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":"Uncertainty estimation for dosimetry in radiation oncology","authors":"Wolfgang Lechner ,&nbsp;Hugo Palmans","doi":"10.1016/j.phro.2025.100773","DOIUrl":"10.1016/j.phro.2025.100773","url":null,"abstract":"<div><div>Accurate dosimetry in radiation oncology is one of the main pillars of a successful cancer treatment. An integral part of dose measurements and calculations is the thorough and adequate assessment of the involved uncertainties. Unfortunately, this step is often neglected or done in a way which makes it challenging for others to understand the quality of presented results. In this review we summarize the concepts on the expression of uncertainties and apply these to practical examples in the context of radiation oncology. Basic concepts such as Type A and Type B uncertainties, their assessment and potential correlations as well as more advanced concepts such as effective degrees of freedom are introduced. Finally, this review gives suggestions on how the results can be presented, how the resulting uncertainty budget can be used to identify the main contributors and how the combined uncertainty can be used to establish tolerance and action limits for quality assurance processes.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100773"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168821","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":"Leveraging network uncertainty to identify regions in rectal cancer clinical target volume auto-segmentations likely requiring manual edits","authors":"Federica C. Maruccio ,&nbsp;Rita Simões ,&nbsp;Joëlle E. van Aalst ,&nbsp;Charlotte L. Brouwer ,&nbsp;Jan-Jakob Sonke ,&nbsp;Peter van Ooijen ,&nbsp;Tomas M. Janssen","doi":"10.1016/j.phro.2025.100771","DOIUrl":"10.1016/j.phro.2025.100771","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>While Deep Learning (DL) auto-segmentation has the potential to improve segmentation efficiency in the radiotherapy workflow, manual adjustments of the predictions are still required. Network uncertainty quantification has been proposed as a quality assurance tool to ensure an efficient segmentation workflow. However, the interpretation is often complicated due to various sources of uncertainty interacting non-trivially. In this work, we compared network predictions with both independent manual segmentations and manual corrections of the predictions. We assume that manual corrections only address clinically relevant errors and are therefore associated with lower aleatoric uncertainty due to less inter-observer variability. We expect the remaining epistemic uncertainty to be a better predictor of segmentation corrections.</div></div><div><h3>Materials and Methods</h3><div>We considered DL auto-segmentations of the mesorectum clinical target volume. Uncertainty maps of nnU-Net outputs were generated using Monte Carlo dropout. On a global level, we investigated the correlation between mean network uncertainty and network segmentation performance. On a local level, we compared the uncertainty envelope width with the length of the error from both independent contours and corrected predictions. The uncertainty envelope widths were used to classify the error lengths as above or below a predefined threshold.</div></div><div><h3>Results</h3><div>We achieved an AUC above 0.9 in identifying regions manually corrected with edits larger than 8 mm, while the AUC for inconsistencies with the independent contours was significantly lower at approximately 0.7.</div></div><div><h3>Conclusions</h3><div>Our results validate the hypothesis that epistemic uncertainty estimates are a valuable tool to capture regions likely requiring clinically relevant edits.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100771"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934928","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":"The bone rigidity error as a simple, quantitative, and interpretable metric for patient-specific validation of deformable image registration","authors":"Andreas Smolders ,&nbsp;Tony Lomax ,&nbsp;Francesca Albertini","doi":"10.1016/j.phro.2025.100767","DOIUrl":"10.1016/j.phro.2025.100767","url":null,"abstract":"<div><h3>Background and Purpose:</h3><div>Despite its potential, deformable image registration (DIR) is underutilized clinically, especially in time-sensitive cases, due to a lack of comprehensive metrics for assessing solution quality. Here, we propose a metric of physical plausibility, the bone rigidity error (BRE), that penalizes non-rigid transformations within individual bones, based on the assumption that bones do not deform.</div></div><div><h3>Materials and Methods:</h3><div>The BRE is calculated by segmenting bones individually and isolating the vectors of a deformable vector field within each bone. A rigid registration is least-square fitted to these vectors, and the BRE is calculated as the average deviation of these vectors from the fitted rigid registration. A lower BRE indicates better rigidity preservation. We evaluated the BRE for 6 DIR algorithms on 32 patients with 137 computed tomography (CT)-to-CT registrations across relevant anatomical sites.</div></div><div><h3>Results:</h3><div>The BRE varied widely between DIR algorithms, up to a factor of 3 on average for inhale-to-exhale thoracic CT registration. Despite large BRE differences between anatomical sites within each algorithm, some algorithms consistently outperformed others. Notably, a low BRE was not correlated with poorer image similarity, and the BRE was only weakly correlated to target registration error. Furthermore, we proposed bone-specific inspection thresholds for patient-specific validation. BRE calculation required less than 5.5 s.</div></div><div><h3>Conclusions:</h3><div>The BRE is an automatic, interpretable, fast, and easy-to-implement metric to assist validation of DIR algorithms, which show widely varying performance. It provides a useful complementary metric for patient-specific validation, especially in time-sensitive applications.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100767"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904515","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":"Comparing methods to improve cone-beam computed tomography for dose calculations in adaptive proton therapy","authors":"Casper Dueholm Vestergaard ,&nbsp;Nadine Vatterodt ,&nbsp;Ulrik Vindelev Elstrøm ,&nbsp;Kenneth Jensen ,&nbsp;Ole Nørrevang ,&nbsp;Ludvig Paul Muren ,&nbsp;Stine Sofia Korreman ,&nbsp;Vicki Trier Taasti","doi":"10.1016/j.phro.2025.100784","DOIUrl":"10.1016/j.phro.2025.100784","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Proton therapy requires dose monitoring, often performed based on repeated computed tomography (reCT) scans. However, reCT scans may not accurately reflect the internal anatomy and patient positioning during treatment. In-room cone-beam CT (CBCT) offers a potential alternative, but its low image quality limits proton dose calculation accuracy. This study therefore evaluated different methods for quality-improvement of CBCTs (synthetic CTs; sCTs) for use in adaptive proton therapy of head-and-neck cancer patients.</div></div><div><h3>Materials and methods</h3><div>Thirty-five CBCTs from twenty-four head-and-neck cancer patients were used to assess four sCT generation methods: an intensity-correction method, two deformable image registration methods, and a deep learning-based method. The sCTs were evaluated against same-day reCTs for CT number accuracy, proton range accuracy through single-spot plans, and dose recalculation accuracy of clinical plans via dose-volume-histogram (DVH) parameters.</div></div><div><h3>Results</h3><div>All four methods generated sCTs with improved image quality while preserving the anatomy relative to the CBCT. The differences in absolute median proton range between sCT methods were small and generally less than the difference between sCT and reCT, which had median differences of 1.0–1.1 mm. Similarly, differences in DVH parameters were generally small between the sCT methods. While outliers were identified for all four methods, these outliers were often consistent for all sCT methods and could be attributed to anatomical and/or positional discrepancies between the CBCT and reCT.</div></div><div><h3>Conclusions</h3><div>All four sCT methods enabled accurate proton dose calculation and preserved the anatomy, making them of value for adaptive proton therapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100784"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144088929","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 prompt gamma verification for cone-beam computed tomography-based online adaptive proton therapy","authors":"Stefanie Bertschi ,&nbsp;Kristin Stützer ,&nbsp;Jonathan Berthold ,&nbsp;Ulrik Elstrøm ,&nbsp;Anne Vestergaard ,&nbsp;Giuliano Perotti Bernardini ,&nbsp;Gabriel Marmitt ,&nbsp;Guillaume Janssens ,&nbsp;Julian Pietsch ,&nbsp;Stefan Both ,&nbsp;Stine Korreman ,&nbsp;Christian Richter","doi":"10.1016/j.phro.2025.100778","DOIUrl":"10.1016/j.phro.2025.100778","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Prompt-gamma based <em>in vivo</em> treatment verification, such as prompt-gamma imaging (PGI), is crucial for detecting anatomical changes and serving as safety net during proton therapy treatments. This is especially important in an online-adaptive setting, when imaging will be based on cone-beam computed tomography (CBCT). This study investigated whether PGI, proven effective to detect relevant anatomical changes in clinical settings, can also verify treatment plans adapted on CBCTs, particularly the reliability of CBCT-based PGI-simulations of expected prompt-gamma distributions, a key requirement for PGI-based verification.</div></div><div><h3>Material and methods</h3><div>For a homogeneous and anthropomorphic phantom, a fan-beam computed tomography (CT) and a CBCT were acquired. Corrected CBCT and virtual CT datasets were generated. PGI simulations and independent dose calculations were performed on the different CBCT datasets and compared to the fan-beam CT, extracting PGI-based and integrated-depth-dose (IDD)-based range-shifts. For three head-and-neck cancer patients, PGI-based shifts between the fan-beam CT and a synthetic CT (from a daily CBCT) were compared to line-dose-based shifts from clinical dose calculations.</div></div><div><h3>Results</h3><div>For the homogeneous phantom, all CBCT datasets enabled adequate PGI simulations, with PGI-based shifts correlating very closely with IDD-based shifts. For the anthropomorphic phantom and the three patient datasets, observed PGI-based shifts were correlated to IDD-based shifts.</div></div><div><h3>Conclusions</h3><div>For phantom and patient data, PGI simulations depended mainly on the reliability of depth-dose distributions on the planning image with negligible uncertainties from PG emission. For CBCT-based OAPT, correct depth-dose distributions are required. Hence, PGI is also a promising treatment verification tool for CBCT-based OAPT.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100778"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941761","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":"Transmission beam planning for improved robustness and efficiency in proton therapy for head and neck cancer","authors":"Alessandro Vai ,&nbsp;Alfredo Mirandola ,&nbsp;Vittoria Pavanello ,&nbsp;Giuseppe Magro ,&nbsp;Matteo Bagnalasta ,&nbsp;Luca Trombetta ,&nbsp;Anna Maria Camarda ,&nbsp;Rossana Ingargiola ,&nbsp;Sara Ronchi ,&nbsp;Anna Cavallo ,&nbsp;Marzia Franceschini ,&nbsp;Andrea Riccardo Filippi ,&nbsp;Nicola Alessandro Iacovelli ,&nbsp;Mario Ciocca ,&nbsp;Ester Orlandi","doi":"10.1016/j.phro.2025.100777","DOIUrl":"10.1016/j.phro.2025.100777","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Optimizing head and neck cancer (HNC) plans with single-energy proton beams that fully traverse the patient (transmission beams) can improve robustness and delivery efficiency, complementing conventional approaches.</div></div><div><h3>Materials and Methods</h3><div>Experimental measurements, validated with Monte Carlo (MC) simulations, were carried out on a uniform water-equivalent plastic phantom (RW3) containing a metal component (2-Euro coins) irradiated with a single high energy proton field (228.6 MeV) to verify the transmission beam concept. 28 nasopharyngeal cancer (NPC) intensity modulated proton therapy (IMPT) were then optimized with nine coplanar single-energy fields (228.6 MeV), positioning the Bragg peaks well beyond the patient body, so called transmission beam mode. These plans (IMPT-TB) were compared to conventional IMPT and volumetric modulated arc therapy (VMAT) photon plans in terms of dose distributions quality, expected organ at risk (OAR) toxicity, robustness and delivery time.</div></div><div><h3>Results</h3><div>Transmission beams minimized dose perturbation by metal objects (∼7% max relative variation at 18 cm depth). IMPT-TB plans achieved comparable dose distribution and expected toxicities to IMPT, increasing the dose bath (+96 % vs. IMPT) but remaining significantly lower than VMAT (−31.4 %). For 94 % of patients (N = 26), IMPT-TB met at least one additional dose constraint that the corresponding IMPT plan failed to satisfy. Moreover, in the analyzed subgroup (N = 5), IMPT-TB plans delivered with our synchrotron exhibit a 67 % reduction in beam time compared to IMPT plans.</div></div><div><h3>Conclusions</h3><div>IMPT-TB plans demonstrated enhanced robustness and significantly faster delivery compared to IMPT. Transmission beams could be clinically implemented, also in conjunction with standard IMPT, for proton radiation treatment of NPC.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100777"},"PeriodicalIF":3.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941194","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}