Physics and Imaging in Radiation Oncology最新文献

{"title":"Repeatability and reproducibility of MRI-derived radiomics on a 0.35 T MR-Linac using a tissue-mimicking phantom","authors":"Florian Collard,&nbsp;Fanny Herault,&nbsp;Ludovic Vanquin,&nbsp;Anne-Laure Gagez,&nbsp;Alain Loussert,&nbsp;Dominique Collard,&nbsp;David Pasquier","doi":"10.1016/j.phro.2026.101035","DOIUrl":"10.1016/j.phro.2026.101035","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Magnetic resonance–guided radiotherapy provides real-time soft-tissue–based targeting during dose delivery. Beyond image guidance, magnetic resonance linear accelerator (MR-Linac) systems offer new opportunities for developing magnetic resonance imaging (MRI)-derived radiomics biomarkers. However, the reproducibility of these biomarkers in a low-field MR-Linac environment remains unclear.</div></div><div><h3>Materials and methods</h3><div>This study evaluated the repeatability and reproducibility of MRI-derived radiomic features acquired on a 0.35 T MR-Linac using a tissue-mimicking phantom containing multiple tissue-equivalent materials. Fifty balanced steady-state free precession acquisitions were performed over 10 sessions, enabling both intra- and inter-session analyses. Forty-eight preprocessing pipelines combining normalization, discretization, and bias-field correction were assessed using the coefficient of variation and intraclass correlation coefficient for 68 radiomic features across 12 defined regions of interest.</div></div><div><h3>Results</h3><div>The combination of N4 bias correction and z-score normalization yielded the highest overall stability, with several first-order (e.g. Entropy, Mean) and texture-based (e.g. glcm_DifferenceEntropy and glrlm_ShortRunEmphasis) features showing a coefficient of variation &lt;5% and/or an intraclass correlation coefficient (2,1) &gt; 0.85 across phantom materials. Stability varied with phantom composition, with higher reproducibility in homogeneous PVP-40 and water inserts compared to fat or fibroglandular compartments. Comparison with previous 0.35 T MR-Linac studies identified a consistent subset of robust features, supporting their potential as standardized MRI-derived radiomic biomarkers.</div></div><div><h3>Conclusions</h3><div>These findings demonstrated the critical role of preprocessing and tissue composition in feature reproducibility and highlighted the importance of tissue-mimicking phantoms for validating MR-Linac-based quantitative imaging pipelines.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101035"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148477866","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":"Development of a cost-effective end-to-end commissioning test for simulation-omitted direct-to-unit adaptive radiotherapy","authors":"Da Wang,&nbsp;Justin Visak,&nbsp;Sean Domal,&nbsp;Zhisheng Tong,&nbsp;Viktor Iakovenko,&nbsp;Tsuicheng Chiu,&nbsp;Andrew Godley,&nbsp;David Parsons,&nbsp;Mu-Han Lin","doi":"10.1016/j.phro.2026.101028","DOIUrl":"10.1016/j.phro.2026.101028","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Direct-to-Unit (simulation-omitted) adaptive radiotherapy (ART) enables same-day treatment by generating treatment plans from diagnostic images, eliminating the need for computed tomography (CT) simulation. These workflows rely on online plan re-optimization to account for anatomical, CT-number, and setup variations. However, no standardized end-to-end (E2E) credentialing protocol currently exists to validate the accuracy of Direct-to-Unit ART. Although customized ART phantoms are available, they are often costly, and impractical for one-time commissioning. To address this gap, we developed a low-cost E2E commissioning framework using a commercially available CIRS ZEUS phantom to verify workflow accuracy while minimizing financial burden.</div></div><div><h3>Materials and Methods</h3><div>E2E commissioning tests were performed on Varian Ethos and Elekta Unity systems using a CIRS ZEUS phantom (Model 008Z) equipped with inserts for ionization chamber point-dose and planar film measurements. The ionization chamber and Gafchromic EBT4 films were independently cross-calibrated on an Elekta Versa linear accelerator. Pseudo–diagnostic CT datasets were generated and deformed to simulate anatomical variation. Pre-plans (2 Gy × 30 fractions) were created and delivered across three ART fractionation schemes. Point-dose measurements were compared with system-reported values, and planar dose distributions were evaluated using global gamma analysis.</div></div><div><h3>Results</h3><div>All point-dose differences were within 3% (for high-dose regions) or 3 cGy (for low-dose regions) of the system-reported values. All planar film measurements achieved gamma pass rates exceeding 90% using 3%/3 mm criterion.</div></div><div><h3>Conclusion</h3><div>This cost-effective E2E approach provides a practical commissioning solution for Direct-to-Unit ART, supporting safe clinical implementation and facilitating cross-institutional standardization.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101028"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148477915","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":"Quantifying manual editing time in autocontouring via audit log analysis","authors":"Geert De Kerf,&nbsp;Gabriele Balletti,&nbsp;Nina Menten,&nbsp;Michaël Claessens,&nbsp;Thibaut D'homme,&nbsp;Joachim Marichal,&nbsp;Mark J. Gooding,&nbsp;Dirk Verellen","doi":"10.1016/j.phro.2026.101059","DOIUrl":"10.1016/j.phro.2026.101059","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Artificial intelligence (AI)-based contouring reduces delineation workload, yet manual corrections remain required. Reliable, scalable quantification of structure-level editing time is needed to evaluate clinical usability beyond geometric similarity metrics as geometric metrics may not reflect how tooling impacts edit time.</div></div><div><h3>Materials and methods</h3><div>This retrospective observational study analysed 3083 AI-generated, edited structures created in routine practice. Structure-modifying actions were extracted from the treatment planning system audit log database and converted to per-structure editing time by summing inter-event intervals. Automatic times were benchmarked against manual time recordings for 54 structures across 8 patient cases using Lin's concordance correlation coefficient (CCC). Added path length (APL) between AI and corrected contours was computed, and the associations between editing time, APL and tooling (interpolation use) were investigated using Spearman's correlation coefficient.</div></div><div><h3>Results</h3><div>Audit log–derived editing time agreed well with manual timing (CCC = 0.93). In the full cohort, 3083/24970 structures were edited (12% correction rate). Brush tools were used in 80% and contour interpolation in 42% of edited structures. Median editing time and APL were higher with interpolation than without (81 s vs 58 s; 232 mm vs 18 mm; both <em>p</em> &lt; 0.05), and correlation between editing time and APL was fair (<em>r</em> = 0.38 vs 0.51).</div></div><div><h3>Conclusions</h3><div>Vendor audit logs could be translated into accurate structure-level editing time estimates, enabling low-burden monitoring of manual workload. Editing strategy influenced time–geometry relationships, supporting log-based time endpoints alongside geometric metrics for meaningful auto-contouring evaluation.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101059"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148738715","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":"Longitudinal computed tomography body composition changes in patients receiving curative radiotherapy for non-small cell lung cancer","authors":"Ying Zhang,&nbsp;Sumeet Hindocha,&nbsp;Arjun K. Ghosh,&nbsp;Miguel Garrett Fernandes,&nbsp;Maria A. Hawkins,&nbsp;Charles-Antoine Collins Fekete","doi":"10.1016/j.phro.2026.101055","DOIUrl":"10.1016/j.phro.2026.101055","url":null,"abstract":"<div><h3>Background and purpose</h3><div>To determine whether longitudinal changes on routine thoracic computed tomography (CT) predict overall survival (OS) in non-small cell lung cancer (NSCLC) after curative radiotherapy and identify dose predictors of adverse tissue changes.</div></div><div><h3>Materials and methods</h3><div>We performed a retrospective, single-centre study of 231 stage I-IV NSCLC patients who had at least two follow-up scans. In total, 2708 CT scans were analysed (median follow-up, 22 months; range, 1–97). Automated segmentation quantified left ventricular (LV) myocardium, L1 skeletal muscle (SKM) and fat volumes. For each tissue, baseline-normalised trajectories were used to compute monthly rates of change (“velocity”), and non-linear associations with OS were evaluated. Logistic regression identified dose metrics associated with adverse tissue change.</div></div><div><h3>Results</h3><div>SKM velocity stratified OS (C-index, 0.70): SKM loss &lt; −0.4%/month vs ≥ −0.4%/month, HR 4.41 (95% CI 2.46–7.91, <em>p</em> &lt; 0.005). LV-myocardial mass velocity showed a U-shaped relationship with OS (C-index, 0.75): atrophy &lt; −0.3%/month vs stable, HR 4.12 (95% CI 1.65–10.27, <em>p</em> &lt; 0.005); hypertrophy &gt;0.3%/month vs stable, HR 7.90 (95% CI 2.82–22.15, p &lt; 0.005). Dose predictors included oesophagus V_10Gy for SKM loss (OR, 1.40; <em>p</em> = 0.03), Aorta V_5Gy for myocardial atrophy (OR, 1.71; <em>p</em> = 0.02), and right-atrium V_10Gy for myocardial hypertrophy (OR, 1.63; p = 0.02).</div></div><div><h3>Conclusion</h3><div>Longitudinal CT biomarkers, particularly SKM loss rate and deviation in LV-myocardial mass, are associated with OS after curative NSCLC irradiation. These findings require validation in multicentre studies with more complete clinical information.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101055"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148739230","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":"Radiomic analysis of pathologically confirmed mandibular osteoradionecrosis to identify cases with associated recurrence: a multicentric retrospective study","authors":"Olivier Ozcan,&nbsp;Remy Laluc,&nbsp;Aline Carsin-Vue,&nbsp;Nathaniel Assouly,&nbsp;Esteban Brenet,&nbsp;Antonio Da Silva Ribeiro Mota,&nbsp;Stephane Derruau,&nbsp;Marine Fontaine,&nbsp;Camille Invernizzi,&nbsp;Oriane Marques,&nbsp;Nicolas Passat,&nbsp;Arnaud Beddok","doi":"10.1016/j.phro.2026.101031","DOIUrl":"10.1016/j.phro.2026.101031","url":null,"abstract":"<div><div>Differentiating mandibular osteoradionecrosis (ORN) from tumor recurrence remains challenging on preoperative imaging. We conducted a multicenter retrospective study including 24 patients with histologically confirmed ORN who underwent surgery and had preoperative CT available. Radiomic features were extracted using an IBSI-compliant pipeline and compared between pure ORN (<em>n</em> = 21) and ORN with recurrence (<em>n</em> = 3). Three features showed nominal uncorrected differences between groups. Given the rarity of histologically confirmed recurrence, this study was designed as an exploratory hypothesis-generating analysis. These findings suggest that CT radiomics may capture subtle imaging differences and warrant validation in larger cohorts.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101031"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148658293","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":"Integrating computed tomography image features improves clinical prediction models for outcomes in nasopharyngeal carcinoma patients treated with (chemo)radiation","authors":"Guanzhi Zhou,&nbsp;Baoqiang Ma,&nbsp;Yan Li,&nbsp;Pei Yang,&nbsp;Yingrui Shi,&nbsp;Arjen van der Schaaf,&nbsp;Lisanne V. van Dijk,&nbsp;Johannes A. Langendijk,&nbsp;Nanna M. Sijtsema","doi":"10.1016/j.phro.2026.101040","DOIUrl":"10.1016/j.phro.2026.101040","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Clinical prognostic models for nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiotherapy (IMRT) with or without chemotherapy remain insufficient to capture tumour heterogeneity. We investigated whether computed tomography (CT)-based signatures add prognostic value for overall survival, progression-free survival, local control and distant control in NPC patients.</div></div><div><h3>Materials and methods</h3><div>The study population consisted of 1360 patients with stage I–IVa NPC treated with (chemo)IMRT (2013–2017). Radiomic and deep-learning features were analysed with twelve clinical variables. Radiomic models were built using bootstrap resampling feature selection and multivariable Cox regression; deep-learning models used 3D ResNet-18 or DenseNet-121. Models were evaluated on an internal hold-out test set (<em>n</em> = 409; training set <em>n</em> = 951) with the concordance index and compared against clinical-only reference models. Decision curve analysis was used to assess clinical utility.</div></div><div><h3>Results</h3><div>Adding radiomic primary tumour features (Neighbouring Gray Tone Difference Matrix - coarseness) improved local control concordance index from 0.51 to 0.60 (<em>p</em> = 0.02). A DenseNet-121 combining clinical data with composite primary tumour and lymph node masks achieved the highest distant control (0.68 vs 0.66, <em>p</em> = 0.01). For overall survival and progression-free survival, the improvements were not significant. Decision curve analysis demonstrated net benefit of the DenseNet-121 distant control model over treat-all and treat-none strategies at threshold probabilities of 10–25%.</div></div><div><h3>Conclusions</h3><div>Incorporating CT-based radiomic and deep-learning features into prognostic models significantly improved prediction of local and distant control in NPC, supporting their potential as imaging biomarkers for refined risk stratification.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101040"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13416826/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148621641","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 review on radiological properties of fused deposition modelling material for three-dimensional printing in proton and light ion beam therapy","authors":"Christina Stengl,&nbsp;Christina Mooshammer,&nbsp;Jonas Mahnke,&nbsp;Armin Runz,&nbsp;José Vedelago","doi":"10.1016/j.phro.2026.101042","DOIUrl":"10.1016/j.phro.2026.101042","url":null,"abstract":"<div><h3>Background and Purpose:</h3><div>Fused Deposition Modelling (FDM) three-dimensional (3D) printing offers a flexible and economical method for producing radiotherapy phantoms with tailored geometries and material properties. While numerous studies have focused on imaging or photon radiotherapy, research on 3D printing for proton and light ion beam therapy remains limited. Accurate knowledge of the radiological properties of FDM-printed materials is crucial to ensure reliable dose calculation and treatment planning in ion beam therapy.</div></div><div><h3>Materials and Methods:</h3><div>A comprehensive literature review was conducted to identify publications reporting relevant radiological parameters, including mass density, computed tomography (CT) number given in Hounsfield units (HU), electron density, and stopping power, for FDM printing filaments. Based on the collected data, an FDM lookup table was generated, summarising the radiological properties of these materials across different printing settings.</div></div><div><h3>Results:</h3><div>A total of 17 material classes comprising 70 distinct filaments were analysed and indexed in an open-access lookup table. Polylactic acid (PLA) was the most frequently investigated material, reported in over 34 publications. Among the investigated radiological parameters, the CT number showed the greatest variability for a given material. For samples printed at 100% infill, values ranged from -180 HU to 227 HU for PLA. Recommendations for reducing this variability through standardised reporting are provided.</div></div><div><h3>Conclusion:</h3><div>This review provides an overview of FDM 3D printing materials in ion beam therapy. It serves as a practical reference for clinical personnel, medical physicists, and researchers in selecting suitable materials for radiotherapy applications. Moreover, it highlights the need for standardised characterisation methodologies and 3D printing guidelines.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101042"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13416827/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148621598","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":"Base of tongue volume and dose as predictors of late dysphagia after definitive or adjuvant radiotherapy for oral cavity squamous cell carcinoma","authors":"Joseph Azria,&nbsp;Arnaud Beddok,&nbsp;Esteban Brenet,&nbsp;Delphine Antoni,&nbsp;Laurence Auzeau,&nbsp;Nathaniel Assouly,&nbsp;Marine Fontaine,&nbsp;Sofiane Guendouzen,&nbsp;Jean-Claude Merol,&nbsp;Yacine Merrouche,&nbsp;Philippe Guilbert,&nbsp;Antonio Da Silva Ribeiro Mota","doi":"10.1016/j.phro.2026.101038","DOIUrl":"10.1016/j.phro.2026.101038","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Radiation-induced dysphagia is a major determinant of quality of life in patients treated for oral cavity squamous cell carcinoma (OCSCC). While dose to the pharyngeal constrictor muscles has been extensively investigated, the base of tongue (BOT) remains poorly studied. This study aimed to evaluate the association between BOT volume and dose–volume parameters and late dysphagia.</div></div><div><h3>Material and methods</h3><div>Fifty-two patients with OCSCC treated with volumetric modulated arc therapy (VMAT) between 2019 and 2023 were retrospectively analyzed. All patients had a prophylactic feeding tube (FT) placed before VMAT. The base of tongue was delineated using an artificial intelligence-based segmentation algorithm and reviewed by a senior radiation oncologist. Late dysphagia was defined as prolonged FT dependency using the cohort-specific 75th percentile (&gt; 442.5 days). Volumetric and dose/volume parameters of the BOT (D_0%–D_100%) were analyzed using logistic regression, receiver operating characteristic (ROC) curve analysis, and Kaplan–Meier methods.</div></div><div><h3>Results</h3><div>The median BOT volume for the entire cohort was 18.4 cm³ (interquartile range [IQR]: 15.7–21.3 cm³). Patients with late dysphagia had smaller BOT volumes than those without (15.9 vs. 19.5 cm³, <em>p</em> = 0.02). A BOT volume &lt; 19.12 cm³ was associated with increased dysphagia risk. No dose/volume parameter reached statistical significance, although a trend suggested lower risk for a BOT D_50% &lt; 52.2 Gy (<em>p</em> = 0.21). A combined model integrating BOT volume and D_50% achieved an area under the curve (AUC) of 0.74 (95% CI: 0.61–0.87).</div></div><div><h3>Conclusions</h3><div>Smaller BOT volume was associated with increased risk of prolonged FT dependency after radiotherapy for OCSCC. BOT dose metrics were not significant but showed hypothesis-generating trends that warrant validation in larger cohorts and dose-optimization studies.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101038"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148658294","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":"Assessment of planning organ at risk volume margins in non-adaptive pancreatic stereotactic body radiotherapy","authors":"Maxwell Robinson,&nbsp;Ahmed Eltinay,&nbsp;Ben George,&nbsp;Robert Owens,&nbsp;James Good,&nbsp;Somnath Mukherjee,&nbsp;Rebecca Muirhead","doi":"10.1016/j.phro.2026.101043","DOIUrl":"10.1016/j.phro.2026.101043","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Organ at risk (OAR) motion results in increased risk of radiotherapy treatment side effects due to the potential for greater dose than intended being delivered. This is of particular concern in stereotactic ablative body radiotherapy (SABR). The study aim was to assess the role of planning organ at risk volume (PRV) margins applied to OARs of the gastrointestinal (GI) tract over five fraction non-adaptive SABR for pancreatic cancer.</div></div><div><h3>Materials and Methods</h3><div>The clinical adaptive magnetic resonance-guided radiotherapy baseline planning for 10 patients was combined with retrospective replanning respecting constraints to OAR plus a margin of 2–5 mm. Baseline planning/replanning was applied to OAR contouring at treatment fractions without plan adaptation. The impact of PRV margin was assessed in terms of the encompassing of OAR motion, effect on delivered dose, and degree of associated compromise in planned treatment volume (PTV) dose coverage.</div></div><div><h3>Results</h3><div>Whilst variable across individual OARs, a 2–5 mm margin poorly encompassed motion in 40–70% of fractions. However, a 2–5 mm margin did effectively limit dose increases in most cases such that delivered biological effective dose (BED) did not exceed, on average, the baseline value. A margin of 2–3 mm resulted in minor PTV compromise (D_70% median PTV BED decrease &lt;10 Gy), whereas a 5 mm margin resulted in moderate compromise (D_70% median PTV BED decrease ∼20 Gy).</div></div><div><h3>Conclusions</h3><div>A PRV margin of 2–5 mm for OARs limits the increase in delivered dose. Consideration of such a margin is relevant in optimizing non-adaptive treatment practice.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101043"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148658295","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":"Retrospective intrafraction motion verification using triggered kilovoltage images during bone metastases stereotactic body radiotherapy","authors":"Quentin Techer,&nbsp;Noé Grandgirard,&nbsp;Saturnin Sandjong,&nbsp;Vincent Marchesi,&nbsp;Paul Retif","doi":"10.1016/j.phro.2026.101054","DOIUrl":"10.1016/j.phro.2026.101054","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Triggered kilovoltage images acquired during radiotherapy delivery remain underexploited for quantitative intrafraction motion analysis. This study aimed to develop and evaluate a retrospective workflow for intrafraction motion verification using triggered kilovoltage images during bone metastases stereotactic body radiotherapy.</div></div><div><h3>Materials and methods</h3><div>Triggered kilovoltage images and corresponding treatment-planning data were retrospectively extracted from 49 patients treated in two radiotherapy centers. For each triggered image, a digitally reconstructed radiograph was generated from planning computed tomography dataset. After preprocessing, rigid in-plane registration between triggered images and digitally reconstructed radiographs was performed. The workflow was evaluated using phantom experiments with known physical displacements and patient datasets with simulated shifts, then applied to 8717 triggered images acquired during 183 treatment fractions.</div></div><div><h3>Results</h3><div>Correct registration was obtained for 7105 images (81.5%), while 1612 images (18.5%) were classified as aberrant and excluded from motion analysis. After exclusion, the mean displacement vector magnitude was 1.2 ± 0.8 mm. Overall, 85% of measurements showed displacements ≤2 mm and 98% showed displacements ≤3 mm. Sustained displacement events exceeding 2 mm over three consecutive images were observed in 405 of 7105 images (5.7%) and in 46 of 159 analyzable fractions (28.9%). The mean computation time per image registration was 1699 ± 504 ms.</div></div><div><h3>Conclusions</h3><div>Triggered kilovoltage images contain quantitative information that can support retrospective intrafraction motion assessment during bone metastases stereotactic body radiotherapy. This workflow may help identify fractions requiring further review and support offline quality assurance, although prospective validation is required before clinical implementation.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"40 ","pages":"Article 101054"},"PeriodicalIF":3.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148738714","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}