Physics and Imaging in Radiation Oncology最新文献

{"title":"Trigger-based adaptive proton therapy and changes in target coverage and cardiac dose in esophageal cancer","authors":"Vlad Badiu,&nbsp;Esther Kneepkens,&nbsp;Dominique Reijtenbagh,&nbsp;Maaike Berbée,&nbsp;Richard Canters","doi":"10.1016/j.phro.2026.101104","DOIUrl":"10.1016/j.phro.2026.101104","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Inter-fractional anatomical variations during proton therapy for esophageal cancer may compromise target coverage and increase dose to surrounding organs. Adaptive replanning can mitigate these effects, but its cumulative dose-based and clinical impact remains insufficiently characterized. We evaluated offline adaptive intensity-modulated proton therapy (IMPT) triggered by target underdose or cardiac overdose using deformable dose accumulation.</div></div><div><h3>Materials and methods</h3><div>A retrospective cohort of 192 esophageal cancer patients treated with IMPT was analyzed. Eighty-five underwent adaptive replanning and 107 were treated non-adaptively. Dose accumulation was performed by assigning each fraction to the closest weekly repeat computed tomography (CT) scan and deformably mapping doses to the planning CT. Accumulated doses from adapted and non-adapted plans were compared for internal target volume (ITV) and gross tumor volume (GTV) coverage, target hotspots, heart and lung dose, and normal tissue complication probability (NTCP) for 2-year post-treatment mortality.</div></div><div><h3>Results</h3><div>Compared with the non-adaptive treatment scenario, the adaptive scenario increased ITV D_98% by 1.9 percentage points (pp) and GTV D_98% by 0.8 pp. in the target underdose subgroup. In the cardiac overdose subgroup, mean heart dose decreased by 1.0 Gy and heart V_40Gy by 1.7 pp., with no increase in mean lung dose. NTCP for 2-year post-treatment mortality decreased by 1.5 pp. in this subgroup.</div></div><div><h3>Conclusions</h3><div>Trigger-based adaptive IMPT improved cumulative target coverage and cardiac sparing without increasing lung dose. Target underdose and cardiac overdose triggers provided complementary benefits, supporting their use in structured adaptive replanning.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101104"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149141566","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":"3D analysis and evolution of prostate and tumor oxygenation using MRI-derived relative oxygen extraction fraction during MR-guided stereotactic body radiotherapy","authors":"Thomas Berger,&nbsp;Ariane Lapierre,&nbsp;Perla Zidane,&nbsp;Hayder Aloraibi,&nbsp;Samy Horn,&nbsp;Angela Boros,&nbsp;Frederic Cervenansky,&nbsp;Benjamin Leporq,&nbsp;Olivier Beuf,&nbsp;William Henry Nailon,&nbsp;Olivier Chapet","doi":"10.1016/j.phro.2026.101097","DOIUrl":"10.1016/j.phro.2026.101097","url":null,"abstract":"<div><h3>Background/Purpose</h3><div>Tumor hypoxia is a major cause of radioresistance, motivating the development of biomarkers related to tissue oxygen physiology that can be monitored throughout treatment. MRI-derived relative Oxygen Extraction Fraction (rOEF) is a non-invasive imaging biomarker related to tissue oxygen extraction. This study characterized the temporal evolution of rOEF during MR-guided stereotactic body radiotherapy (MRgSBRT) for prostate cancer.</div></div><div><h3>Materials/Methods</h3><div>Twenty-three prostate cancer patients treated with five-fraction MRgSBRT were analyzed. rOEF maps were acquired at treatment planning and at each treatment fraction. Average rOEF was extracted from the healthy prostate, gross tumor volume (GTV), and two gluteal muscle regions receiving either residual (in-field) or negligible (out-of-field) irradiation. Longitudinal changes in average rOEF and in the fraction of GTV voxels with rOEF &gt;70% were quantified using patient-specific linear fits. Slopes of average rOEF in the healthy prostate were also calculated between successive imaging sessions.</div></div><div><h3>Results</h3><div>Average rOEF decreased significantly in all irradiated regions (healthy prostate, GTV and in-field gluteal muscle), with no significant change in the out-of-field gluteal muscle. The fraction of GTV voxels with rOEF &gt;70% also declined significantly. In the healthy prostate, rOEF decreased predominantly during the first four fractions, with the steepest median slope observed between planning and the first treatment fraction (−3.2).</div></div><div><h3>Conclusions</h3><div>MRgSBRT was associated with a progressive reduction in rOEF confined to irradiated tissues, with the largest decrease in healthy prostate rOEF occurring after the first irradiation. These findings suggest rOEF could be a potential imaging biomarker of physiological changes associated with radiation exposure and warrant further investigation of its relationship with physiological processes and tissue hypoxia.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101097"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149141565","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":"Response to Khodamoradi: Methodological clarifications regarding NanOx predictions in helium SOBP","authors":"Thomas Berger,&nbsp;Gersende Alphonse,&nbsp;Mario Alcocer-Avila,&nbsp;Caterina Monini,&nbsp;Charbel Koumeir,&nbsp;Claire Rodriguez-Lafrasse,&nbsp;Nicolas Varmenot,&nbsp;Vincent Métivier,&nbsp;Ferid Haddad,&nbsp;Jean Michel Létang,&nbsp;Étienne Testa","doi":"10.1016/j.phro.2026.101088","DOIUrl":"10.1016/j.phro.2026.101088","url":null,"abstract":"","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101088"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149141527","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":"Benchmarking intermediate dose spillage in single target stereotactic radiosurgery for brain metastases","authors":"Youness Nour,&nbsp;Shari Wiegreffe,&nbsp;Tuba Tekin,&nbsp;Lara Caglayan,&nbsp;Christina Leitzen,&nbsp;Cas S. Dejonckheere,&nbsp;Davide Scafa,&nbsp;Julian P. Layer,&nbsp;Victoria Volkenborn,&nbsp;Fabian Kugel,&nbsp;Stephan Garbe,&nbsp;Christos Moustakis,&nbsp;Dimos Baltas,&nbsp;Gustavo R. Sarria,&nbsp;Anca-L. Grosu,&nbsp;Eleni Gkika","doi":"10.1016/j.phro.2026.101105","DOIUrl":"10.1016/j.phro.2026.101105","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Intermediate-dose spillage is central to normal-brain sparing in stereotactic radiosurgery, yet fixed adverse-event and relative indices do not define achievable plan quality for single-target linear accelerator treatments. The aim was to derive a volume-dependent absolute benchmark for the 50% prescription isodose volume (V_50%; equivalent to V_{10 Gy} for 20 Gy plans) for brain metastases.</div></div><div><h3>Materials and methods</h3><div>In total, 276 single-isocenter single-target plans were analyzed: 178 idealized model plans and 98 clinical plans. Power-law regression in log-log space modeled spillage against planning target volume (PTV, cm³). The volume-scaling exponents were 0.83 for the ideal references and 0.75 for the simplified clinical threshold. The clinical upper threshold was derived using q = 0.90 quantile regression. Threshold-exceeding plans were reviewed for anatomical or technical justification.</div></div><div><h3>Results</h3><div>In the model cohort V_50% value correlated strongly with PTV (<em>r</em> = 0.994, <em>p</em> &lt; 0.001). The ideal mean model was V_50% = 3.71 × PTV^0.83, the conservative ideal-planning reference was V_50% = 4.10 × PTV^0.83, and the clinical upper threshold was V_50% = 5.00 × PTV^0.75. Ten of 98 clinical plans (10%) exceeded the threshold. Seven lacked anatomical justification and were replanned, reducing V_50% by a median of 14% (range 7–29%) without compromising target coverage.</div></div><div><h3>Conclusions</h3><div>A volume-based V_50% benchmark provided a complementary quality-assurance reference for single-target linear accelerator radiosurgery for brain metastases. It flagged plans that warranted structured review alongside target coverage, organs of interest, conformity, and gradient metrics.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101105"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149200272","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":"Computed tomography and magnetic resonance imaging radiomics for predicting non-complete response after chemoradiotherapy in unresectable locally advanced head and neck squamous cell carcinoma","authors":"Krittee Chesdachai,&nbsp;Kullathorn Thephamongkhol,&nbsp;Anucha Chaichana,&nbsp;Jiraporn Setakornnukul","doi":"10.1016/j.phro.2026.101074","DOIUrl":"10.1016/j.phro.2026.101074","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Non-complete response after chemoradiotherapy in unresectable locally advanced head and neck squamous cell carcinoma (LA-HNSCC) has been associated with poor prognosis. We compared clinical, computed tomography (CT), and magnetic resonance imaging (MRI) radiomics models for predict non-complete response of the primary tumor, and estimated each data type's marginal contribution across all configurations.</div></div><div><h3>Materials and methods</h3><div>This retrospective study included 88 patients (67 complete and 21 non-complete responders) treated with definitive chemoradiotherapy. Radiomic features were extracted from pre-treatment contrast-enhanced CT and multi-parametric MRI. Models were optimized under nested leave-one-out cross-validation across 366 configurations spanning imbalance handling, feature selection, and classifier. Each data type's marginal contribution was estimated as the mean paired AUC difference versus a parsimonious clinical model. Early and late fusion were tested, and clinical utility was assessed by exploratory decision curve analysis.</div></div><div><h3>Results</h3><div>In a best-configuration comparison, the MRI model achieved the highest discrimination (AUC 0.91, 95% CI 0.81–0.98) but did not significantly outperform the parsimonious clinical model (AUC 0.75, DeLong <em>p</em> = 0.058). Across all configurations, no single-modality or feature-level fusion exceeded the clinical baseline, each performing significantly below it (all <em>p</em> &lt; 0.05). Only decision-level fusion combining clinical and imaging data was positive, reaching significance for clinical plus CT (mean ΔAUC +0.059, <em>p</em> = 0.031).</div></div><div><h3>Conclusions</h3><div>A properly specified clinical model was a strong benchmark for radiomics. Single-best pipeline results can overstate radiomic value in small cohorts, and biascontrolled evaluation with external validation is essential before clinical use.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101074"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148937971","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":"ESTRO consensus recommendations on total skin electron beam technique - Endorsed by ILROG","authors":"Christos Moustakis,&nbsp;Isak Hannes Wahlstedt,&nbsp;Kalliopi-Pola Platoni,&nbsp;Tze Yee Lim,&nbsp;María Aurora Vicedo González,&nbsp;Trinitat García Hernández,&nbsp;Mario Levis,&nbsp;Gabriele Simontacchi,&nbsp;Belinda A. Campbell,&nbsp;Stefanie Corradini,&nbsp;Stephen Morris,&nbsp;George Patatoukas,&nbsp;Youlia Kirova,&nbsp;Bouthaina Dabaja,&nbsp;Hans Theodor Eich,&nbsp;Sabbah I. Hammoury,&nbsp;Andrea Baehr,&nbsp;Livia Marrazzo,&nbsp;Laila König,&nbsp;Mohamed A. Schumann,&nbsp;Khaled Elsayad","doi":"10.1016/j.phro.2026.101075","DOIUrl":"10.1016/j.phro.2026.101075","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Total skin electron beam therapy (TSEBT) is an established radiation treatment modality for the management of cutaneous T-cell lymphoma (CTCL). In recent years, there has been an increasing interest in dose de-escalation strategies aimed at lowering treatment-induced side effects whilst maintaining efficacy. This evolution in clinical practice has highlighted the need for consistent technical standards to ensure treatment quality and comparability across medical institutions. A unified set of recommendations for TSEBT in the modern era was sought by the European Society for Radiotherapy and Oncology (ESTRO) Guidelines Sub-Group on Physics, including physical requirements, with the aim of harmonizing clinical practice, promoting homogeneity for clinical trials, and facilitating wider adoption of the technique.</div></div><div><h3>Material and methods</h3><div>The ESTRO Guidelines Committee developed these recommendations using a Delphi consensus methodology. An expert panel consisting of radiation oncologists and medical physicists with specific expertise in the radiation treatment of primary cutaneous lymphoma was convened. Panel members completed a 14-question survey focusing on key technical aspects of TSEBT.</div></div><div><h3>Results</h3><div>Consensus was achieved on the principal physical and technical components of TSEBT delivery, including prescribed dose levels, field dimensions, treatment techniques, and QA requirements. Areas of agreement reflect current best practices and address sources of variability that may impact treatment reproducibility.</div></div><div><h3>Conclusions</h3><div>ESTRO recommendations provide a standardised framework for the delivery of TSEBT in the management of CTCL, supporting safe implementation and consistency across medical institutions in the context of reduced-dose treatment approaches.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101075"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149052263","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":"CT image generation from ultrashort echo time MRI for dosimetric assessment in lung cancer radiotherapy","authors":"Kaiyi Zheng,&nbsp;Xudong Xue,&nbsp;Qi Zhang,&nbsp;Fengqin Zhou,&nbsp;Jia Xu,&nbsp;Xingyu Wang,&nbsp;Xiaopeng Song,&nbsp;Wei Mao,&nbsp;Zilong Yuan,&nbsp;Yulin Liu","doi":"10.1016/j.phro.2026.101087","DOIUrl":"10.1016/j.phro.2026.101087","url":null,"abstract":"<div><h3>Background and purpose</h3><div>To facilitate magnetic resonance imaging (MRI)-only radiotherapy workflows and overcome the lack of electron density information in MRI for accurate radiotherapy dose calculation, we proposed a cycle-consistent generative adversarial network-based framework, Fast Fourier Transform Spatial-Channel Net (FFTSC-Net). This study aimed to synthesize high-quality synthetic computed tomography (sCT) from lung ultrashort echo time-MRI (UTE-MRI) and assess its potential clinical dosimetric viability.</div></div><div><h3>Materials and methods</h3><div>UTE-MRI and CT data from 60 patients with lung cancer were retrospectively collected and spatially aligned through deformable registration. FFTSC-Net was developed by integrating spatial and channel reconstruction convolution, squeeze-and-excitation, and residual fast Fourier transform modules, alongside a dual contrastive loss function. The synthesis quality was evaluated using structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and mean absolute error (MAE). The clinical feasibility was assessed through Hounsfield unit (HU) consistency analysis in organs at risk (OARs) and planning target volume (PTV), dose volume histogram parameters, and gamma passing rates.</div></div><div><h3>Results</h3><div>FFTSC-Net achieved an SSIM of 0.80, PSNR of 20.07 dB, and MAE (HU) of 59.31. No statistically significant differences were observed in HU distributions for lungs, spinal cord, and PTV compared with planning CT (<em>p</em> &gt; 0.05). Dosimetric analysis revealed no significant differences across all PTV and OAR indices (<em>p</em> &gt; 0.05). Gamma passing rates reached 95.39% (2%/2 mm) and 98.08% (3%/3 mm).</div></div><div><h3>Conclusion</h3><div>FFTSC-Net demonstrates high image fidelity and dosimetric accuracy, supporting its potential for MRI-only radiotherapy planning in patients with lung cancer.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101087"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149052264","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":"AI-based detection of temporal changes in MR-Linac images acquired during routine prostate radiotherapy","authors":"Seungbin Park,&nbsp;Peilin Wang,&nbsp;Joshua Paik,&nbsp;Ryan Pennell,&nbsp;Francesca Khani,&nbsp;Himanshu Nagar,&nbsp;Timothy McClure,&nbsp;Emily S. Weg,&nbsp;Mert R. Sabuncu,&nbsp;Daniel Margolis,&nbsp;Heejong Kim","doi":"10.1016/j.phro.2026.101081","DOIUrl":"10.1016/j.phro.2026.101081","url":null,"abstract":"<div><h3>Background and purpose:</h3><div>To investigate whether an AI-based method can detect subtle inter-fraction changes in MR-Linac images acquired during radiotherapy and explore the broader potential of MR-Linac imaging.</div></div><div><h3>Material and methods:</h3><div>This retrospective study included longitudinal 0.35T MR-Linac images from 761 patients. To identify temporal changes, we employed a deep learning model using temporal ordering via pairwise comparison, previously shown effective for longitudinal imaging studies. The model was trained using first-to-last fraction pairs (<span><math><msub><mrow><mi>F</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-<span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>L</mi></mrow></msub></math></span>) and all pairs (<em>All-pairs</em>). Performance was assessed using quantitative metrics (accuracy and AUC) and compared against a radiologist’s performance. Qualitative evaluation was performed using saliency maps, which identify anatomical regions associated with temporal imaging changes.</div></div><div><h3>Results:</h3><div>The <span><math><msub><mrow><mi>F</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>–<span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>L</mi></mrow></msub></math></span> model demonstrated high performance (AUC=0.99; accuracy=0.95) and outperformed the radiologist in temporal ordering task. The <em>All-pairs</em> model also showed high performance (AUC = 0.97; accuracy = 0.91). The performance was correlated to fractional intervals and was reduced for non-radiation-exposed timepoints (<span><math><mrow><mi>S</mi><mi>i</mi><mi>m</mi></mrow></math></span> and <span><math><msub><mrow><mi>F</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>). Patients who later developed biochemical recurrence exhibited smaller longitudinal changes in model logits during radiotherapy. Regions contributing to predictions included the prostate, bladder, and pubic symphysis.</div></div><div><h3>Conclusions:</h3><div>These findings demonstrate the feasibility of detecting subtle inter-fractional changes over short periods (two days on average) in routine MR-Linac images during prostate radiotherapy and contribute to the development of imaging biomarkers for treatment response.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101081"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149052265","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":"ESTRO-EPTN guidelines for independent dose calculation and log file-based patient-specific quality assurance in scanned particle therapy","authors":"Loïc Grevillot,&nbsp;Oliver Jäkel,&nbsp;Abdallah Qubala,&nbsp;Julian Horn,&nbsp;Adam H. Aitkenhead,&nbsp;Xiaoying Liang,&nbsp;Giuseppe Magro,&nbsp;Klará Badraoui-Čuprová,&nbsp;Jan Vilimovský,&nbsp;Jörg Wulff,&nbsp;Katrin Henkner,&nbsp;Catharine H. Clark,&nbsp;Damir Skrijelj,&nbsp;Ilaria Rinaldi,&nbsp;Kevin Souris,&nbsp;Séverine Rossomme,&nbsp;Franciska Lebbink,&nbsp;Liu Hong,&nbsp;Dawid Krzempek,&nbsp;Stefan Menkel,&nbsp;Marie Vidal","doi":"10.1016/j.phro.2026.101109","DOIUrl":"10.1016/j.phro.2026.101109","url":null,"abstract":"<div><div>Background and Purpose: Independent dose calculation (IDC) and log file-based patient-specific quality assurance (PSQA) are increasingly used in scanned particle therapy (PT) to address pitfalls of phantom-based verifications. Highly modulated treatment fields, steep dose gradients, and growing interest for adaptive treatments require quality assurance (QA) approaches that are cost effective, patient-specific, and closely linked to the delivered treatment. Practical guidance is therefore needed for the safe clinical implementation of IDC- and log file-based PSQA.</div><div>Materials and Methods: The ESTRO-EPTN (European Particle Therapy Network) developed consensus-based recommendations on IDC- and log file-based PSQA in PT. Current clinical practice, commissioning strategies, risk-management approaches, and available technical solutions were evaluated. Following a review of the literature, expert-based guidelines were developed covering clinical scopes, acceptance, commissioning and validation, integration with machine QA, data management, governance, and staged implementation.</div><div>Results: IDC- and log file-based PSQA were identified as complementary elements within a quality-management framework. Log file-based approaches enable evaluation of the delivered treatment fraction(s), while IDC provides computational verification of the planned dose. When appropriately validated, these methods increase sensitivity to potentially clinically relevant deviations and can substantially reduce reliance on phantom-based measurements. Safe application requires robust machine QA, characterization of model limitations, risk analysis, and data traceability. Recommendations applicable to all centers were developed for IDC. Log file-based PSQA recommendations include minimum requirements for the vendors.</div><div>Conclusions: These recommendations aim to promote consistent and safe adoption across PT centers, while preserving the need for machine QA.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101109"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149199855","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":"Evidence-based design of a patient-specific quality assurance program through retrospective analysis of pretreatment and in vivo results","authors":"Esther Decabooter,&nbsp;Sebastiaan M.J.J.G. Nijsten","doi":"10.1016/j.phro.2026.101106","DOIUrl":"10.1016/j.phro.2026.101106","url":null,"abstract":"<div><h3>Background and purpose</h3><div>As radiotherapy techniques become increasingly complex, patient-specific quality assurance (PSQA) must evolve to detect a broad spectrum of potential failure modes across the treatment chain. This study presents a extensive evaluation of a multi-modal PSQA program by assessing its ability to detect clinically relevant failure modes and quantifying its efficacy.</div></div><div><h3>Materials and Methods</h3><div>A five-year retrospective analysis was conducted of an integrated PSQA program implemented at Maastro, combining secondary dose calculations, log-file based verification, and Electronic Portal Dosimetry (EPD) in both pretreatment and <em>in vivo</em> workflows. The efficacy of individual QA methods and the overall program was quantified using positive predictive values (PPVs). PSQA outcomes were linked to potential improvements in treatment planning strategies and delivery techniques.</div></div><div><h3>Results</h3><div>A total of 18,558 treatment plans were analyzed in the pretreatment workflow and 1817 treatment plans in the <em>in vivo</em> workflow. Nearly all high-priority failure modes could be detected except machine output miscalibration. Combining PSQA methods substantially improved PPVs across failure categories. The <em>in vivo</em> workflow flagged the most failure modes and additionally gives insight into possible improvements in planning strategies or treatment techniques.</div></div><div><h3>Conclusions</h3><div>This retrospective analysis demonstrated that a comprehensive framework incorporating independent, purpose-specific PSQA methods is essential to detect a wide range of treatment deviations. Combining complementary methods improves the reliability and interpretability of results. The clinical impact of a PSQA program can be further enhanced by adopting more clinically meaningful evaluation metrics and using the results to guide the optimization of new treatment strategies.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101106"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149199857","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}