Physics and Imaging in Radiation Oncology最新文献

{"title":"Prospective validation of a pretreatment 18F-FDG PET/CT and mean lung dose model for early radiation pneumonitis","authors":"Maria Thor ,&nbsp;Aditya Apte ,&nbsp;Milan Grkovski ,&nbsp;Charles B. Simone II ,&nbsp;Daphna Y. Gelblum ,&nbsp;Masoud Zarepisheh ,&nbsp;Puneeth Iyengar ,&nbsp;Abraham J. Wu ,&nbsp;Jacob Y. Shin ,&nbsp;Tafadzwa Chaunzwa ,&nbsp;Jennifer Ma ,&nbsp;David Billing ,&nbsp;Mark Dunphy ,&nbsp;Jamie E. Chaft ,&nbsp;Daniel R. Gomez ,&nbsp;Joseph O. Deasy ,&nbsp;Narek Shaverdian","doi":"10.1016/j.phro.2025.100844","DOIUrl":"10.1016/j.phro.2025.100844","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Early onset radiation pneumonitis (RP_Early) after concurrent chemoradiotherapy (cCRT) can lead to consolidation immunotherapy (IO) discontinuation, and poor survival in locally advanced non-small cell lung cancer (LA-NSCLC). This work assessed the external validity of a previously published RP_Early risk model.</div></div><div><h3>Material and methods</h3><div>The RP_Early risk model utilizes pretreatment 18F-FDG PET/CT imaging of the normal lungs and the mean lung dose (MLD). The 90th percentile of the standardized uptake value (SUV_P90) and the MLD model parameters from the previous derivation cohort (N = 160) were applied in the independent cohort (50 consecutive LA-NSCLC patients treated with cCRT and IO) where model performance was evaluated (area under the receiver-operating characteristic curve (AUC), <em>p-values</em>, and the Hosmer-Lemeshow test (<em>pHL</em>)).</div></div><div><h3>Results</h3><div>Seven patients (14 %) developed RP_Early. Model performance of the previously developed SUV_P90 and MLD model improved with re-fitting (AUC = 0.76 <em>vs.</em> 0.72; p = 0.01 <em>vs.</em> 0.10; pHL = 0.66 <em>vs.</em> 0.94). Above a clinically desirable 10 % predicted RP_Early, after refitting model coefficients in the combined derivation and validation cohorts (N = 210), the MLD was 13 ± 2.2 EQD2₃ Gy (SUV_P90 = 1.2 ± 0.3) above the RP_Early risk threshold <em>vs.</em> 8.5 ± 2.6 EQD2₃ Gy (0.9 ± 0.2) below the threshold. For an SUV_P90 of 1.1 and an MLD of 11 Gy EQD2₃ Gy, 25/27 patients developing RP_Early were captured.</div></div><div><h3>Conclusion</h3><div>The previously developed SUV_P90 and MLD-based risk model for RP_Early demonstrated a high probability to correctly predict RP_Early in the independent cohort. This now validated RP_Early risk model with derived high-risk indications could enable personalized thoracic RT planning to reduce the risk of RP_Early and of discontinuing life-prolonging IO post-cCRT.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100844"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221817","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":"Leveraging dixon-based magnetic resonance imaging for pelvic bone marrow imaging in radiotherapy","authors":"Chuyan Wang ,&nbsp;Haoping Xu ,&nbsp;Zhenkui Wang ,&nbsp;Li Tong ,&nbsp;Xijing Zhang ,&nbsp;Fuhua Yan ,&nbsp;Jiayi Chen ,&nbsp;Yingli Yang","doi":"10.1016/j.phro.2025.100841","DOIUrl":"10.1016/j.phro.2025.100841","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Pelvic radiotherapy-induced bone marrow (BM) damage adversely affects patient prognosis. Progress in BM-sparing radiotherapy is limited by the lack of standardized BM quantification and the inherent constraints of magnetic resonance spectroscopy (MRS), the current gold standard for BM magnetic resonance imaging (MRI). Proton density fat fraction (PDFF), derived from DIXON-based MRI, has emerged as an imaging biomarker for detecting BM changes. This study evaluated the potential of DIXON-based MRI in pelvic BM for radiotherapy.</div></div><div><h3>Materials and methods</h3><div>Three existing DIXON-based techniques were optimized and compared to establish clinical protocols. <em>In vitro</em> measurements were performed using fat phantoms calibrated against thermogravimetric analysis, while <em>in vivo</em> measurements were based on data from 30 volunteers with MRS serving as the reference standard. Quantitative accuracy was assessed using mean absolute error (MAE), repeatability via intra-class correlation coefficients (ICCs), and image quality using an ACR phantom.</div></div><div><h3>Results</h3><div>Comprehensive evaluation identified optimal parameters for each DIXON-based sequence. For <em>in vitro</em> measurements, the MAE for MRS was 3.5 % and the highest MAE across three optimized DIXON-based sequences was 5.9 %. For <em>in vivo</em> measurements, linear regressions between MRS and each of the optimized DIXON-based sequence resulted in R² ≥ 0.93 and MAE ≤ 7.6 %. All three optimized DIXON-based sequences demonstrated high repeatability (ICCs ≥ 0.97) and clearly visualized BM with varying fat fractions, with no consistently outperforming in image quality.</div></div><div><h3>Conclusion</h3><div>For BM assessment, this study demonstrated DIXON-based PDFF quantification achieved high accuracy, repeatability, and image quality, supporting its potential for radiotherapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100841"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221820","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":"Diffusion-weighted imaging-derived parameters as quantitative imaging biomarkers in magnetic resonance-guided radiotherapy: a systematic review","authors":"Jing Yuan ,&nbsp;Darren M.C. Poon ,&nbsp;Oi Lei Wong ,&nbsp;Cindy Xue ,&nbsp;Amy Tien Yee Chang ,&nbsp;Bin Yang","doi":"10.1016/j.phro.2025.100843","DOIUrl":"10.1016/j.phro.2025.100843","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Magnetic Resonance Linear Accelerators (MR-LINACs) have transformed radiotherapy by integrating high-resolution magnetic resonance imaging (MRI) with precise radiation delivery. Diffusion-Weighted Imaging (DWI)-derived parameters are promising non-invasive quantitative imaging biomarkers (QIBs) for MR-guided radiotherapy (MRgRT), primarily through apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models; however, their clinical utility and validation on MR-LINAC systems remain underexplored. This systematic review evaluates DWI’s technical development, validation, and clinical role in MRgRT using MR-LINACs.</div></div><div><h3>Material and methods</h3><div>Following PRISMA guidelines, PubMed/MEDLINE, Web of Science, and Scopus (2014–2024) were searched for English-language studies on DWI in MRgRT with MR-LINACs (0.35 T or 1.5 T). Eligible studies included technical and clinical research with phantoms, volunteers, or patients. Data on study characteristics, DWI protocols, validation metrics, and clinical endpoints were extracted and qualitatively synthesized; heterogeneity precluded <em>meta</em>-analysis.</div></div><div><h3>Results</h3><div>Thirty-four studies (11 at 0.35 T, 23 at 1.5 T) were included (29 prospective, 5 retrospective), with 28 involving patients (N = 484) across cancers. DWI, primarily via single-shot EPI (median time ∼4–5 min, b-values 0–2000 s/mm²), demonstrates robust technical feasibility (27 studies) and emerging clinical validity (8 studies, ∼212 patients). Most validation remains single-center; multi-center and cost-effectiveness data are lacking, and only one study systematically evaluated imaging-genomic correlation with IVIM.</div></div><div><h3>Discussion</h3><div>DWI on MR-LINACs is technically available, feasible, and clinically promising for MRgRT. However, its QIB potential is limited by inconsistent protocols, hardware constraints, and preliminary clinical validation. Standardized protocols, hardware upgrades, and rigorous multi-center trials are essential to establish DWI-derived parameters as reliable QIBs for MRgRT.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100843"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268550","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":"Evaluation and tuning of a commercial automated planning system for prostate radiotherapy","authors":"Antony Carver,&nbsp;Stuart Green","doi":"10.1016/j.phro.2025.100834","DOIUrl":"10.1016/j.phro.2025.100834","url":null,"abstract":"<div><h3>Background and Purpose:</h3><div>Artificial Intelligence (AI) based automated planning is increasing in popularity. Guidance has been published recommending approaches for the safe implementation and monitoring of these techniques. An evaluation of a commercial AI tool was undertaken and reported along with the specific methods used to evaluate, tune and monitor the plan quality.</div></div><div><h3>Materials and Methods:</h3><div>A total of 335 previously planned prostate patients were used to evaluate and commission a commercial AI based planning solution. The quality of the automatically produced plans was compared to previous practice using models inspired by existing research into knowledge based planning. A quantile regression based technique identified the most optimal historic plans to be used for model tuning. Finally, a control chart based method was validated for post-deployment monitoring of the produced plan quality.</div></div><div><h3>Results:</h3><div>The baseline model provided by the manufacturer was found to provide good plan quality overall with 9 out 15 plan quality metrics found to have lower variance after accounting for anatomy. Rectum sparing was found to be inferior to human generated plans. Two further iterations of the model were produced in collaboration with the manufacturer. Further iterations of the model resulted in comparable rectum sparing, a 0.02 mean difference in rectum V50 Gy, was achieved whilst maintaining much of the improved consistency.</div></div><div><h3>Conclusions:</h3><div>A method to implement the guidance for commissioning of automated and AI based planning tools is presented alongside a method for monitoring the subsequent plan quality. The final plan quality achieved was comparable to or better than the original plans following two revisions.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100834"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221821","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":"First experimental demonstration of magnetic resonance-guided multileaf collimator tracking for (ultra-)hypofractionated prostate radiotherapy","authors":"Prescilla Uijtewaal ,&nbsp;Pim T.S. Borman ,&nbsp;Peter L. Woodhead ,&nbsp;Hans C.J. de Boer ,&nbsp;Bas W. Raaymakers ,&nbsp;Martin F. Fast","doi":"10.1016/j.phro.2025.100828","DOIUrl":"10.1016/j.phro.2025.100828","url":null,"abstract":"<div><h3>Background and purpose:</h3><div>(Ultra-)hypofractionated radiotherapy is an effective treatment for localized prostate cancer, but intrafraction motion can increase toxicity and/or reduce treatment efficacy. Therefore, motion management is essential. This study explores magnetic resonance imaging (MRI)-guided multileaf collimator (MLC) tracking for 2-fraction prostate radiotherapy on an MR-linac.</div></div><div><h3>Materials and methods:</h3><div>We compared two MRI-guided MLC centroid tracking workflows, each using a different motion manager to derive and stream target positions to our in-house MLC tracking software. The first workflow relies on interleaved 2D (2.5D) cine-MRI, introducing minimal latency. In contrast, the second workflow utilized 3D cine-MRI, which operates at a relatively lower imaging frequency that introduces more latency.</div><div>For experimental validation, we used a motion phantom equipped with an integrated insert that combines film with plastic scintillation dosimetry. A 2x12 Gy 11-beam prostate intensity modulated radiotherapy plan was created for tracking deliveries.</div></div><div><h3>Results:</h3><div>The signal latency introduced by the motion managers was 0.6 s for 2.5D cine-MRI and 6.3 s for 3D cine-MRI. Despite this latency, MLC tracking effectively restored the planned dose, improving the 2%/2mm local gamma pass-rates from 21% (due to linear drift) to 89% (2.5D) and 91% (3D). Plastic scintillator measurements showed reduced dose deviations at the periphery of the clinical target volume from 13–64% (no tracking) to 0–11% (2.5D) and 2–26% (3D).</div></div><div><h3>Conclusion:</h3><div>Our experiments demonstrated the technical feasibility of 2.5D and 3D cine-MRI-based MLC tracking on an MR-linac for 2-fraction prostate radiotherapy, with both motion management strategies achieving comparable dosimetric improvements despite the difference in latency.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100828"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268547","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":"Identifying the optimal time point for adaptive re-planning in prostate cancer radiotherapy to minimise rectal toxicity using normal tissue imaging biomarkers","authors":"Zhuolin Yang ,&nbsp;David J. Noble ,&nbsp;Sarah Elliot ,&nbsp;Leila Shelley ,&nbsp;Thomas Berger ,&nbsp;Raj Jena ,&nbsp;Duncan B McLaren ,&nbsp;Neil G. Burnet ,&nbsp;William H. Nailon","doi":"10.1016/j.phro.2025.100850","DOIUrl":"10.1016/j.phro.2025.100850","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Adaptive radiotherapy (ART) in prostate cancer (PCa), although not yet standard practice, is typically triggered by inter-fractional anatomical changes that emerge progressively during treatment. This study investigates whether radiomics extracted before and during treatment can identify the optimal time point for re-planning, with the goal of reducing late rectal bleeding.</div></div><div><h3>Materials and methods</h3><div>This study included 187 PCa patients from the single-centre, prospectively collected VoxTox dataset (UK-CRN-ID-13716), treated with image-guided radiotherapy using TomoTherapy and daily MVCT. Patients received either 74 Gy in 37 fractions (N = 110) or 60 Gy in 20 fractions (N = 77). Radiomic features were extracted from pre-treatment planning CTs and daily MVCTs. Grade ≥ 1 rectal bleeding was assessed at 2 years post-treatment using CTCAE v4.03. Two analysis strategies were employed: a separate analysis, where weekly features were evaluated independently; and a cumulative analysis, which progressively incorporated features from previous weeks. Logistic regression models with elastic net penalty were trained and evaluated using AUC.</div></div><div><h3>Results</h3><div>In both groups, week 1 provided the highest standalone predictive performance (test AUC = 0.766 for 74 Gy; 0.734 for 60 Gy). In the cumulative analysis, week 3 was optimal for the 74 Gy group (test AUC = 0.767), balancing performance and timing. For the 60 Gy group, week 1 remained optimal but suffered from reduced generalisability (test AUC = 0.643).</div></div><div><h3>Conclusions</h3><div>Radiomic analysis of daily imaging can support early, proactive ART in PCa, offering a personalised strategy to reduce late rectal bleeding beyond conventional anatomy-based approaches.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100850"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268549","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":"A phantom study of internal target volume and mid-position accuracy in adaptive and conventional four-dimensional computed tomography across regular and irregular motion","authors":"Bart J.J. Kremers ,&nbsp;Dave S.C. van Gruijthuijsen ,&nbsp;Dominique Reijtenbagh ,&nbsp;Jacco L.G. Steenhuijsen ,&nbsp;Mariska de Smet ,&nbsp;Rob H.N. Tijssen","doi":"10.1016/j.phro.2025.100845","DOIUrl":"10.1016/j.phro.2025.100845","url":null,"abstract":"<div><div>This technical note evaluates the performance of an adaptive four-dimensional computed tomography (4DCT) acquisition method compared to conventional 4DCT using a motion phantom. Metrics assessed include deviations in volume, CT number, diameter, peak-to-peak amplitude and determination of the internal target volume (ITV) and mid-position. Under regular breathing, most measurements fall within predefined clinical tolerances for all systems. Under irregular motion, the adaptive method showed reduced deviations in ITV and minimal impact on mid-position determination. These findings support the clinical value of adaptive 4DCT in improving motion management and target definition accuracy in radiotherapy planning.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100845"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268548","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":"Dynamic proton arc treatment planning study for oesophageal cancer","authors":"Macarena Chocan Vera ,&nbsp;Anne-Catherine Wéra ,&nbsp;Hamdiye Ozan ,&nbsp;Erik Engwall ,&nbsp;Viktor Wase ,&nbsp;Otte Marthin ,&nbsp;Johan Sundström ,&nbsp;Sophie Wuyckens ,&nbsp;Karin Haustermans ,&nbsp;Ana M. Barragán-Montero ,&nbsp;Kevin Souris ,&nbsp;John A. Lee ,&nbsp;Edmond Sterpin","doi":"10.1016/j.phro.2025.100837","DOIUrl":"10.1016/j.phro.2025.100837","url":null,"abstract":"<div><div>Particle Arc Therapy (PAT) is considered a promising technique to improve conformity and reduce toxicities. Robustly optimized PAT plans were evaluated versus Intensity Modulated Proton Therapy (IMPT) for oesophageal cancer in 17 patients. Impact of motion, setup and range uncertainties on target coverage, plan quality and Organs At Risk (OAR) doses were assessed. PAT (two 80°–200°arcs) reduced OAR doses (spinal canal <span><math><msub><mrow><mi>D</mi></mrow><mrow><mn>0</mn><mo>.</mo><mn>05</mn><msup><mrow><mtext>cm</mtext></mrow><mrow><mn>3</mn></mrow></msup></mrow></msub></math></span>: 5.12 Gy (12.8%), lungs and heart <span><math><msub><mrow><mi>D</mi></mrow><mrow><mtext>mean</mtext></mrow></msub></math></span>: 0.39 Gy (8.8%) and 0.83 Gy (10.5%)) while maintaining robustness. Similar toxicities were observed, but delivery time was doubled for PAT, indicating that further development is needed.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100837"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221814","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":"Integrating dose–volume histogram parameters and radiomics-based machine learning to identify carbon ion radiotherapy-induced acute oral mucositis in patients with head and neck cancer","authors":"Xiangdi Meng ,&nbsp;Zhuojun Ju ,&nbsp;Makoto Sakai ,&nbsp;Yang Li ,&nbsp;Atsushi Musha ,&nbsp;Nobuteru Kubo ,&nbsp;Hidemasa Kawamura ,&nbsp;Tatsuya Ohno","doi":"10.1016/j.phro.2025.100842","DOIUrl":"10.1016/j.phro.2025.100842","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Acute oral mucositis (AOM) is a critical adverse event in head and neck cancer (HNC) requiring early intervention during carbon ion radiotherapy (CIRT). Considering external irradiation and internal mucosal heterogeneity, this study developed a classification model integrating maximum dose (Dmax) and dose-volume-based radiomics (RaV_x) for early identification of grade ≥ 2 AOM.</div></div><div><h3>Methods and materials</h3><div>We retrospectively analyzed 190 HNC patients treated with CIRT (training: test = 7:3). Radiomic features were extracted from the entire oral mucosa and dose-specific subregions [RaV_x, 10–50 Gy(RBE) in 10-Gy increments]. Feature selection employed logistic regression, random forest, and XGBoost, followed by Spearman’s correlation test. Six two-stage models were developed: Stage 1 stratified patients into high- and low-dose groups using a Dmax threshold (Dmax model), while Stage 2 further classified high-dose patients using a support vector machine (SVM) with selected RaV_x features (RaV_x-SVM model). Classification performance was assessed in training and test sets using bootstrap validation.</div></div><div><h3>Results</h3><div>Grade ≥ 2 AOM occurred in 61.6 % of patients. The Dmax model with a 50 Gy(RBE) threshold achieved 87.2 % accuracy but had a high false-positive rate (FPR = 31.4 %). The RaV_x-SVM model reduced false positives, with the RaV_{40 Gy(RBE)}-SVM-model performing best. The integrated Dmax₅₀&amp;RaV_{40 Gy(RBE)}-SVM model achieved 97.0 % accuracy (FPR 2.0 %) in training and 96.5 % mean accuracy (mean FPR 4.7 %) in the test.</div></div><div><h3>Conclusions</h3><div>Dose-volume radiomics effectively identified low-risk AOM patients in the high-dose group. The integrated model demonstrated high accuracy in identifying HNC patients with grade ≥ 2 AOM during CIRT.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100842"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221819","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":"Radiological response assessment after stereotactic body radiotherapy for spine metastases using magnetic resonance imaging: a systematic review","authors":"Keivan Daneshvar ,&nbsp;Mohammadamin Shahrbaf ,&nbsp;Johannes Heverhagen ,&nbsp;Katarina Bryjova ,&nbsp;Daniel M. Aebersold ,&nbsp;Pejman Jabehdar Maralani ,&nbsp;Arjun Sahgal ,&nbsp;Matthias Guckenberger ,&nbsp;Hossein Hemmatazad","doi":"10.1016/j.phro.2025.100840","DOIUrl":"10.1016/j.phro.2025.100840","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Magnetic resonance imaging (MRI) plays a central role in evaluating treatment response after stereotactic body radiotherapy (SBRT) for spinal metastases. However, current guidelines focus mainly on conventional MRI sequences and lack standardized, comprehensive criteria for post-treatment assessment. This systematic review aimed to summarize available evidence on MRI-based response assessment following spine SBRT, emphasizing the potential of advanced MRI techniques and computational tools to improve clinical decision-making.</div></div><div><h3>Materials and methods</h3><div>We systematically searched PubMed, Scopus, Web of Science, and Embase from their inception to August 1, 2024. Two reviewers independently screened studies on MRI-based response assessment after SBRT for spinal metastases, evaluated eligibility, and extracted data on MRI techniques, response criteria, imaging biomarkers, and clinical outcomes.</div></div><div><h3>Results</h3><div>Thirteen studies met the inclusion criteria. Tumor volume changes assessed by sagittal T1-weighted MRI, with a minimum detectable difference of approximately 11 %, were essential for evaluating local control. T2 signal alterations and reductions in dynamic contrast-enhanced (DCE) MRI perfusion parameters, such as K_trans and V_p, correlated with improved outcomes, including pain relief and local control. Pseudo-progression and intralesional fatty content were identified as key imaging features that may mimic progression. Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) mapping showed promise as response biomarkers, but lack clinical validation. Radiomics and machine learning models improved predictive accuracy for treatment outcomes and individual follow-up strategies.</div></div><div><h3>Conclusions</h3><div>MRI provides essential morphological and functional biomarkers for response assessment after spine SBRT. Standardized, multi-parametric MRI protocols and computational tools are needed to optimize patient care.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100840"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221822","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}