PDD) curves were generated for beta sources, and photon sources. Multi-applicator configurations were evaluated on planar and curved surfaces under both simultaneous and sequential delivery. Applicator-size effects were examined using two active radii (5.50 mm and 2.75 mm). Dose uniformity was quantified using the mean dose and the peak-to-valley ratio (PVR) at 1 mm depth.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Beta sources were strongly affected by applicator size and geometry, producing larger variations in near-surface dose uniformity than photon sources. Sequential delivery reduced peak-to-valley modulation for all radioisotopes. Reducing the applicator radius increased the number of deliverable positions on curved surfaces by 60%–83%, increased mean dose by 28%–71%, and decreased PVR by 33%–86%, indicating improved uniformity. Photon sources showed more stable behavior, with lower sensitivity to applicator geometry and size.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Radioisotope type, applicator radius, and delivery mode significantly influence superficial dose distributions. Smaller applicators and sequential deployment improve dose uniformity, particularly for beta sources. These results provide practical guidance for radioiso","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A coarse-to-fine framework combining deep learning and Monte Carlo for BNCT patient position optimization toward inverse planning","authors":"Yoonho Na,&nbsp;Chang-min Lee,&nbsp;Kyuri Kim,&nbsp;Hyungjoo Cho,&nbsp;Jimin Lee,&nbsp;Sung-Joon Ye","doi":"10.1002/mp.70642","DOIUrl":"https://doi.org/10.1002/mp.70642","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Boron Neutron Capture Therapy (BNCT) utilizes high linear energy transfer (LET) charged particles from the ¹⁰B(n,α)⁷Li reaction to selectively destroy tumor cells. Unlike conventional radiation therapy, BNCT facilities rely on fixed beam ports, making patient positioning critical in treatment planning. Current treatment planning, however, depends on manual forward planning using computationally intensive Monte Carlo (MC) simulations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>We propose an automated patient position optimization framework for BNCT to address these limitations. This method overcomes the computational bottleneck of MC simulations by integrating a rapid deep learning (DL) dose prediction model with a high-fidelity GPU-accelerated MC engine, enabling efficient inverse planning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We developed a hybrid coarse-to-fine optimization workflow driven by the Trust Region Bayesian Optimization (TuRBO) algorithm. In the coarse stage, a 3D U-Net architecture rapidly identifies promising patient positions. In the fine stage, the solution is refined within a restricted parameter bound using the GPU-accelerated MC engine. We evaluated the framework on the GLIS-RT open dataset (229 glioblastoma patients, split into train, validation, and test sets at a 70:20:10 ratio).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Optimizing the patient position with TuRBO improved target dose and homogeneity over a non-optimized baseline, reaching equivalent plan quality about 5.65× faster than an exhaustive grid search. In the coarse stage, the DL dose predictor ran about 37× faster than the high-fidelity MC. The coarse-to-fine workflow then matched high-fidelity MC plan quality while cutting optimization time by a factor of 2.7, outperforming optimization driven by the DL predictor alone. Two-port plans required no change to the method, where the added geometric freedom raised the mean target dose from 59.96% to 74.91% and lowered the homogeneity index (HI) from 1.226 to 0.647.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>We successfully developed a Bayesian optimization (BO) framework for BNCT patient positioning. The proposed coarse-to-fine approach effectively balances computational speed with accuracy, offering a practical way toward automated inverse planning in BNCT.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70642","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and rapid generation of high-quality CT images from CBCT using a flow matching model","authors":"Zhibin Li,&nbsp;Li Chen,&nbsp;Guanghui Gan,&nbsp;Jian Guo,&nbsp;Songbing Qin,&nbsp;Long Chen","doi":"10.1002/mp.70637","DOIUrl":"https://doi.org/10.1002/mp.70637","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Generating high-quality CT images from cone-beam computed tomography (CBCT) is critical for clinical applications such as online adaptive radiotherapy (ART). Although deep learning methods, including diffusion models, have shown remarkable advances, persistent challenges remain in terms of image quality and computational efficiency.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>This study aims to leverage the flow matching model for CBCT-to-CT translation, enabling the rapid and efficient synthesis of high-quality CT images for clinical application.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Our proposed method is built upon the flow matching model, a powerful multi-step generative framework that is designed to construct a continuous trajectory that transforms data from a prior distribution to a complex target distribution. A cohort of 135 abdominal-pelvic CT scans was used for model training (95 cases), validation (15 cases), and testing (25 cases). To ensure accurate evaluation, a dataset of rigorously paired CBCT-CT images was generated by simulating the CBCT imaging process. A comprehensive assessment of the model's performance was conducted with respect to structural consistency, detail fidelity, image blurring, and texture realism. The proposed method was benchmarked against the state-of-the-art probabilistic diffusion model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>As the number of sampling steps increases, the metrics reflecting image sharpness exhibit a consistent upward trend, indicating progressive improvement in clarity. An optimal balance among textual realism, detail fidelity, and computational efficiency was achieved within the 20–50 step range. At the 20 sampling steps, the proposed model can generate a 100-slice CT volume within 20 s, with a mean absolute error (MAE) of 12.25, a structure similarity index measure (SSIM) of 0.977, and a peak signal-to-noise ratio (PSNR) of 42.03. Compared to the conventional diffusion model, the proposed method delivers superior performance with fewer sampling steps, demonstrating its potential for efficient generation of high-quality medical images.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The proposed flow matching model enables efficient and rapid generation of high-quality synthetic CT images from CBCT, substantially outperforming existing diffusion models and demonstrating strong potential for time-sensitive clinical applications such as online ART.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-view scout scans with deep learning for ultra-low dose attenuation correction in PET","authors":"Florence M. Muller,&nbsp;Margaret E. Daube-Witherspoon,&nbsp;Michael J. Parma,&nbsp;Amy E. Perkins,&nbsp;Peter B. Noël,&nbsp;Christian Vanhove,&nbsp;Stefaan Vandenberghe,&nbsp;Joel S. Karp","doi":"10.1002/mp.70647","DOIUrl":"https://doi.org/10.1002/mp.70647","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Accurate attenuation correction (AC) is essential for quantitative positron emission tomography (PET). Conventional CT-based AC provides reliable attenuation (μ-) maps but adds radiation, introduces PET/CT misalignment artifacts, and is unavailable on stand-alone PET systems. Existing deep learning (DL) methods use non-attenuation corrected (NAC) PET data to predict CT-like or directly AC-PET images, but their dependence on emission characteristics limits generalizability across tracers and anatomical coverage, especially for long axial field-of-view PET.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>We propose incorporating tissue-density information from dual-view scout radiographs as supplementary input to NAC PET, acquired with a clinically significant radiation reduction relative to standard low-dose CT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two DL methods were evaluated for generating transmission (Tr) images as surrogate μ-maps for PET AC: (1) (NAC)-to-(Tr), using coronal and sagittal NAC PET slices, and (2) (NAC + Scout)-to-(Tr), combining NAC PET with anterior-posterior and lateral scout views. 53 research scans across four tracers from the PennPET Explorer were used for training and testing, with three additional tracers included for testing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>(NAC + Scout)-to-(Tr) improved quantitative accuracy, reducing NRMSE% to &lt; 10% (versus up to 18% for (NAC)-to-(Tr)) and SUV biases to within -10%, with significant reductions in brain, liver, and muscle compared to (NAC)-to-(Tr). Out-of-distribution evaluation confirmed generalizability, maintaining SUV biases below 5%-8% versus 10%-13% for (NAC)-to-(Tr). In a longitudinal biodistribution study, the scout-guided model showed consistent performance across repeat scans.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>By leveraging routinely acquired scout scans, this approach enables accurate quantitative PET reconstruction without a full CT, substantially reducing radiation dose and misalignment artifacts.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70647","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Develop a novel non-coplanar trajectory optimization algorithm for an efficient 4pi spot-scanning proton Arc (SPArc-4pi) treatment delivery","authors":"Xiaoda Cong,&nbsp;Shupeng Chen,&nbsp;Peilin Liu,&nbsp;Peng Chen,&nbsp;Xiangkun Xu,&nbsp;Xiaoqiang Li,&nbsp;Peter Chen,&nbsp;Prakash Chinnaiyan,&nbsp;Xuanfeng Ding","doi":"10.1002/mp.70639","DOIUrl":"https://doi.org/10.1002/mp.70639","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The degree of freedom has been recognized as a key factor in particle beam therapy, such as improving the dose conformity and linear energy transfer distributions. Therefore, proton arc therapy has drawn significant interest in the Society of Radiation Oncology as a potentially efficient and optimal treatment option for cancer patients. However, state-of-the-art spot-scanning proton arc therapy (SPArc) still relies on single or dual- co-planar arc trajectories, which limits its capacity to advance the treatment outcome further. There is an urgent need to explore particle beam therapy's full potential via 4pi.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study aims to develop the first 4pi arc optimization algorithm that searches for efficient arc trajectories in 4pi space, explores the potential dosimetric improvements, and demonstrates its feasibility through simulation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Dynamic Programming, originally from control theory, was translated into this new concept of the 4pi SPArc optimization algorithm (SPArc&lt;sub&gt;-4pi&lt;/sub&gt;) for the trajectory search and route decision-making. It breaks down the complicated and high-computational-demand main problem into a series of small sub-problems and searches for delivery-efficient 4pi arc trajectories through an iterative approach. Five different disease sites, e.g., head &amp; neck, partial brain, clival brain chordoma, lung and pancreatic cancer, were used for testing purposes. Conventional Intensity Modulated Proton Therapy (IMPT) and 2D co-planar arc (SPArc&lt;sub&gt;-2d&lt;/sub&gt;) plans were generated as a benchmark. Treatment delivery efficiency was evaluated through a published and validated dynamic arc system controller. Plan quality was assessed through target coverage and organ at risk (OAR) sparing.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The new SPArc&lt;sub&gt;-4pi&lt;/sub&gt; demonstrated superior dosimetric performance across various evaluation metrics for all five disease sites. The simulation result shows that SPArc&lt;sub&gt;-4pi&lt;/sub&gt; is able to be delivered within a reasonable time of around 5–11 mins, which is comparable to the SPArc&lt;sub&gt;-2d&lt;/sub&gt; plans&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The study introduced the first optimization algorithm for SPArc&lt;sub&gt;-4pi&lt;/sub&gt; technique. It not only showed SPArc&lt;sub&gt;-4pi&lt;/sub&gt; ‘s potential to improve the plan quality via a greater degree of freedom compared to the conventi","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70639","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust optimization of catheter positions and dwell times for HDR prostate brachytherapy","authors":"Joseph B. Schulz,&nbsp;Bryan P. Bednarz,&nbsp;John M. Floberg,&nbsp;Jordan M. Slagowski","doi":"10.1002/mp.70640","DOIUrl":"https://doi.org/10.1002/mp.70640","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;HDR prostate brachytherapy plans are sensitive to catheter placement uncertainty, as discrepancies between planned and delivered catheter positions can degrade target coverage and increase organ at risk dose. Current inverse planning methods optimize dwell times for a fixed implant geometry and do not account for geometric uncertainty during planning. Existing robust optimization approaches for HDR brachytherapy are similarly limited to dwell time optimization, and no framework has jointly optimized catheter configurations and dwell times while explicitly incorporating catheter insertion uncertainty.&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 an analytical inverse planning method for prostate HDR brachytherapy that improves robustness to catheter placement uncertainty while maintaining nominal target coverage and organ at risk constraints.&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;Overall, 32 previously treated prostate HDR cases were retrospectively analyzed. Dose was modeled with a TG-43U1 influence matrix. A candidate catheter set was generated by adding four translated trajectories per clinical catheter at &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;±&lt;/mo&gt;\u0000 &lt;mn&gt;5&lt;/mn&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;mi&gt;mm&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$pm 5nobreakspace mathrm{mm}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; in the anterior posterior and lateral directions, with dwell positions cropped to remain within the loading structure. Dwell times and catheter selection were optimized using a dose fidelity term with a group minimax concave penalty (gMCP) to enforce catheter level sparsity, and a surface restricted dose gradient penalty (SDGP) applied to organ at risk surface voxels. Four strategies were compared: clinical planning, dose fidelity+SDGP, dose fidelity+gMCP, and dose fidelity+gMCP+SDGP. Hyperparameters remained fixed for all patients, respectively. All nominal plans were normalized to PTV &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;V&lt;/mi&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;100&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;=&lt;/mo&gt;\u0000 &lt;mn&gt;95&lt;/mn&gt;\u0000 &lt;mo&gt;%&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 ","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70640","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SAR validation of RF coils and implants in a B0-free RF safety laboratory","authors":"Nur Izzati Huda Zulkarnain,&nbsp;Mazin M. Mustafa,&nbsp;Alireza Sadeghi-Tarakameh,&nbsp;Mert Ates,&nbsp;Jeromy Thotland,&nbsp;Steve Jungst,&nbsp;Arcan Erturk,&nbsp;Lance DelaBarre,&nbsp;Matt Waks,&nbsp;Russell L. Lagore,&nbsp;Kamil Ugurbil,&nbsp;Gregory J. Metzger,&nbsp;Gregor Adriany,&nbsp;Yigitcan Eryaman","doi":"10.1002/mp.70636","DOIUrl":"https://doi.org/10.1002/mp.70636","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;As MRI continues to advance toward higher field strengths, RF safety assessment has become more complex. Accurate estimation of specific absorption rate (SAR) is essential for evaluating both hardware and implant safety, yet thermometry and simulation-only approaches face limitations. In addition, these evaluations are typically performed within the MR scanner, where failures or excessive loading can damage the transmit chain and result in costly repairs and scanner downtime. To overcome these challenges, alternative experimental approaches that enable direct and controlled SAR validation outside the MR environment are needed.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study demonstrates direct SAR validation of RF hardware and implants in a dedicated B0-free RF safety laboratory. The work aims to establish direct SAR measurement as a practical and accurate alternative for quantitative safety verification while expanding the range of tools available for MR hardware evaluation beyond the constraints of the scanner environment.&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;Hardware assessments were conducted in the safety lab equipped with a 16-channel broadband RF amplifier system (45–450 MHz), a 100 dB shielded Faraday cage, automated 3D and 1D motion systems, and a high-precision SAR probe. For coil validation, direct SAR mapping was performed on a custom-built parallel transmit (pTx) coil and a commercial single-channel RF coil at 447 and 297 MHz, respectively, and results were compared with electromagnetic simulations. Transfer function (TF) validation for a directional DBS electrode at 128 MHz was performed in a rectangular electric-field generator, whose field distribution was first validated using the SAR probe. The same probe was then used to compare measured SAR with TF-based SAR predictions, providing a direct quantitative validation of the TF method.&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;Measured SAR distributions showed strong quantitative agreement with simulations across all experiments. For the 8-channel pTx head coil at 447 MHz, the normalized root-mean-square error (NRMSE) across four excitation patterns was below 13%. For the commercial single-channel head coil at 297 MHz, plane-wise comparisons across axial, coronal, and sagittal slices yielded an average NRMSE value of 7.18%, demonstrating spatial consistency between measured and simulated fields. The electric-field generator used for DBS transfer function (TF) validation exhibited 3.68% NRMSE relative to simulation, confirm","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70636","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation and correction of respiratory motion in pediatric renal SPECT through a data-driven center-of-mass method","authors":"Sophia Pells,&nbsp;P. Hendrik Pretorius,&nbsp;Justin Pijanowski,&nbsp;Frederic Fahey,&nbsp;S. Ted Treves,&nbsp;Neha Kwatra,&nbsp;Xinhua Cao,&nbsp;William McCarthy,&nbsp;Sarah Van Hoesen,&nbsp;Katelyn Collins,&nbsp;Yongyi Yang,&nbsp;Valentina Ferrer Valencia,&nbsp;Michael A. King","doi":"10.1002/mp.70635","DOIUrl":"https://doi.org/10.1002/mp.70635","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;Respiratory motion is known to cause blurring in Single-Photon Emission Computed Tomography (SPECT) images which can mask or mimic disease. Pediatric imaging with &lt;sup&gt;99m&lt;/sup&gt;Tc-labeled dimercaptosuccinic acid (DMSA) is used to assess cortical defects in kidneys and may be especially susceptible to artifacts introduced by respiratory motion due to the thin kidney cortices and small kidney volumes seen in many pediatric patients.&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;The purpose of this study was to assess a data-driven method to estimate respiratory motion signals in pediatric &lt;sup&gt;99m&lt;/sup&gt;Tc-DMSA renal SPECT and to evaluate the impact of respiratory motion correction on image quality.&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;Listmode &lt;sup&gt;99m&lt;/sup&gt;Tc-DMSA SPECT data were acquired for 77 pediatric patients aged from 6 weeks to 20 years. The data were binned into 100 ms temporal frames and forward-projected kidney masks were used in determining the axial center-of-mass (aCOM) of counts in each temporal frame as a surrogate renal respiratory motion signal for each patient. Amplitudes of respiratory motion in the lateral, anterior–posterior and axial (superior-inferior) axes were determined using a rigid-body six-degree-of-freedom intensity-based registration method and evaluated as a function of patient weight. Welch &lt;i&gt;t&lt;/i&gt;-tests were performed to compare the respiratory motion amplitudes of male and female patients. Subsequently, a rigid-body 6-degree-of-freedom respiratory motion correction was applied during reconstruction and the images were quantitatively assessed for improvement in contrast and sharpness.&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;Renal respiratory motion surrogate signals were estimated for 69 patients, after eight were removed due to gross body motion. Axial, lateral and anterior–posterior translational renal respiratory motion amplitudes were all found to positively correlate with patient weight, with lateral motion showing the strongest correlation. Respiratory motion was largest in the axial direction where it ranged from (2.19 &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mo&gt;±&lt;/mo&gt;\u0000 &lt;annotation&gt;$pm$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; 0.48) mm for the patients under 7 kg to (6.96 &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mo&gt;±&lt;/mo&gt;\u0000 &lt;annotation&gt;$pm$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; 3.07) mm for patients over 60 kg. No significant differences were found in axial or anterior–posterior renal respiratory motion between mal","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of millimeter-scale target motion on the precision of spatially fractionated radiation therapy using proton minibeams","authors":"Oxana Actis,&nbsp;Cristian Fernandez-Palomo,&nbsp;Verdiana Trappetti,&nbsp;Michele Togno,&nbsp;Paolo Pellicioli,&nbsp;Dominic Leiser,&nbsp;David Meer,&nbsp;Valentin Djonov","doi":"10.1002/mp.70638","DOIUrl":"https://doi.org/10.1002/mp.70638","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>While pencil beam scanning (PBS) with motion mitigation such as re-scanning, breath hold, or gating is well established for treating moving targets in clinical practice, the precision for Spatially Fractionated Radiation Therapy (SFRT) using proton minibeams introduces presents a unique challenge. The sub-millimeter precision required for SFRT cannot be achieved with typical PBS spot sizes (millimeters), necessitating multi-slit beam collimation, which reduces the dose rate and reintroduces motion as a critical issue. In this study, we report on our experience with minibeam irradiations of chorioallantoic membranes (CAM) of chick embryos and discuss potential solutions to the motion problem.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The first experiment was conducted at a PBS gantry using 130 MeV protons and a 6 cm thick copper multi-slit collimator with 0.3 mm wide slits and 1 mm spacing. To achieve a target peak dose of 30 Gy, CAM samples were irradiated with more than 10 re-scans. Due to a 91% beam loss in the collimator, the total irradiation time extended to two min.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Post-irradiation analysis using gafchromic film revealed smearing of the minibeam profiles, while biological tissue analysis uncovered unexpected and disrupted dose effects, likely caused by irregular CAM movement during irradiation. A subsequent experiment, incorporating additional setup optimizations such as reduced air gap and increased dose rate, shortened the irradiation time to below one min. This led to sharper dose profiles with negligible variation in valley dose and peak width, although a reduction in peak dose of 8%–13% was still observed. This variation is considered acceptable for our biological experiments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>For clinical applications, minibeam re-scanning is likely to be feasible only under ultra-high dose rate conditions (e.g., those required to induce the FLASH effect), where sufficiently short irradiation times minimize motion-induced dose degradation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/mp.70638","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory personalized radiobiological modeling of bystander and immune effects to inform SFRT-SBRT scheduling","authors":"Jiaxin Li,&nbsp;Fen Wang,&nbsp;Wangyao Li,&nbsp;Chayu Yang,&nbsp;Jufri Setianegara,&nbsp;Shahed Badiyan,&nbsp;Kenneth Westover,&nbsp;Sean Domal,&nbsp;Yuting Lin,&nbsp;Hao Gao","doi":"10.1002/mp.70643","DOIUrl":"https://doi.org/10.1002/mp.70643","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;Spatially fractionated radiation therapy (SFRT) demonstrates clinical efficacy against bulky tumors, but optimal treatment scheduling remains empirical. The technique's heterogeneous dose distribution triggers complex biological effects—including bystander signaling and immune activation—that are not captured by conventional dose-response models.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Purpose&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study aims to develop a proof-of-concept computational framework to simulate tumor and immune responses during combined Lattice radiotherapy and SBRT) as an initial step toward patient-specific modeling.&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 four-compartment ordinary differential equation (ODE) model was established to simulate tumor and lymphocyte dynamics, integrating Gompertz tumor growth kinetics, direct radiation-induced cell killing, and indirect biological effects mediated by intercellular signaling and immune activation. Bystander signaling was described by reaction–diffusion equations modeling spatial propagation from high- to low-dose regions. Immune responses were modeled with coupled lymphocyte-tumor equations, with lymphocyte dose exposure estimated using the HEDOS model. Model parameters were derived from literature and fitted to tumor volume and absolute lymphocyte count (ALC) data from four non-small cell lung cancer (NSCLC) patients treated with SFRT and SBRT.&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 model demonstrated feasibility in reproducing tumor volume (normalized root-mean-square error [NRMSE]: 0.071–0.197) and ALC dynamics (NRMSE: 0.017–0.385). Simulations revealed substantial inter-patient heterogeneity in the estimated contributions of direct radiation and immune-mediated effects, with immune-mediated killing exceeding direct radiation in 2 patients. Combined SFRT-SBRT achieved superior tumor control over either modality alone in our simulations. Notably, the optimal SFRT-SBRT interval appeared patient-specific: extending the interval to 2 months improved outcomes in some patients, while others showed limited benefit, depending on the balance between treatment-induced cell kill and tumor regrowth.&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;We developed a radiobiological model that simulates tumor and lymphocyte dynamics under combined SFRT–SBRT regimens, providing a preliminary framework for exploring personalized SFRT-SBRT scheduling. These findings warrant further prospective validation in larger patient cohorts before clinical translation.&lt;/p&gt;\u0000 &lt;/section","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"53 9","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148753834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}