Physics and Imaging in Radiation Oncology最新文献

{"title":"Impact of dynamic beam delivery of intensity-modulated radiation therapy and volumetric modulated arc therapy on circulating immune cell exposure in glioma","authors":"Abdelkhalek Hammi,&nbsp;Nadya Shusharina,&nbsp;Eleni Gkika,&nbsp;Youness Nour","doi":"10.1016/j.phro.2026.101070","DOIUrl":"10.1016/j.phro.2026.101070","url":null,"abstract":"<div><h3>Background and purpose</h3><div>To compare how intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) affect circulating blood cells (CBC) depletion in glioma patients.</div></div><div><h3>Materials and methods</h3><div>Twenty-eight glioma patients were retrospectively analyzed. Mean clinical target volume (CTV) was 293.8 ± 152.4 cm³ (μ±<span><math><mi>σ</mi></math></span>). For each clinical IMRT or VMAT plan, a corresponding plan using the alternative technique was generated with identical objectives and constraints. A 4D dynamic blood-flow model simulated cerebral blood flow and time-resolved dose delivery to estimate accumulated dose and CBC depletion. Endpoints included irradiated blood volume (V_D&gt;0) and CBC depletion relative to baseline. Linear mixed-effects modeling assessed technique, CTV volume, and their interaction.</div></div><div><h3>Results</h3><div>After one fraction, mean V_D&gt;0 was higher with IMRT than VMAT (49.9% ± 7.2% vs 38.6% ± 6.3%; <em>p</em> &lt; 0.00001). IMRT exposed more CBC volume in 24 of 28 patients; the four exceptions had the smallest CTVs. After three fractions, approximately 90% of CBCs were exposed with IMRT versus 77% with VMAT. Estimated CBC depletion was 13.9% with IMRT and 12.8% with VMAT (mean paired difference, 1.0 ± 1.7 percentage points; 95% CI, 0.3–1.7; <em>p</em> = 0.003). Depletion increased with CTV volume for both techniques, with a technique-by-CTV interaction of −0.41 percentage points per 100 cm³ (<em>p</em> = 0.041).</div></div><div><h3>Conclusions</h3><div>IMRT and VMAT produced different blood dose distributions. However, the mean depletion difference was small relative to estimated intersubject variability and does not establish a clinically meaningful advantage for either technique.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101070"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148937970","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":"Integration of an echocardiographic motion-management system into photon-based stereotactic arrhythmia radioablation planning","authors":"Hans Oppitz,&nbsp;Amelie L. Matusche,&nbsp;Laura Mantovani,&nbsp;Mathieu Kruska,&nbsp;Kerstin Siebenlist,&nbsp;Nour Alfakhouri,&nbsp;Adriano Garonna,&nbsp;Elisabetta Bonzano,&nbsp;Ester Orlandi,&nbsp;Viviana Vitolo,&nbsp;Adele Valentini,&nbsp;Nicoletta Basla,&nbsp;Frank A. Giordano,&nbsp;Oliver Blanck,&nbsp;Roberto Rordorf,&nbsp;Jens Fleckenstein,&nbsp;Judit Boda-Heggemann,&nbsp;Lena Kästner","doi":"10.1016/j.phro.2026.101096","DOIUrl":"10.1016/j.phro.2026.101096","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Cardiorespiratory ultrasound motion monitoring may enhance the precision of dose delivery for stereotactic arrhythmia radioablation (STAR) of ventricular tachycardia. This treatment planning study aimed to evaluate the feasibility of photon-based STAR planning in the presence of an ultrasound probe.</div></div><div><h3>Materials and methods</h3><div>For sixteen targets in fourteen patients, three treatment plans were retrospectively created and compared: a reference plan without an ultrasound probe and two plans in which the ultrasound probe was spared from the primary treatment beam (apical or parasternal probe positions). Descriptive and statistical analyses were performed for target/organ dose-volume and treatment beam metrics, conformity-indices and maximum probe exposure.</div></div><div><h3>Results</h3><div>The ultrasound probe could be spared from the primary beam in all cases with D_{0.035 cm³} &lt; 1 Gy (median 0.2 Gy with apical and 0.4 Gy with parasternal placement) with slightly elevated organ dose-volume metrics and no significant differences in target dose-volume metrics. The conformity-index (50 % isodose line) differed significantly for apical and parasternal probe position (median reference plan 4.0 vs. 5.0 and 4.5, respectively; <em>p</em> &lt; 0.01). The parasternal position gave slightly superior results compared to the apical position (e.g., heart minus planning target volume V_{12.5 Gy} 7.6 % [4.7–13.3] vs. 8.2 % [6.4–12.5]; left lung V_{10 Gy} 3.4 % [1.0–4.5] vs. 4.2 % [1.6–6.8]), albeit in all plans dose guidance parameters remained within clinically acceptable limits.</div></div><div><h3>Conclusions</h3><div>The ultrasound probe could be spared from the primary beam without compromising photon-based STAR plan quality beyond clinically acceptable deviations. The results support further investigation of ultrasound-based STAR motion management.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101096"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149141426","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":"Six-year data from three magnetic resonance-guided radiotherapy systems demonstrate long-term stability of linear accelerator quality assurance","authors":"Guido C. Hilgers,&nbsp;Simon J. Woodings,&nbsp;Thomas A. Foppen,&nbsp;Jochem W.H. Wolthaus,&nbsp;André W. Minken,&nbsp;Bas W. Raaymakers,&nbsp;Bram van Asselen","doi":"10.1016/j.phro.2026.101091","DOIUrl":"10.1016/j.phro.2026.101091","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Magnetic resonance-guided radiotherapy systems require comprehensive quality assurance (QA) programs to ensure safe and precise treatment delivery. This study evaluates the long-term behavior and variability of linac-related QA results across three clinically operated 1.5 T MRI-linacs at a single institution and assesses compliance with tolerance limits.</div></div><div><h3>Materials and Methods</h3><div>QA data acquired over a six-year period from three clinically operated 1.5 T MRI-linacs were retrospectively analyzed. A range of linac-related dosimetric and mechanical QA tests was included. Performance envelopes (mean ± 2 SD) were constructed to characterize variability relative to tolerance limits.</div></div><div><h3>Results</h3><div>For 11 of 13 QA tests, performance envelopes for the associated metrics remained within the applied tolerance limits. For the two remaining tests, envelopes slightly extended beyond these limits. These deviations were not considered clinically relevant, and their underlying causes were understood. No progressive trends of clinical relevance were observed in the linac-specific time series.</div></div><div><h3>Conclusions</h3><div>Stability of linac-related QA results was demonstrated over six years across three MRI-linacs, supporting reconsideration of the QA program.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101091"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149199971","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":"Interplay effect evaluation on lung and esophageal cancer patients treated with compact proton system in free breathing","authors":"Giorgio Cartechini,&nbsp;Esther Kneepkens,&nbsp;Gloria Vilches-Freixas,&nbsp;Richard Canters,&nbsp;Mirko Unipan,&nbsp;Marije Velders,&nbsp;Indra Lubken,&nbsp;Maud Cobben,&nbsp;Anouk Vullings,&nbsp;Janou Buck,&nbsp;Maud van den Bosch,&nbsp;Steffy Paulissen,&nbsp;Julie Schoemakers,&nbsp;Dianne Hartgerink,&nbsp;Judith van Loon,&nbsp;Stephanie Peeters,&nbsp;Ilaria Rinaldi","doi":"10.1016/j.phro.2026.101085","DOIUrl":"10.1016/j.phro.2026.101085","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Pencil beam scanning proton therapy is sensitive to respiratory motion, which can cause dose discrepancies due to the interplay between tumor and beam delivery motion. This study evaluates the clinical impact of interplay for lung and esophageal cancer patients treated in free-breathing, without rescanning.</div></div><div><h3>Materials and methods</h3><div>Interplay was evaluated in 36 patients (18 lung, 18 esophageal) using both predictive and <em>a posteriori</em> approaches. The predictive method, for pre-treatment assessment, employed 24 synthetic sinusoidal breathing patterns to model respiratory motion. The <em>a posteriori</em> method incorporated patient-specific breathing traces and machine log files. Fraction-accumulated dynamic 4D dose distributions were generated and compared with the institutional 4D robustness evaluation.</div></div><div><h3>Results</h3><div>The predictive method agreed closely with <em>a posteriori</em> evaluation, with a median Relative Distribution Error &lt; 1% across all dose-volume metrics. Interplay-induced underdosage in the first fraction (−1% to −2%) decreased after ∼5 fractions, with cumulative D_98%, D_95% and V_95% values converging to within 2% of planned doses. Two plans, one lung and one esophageal, showed persistent underdosage exceeding 5%, consistent with 4D robustness evaluation failures. For the esophageal case, a revised beam arrangement restored robustness.</div></div><div><h3>Conclusions</h3><div>Internal target volume-based robust optimization combined with machine-specific beam delivery characteristics provides motion robustness for most lung and esophageal patients treated in free-breathing. Additional motion mitigation was not required for most patients treated under conventional fractionation. However, small targets with large motion remain at risk of interplay-induced underdosage, warranting caution, as this combination may compromise plan robustness.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101085"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148996837","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":"New reconstruction algorithm for stack artifact reduction in breathing-adaptive four-dimensional computed tomography","authors":"Juliane Szkitsak,&nbsp;Maximilian Heider,&nbsp;Niklas Andre Lackner,&nbsp;Charlotte Frei,&nbsp;Allison Lamrani,&nbsp;Christopher Dürrbeck,&nbsp;Annika Oleszczuk,&nbsp;Mushawar Ahmad,&nbsp;Jannis Dickmann,&nbsp;Janis Langkrär,&nbsp;Oliver J. Ott,&nbsp;Stefanie Corradini,&nbsp;Rainer Fietkau,&nbsp;Christoph Bert","doi":"10.1016/j.phro.2026.101102","DOIUrl":"10.1016/j.phro.2026.101102","url":null,"abstract":"<div><div><u>Background and Purpose</u>: Even with new adaptive four-dimensional computed tomography (4DCT) techniques, artifacts can still occur with strong irregular breathing amplitudes. A new image reconstruction algorithm, currently available for cardiac CT, was tested on 4DCT data for its performance to reduce stack artifacts and thus improve anatomical correctness.</div><div><u>Materials and Methods</u>: The ‘ZeeFree’ algorithm employs a deformable image registration during reconstruction to reduce remaining stack artifacts. Its performance was evaluated using data of 20 irregular breathing (‘challenging group’) and 10 randomly selected (‘verification group’) patients with tumors in the thorax. Using a 5-score-scale, image quality in terms of stack artifacts was rated by three physicians and three physicists. Statistical significance was assessed using the Wilcoxon signed-rank test for the mean ratings and the Chi-square test for anatomical correctness.</div><div><u>Results</u>: Expert scoring revealed that 88.3% of the amplitude-based ZeeFree reconstructions showed (almost) no artifacts (rated with ≥ 4) compared to 66.8% of the standard reconstruction. With phase-based binning, 70.0% of the ZeeFree and 23.3% of standard were rated with a score ≥ 4. Mean scores were 4.1 and 4.0 for amplitude- and phase-based binning with ZeeFree and 3.4 and 2.5 for standard reconstruction, respectively. Differences were significant (<em>p</em> &lt; 0.001). 91.1% (ZeeFree) and 41.1% (standard) were rated as anatomically correct. Again, differences were significant (<em>p</em> &lt; 0.001).</div><div><u>Conclusions</u>: This study demonstrated a statistically significant reduction of stack artifacts, resulting in improved anatomical correctness when ZeeFree was applied to 4DCTs. The algorithm was not observed to introduce new artifacts on already artifact-free images.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101102"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149141482","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":"Efficient deep learning-driven workflows for accelerated single-fraction radiation therapy planning of a solitary tumour in the lung","authors":"Mathieu Gaudreault,&nbsp;Nicholas Hardcastle,&nbsp;Katrina Woodford,&nbsp;Jason Li,&nbsp;Kenton Thompson,&nbsp;Susan Harden,&nbsp;Sandro Porceddu,&nbsp;Vanessa Panettieri","doi":"10.1016/j.phro.2026.101082","DOIUrl":"10.1016/j.phro.2026.101082","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Same-day, single-fraction radiotherapy requires efficient planning. We introduce two deep learning (DL) dose prediction-driven workflows to generate clinically acceptable plans for treating metastases in the lung.</div></div><div><h3>Materials and methods</h3><div>Consecutive patients treated for a tumour in the lung (11/2018–11/2024) were considered. One workflow used the computed tomography density map and a synthetic dose built from the tumour segmentation as inputs for the DL model [<em>without-organs of interest (OOI)</em>]. The other workflow additionally used predicted OOI segmentations (<em>with-OOI</em>). Optimisation objectives were extracted from the predicted dose by the treatment planning system (TPS). Generated plans were compared with clinical plans with the number of achieved goals, conformity index CI₁₀₀, and control point modulation complexity score (cpMCS). Plan complexity increases with decreasing cpMCS. Processing times were recorded.</div></div><div><h3>Results</h3><div>Training and testing datasets contained 200 and 56 treatments, respectively. Without- / with-OOI workflows generated plans in 8.8 and 9.6 min. The 3%/3 mm gamma passing rates between predicted and clinical doses were median ± interquartile range 99.4 ± 0.7% / 99.3 ± 0.8%. After dose optimisation in the TPS, 25% of plans had a higher number of achieved clinical goals relative to clinical plans in both workflows. The conformity was improved (CI₁₀₀ = −5.3% / −3.9% relative to the clinical value, <em>p</em>-values &lt;0.001) at the cost of increased complexity (cpMCS = −19.4% / −19.0%, <em>p</em>-values &lt;0.001).</div></div><div><h3>Conclusions</h3><div>Workflows driven by DL dose prediction could generate a clinically acceptable plan in less than ten minutes for same-day, single-fraction treatment of a tumour in the lung.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101082"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149141567","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":"Automated workflow for target volume propagation in online adaptive magnetic resonance guided radiotherapy for lung lesions using foundation models","authors":"Denis Dudas,&nbsp;Tom Julius Blöcker,&nbsp;Miguel A. Palacios,&nbsp;Chengtao Wei,&nbsp;Chukwuka Eze,&nbsp;Stefanie Corradini,&nbsp;Claus Belka,&nbsp;Christopher Kurz,&nbsp;Guillaume Landry","doi":"10.1016/j.phro.2026.101077","DOIUrl":"10.1016/j.phro.2026.101077","url":null,"abstract":"<div><h3>Background and purpose</h3><div>This study presents a novel workflow for automated gross tumor volume (GTV) adaptation in online adaptive magnetic resonance imaging (MRI)-guided radiotherapy using promptable segmentation foundation models and evaluates its impact on the quality of adapted treatment plans.</div></div><div><h3>Materials and methods</h3><div>Treatment planning GTV contours in lung cancer patients, treated at an MRI-Linac, were propagated to daily MRI using affine or deformable image registration. Subsequently, propagated contours were refined using MedSAM2 or nnInteractive foundation models. The prompting strategy was optimized using an internal validation dataset (16 patients with single GTV, 143 fractions), and its accuracy was evaluated on internal and external datasets (total of 39 patients with single GTV, 225 fractions). In the dose-volume histogram (DVH) evaluation, daily treatment plans were reoptimized to GTVs and planning target volumes (PTV) generated by the proposed workflow. The resulting DVHs were compared with the originals.</div></div><div><h3>Results</h3><div>NnInteractive improved the segmentation accuracy significantly compared to affine- and TransMorph-based propagation methods. The Dice similarity coefficient improved by up to 15% compared to affine-based propagation, but only marginal improvements were observed compared to TM-based propagation. The DVH evaluation revealed no systematic degradation of plan quality. Most DVH metrics did not differ significantly from the original treatment plans. In 17 out of 21 cases, 100% of the clinically approved GTV volume remained covered by the prescribed dose after the reoptimization.</div></div><div><h3>Conclusion</h3><div>The proposed workflow is feasible and enables automated daily GTV adaptation with improved segmentation accuracy and comparable quality of adapted treatment plans.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101077"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148937969","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":"Quality assurance for deep learning-based proton therapy planning in routine clinical use for oropharyngeal cancer","authors":"Ilse G. van Bruggen,&nbsp;Minke J. Brinkman-Akker,&nbsp;Ilse D. Jonkhof,&nbsp;Johannes A. Langendijk,&nbsp;Stefan Both,&nbsp;Erik W. Korevaar","doi":"10.1016/j.phro.2026.101067","DOIUrl":"10.1016/j.phro.2026.101067","url":null,"abstract":"<div><div>Quality assurance is required to ensure safe and reliable use of deep learning (DL)–based intensity modulated proton therapy (IMPT) planning for oropharyngeal cancer patients. This study presents a range of quality assurance measures applied during routine clinical use and include manual adjustments to DL-based plans, independent organ-of-interest dose guidance and multidisciplinary plan review. DL-based plans were clinically acceptable for all 78 patients and achieved 1.1 Gy (RBE) lower parotid dose than manual plans. The implemented quality assurance measures enabled safe routine clinical use of DL-based IMPT planning over 28-months.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101067"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148937999","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 novel approach for spot boosting selection and treatment plan optimization to enhance prompt gamma monitoring of proton therapy","authors":"Beatrice Foglia,&nbsp;Junjie Yang,&nbsp;Louna Chinaud,&nbsp;Albin Fredriksson,&nbsp;Rasmus Nilsson,&nbsp;Nicolas Depauw,&nbsp;Thomas Bortfeld,&nbsp;Guillaume Janssens,&nbsp;Marco Pinto,&nbsp;Katia Parodi","doi":"10.1016/j.phro.2026.101063","DOIUrl":"10.1016/j.phro.2026.101063","url":null,"abstract":"<div><h3>Background and Purpose:</h3><div>Despite continuous progress, proton therapy remains challenged by delivery uncertainties. <em>In vivo</em> monitoring can help address these limitations. Prompt-gamma (PG) imaging is a monitoring technique suitable for adaptive particle therapy, though it suffers from low signal at typical fraction doses. A treatment planning strategy was evaluated, that boosts selected spots to enhance monitoring.</div></div><div><h3>Material and Methods:</h3><div>A prostate and a head-and-neck plans were generated with a research version of RayStation (RaySearch, Sweden) treatment planning system. A detailed workflow was implemented to select candidate spots to artificially increase the number of protons (boosting) delivered according to specific criteria. Two boosting modalities were applied: (1) assigning a fixed number of protons per boosted spot; (2) maximizing the number of protons, given a lower bound. Reoptimized, boosted plans were compared to the initial one in terms of dose, dose-averaged linear-energy-transfer (LET), LET-weighted dose and robustness.</div></div><div><h3>Results:</h3><div>Boosted plans preserved target coverage and normal tissue sparing until a boost level of around 7 × 10⁸ protons, although dependent on patient case and number of boosted spots. Tumor coverage was ensured after dose rescaling. Sparing of normal tissue was deemed acceptable compared to the initial plan, until a certain boost level. <em>In silico</em> PG signals after boosting confirmed higher number of counts and noise level reduction.</div></div><div><h3>Conclusions:</h3><div>Spot boosting is a feasible approach to enhance monitoring with secondary radiation, like PG, without compromising the plan quality. Its integration into clinics could enable an improved delivery quality assurance and a more precise proton therapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101063"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148856164","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":"Predicting the benefit of adaptive radiotherapy in head and neck Cancer using cone-beam computed tomography","authors":"Donghoon Lee,&nbsp;Michalis Aristophanous,&nbsp;Phillip Lichtenwalner,&nbsp;Shira Abraham,&nbsp;William Donahue,&nbsp;Mohammad Nehmeh,&nbsp;Amanda Caringi,&nbsp;Peng Zhang,&nbsp;Yu-Chi Hu,&nbsp;Pengpeng Zhang,&nbsp;Laura Cerviño,&nbsp;Daphna Gelblum,&nbsp;Sean McBride,&nbsp;Nadeem Riaz,&nbsp;Linda Chen,&nbsp;Yao Yu,&nbsp;Kaveh Zakeri,&nbsp;Nancy Lee,&nbsp;Eric Aliotta","doi":"10.1016/j.phro.2026.101069","DOIUrl":"10.1016/j.phro.2026.101069","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Adaptive radiotherapy for head and neck cancer is resource-intensive, and existing geometric triggers lack a quantitative dose basis. We developed a model based on dose differences derived from cone-beam computed tomography to predict adaptive radiotherapy benefit.</div></div><div><h3>Materials and methods</h3><div>Seventy-four patients with head and neck cancer treated with sequential-phase intensity-modulated radiotherapy and offline adaptive radiotherapy were analyzed. Patients were labeled as high or low adaptive radiotherapy benefit by k-means clustering of dose features derived from the resimulation computed tomography. A multivariable logistic regression classifier was trained on percent mean dose differences measured on the week 3 cone-beam computed tomography for five normal tissues (both parotid glands, both submandibular glands, and the oral cavity) and evaluated by leave-one-out cross-validation, alongside a parallel classifier using normal tissue volume changes.</div></div><div><h3>Results</h3><div>Dose differences correlated with adaptive radiotherapy benefit for all five normal tissues (Spearman <span><math><msub><mi>ρ</mi><mi>s</mi></msub></math></span> = −0.76 to −0.43; all <em>p</em> &lt; 0.01, Jonckheere–Terpstra trend test), whereas volume changes showed no significant association (all <em>p</em> &gt; 0.10). The dose model achieved an area under the receiver operating characteristic curve of 0.78 versus 0.54 for the volume model. On univariate analysis the ipsilateral parotid gland was the strongest single-organ predictor, whereas the multivariable model assigned the largest standardized coefficient to the ipsilateral submandibular gland, reflecting collinearity between the parotid glands.</div></div><div><h3>Conclusions</h3><div>Dose differences derived from cone-beam computed tomography provide an objective, quantitative basis for predicting adaptive radiotherapy benefit in head and neck cancer, offering a practical alternative to geometric triggers and supporting selective, resource-efficient adaptation.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"41 ","pages":"Article 101069"},"PeriodicalIF":3.2,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148937972","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}