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":"New modalities for ultra-high dose rate irradiation and FLASH experiments","authors":"Gabriel Adrian,&nbsp;Raphaël Moeckli,&nbsp;Elke Beyreuther,&nbsp;Ludvig P. Muren,&nbsp;Brita Singers Sørensen","doi":"10.1016/j.phro.2025.100861","DOIUrl":"10.1016/j.phro.2025.100861","url":null,"abstract":"","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100861"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466706","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 implementation of photon-counting dector computed tomography for optimizing segmentation in head-and-neck cancer radiotherapy","authors":"Niccolò Bertini ,&nbsp;Hubert S. Gabryś ,&nbsp;Hatem Alkadhi ,&nbsp;Lotte Wilke ,&nbsp;Patrick Wohlfahrt ,&nbsp;Serena Psoroulas ,&nbsp;Eugenia Vlaskou ,&nbsp;Laura Motisi ,&nbsp;Matthias Guckenberger ,&nbsp;Stephanie Tanadini-Lang ,&nbsp;Panagiotis Balermpas","doi":"10.1016/j.phro.2025.100864","DOIUrl":"10.1016/j.phro.2025.100864","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Photon-counting detector computed tomography (PCD-CT) offers advancements over conventional energy-integrating detector computed tomography (EID-CT). This study is the first to investigate the use of PCD-CT for delineation purposes.</div></div><div><h3>Materials and methods</h3><div>Twelve patients with head-and-neck cancer were prospectively included. Delineation of clinical target volume (CTV) and organs at risk (OARs) was performed by three physicians using EID-CT (120 kVp) and PCD-CT at virtual monoenergetic levels of 140 keV and 50 keV. Segmentation accuracy was assessed and contouring-confidence was rated.</div></div><div><h3>Results</h3><div>The ratio of the mean computed tomography dose index (CTDI) for EID-CT/PCD-CT for all patients was 2.72. The study revealed high inter-observer agreement for the mandible, oral cavity, parotid glands, and submandibular glands, with DSCs exceeding 0.8 across both EID-CT and PCD-CT. No differences in delineation agreement were observed, while a significant improvement was found for the lips (p = 0.001) and oral cavity (p = 0.003) when combining 140  keV and 50  keV images in PCD-CT compared to EID-CT. PCD-CT outperformed EID-CT in terms of contouring confidence.</div></div><div><h3>Conclusion</h3><div>The study established the feasibility of PCD-CT for radiotherapy planning. PCD-CT-based delineation provides results comparable to EID-CT, with the added advantages of reduced radiation dose, improved image quality and higher delineation confidence. Significant improvements in delineating specific structures, such as the lips and oral cavity, were observed when combining multiple energy levels in PCD-CT.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100864"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145614338","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 cone-beam computed tomography based workflow for online adaptive ultra-hypofractionated radiotherapy of prostate cancer","authors":"Miriam Eckl ,&nbsp;Nour Alfakhori ,&nbsp;Marvin Willam ,&nbsp;Hans Oppitz ,&nbsp;Constantin Dreher ,&nbsp;Michael Ehmann ,&nbsp;Judit Boda-Heggemann ,&nbsp;Frank A. Giordano ,&nbsp;Jens Fleckenstein","doi":"10.1016/j.phro.2025.100869","DOIUrl":"10.1016/j.phro.2025.100869","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Cone beam computed tomography (CBCT)-based approaches for online adaptive radiation therapy (oART) have recently become clinically available for ultra-hypofractionated prostate stereotactic body radiation therapy (SBRT). This work assessed the changes of relevant dose-volume-histogram (DVH) parameters and their robustness against morphologic variations during adaptation.</div></div><div><h3>Materials and methods</h3><div>Sixteen prostate cancer patients were treated with oART in an SBRT regimen (40<!--> <!-->Gy in 5 treatment sessions (Tx) to the clinical target volume (CTV), PACE-B constraints). Two CBCTs were acquired daily: CBCT1 for adaptive planning and CBCT2 after adaptation for position verification. Adapted plans optimized on CBCT1 (ART_CBCT1) were recalculated on CBCT2 (ART_CBCT2) and compared to treatment plans on CBCT1 after image guidance (IGRT_CBCT1) for relevant DVH metrics: V_40Gy(CTV), V_37Gy(bladder), V_36Gy(rectum). Spearman’s rank coefficients r with p-values (5% significance level) were determined to analyze correlations between adaptation time (ΔT) and bladder filling as well as Tx and median prostate volume.</div></div><div><h3>Results</h3><div>oART improved median V_40Gy(CTV) from 86% in IGRT_CBCT1 to 94% in ART_CBCT2. Inter-fractional prostate swelling (<span><math><mrow><msub><mi>r</mi><mrow><mi>T</mi><mi>x</mi><mo>,</mo><mi>V</mi><mi>o</mi><mi>l</mi><mo>(</mo><mi>p</mi><mi>r</mi><mi>o</mi><mi>s</mi><mi>t</mi><mi>a</mi><mi>t</mi><mi>e</mi><mo>)</mo></mrow></msub><mrow><mo>=</mo><mn>0.98</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.005</mn><mo>)</mo></mrow></mrow></math></span> was responsible for CTV deviations. Bladder filling (<span><math><mrow><msub><mi>r</mi><mrow><mi>Δ</mi><mi>T</mi><mo>,</mo><mi>V</mi><mi>o</mi><mi>l</mi><mo>(</mo><mi>b</mi><mi>l</mi><mi>a</mi><mi>d</mi><mi>d</mi><mi>e</mi><mi>r</mi><mo>)</mo></mrow></msub><mo>=</mo><mn>0.34</mn><mo>,</mo><mi>p</mi><mo>=</mo><mn>0.002</mn></mrow></math></span>) and rectal gas migration during the median adaptation time <span><math><mrow><mi>Δ</mi><mi>T</mi><mo>=</mo><mn>24.0</mn><mspace></mspace><mi>m</mi><mi>i</mi><mi>n</mi></mrow></math></span> increased V_37Gy(bladder) from 4.9 cm³ in ART_CBCT1 to 6.5 cm³ in ART_CBCT2 and V_36Gy(rectum) from 0.5 cm³ to 0.6 cm³ and led to 10 constraint violations, each.</div></div><div><h3>Conclusion</h3><div>Compared to IGRT, daily oART substantially improved CTV coverage. Besides inter-fractional prostate swelling, constraint violations originated from seminal vesicles motion, rectal gas or bladder filling during adaptation. Treatment adaptation times should therefore be minimized whenever possible.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100869"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145576374","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":"Proton radiography interpretation with artificial intelligence for treatment deviation detection in proton therapy","authors":"Giuliano Perotti Bernardini,&nbsp;Arthur Galapon,&nbsp;Gabriel Guterres Marmitt,&nbsp;Jeffrey Free,&nbsp;Peter van Ooijen,&nbsp;Johannes Langendijk,&nbsp;Stefan Both","doi":"10.1016/j.phro.2025.100872","DOIUrl":"10.1016/j.phro.2025.100872","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Patient setup errors, anatomical changes, and uncertainties in proton range estimation degrade dose conformity in proton therapy. Adaptive proton therapy (APT) mitigates these deviations by monitoring and adjusting treatment plans. Proton radiography (PR) offers direct proton range information, making it a promising method to detect such deviations. In this study, we developed and evaluated an artificial intelligence (AI) PR tool for automated interpretation and classification of treatment deviations.</div></div><div><h3>Materials and methods</h3><div>Computed Tomography (CT) scans from 32 head-and-neck cancer patients were synthetically modified to simulate setup errors (±2–4 mm), calibration curve errors (±3–5% for fat/soft tissue, ±7–11% for bone), and anatomical changes (±2–12 mm mimicking weight variations). PR simulations were performed using OpenREGGUI to generate integral depth dose (IDD) curves and range shift maps (RSMs) across 260 × 260 mm² PR fields, resulting in 14,503 RSMs. A convolutional neural network (EfficientNet-v2-M) was trained from scratch for multi-label classification. Performance was evaluated on the synthetic dataset and an independent clinical dataset of 22 patients who underwent plan adaptation.</div></div><div><h3>Results</h3><div>The CNN classified treatment deviations within one second per image. On the synthetic dataset, it achieved 97% precision, 92% recall, 93% F1-score, and 92% F2-score. On the clinical validation set, it maintained high performance metrics: 86% precision, 88% recall, 86% F1-score, and 87% F2-score, demonstrating strong generalization to clinical scenarios.</div></div><div><h3>Conclusions</h3><div>The AI-enhanced PR tool enables fast, automated detection of treatment deviations in proton therapy, supporting its integration into APT workflows and online plan adaptation for improved quality assurance.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100872"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681035","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 automated electromagnetic tracking-based needle reconstruction in the intraoperative high-dose-rate prostate brachytherapy workflow","authors":"Ioannis Androulakis ,&nbsp;Jérémy Godart ,&nbsp;Miranda E.M.C. Christianen ,&nbsp;Henrike Westerveld ,&nbsp;Lorne Luthart ,&nbsp;Remi A. Nout ,&nbsp;Mischa S. Hoogeman ,&nbsp;Inger-Karine K. Kolkman-Deurloo","doi":"10.1016/j.phro.2025.100884","DOIUrl":"10.1016/j.phro.2025.100884","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Manual transrectal ultrasound (TRUS) reconstruction, currently used in intraoperative prostate brachytherapy, is error‑prone. Automated implant reconstruction with electromagnetic tracking (EMT) has the potential to improve accuracy. The aim of this study was to implement and validate afterloader‑integrated EMT for automated implant reconstruction.</div></div><div><h3>Materials and Methods</h3><div>An afterloader prototype equipped with an integrated EMT system was used in conjunction with a TRUS-based treatment planning system and setup. A workflow was developed to transform the EMT measurements into the implant reconstruction and import this into the treatment planning software. The workflow was retrospectively evaluated using clinical data from 14 patients. To align the EMT measurements with the treatment-planning coordinate system without a TRUS-based pre-reconstruction, a novel setup was developed using a single reference sensor integrated into the template holder. The reproducibility and accuracy of the workflow using this latter setup was evaluated in phantom measurements.</div></div><div><h3>Results</h3><div>The retrospective evaluation revealed that errors in active dwell positions of up to 10.2 mm caused absolute V_100% differences of up to 5.3 % of the target volume, and up to 24.4 %, 2.1 %, and 14.1 % of the prescribed dose for urethra D_0.1cm₃, rectum D_2cm3, and bladder D_1cm3, respectively. In phantom measurements with our novel setup using reference sensor registration, EMT-based reconstruction demonstrated high reproducibility (0.5 mm) and agreement with TRUS-based reconstruction (0.7 mm), requiring a measurement time of &lt; 23 s per implanted needle.</div></div><div><h3>Conclusion</h3><div>The implementation of EMT-based reconstruction on clinical data shows clinically relevant impact on dose-volume metrics of TRUS-based implant reconstructions errors. Using the novel workflow and hardware, highly accurate and automated implant reconstruction is possible.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100884"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681027","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":"Individualised dose mapping uncertainty estimation in the reirradiation setting","authors":"Chelmis Muthoni Thiong’o ,&nbsp;Marcel van Herk ,&nbsp;Kathryn Banfill ,&nbsp;Clara Chan ,&nbsp;Catherine Harris ,&nbsp;Matthew Lowe ,&nbsp;Tom Marchant ,&nbsp;Iskandar Mohamed ,&nbsp;Golnoosh Motamedi-Ghahfarokhi ,&nbsp;David Thomson ,&nbsp;Ane Appelt ,&nbsp;Eliana Vasquez Osorio","doi":"10.1016/j.phro.2025.100881","DOIUrl":"10.1016/j.phro.2025.100881","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Deformable image registration (DIR) allows assessing radiation doses of previous treatment courses in reirradiation planning scans. However, DIR can introduce uncertainties in dose mapping. Estimating these uncertainties for individual patients remains a key challenge. We developed an individualised approach to estimate uncertainties in dose mapping using a commercially available treatment planning system.</div></div><div><h3>Materials and methods</h3><div>For 54 patients who underwent reirradiation (27 head and neck, H&amp;N, and 27 lung cases), we performed 16 DIRs per patient. We assessed each DIR geometrically using the mean distance to agreement (mDTA) between mapped contours and the corresponding structures of 30 to 34 organs at risk (OARs). We then estimated dose mapping uncertainties for structures where DIR resulted in plausible registrations, defined as mDTA ≤ 0.3 cm. We calculated the uncertainty of dose-volume-histogram estimates (mean and D0.1 cm³) and voxel-wise uncertainties using standard deviation (SD). We also tested the impact of using fewer registrations.</div></div><div><h3>Results</h3><div>DIR resulted in plausible mappings for both patient cohorts’ OARs, ranging between 78.6 % and 88.2 %, varying between patients and OARs. Mean dose uncertainties ranged between 0 Gy and 0.43 Gy, while larger differences were observed for D0.1 cm3, between 0 Gy and 0.78 Gy. As expected, large voxel-wise uncertainties were in regions of steep dose gradients. Performance between registration sets was similar.</div></div><div><h3>Conclusion</h3><div>We developed a method to estimate dose mapping uncertainties with integrated quality control for reirradiation. Differences between patients were observed, justifying the need for individualised DIR assessment. Few registrations were a pragmatic approach.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100881"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681033","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":"Triggered plan adaptation using multi-image optimization for improved robustness in head-and-neck cancer proton therapy","authors":"Nadine Vatterodt ,&nbsp;Brian Winey ,&nbsp;Stine S. Korreman","doi":"10.1016/j.phro.2025.100871","DOIUrl":"10.1016/j.phro.2025.100871","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Anatomical variations in head-and-neck (HNC) proton therapy may degrade target coverage and organ-at-risk (OAR) sparing. This study introduces a triggered robust adaptation strategy utilizing multi-image optimization to progressively enhance plan robustness guided by observed dose deviations for targets and OARs.</div></div><div><h3>Material and methods</h3><div>Five oropharyngeal cancer patients treated with proton therapy were retrospectively analyzed. Synthetic computed tomography (CT) scans were generated from daily cone-beam CTs for dose recalculation. Four strategies were compared: no adaptation (<em>NA</em>), triggered adaptation without anatomical robustness (<em>TA</em>), and triggered robust adaptation using single (<em>TRA-S</em>) or multiple (<em>TRA-M</em>) triggered fraction images. Adaptation was triggered by exceeded thresholds in dose-volume metric deviations. Treatment strategies were evaluated by comparing target coverage, OAR dose, integral dose and number of threshold violations.</div></div><div><h3>Results</h3><div><em>TRA-S</em> and <em>TRA-M</em> consistently improved target coverage up to +0.76 Gy in median D_98% vs. <em>NA</em>, with fewer threshold violations (5 and 4) compared to <em>NA</em> and <em>TA</em> (both 8). Larger unfavorable dose deviations were reduced, with OAR doses generally comparable to NA. <em>TA</em> maintained OAR doses closer to the planned values, while not improving target coverage in all cases. Integral dose increased with <em>TRA</em> strategies up to 3.7 Gy·L compared to <em>NA</em>. Differences between <em>TRA-S</em> and <em>TRA-M</em> were generally small.</div></div><div><h3>Conclusion</h3><div>Triggered robust adaptation balanced target coverage and OAR sparing, while requiring fewer adaptations compared to triggered adaptation without anatomical robustness. It offers a potential pathway for implementing anatomical robust optimization in HNC proton therapy without relying on predicted images or additional CT scans.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100871"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681034","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 spot-scanning proton arc therapy with functional avoidance strategies to reduce pulmonary toxicity","authors":"Yingxuan Chen ,&nbsp;Peilin Liu ,&nbsp;Xiaoda Cong ,&nbsp;Edward Castillo ,&nbsp;Richard Castillo ,&nbsp;Inga Grills ,&nbsp;Craig Stevens ,&nbsp;Xiangkun Xu ,&nbsp;Xiaoqiang Li ,&nbsp;Yevgeniy Vinogradskiy ,&nbsp;Xuanfeng Ding","doi":"10.1016/j.phro.2025.100876","DOIUrl":"10.1016/j.phro.2025.100876","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Functional avoidance radiotherapy has emerged as a promising technique using functional imaging to minimize pulmonary toxicity by reducing doses to functional lung. This study aims to investigate the potential dose-volume advantages of a novel spot-scanning proton arc (SPArc) therapy for functional avoidance radiotherapy with four-dimensional computed tomography (4DCT)-based ventilation imaging.</div></div><div><h3>Material and methods</h3><div>Twenty-five patients from a prospective functional avoidance clinical trial treated with intensity-modulated photon radiotherapy were included. Robustly optimized intensity modulated proton therapy (IMPT) and SPArc plans were generated in RayStation. Functional lung contour was derived from the 4DCT-based ventilation imaging and utilized as an optimization structure in photon as well as IMPT and SPArc functional planning. The dose distributions were compared, and normal tissue complication probability (NTCP) models were applied to estimate the probability of pulmonary toxicity.</div></div><div><h3>Results</h3><div>Using clinical photon plans as the baseline for comparison, both proton plans achieved equivalent target coverage and reduced dose to organs at risk. Compared with photon plans, the median absolute reduction of fV_20Gy (the volume of functional lung receiving ≥ 20 Gy) was 3.7 percentage points (pp) with IMPT and 13.0 pp with SPArc. Using fV_20Gy for NTCP estimation, the median reduction of probability of grade ≥ 2 pneumonitis was 5.0 pp with IMPT and was 14.9 pp with SPArc.</div></div><div><h3>Conclusions</h3><div>Our study highlighted the potential of SPArc to spare dose to functional lung. NTCP results further indicated that the risk of pulmonary complications can be reduced with SPArc compared to photon or IMPT for functional avoidance radiotherapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"36 ","pages":"Article 100876"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145681096","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}