Physics and Imaging in Radiation Oncology最新文献

{"title":"Diurnal variation of the distance between cranium and the third lumbar vertebra and its implications for craniospinal irradiation","authors":"Annele Heikkilä ,&nbsp;Maija Rossi ,&nbsp;Antti Vanhanen ,&nbsp;Tuomas Koivumäki ,&nbsp;Michiel Postema ,&nbsp;Eeva Boman","doi":"10.1016/j.phro.2025.100760","DOIUrl":"10.1016/j.phro.2025.100760","url":null,"abstract":"<div><div>The spine shortens during the day because of gravity. This study quantified the effect of treatment fraction timing on spinal length in 13 craniospinal irradiation patients. The distance deviation from the base of skull to the third lumbar vertebra in daily planar kilovoltage setup images compared to the treatment planning computed tomography image was determined. The time deviation between the treatment fraction and planning computed tomography image was registered. A distance decrease of <span><math><mrow><mn>0</mn><mo>.</mo><mn>8</mn><mo>±</mo><mn>0</mn><mo>.</mo><mn>2</mn></mrow></math></span> mm/hour was observed. Timing the treatment fractions within two hours of the planning imaging session is advisable to minimise the potential dosimetric impact of diurnal variations.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100760"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feasibility of celiac axis delineation and treatment on combined magnetic resonance imaging and linear accelerator systems","authors":"Sara N. Lim ,&nbsp;Yirong Liu ,&nbsp;Anugayathri Jawahar ,&nbsp;Bharat B. Mittal ,&nbsp;Tarita O. Thomas","doi":"10.1016/j.phro.2025.100768","DOIUrl":"10.1016/j.phro.2025.100768","url":null,"abstract":"<div><div>Trials have been performed on irradiating celiac plexus for pancreatic cancer pain management. Images from a combined magnetic resonance imaging and linear accelerator system (MR-linac) for ten patients were assessed for delineation of celiac ganglia, aiming for smaller target volumes and reducing treatment risks <em>versus</em> standard linac-based treatments. MRI-linacs showed superior soft tissue contrast, enabling increased dose to ganglia while irradiating smaller target volumes <em>versus</em> regular linacs (median: 0.8 cm³ vs. 32.2 cm³, p &lt; 0.05 for ten pairs of plans). While further studies are needed, MR-linac treatments could improve targeting precision, minimize dose to organs-at-risk and enhance effectiveness in palliative care.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100768"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volume change of the prostate during moderately hypo-fractionated radiotherapy assessed by artificial intelligence","authors":"Rasmus L. Christiansen ,&nbsp;Bahar Celik ,&nbsp;Lars Dysager ,&nbsp;Christina J. Nyborg ,&nbsp;Steinbjørn Hansen ,&nbsp;Tine Schytte ,&nbsp;Søren N. Agergaard ,&nbsp;Anders S. Bertelsen ,&nbsp;Uffe Bernchou ,&nbsp;Christian R. Hansen ,&nbsp;Karina L. Gottlieb ,&nbsp;Nis Sarup ,&nbsp;Ebbe L. Lorenzen","doi":"10.1016/j.phro.2025.100770","DOIUrl":"10.1016/j.phro.2025.100770","url":null,"abstract":"<div><h3>Background</h3><div>Diagnostic quality MRI acquired daily for radiotherapy (RT) planning on an MR-linac allows longitudinal evaluation of the patients’ anatomy. This study investigated changes in prostate volume during MR-guided RT. The changes were assessed from manual delineations used clinically for daily online adaptation as well as automated segmentation by artificial intelligence (AI). The consistency and congruity of these two methods were evaluated.</div></div><div><h3>Methods</h3><div>The prostate volumes were extracted from daily planning MRI scans of 45 patients receiving 60 Gy in 20 fractions. These volumes were manually edited during the online adaptive treatment planning workflow. The prostate was re-segmented retrospectively for each fraction by AI with an in-house developed nnU-net, trained on prostate cancer patients. The volume for each fraction was normalized to the volume at the patients’ 1st fraction to identify possible time trends.</div></div><div><h3>Results</h3><div>Increased population mean prostate volume was seen both based on manual and automatic segmentation. However, based on manual delineations, the peak volume occurred at the 12th fraction at 106.8% of the initial volume, while based on automatic segmentation, the volume peaked at a mean increase 110.8% by the 5th fraction. Standard deviation of volumes for automated segmentation (5.2%) versus manual delineation (12.7%), and reduced variation between fractions from 3.6% to 2.6% indicate better consistency of the automatic segmentation.</div></div><div><h3>Conclusion</h3><div>Automated segmentation by our locally trained nnU-net was more consistent than manual delineations performed clinically. The population mean increase in prostate volume peaked at 110.8% by the 5th fraction after reduce over the remaining treatment course.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100770"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cone-beam computed tomography reconstruction for a commercial proton beam therapy system","authors":"Josh W.H. Lindsay ,&nbsp;Simon J.P. Meara ,&nbsp;Matthew Clarke ,&nbsp;Matthew Lowe ,&nbsp;David Lines ,&nbsp;Marianne C. Aznar ,&nbsp;Marcel van Herk","doi":"10.1016/j.phro.2025.100745","DOIUrl":"10.1016/j.phro.2025.100745","url":null,"abstract":"<div><h3>Background &amp; Purpose:</h3><div>Cone-beam computed tomography (CBCT) images are used in image-guided radiotherapy to track anatomical changes throughout treatment and to set up patients to ensure accurate delivery of therapeutic radiation at each treatment session. An offline method of CBCT reconstruction workflow, operating on 2D projection images and specific to the imaging system in question, is needed for many image optimisation studies. Here we present a methodology to reconstruct CBCT images from these data for a commercial proton beam therapy machine, accounting for the variation in exposure and beam hardening from filtration due to gantry rotation during CBCT acquisition.</div></div><div><h3>Materials &amp; Methods:</h3><div>Projection data of solid water phantoms were acquired to model bow-tie filter motion and beam hardening effects. Projection data and system CBCT reconstructions of a Catphan504 phantom were acquired for validation of the method, as well as a retrospectively accessed patient image. The presented workflow was assessed against the clinical reconstructions using uniformity, signal-to-noise-ratio, and contrast-to-noise-ratio measured in the phantom images.</div></div><div><h3>Results:</h3><div>The offline workflow eliminated crescent artefacts due to variable exposure and beam hardening in phantom and patient images. Signal-to-noise and contrast-to-noise ratios were similar compared to system reconstructions, although with slight differences thought to be due to interplay effects in the bow-tie filter.</div></div><div><h3>Conclusion:</h3><div>A workflow was developed to emulate the CBCT reconstruction process for a commercial proton therapy machine, providing a useful tool for optimised acquisition parameters and novel reconstruction processes using this system.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100745"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty-guided pancreatic tumor auto-segmentation with Tversky ensemble","authors":"Cenji Yu ,&nbsp;Skylar S. Gay ,&nbsp;Aashish C. Gupta ,&nbsp;Rachael M. Martin-Paulpeter ,&nbsp;Ethan B. Ludmir ,&nbsp;Yao Zhao ,&nbsp;Jack Duryea ,&nbsp;Xinru Chen ,&nbsp;Carlos E. Cardenas ,&nbsp;Jinzhong Yang ,&nbsp;Albert C. Koong ,&nbsp;Tucker J. Netherton ,&nbsp;Dong Joo Rhee ,&nbsp;Laurence E. Court","doi":"10.1016/j.phro.2025.100740","DOIUrl":"10.1016/j.phro.2025.100740","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Pancreatic gross tumor volume (GTV) delineation is challenging due to their variable morphology and uncertain ground truth. Previous deep learning-based auto-segmentation methods have struggled to handle tasks with uncertain ground truth and have not accommodated stylistic customizations. We aim to develop a human-in-the-loop pancreatic GTV segmentation tool using Tversky ensembles by leveraging uncertainty estimation techniques.</div></div><div><h3>Material and methods</h3><div>In this study, we utilized a total of 282 patients from the pancreas task of the Medical Segmentation Decathlon. Thirty patients were randomly selected to form an independent test set, while the remaining 252 patients were divided into an 80–20 % training-validation split. We incorporated Tversky loss layer during training to train a five-member segmentation ensemble with varying contouring tendencies. The Tversky ensemble predicted probability maps by estimating pixel-level segmentation uncertainties. Probability thresholding was employed on the resulting probability maps to generate the final contours, from which eleven contours were extracted for quantitative evaluation against ground truths, with variations in the threshold values.</div></div><div><h3>Results</h3><div>Our Tversky ensemble achieved DSC of 0.47, HD95 of 12.70 mm and MSD of 3.24 mm respectively using the optimal thresholding configuration. We outperformed the Swin-UNETR configuration that achieved the state-of-the-art result in the pancreas task of the medical segmentation decathlon.</div></div><div><h3>Conclusions</h3><div>Our study demonstrated the effectiveness of employing an ensemble-based uncertainty estimation technique for pancreatic tumor segmentation. The approach provided clinicians with a consensus probability map that could be fine-tuned in line with their preferences, generating contours with greater confidence.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100740"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spot-optimization reduces beam delivery time in liver breath hold intensity modulated proton therapy","authors":"Michael Butkus ,&nbsp;Daniel Bastawros ,&nbsp;Yunze Yang ,&nbsp;Roberto Cassetta ,&nbsp;Roni Hytonen ,&nbsp;Robert Kaderka","doi":"10.1016/j.phro.2025.100763","DOIUrl":"10.1016/j.phro.2025.100763","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Liver irradiations with intensity-modulated proton therapy (IMPT) often require motion mitigation techniques that prolong treatment. A prototype spot-optimization algorithm was tested to evaluate whether plan delivery time could be reduced while preserving quality.</div></div><div><h3>Methods and materials</h3><div>Fifteen patients previously treated with liver IMPT using breath-hold were re-planned with nominal treatment planning system (TPS) settings and using a prototype spot-optimization algorithm in which combinations of minimum Monitor Unit (MU) and layer-spacing settings were tested: 1MU/1MeV, 3MU/3MeV, 1MU/5MeV, 5MU/3MeV. Spot-optimized and nominals plans were compared using standard dose-volume histogram (DVH) metrics for targets and organs-at-risk. A Wilcoxon signed-rank test was applied (p &lt; 0.05). Delivery time for all plans were measured by creating and delivering IMPT quality assurance (QA) plans. Gamma analyses were performed on all plans to test deliverability. Plans were considered deliverable if &gt;90 % of points passed a gamma criterion of 3 %/3mm.</div></div><div><h3>Results</h3><div>Minimal DVH differences were observed between nominal and spot-optimized plans. For the 3MU/3MeV setting, no DVH metrics were significantly different. Median and interquartile range (IQR) delivery times for these plans were 40 % (38 %<strong>–</strong>44 %) faster than nominal plans. 5MU/3MeV plans had median (IQR) delivery times 59 % (52 %<strong>–</strong>61 %) faster than nominal plans but had a small but significant increase in Liver_Eff D_mean with a median (IQR) difference of 0.2 Gy(RBE) (0.0<strong>–</strong>0.4 Gy(RBE)). QA analysis showed all spot-optimized plans were deliverable.</div></div><div><h3>Conclusions</h3><div>The spot-optimization algorithm produced clinically deliverable plans with negligible DVH differences to nominal plans and reduced delivery time of liver IMPT by over one-third.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100763"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A 0.05 mm3 diode-based single charged-particle real-time radiation detector for electron radiotherapy","authors":"Kyoungtae Lee ,&nbsp;Rahul Lall ,&nbsp;Michel M. Maharbiz ,&nbsp;Mekhail Anwar","doi":"10.1016/j.phro.2025.100762","DOIUrl":"10.1016/j.phro.2025.100762","url":null,"abstract":"<div><div>Real-time radiation monitoring at the single-particle level is an unmet need for electron radiotherapy, especially for dose deposition to targets in motion or critical OARs. We have developed a first-in-class CMOS-based 0.05 mm³ single electron sensitive detector. The chiplet integrates all the requisite electronics. The functionality of the system is verified under 6 and 9 MeV clinical electron beams. Percentage depth vs. pulse-width curves for 6 and 9 MeV beams are measured and verified using Monte-Carlo simulations. The proposed system has the potential to enhance the electron radiotherapy quality and safety, providing real-time dosimetry from multiple sites simultaneously.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100762"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Partial adaptation for online-adaptive proton therapy triggered by during-delivery treatment verification: Feasibility study on prostate cancer treatments","authors":"Virginia Gambetta ,&nbsp;Victoria Pieta ,&nbsp;Jonathan Berthold ,&nbsp;Tobias Hölscher ,&nbsp;Albin Fredriksson ,&nbsp;Christian Richter ,&nbsp;Kristin Stützer","doi":"10.1016/j.phro.2025.100755","DOIUrl":"10.1016/j.phro.2025.100755","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Online treatment verification during proton therapy delivery may detect deviations due to anatomical changes occurring along the treatment course and trigger immediate intervention, if necessary. We investigated the potential of partial plan adaptation in two-field prostate cancer treatments as a solution for online-adaptive proton therapy (OAPT) after the detection of relevant treatment deviations during the first field delivery.</div></div><div><h3>Materials and Methods</h3><div>In a retrospective study, ten fractions from eight prostate cancer patients with prompt gamma imaging (PGI) detected treatment deviations, which were confirmed on respective in-room control computed tomography (cCT) scans, were considered. For each cCT, a dose-mimicking-based robust partial adaptation reoptimized the second field by considering the suboptimal dose delivery of the first non-adapted, PGI-monitored field. The results were compared to the non-adapted scenario and upfront full adaptation (both fields) in terms of achievable target coverage (prescription: 48 Gy/60 Gy to low-risk/high-risk target) and organ-at-risk (OAR) sparing.</div></div><div><h3>Results</h3><div>Partially adapted plans showed comparable target coverage (median <em>D</em>_98%: 99.9%/98.0% for low-/high-risk target) to fully adapted plans (100.3%/98.7%) and were superior to non-adapted plans (98.7%/94.5%). Achievable OAR sparing was patient-specific depending on the proximity to the target region, but within clinical goals for the partially and fully adapted plans.</div></div><div><h3>Conclusions</h3><div>Partial adaptation triggered mid-delivery of a fraction can still generate plans of comparable conformity to full adaptation, even in the case of plans with only two, opposing fields. A verification-triggered OAPT may therefore become an alternative to upfront OAPT, saving time and imaging dose in fractions without relevant anatomy changes.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100755"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving outcome prediction in oropharyngeal carcinoma through the integration of diffusion-weighted magnetic resonance imaging radiomics","authors":"Heleen Bollen ,&nbsp;Rüveyda Dok ,&nbsp;Frederik De Keyzer ,&nbsp;Sarah Deschuymer ,&nbsp;Annouschka Laenen ,&nbsp;Johannes Devos ,&nbsp;Vincent Vandecaveye ,&nbsp;Sandra Nuyts","doi":"10.1016/j.phro.2025.100759","DOIUrl":"10.1016/j.phro.2025.100759","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Locoregional recurrence (LRR) is the primary pattern of failure in head and neck cancer (HNC) following radiation treatment (RT). Predicting an individual patient’s LRR risk is crucial for pre-treatment risk stratification and treatment adaptation during RT. This study aimed to evaluate the feasibility of integrating pre-treatment and mid-treatment diffusion-weighted (DW)-MRI radiomic parameters into multivariable prognostic models for HNC.</div></div><div><h3>Materials and methods</h3><div>A total of 178 oropharyngeal cancer (OPC) patients undergoing (chemo)radiotherapy (CRT) were analyzed on DW-MRI scans. 105 radiomic features were extracted from ADC maps. Cox regression models incorporating clinical and radiomic parameters were developed for pre-treatment and mid-treatment phases. The models’ discriminative ability was assessed with the Harrel C-index after 5-fold cross-validation.</div></div><div><h3>Results</h3><div>Gray Level Co-occurrence Matrix (GLCM)-correlation emerged as a significant pre-treatment radiomic predictor of locoregional control (LRC) with a C-index (95 % CI) of 0.66 (0.57–0.75). Significant clinical predictors included HPV status, stage, and alcohol use, yielding a C-index of 0.70 (0.62–0.78). Combining clinical and radiomic data resulted in a C-index of 0.72 (0.65–0.80), with GLCM-correlation, disease stage and alcohol use as significant predictors. The mid-treatment model, which included delta (Δ) mean ADC, stage, and additional chemotherapy, achieved a C-index of 0.74 (0.65–0.82). Internal cross-validation yielded C-indices of 0.60 (0.51–0.69), 0.56 (0.44–0.66), and 0.63 (0.54–0.73) for the clinical, combined, and mid-treatment models, respectively.</div></div><div><h3>Conclusion</h3><div>The addition of Δ ADC improves the clinical model, highlighting the potential complementary value of radiomic features in prognostic modeling.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100759"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Organs at risk proximity in central lung stereotactic ablative radiotherapy: A comparison of four-dimensional computed tomography and magnetic resonance-guided breath-hold delivery techniques","authors":"Nicolas Giraud ,&nbsp;Hilâl Tekatli ,&nbsp;Famke L. Schneiders ,&nbsp;John R. van Sornsen de Koste ,&nbsp;Marco Marzo ,&nbsp;Miguel A. Palacios ,&nbsp;Suresh Senan","doi":"10.1016/j.phro.2025.100761","DOIUrl":"10.1016/j.phro.2025.100761","url":null,"abstract":"<div><div>Higher toxicity rates are associated with stereotactic ablative radiotherapy (SABR) to central lung tumors. Breath-hold (BH) magnetic resonance-guided SABR (MR-SABR) can reduce doses to organs at risk (OAR). We quantified the planning target volumes (PTV) to OAR distance in 45 lesions treated using MR-SABR and generated a corresponding four-dimensional computed tomography (4D-CT) based PTV (motion-encompassing internal target volume plus 5 mm). For lesions located ≦3 cm from airways, BH MR-SABR increased the median PTV distance to OAR by 3.7 mm. For lesions ≦3 cm from pericardium, median PTV-OAR separation increased by 2.0 mm with BH. These findings highlight the advantage of BH SABR for central lung tumors.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100761"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}