Pub Date : 2025-12-21DOI: 10.1016/j.phro.2025.100897
Sara Bornedal , Jeehong Lee , Tim Melhus , Anna Embring , Eva Onjukka
When reirradiation dose constraints are derived using accumulated dose, the underlying image registrations contribute to the uncertainty. We performed a structure-based evaluation of deformable image registrations, to estimate the uncertainty in previously published dose constraints related to carotid blowout and osteoradionecrosis after head and neck reirradiation. With the workflow of the current analysis, the uncertainty was small in the majority of the cases (<4 Gy in accumulated equivalent dose in 2-Gy fractions), but with substantial outliers resulting from anatomical alterations. Our previously suggested dose constraints appear to be reliable with regard to the underlying image registrations.
{"title":"Accuracy of reirradiation dose constraints for the mandible and carotids","authors":"Sara Bornedal , Jeehong Lee , Tim Melhus , Anna Embring , Eva Onjukka","doi":"10.1016/j.phro.2025.100897","DOIUrl":"10.1016/j.phro.2025.100897","url":null,"abstract":"<div><div>When reirradiation dose constraints are derived using accumulated dose, the underlying image registrations contribute to the uncertainty. We performed a structure-based evaluation of deformable image registrations, to estimate the uncertainty in previously published dose constraints related to carotid blowout and osteoradionecrosis after head and neck reirradiation. With the workflow of the current analysis, the uncertainty was small in the majority of the cases (<4 Gy in accumulated equivalent dose in 2-Gy fractions), but with substantial outliers resulting from anatomical alterations. Our previously suggested dose constraints appear to be reliable with regard to the underlying image registrations.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100897"},"PeriodicalIF":3.3,"publicationDate":"2025-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842006","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}
Pub Date : 2025-12-21DOI: 10.1016/j.phro.2025.100899
Moghadaseh Khaleghibizaki , Angela Sobremonte , Luis Perles , Surendra Prajapati , Ergys Subashi , Yao Ding , Kristy Brock , Roya Barati , Eugene Koay , Chad Tang , Jinzhong Yang
Compression belts (CBs) are sometimes used to reduce respiratory motion during stereotactic body radiotherapy of abdominal cancers with magnetic resonance (MR)-guided online adaptive planning. This study evaluated the dosimetric effects of overriding the relative electron density (ED) value of CBs in creating synthetic computed tomography (CT) scans for MR-guided adaptive planning. We evaluated plans for 12 patients with abdominal cancer and identified that ED values between 0.2 and 0.3 achieved the best approximation of CB ED in dose calculation. Our study presented an approach to estimate appropriate ED overrides for CBs in MR-guided online adaptive planning.
{"title":"Dosimetric effect of abdominal compression in online adaptive planning for abdominal cancers treated with a 1.5 Tesla magnetic resonance-guided linear accelerator","authors":"Moghadaseh Khaleghibizaki , Angela Sobremonte , Luis Perles , Surendra Prajapati , Ergys Subashi , Yao Ding , Kristy Brock , Roya Barati , Eugene Koay , Chad Tang , Jinzhong Yang","doi":"10.1016/j.phro.2025.100899","DOIUrl":"10.1016/j.phro.2025.100899","url":null,"abstract":"<div><div>Compression belts (CBs) are sometimes used to reduce respiratory motion during stereotactic body radiotherapy of abdominal cancers with magnetic resonance (MR)-guided online adaptive planning. This study evaluated the dosimetric effects of overriding the relative electron density (ED) value of CBs in creating synthetic computed tomography (CT) scans for MR-guided adaptive planning. We evaluated plans for 12 patients with abdominal cancer and identified that ED values between 0.2 and 0.3 achieved the best approximation of CB ED in dose calculation. Our study presented an approach to estimate appropriate ED overrides for CBs in MR-guided online adaptive planning.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100899"},"PeriodicalIF":3.3,"publicationDate":"2025-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842007","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}
Pub Date : 2025-12-20DOI: 10.1016/j.phro.2025.100898
Xingyue Ruan , Xia Li , Muheng Li , Barbara Bachtiary , Antony Lomax , Zhiling Chen , Ye Zhang
Background and purpose
The registration of individual dose distributions to a reference anatomy represents a key step in voxel-based analysis (VBA), a tool for spatially informed dose–response assessment. Accurate deformable image registration (DIR) is essential for addressing anatomical variability across patients. To improve both global and region-specific alignment, we enhanced our in-house DIR algorithm (CPT-DIR) by incorporating contour-informed regularization.
Materials and methods
We evaluated contour-informed CPT-DIR using CT images from 37 Head-and-Neck patients, with seven cases providing ground-truth dose distribution for dose warping validation. Organs at risk (OARs) were delineated manually, with bone contours auto-generated using TotalSegmentator. Contour-informed constraints (Dice Similarity) were integrated to enhance registration in clinically relevant regions. The global registration results were evaluated using MAE, SSIM and PSNR. Geometric accuracy and warped dose accuracy were assessed using Dice Similarity Coefficient (DSC) and Dose-Organ Overlap (DOO). The performance of CPT-DIR, with and without constraints, was benchmarked against conventional B-spline.
Results
CPT-DIR achieved superior accuracy with a MAE of 98.9 ± 6.3 HU, lower than 179.1 ± 17.8 HU for B-spline. Incorporating brainstem contours as regularization improved the DSC from 0.604 ± 0.116 to 0.878 ± 0.017 and DOO from 0.430 ± 0.117 to 0.753 ± 0.043 for brainstem. For the remaining OARs, the enhanced CPT-DIR consistently achieved higher DSC and DOO metrics.
Conclusions
The integration of contour-informed regularization in CPT-DIR improved DIR accuracy, particularly in anatomically and dosimetrically relevant regions. This enhanced spatial alignment demonstrated strong potential for advancing reliable inter-patient dosimetric studies in HN radiotherapy.
{"title":"Contour-informed inter-patient deformable registration for more reliable voxel-based analysis of Head-and-Neck cancer patients","authors":"Xingyue Ruan , Xia Li , Muheng Li , Barbara Bachtiary , Antony Lomax , Zhiling Chen , Ye Zhang","doi":"10.1016/j.phro.2025.100898","DOIUrl":"10.1016/j.phro.2025.100898","url":null,"abstract":"<div><h3>Background and purpose</h3><div>The registration of individual dose distributions to a reference anatomy represents a key step in voxel-based analysis (VBA), a tool for spatially informed dose–response assessment. Accurate deformable image registration (DIR) is essential for addressing anatomical variability across patients. To improve both global and region-specific alignment, we enhanced our in-house DIR algorithm (CPT-DIR) by incorporating contour-informed regularization.</div></div><div><h3>Materials and methods</h3><div>We evaluated contour-informed CPT-DIR using CT images from 37 Head-and-Neck patients, with seven cases providing ground-truth dose distribution for dose warping validation. Organs at risk (OARs) were delineated manually, with bone contours auto-generated using TotalSegmentator. Contour-informed constraints (Dice Similarity) were integrated to enhance registration in clinically relevant regions. The global registration results were evaluated using MAE, SSIM and PSNR. Geometric accuracy and warped dose accuracy were assessed using Dice Similarity Coefficient (DSC) and Dose-Organ Overlap (DOO). The performance of CPT-DIR, with and without constraints, was benchmarked against conventional B-spline.</div></div><div><h3>Results</h3><div>CPT-DIR achieved superior accuracy with a MAE of 98.9 ± 6.3 HU, lower than 179.1 ± 17.8 HU for B-spline. Incorporating brainstem contours as regularization improved the DSC from 0.604 ± 0.116 to 0.878 ± 0.017 and DOO from 0.430 ± 0.117 to 0.753 ± 0.043 for brainstem. For the remaining OARs, the enhanced CPT-DIR consistently achieved higher DSC and DOO metrics.</div></div><div><h3>Conclusions</h3><div>The integration of contour-informed regularization in CPT-DIR improved DIR accuracy, particularly in anatomically and dosimetrically relevant regions. This enhanced spatial alignment demonstrated strong potential for advancing reliable inter-patient dosimetric studies in HN radiotherapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100898"},"PeriodicalIF":3.3,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842008","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}
Pub Date : 2025-12-20DOI: 10.1016/j.phro.2025.100896
Ashaya T. Jaglal , Koen J. Nelissen , Angelique R.W. van Vlaenderen , Amy L. de la Fuente , Famke L. Schneiders , Peter S.N. van Rossum , Jan Wiersma , Wilko F.A.R. Verbakel , Suresh Senan , Jorrit Visser , Eva Versteijne
Background and purpose
Same-day palliative radiotherapy requires rapid workflows, but conventional computed tomography (CT)-based workflows cause delays and strain resources. Advances in cone-beam CT (CBCT) enabled accurate dose calculation and planning without a planning CT. This study evaluated the feasibility and efficiency of a fully CT-free online adaptive workflow for same-day palliative radiotherapy using high-quality CBCT.
Methods and materials
This prospective study enrolled sixteen patients between January–May 2025, of whom fifteen completed same-day treatment. Eligible patients were referred for single-fraction palliative radiotherapy (8 Gy) to non-mobile target volumes. No planning CT was acquired; instead, a reference plan was generated on a phantom with standardized beam setups and planning objectives. On the treatment day, planning and delivery were performed on the Varian Ethos 2.0 platform using HyperSight CBCT, providing more accurate Hounsfield Unit imaging for automated organs at risk segmentation and target definition. Plans were adapted online and delivered while patients were on the couch. Workflow times, plan quality, and patient characteristics were studied.
Results
All fifteen treatments were delivered successfully. All plans met clinical objectives, with planning target volume coverage exceeding required thresholds. The CT-free workflow reduced median departmental time to 73 min, including 28 min in the treatment room, compared with 335 min in a conventional CT-based workflow. In one urgent case, referral-to-treatment time was 2.5 h. Repeated CBCTs were required in 7 patients.
Conclusions
A fully CT-free workflow for palliative radiotherapy is feasible and efficient, enabling same-day treatment, reduces departmental workload, and is well-suited for urgent cases requiring rapid intervention.
{"title":"Implementing a fully computed tomography-free online adaptive palliative radiotherapy: a one-visit workflow","authors":"Ashaya T. Jaglal , Koen J. Nelissen , Angelique R.W. van Vlaenderen , Amy L. de la Fuente , Famke L. Schneiders , Peter S.N. van Rossum , Jan Wiersma , Wilko F.A.R. Verbakel , Suresh Senan , Jorrit Visser , Eva Versteijne","doi":"10.1016/j.phro.2025.100896","DOIUrl":"10.1016/j.phro.2025.100896","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Same-day palliative radiotherapy requires rapid workflows, but conventional computed tomography (CT)-based workflows cause delays and strain resources. Advances in cone-beam CT (CBCT) enabled accurate dose calculation and planning without a planning CT. This study evaluated the feasibility and efficiency of a fully CT-free online adaptive workflow for same-day palliative radiotherapy using high-quality CBCT.</div></div><div><h3>Methods and materials</h3><div>This prospective study enrolled sixteen patients between January–May 2025, of whom fifteen completed same-day treatment. Eligible patients were referred for single-fraction palliative radiotherapy (8 Gy) to non-mobile target volumes. No planning CT was acquired; instead, a reference plan was generated on a phantom with standardized beam setups and planning objectives. On the treatment day, planning and delivery were performed on the Varian Ethos 2.0 platform using HyperSight CBCT, providing more accurate Hounsfield Unit imaging for automated organs at risk segmentation and target definition. Plans were adapted online and delivered while patients were on the couch. Workflow times, plan quality, and patient characteristics were studied.</div></div><div><h3>Results</h3><div>All fifteen treatments were delivered successfully. All plans met clinical objectives, with planning target volume coverage exceeding required thresholds. The CT-free workflow reduced median departmental time to 73 min, including 28 min in the treatment room, compared with 335 min in a conventional CT-based workflow. In one urgent case, referral-to-treatment time was 2.5 h. Repeated CBCTs were required in 7 patients.</div></div><div><h3>Conclusions</h3><div>A fully CT-free workflow for palliative radiotherapy is feasible and efficient, enabling same-day treatment, reduces departmental workload, and is well-suited for urgent cases requiring rapid intervention.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100896"},"PeriodicalIF":3.3,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842009","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}
Pub Date : 2025-12-16DOI: 10.1016/j.phro.2025.100895
Ashlesha Gill , Nicholas Bucknell , Mahsheed Sabet , Milad Mirzaei , Thomas Milan , Adriano Polpo , Pejman Rowshanfarzad
Background and purpose
Respiratory motion is a major source of geometric uncertainty in lung stereotactic body radiation therapy (SBRT), necessitating individualized motion management. The study aimed to examine the lung tumour motion against patient- and tumour-specific factors.
Materials and methods
Motion traces were obtained from 109 retrospective CyberKnife fiducial tracking lung treatments, recorded at 25 Hz through correlation of fiducial and external marker signals. Log files were collected and motion was quantified in the superior-inferior (SI), left–right (LR) and anterior-posterior (AP) directions. Each treatment delivery node (∼2700 per patient) was individually analysed. Clinical data included demographics, comorbidities, prior lung treatments, pulmonary function, and tumour location, size, and histology. Statistical analyses used multivariate and univariate approaches.
Results
Tumour location strongly predicted SI motion, with lower lobes showing up to an 8.2 mm greater motion than upper lobes. Previous surgery or radiotherapy moderately reduced LR motion (–0.5 mm), while tumour diameter showed a weak positive association with LR motion (+0.02 mm per mm). Percentage predicted forced expiratory volume in one second (FEV1) showed moderate positive correlations with AP (+0.01 mm per %) and SI (+0.04 mm per %) motion. Body-mass index (BMI) weakly increased SI motion (+0.2 mm per kg/m2).
Conclusions
Tumour location primarily determined SI motion, with additional increases linked to better pulmonary function and higher BMI. LR motion was greater in patients without prior lung treatment and with larger tumours, while greater AP motion occurred with better pulmonary function. Lung motion variation was quantified to support sub-millimetre SBRT precision.
背景和目的在肺立体定向放射治疗（SBRT）中，呼吸运动是几何不确定性的主要来源，需要个性化的运动管理。该研究旨在检查肺部肿瘤运动对患者和肿瘤特异性因素的影响。材料和方法对109例回顾性射波刀基准跟踪肺部治疗，通过基准和外部标记信号的相关性在25 Hz下记录运动轨迹。收集日志文件，量化上下（SI）、左右（LR）和前后（AP）方向的运动。每个治疗递送节点（每位患者约2700个）被单独分析。临床资料包括人口统计学、合并症、既往肺治疗、肺功能、肿瘤位置、大小和组织学。统计分析采用多变量和单变量方法。结果肿瘤位置对SI运动有较强的预测作用，下叶比上叶运动大8.2 mm。先前的手术或放疗中度降低了LR运动（-0.5 mm），而肿瘤直径与LR运动呈弱正相关（+0.02 mm / mm）。预测一秒钟用力呼气量百分比（FEV1）与AP （+0.01 mm / %）和SI （+0.04 mm / %）运动呈中度正相关。身体质量指数（BMI）微弱增加SI运动（+0.2 mm / kg/m2）。结论：我们的位置主要决定了SI运动，额外的增加与更好的肺功能和更高的BMI有关。未接受过肺部治疗和肿瘤较大的患者LR运动更大，而肺功能较好的患者AP运动更大。肺运动变化被量化，以支持亚毫米SBRT精度。
{"title":"Patient-specific factors associated with tumour motion in lung stereotactic body radiation therapy from real-time tumour tracking traces","authors":"Ashlesha Gill , Nicholas Bucknell , Mahsheed Sabet , Milad Mirzaei , Thomas Milan , Adriano Polpo , Pejman Rowshanfarzad","doi":"10.1016/j.phro.2025.100895","DOIUrl":"10.1016/j.phro.2025.100895","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Respiratory motion is a major source of geometric uncertainty in lung stereotactic body radiation therapy (SBRT), necessitating individualized motion management. The study aimed to examine the lung tumour motion against patient- and tumour-specific factors.</div></div><div><h3>Materials and methods</h3><div>Motion traces were obtained from 109 retrospective CyberKnife fiducial tracking lung treatments, recorded at 25 Hz through correlation of fiducial and external marker signals. Log files were collected and motion was quantified in the superior-inferior (SI), left–right (LR) and anterior-posterior (AP) directions. Each treatment delivery node (∼2700 per patient) was individually analysed. Clinical data included demographics, comorbidities, prior lung treatments, pulmonary function, and tumour location, size, and histology. Statistical analyses used multivariate and univariate approaches.</div></div><div><h3>Results</h3><div>Tumour location strongly predicted SI motion, with lower lobes showing up to an 8.2 mm greater motion than upper lobes. Previous surgery or radiotherapy moderately reduced LR motion (–0.5 mm), while tumour diameter showed a weak positive association with LR motion (+0.02 mm per mm). Percentage predicted forced expiratory volume in one second (FEV<sub>1</sub>) showed moderate positive correlations with AP (+0.01 mm per %) and SI (+0.04 mm per %) motion. Body-mass index (BMI) weakly increased SI motion (+0.2 mm per kg/m<sup>2</sup>).</div></div><div><h3>Conclusions</h3><div>Tumour location primarily determined SI motion, with additional increases linked to better pulmonary function and higher BMI. LR motion was greater in patients without prior lung treatment and with larger tumours, while greater AP motion occurred with better pulmonary function. Lung motion variation was quantified to support sub-millimetre SBRT precision.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100895"},"PeriodicalIF":3.3,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799269","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}
Pub Date : 2025-12-16DOI: 10.1016/j.phro.2025.100891
Bertrand Dewit , Ronald Peeters , Sandra Nuyts , Tom Depuydt
Accurate and reproducible immobilization is critical for effective radiotherapy in the head and neck region, but conventional thermoplastic masks are uncomfortable, labor-intensive and time-consuming to fabricate. A novel patient-specific 3D-printed immobilization device was developed using a digital CT-based workflow. The design targeted stable facial regions and was mechanically validated via simulations. Two nylon-based 3D-printed prototypes were preclinically evaluated on an anthropomorphic phantom, showing high dimensional accuracy, CT/MR compatibility, minimal target dose deviation (<2%), and submillimetric positional reproducibility. While the results demonstrate technical feasibility, clinical validations will be the next step to assess comfort, reproducibility, and workflow integration in radiotherapy.
{"title":"Development and validation of a novel patient-specific 3D-printed head and neck immobilization device for radiotherapy","authors":"Bertrand Dewit , Ronald Peeters , Sandra Nuyts , Tom Depuydt","doi":"10.1016/j.phro.2025.100891","DOIUrl":"10.1016/j.phro.2025.100891","url":null,"abstract":"<div><div>Accurate and reproducible immobilization is critical for effective radiotherapy in the head and neck region, but conventional thermoplastic masks are uncomfortable, labor-intensive and time-consuming to fabricate. A novel patient-specific 3D-printed immobilization device was developed using a digital CT-based workflow. The design targeted stable facial regions and was mechanically validated via simulations. Two nylon-based 3D-printed prototypes were preclinically evaluated on an anthropomorphic phantom, showing high dimensional accuracy, CT/MR compatibility, minimal target dose deviation (<2%), and submillimetric positional reproducibility. While the results demonstrate technical feasibility, clinical validations will be the next step to assess comfort, reproducibility, and workflow integration in radiotherapy.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100891"},"PeriodicalIF":3.3,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842004","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}
Pub Date : 2025-12-16DOI: 10.1016/j.phro.2025.100894
Yoshiro Ieko , Noriyuki Kadoya , Hisanori Ariga
Background and purpose
Deformable image registration (DIR) is an important technique in radiation therapy. To improve DIR accuracy, we applied radiomics-based image filtering as a preprocessing step before DIR.
Materials and methods
Thoracic four-dimensional computed tomography (CT) images of 10 patients with lung or esophageal cancer were examined. Peak-inhale and peak-exhale images were used for DIR. Before DIR, these images were converted into 90-voxel-based radiomics-based filtered images using extracted local radiomics features, respectively. On each filtered image, DIR between the peak-inhale and peak-exhale filtered images was performed. After DIR, the peak-inhale CT images were deformed to peak-exhale CT images using the displacement vector fields obtained from the DIR. The registration errors obtained from each radiomics-based DIR were calculated using landmark pairs and compared with conventional CT-based DIR using the same DIR parameters.
Results
In radiomics-based DIR, the lowest registration errors (95th percentile) for intensity and texture features were 0.96 mm (right-left), 1.35–1.38 mm (anterior-posterior), 2.04–2.13 mm (superior-inferior), and 2.49–2.57 mm (three-dimensional). For CT-based DIR, the corresponding registration errors were 1.31 mm, 1.72 mm, 3.45 mm, and 3.98 mm.
Conclusions
By applying radiomics-based image filtering before DIR as a preprocessing, the registration error was lower than that of conventional CT-based DIR, suggesting that using radiomics may improve the accuracy of DIR.
{"title":"Application of radiomics-based image filtering to improve deformable image registration accuracy in thoracic images","authors":"Yoshiro Ieko , Noriyuki Kadoya , Hisanori Ariga","doi":"10.1016/j.phro.2025.100894","DOIUrl":"10.1016/j.phro.2025.100894","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Deformable image registration (DIR) is an important technique in radiation therapy. To improve DIR accuracy, we applied radiomics-based image filtering as a preprocessing step before DIR.</div></div><div><h3>Materials and methods</h3><div>Thoracic four-dimensional computed tomography (CT) images of 10 patients with lung or esophageal cancer were examined. Peak-inhale and peak-exhale images were used for DIR. Before DIR, these images were converted into 90-voxel-based radiomics-based filtered images using extracted local radiomics features, respectively. On each filtered image, DIR between the peak-inhale and peak-exhale filtered images was performed. After DIR, the peak-inhale CT images were deformed to peak-exhale CT images using the displacement vector fields obtained from the DIR. The registration errors obtained from each radiomics-based DIR were calculated using landmark pairs and compared with conventional CT-based DIR using the same DIR parameters.</div></div><div><h3>Results</h3><div>In radiomics-based DIR, the lowest registration errors (95th percentile) for intensity and texture features were 0.96 mm (right-left), 1.35–1.38 mm (anterior-posterior), 2.04–2.13 mm (superior-inferior), and 2.49–2.57 mm (three-dimensional). For CT-based DIR, the corresponding registration errors were 1.31 mm, 1.72 mm, 3.45 mm, and 3.98 mm.</div></div><div><h3>Conclusions</h3><div>By applying radiomics-based image filtering before DIR as a preprocessing, the registration error was lower than that of conventional CT-based DIR, suggesting that using radiomics may improve the accuracy of DIR.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100894"},"PeriodicalIF":3.3,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799272","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}
Pub Date : 2025-12-13DOI: 10.1016/j.phro.2025.100892
Sarah A. Mason , Bethany Williams , Sophie Alexander , Alex Dunlop , Alison Tree , Emma J. Harris , Helen McNair
Background and Purpose
: Online adaptive radiotherapy (oART) is underused as generating a treatment plan at every fraction is slow and resource intensive. One method to address this involves reusing plans generated online in previous fractions with similar anatomy. However, manually assessing the suitability of each pre-existing treatment plan is prohibitively time-consuming. To gauge potential impact and motivate the development of software to enable plan recycling, we assessed a strategy whereby all pre-existing plans were considered for subsequent fractions in nine hypofractionated prostate patients treated on the magnetic resonance (MR) linear accelerator.
Methods:
The verification MR was used to estimate the delivered dose after adaptation to establish a Current Clinical Practice Benchmark. Each structure from the daily MR was propagated backwards onto the reference and daily MRs from previous fractions to calculate the dose to each structure that would have been received had the corresponding plan been delivered. The resulting dose statistics were assessed against: (A) standard target and organ-at-risk objectives, (B) the Current Clinical Practice Benchmark, and (C) circumstances where a pre-existing plan would have matched or outperformed the online plan.
Results:
The median [interquartile range] percentage of fractions with at least one acceptable pre-existing plan was 25% [20%], 40% [35%], and 60% [20%] for criteria A, B, and C respectively. Reusing the reference plan was only acceptable in 0%–20% of fractions.
Conclusion:
Reusing pre-existing plans is feasible and could accelerate oART and reduce hospital resources in approximately 40% of fractions whilst achieving the same dose-volume metrics as current oART workflows.
{"title":"Feasibility of reusing online-generated treatment plans for adaptive radiotherapy in prostate cancer","authors":"Sarah A. Mason , Bethany Williams , Sophie Alexander , Alex Dunlop , Alison Tree , Emma J. Harris , Helen McNair","doi":"10.1016/j.phro.2025.100892","DOIUrl":"10.1016/j.phro.2025.100892","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>: Online adaptive radiotherapy (oART) is underused as generating a treatment plan at every fraction is slow and resource intensive. One method to address this involves reusing plans generated online in previous fractions with similar anatomy. However, manually assessing the suitability of each pre-existing treatment plan is prohibitively time-consuming. To gauge potential impact and motivate the development of software to enable plan recycling, we assessed a strategy whereby <em>all</em> pre-existing plans were considered for subsequent fractions in nine hypofractionated prostate patients treated on the magnetic resonance (MR) linear accelerator.</div></div><div><h3>Methods:</h3><div>The verification MR was used to estimate the delivered dose after adaptation to establish a Current Clinical Practice Benchmark. Each structure from the daily MR was propagated backwards onto the reference and daily MRs from previous fractions to calculate the dose to each structure that would have been received had the corresponding plan been delivered. The resulting dose statistics were assessed against: (A) standard target and organ-at-risk objectives, (B) the Current Clinical Practice Benchmark, and (C) circumstances where a pre-existing plan would have matched or outperformed the online plan.</div></div><div><h3>Results:</h3><div>The median [interquartile range] percentage of fractions with at least one acceptable pre-existing plan was 25% [20%], 40% [35%], and 60% [20%] for criteria A, B, and C respectively. Reusing the reference plan was only acceptable in 0%–20% of fractions.</div></div><div><h3>Conclusion:</h3><div>Reusing pre-existing plans is feasible and could accelerate oART and reduce hospital resources in approximately 40% of fractions whilst achieving the same dose-volume metrics as current oART workflows.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100892"},"PeriodicalIF":3.3,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799270","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}
Pub Date : 2025-12-11DOI: 10.1016/j.phro.2025.100889
Christopher J.H. Pagett , John Lilley , Christopher O’Hara , Ane Appelt , Louise Murray , Rasmus Bokrantz , Jakob Ödén , Stina Svensson , Mark Harrison , Philip Camilleri , Rebecca Muirhead , Maxwell Robinson , Christopher Thompson
Background and purpose
Reirradiation is clinically challenging, requiring a balance between delivery of dose to tumour while respecting cumulative organ at risk (OAR) dose constraints. Standard prescriptions are often conservative, ignoring patient variability in achievable OAR doses. Isotoxic radiotherapy individualises treatment by delivering the highest equieffective dose in 2 Gy per fraction (EQD2Gy) while meeting OAR constraints. This technical feasibility study assessed isotoxic pelvic reirradiation using cumulative OAR constraints, the original dose distribution as background, and voxel-by-voxel EQD2Gy optimisation.
Materials and methods
Data from 30 patients previously treated with pelvic stereotactic body radiotherapy (SBRT) at three UK centres were included. OARs were delineated on both previous and reirradiation image sets and deformably registered. Previous dose was mapped to the current image set and used as background dose for SBRT planning, following published methods. Initial 25 Gy in five fractions (25 Gy/5#) plans were generated for all patients, with further isotoxic dose escalation conducted up to a maximum of 50 Gy (fraction number fixed) until cumulative EQD2Gy constraints were reached.
Results
For 25 of 30 patients, clinically acceptable isotoxic plans were obtained, with 23 exceeding the standard UK reirradiation prescription dose of 30 Gy/5#. The median isotoxic prescription was 42 Gy/5#, with four patient plans reaching the upper evaluated limit of 50 Gy. Vessels and the sacral plexus were most frequently dose limiting.
Conclusion
This study highlighted the feasibility of isotoxic pelvic reirradiation and supports further investigation into automation and prediction models to streamline implementation in clinical practice.
{"title":"Isotoxic stereotactic reirradiation for recurrent pelvic cancers","authors":"Christopher J.H. Pagett , John Lilley , Christopher O’Hara , Ane Appelt , Louise Murray , Rasmus Bokrantz , Jakob Ödén , Stina Svensson , Mark Harrison , Philip Camilleri , Rebecca Muirhead , Maxwell Robinson , Christopher Thompson","doi":"10.1016/j.phro.2025.100889","DOIUrl":"10.1016/j.phro.2025.100889","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Reirradiation is clinically challenging, requiring a balance between delivery of dose to tumour while respecting cumulative organ at risk (OAR) dose constraints. Standard prescriptions are often conservative, ignoring patient variability in achievable OAR doses. Isotoxic radiotherapy individualises treatment by delivering the highest equieffective dose in 2 Gy per fraction (EQD2Gy) while meeting OAR constraints. This technical feasibility study assessed isotoxic pelvic reirradiation using cumulative OAR constraints, the original dose distribution as background, and voxel-by-voxel EQD2Gy optimisation.</div></div><div><h3>Materials and methods</h3><div>Data from 30 patients previously treated with pelvic stereotactic body radiotherapy (SBRT) at three UK centres were included. OARs were delineated on both previous and reirradiation image sets and deformably registered. Previous dose was mapped to the current image set and used as background dose for SBRT planning, following published methods. Initial 25 Gy in five fractions (25 Gy/5#) plans were generated for all patients, with further isotoxic dose escalation conducted up to a maximum of 50 Gy (fraction number fixed) until cumulative EQD2Gy constraints were reached.</div></div><div><h3>Results</h3><div>For 25 of 30 patients, clinically acceptable isotoxic plans were obtained, with 23 exceeding the standard UK reirradiation prescription dose of 30 Gy/5#. The median isotoxic prescription was 42 Gy/5#, with four patient plans reaching the upper evaluated limit of 50 Gy. Vessels and the sacral plexus were most frequently dose limiting.</div></div><div><h3>Conclusion</h3><div>This study highlighted the feasibility of isotoxic pelvic reirradiation and supports further investigation into automation and prediction models to streamline implementation in clinical practice.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100889"},"PeriodicalIF":3.3,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145799271","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}
Pub Date : 2025-12-11DOI: 10.1016/j.phro.2025.100890
Mathieu Gaudreault , Lachlan McIntosh , Katrina Woodford , Jason Li , Susan Harden , Sandro Porceddu , Nicholas Hardcastle , Vanessa Panettieri
Background and purpose
The monitor units (MU) per control point (CP) control the necessary fine-tuned ablative dose for hypofractionated radiotherapy of oligometastatic cancer. We aimed to introduce strategies maximising the sample size to accurately predict the MU per CP with artificial intelligence (AI).
Materials and methods
The 40/68/88 treatment plans of consecutive patients treated between 01/2019 and 06/2024 at our institution for metastatic cancer to the liver/bone/lung were included. Two approaches were considered to maximise the sample size. In one approach, the samples of each anatomical site were extensively augmented to predict the MU per CP from the dose distribution per CP, providing the MU per beam and meterset weight per CP. In the other approach, all samples from all anatomical sites were combined for training. The number of achieved clinical goals based on dose-volume calculation metrics in AI radiotherapy plans (AI-RTPlan) was compared with the number of achieved clinical goals in the clinical plans.
Results
The mean absolute percentage error between predicted and clinical MU per beam/meterset weight per CP was less than 6.2%. All AI-RTPlans were generated in less than 5 s. At least 90%/5% of patients had the same, or more, achieved clinical goals with AI-RTPlans. Target coverage and dose to organs at risk metrics were within ± 2% and ± 2.3 Gy of the clinical value in all patients, respectively.
Conclusions
Augmenting data extensively and combining anatomical sites were equivalent and proficient strategies to predict machine settings for radiotherapy planning of oligometastatic cancer.
{"title":"A deep learning approach for predicting linear accelerator output settings in automated radiotherapy planning of oligometastatic cancer","authors":"Mathieu Gaudreault , Lachlan McIntosh , Katrina Woodford , Jason Li , Susan Harden , Sandro Porceddu , Nicholas Hardcastle , Vanessa Panettieri","doi":"10.1016/j.phro.2025.100890","DOIUrl":"10.1016/j.phro.2025.100890","url":null,"abstract":"<div><h3>Background and purpose</h3><div>The monitor units (MU) per control point (CP) control the necessary fine-tuned ablative dose for hypofractionated radiotherapy of oligometastatic cancer. We aimed to introduce strategies maximising the sample size to accurately predict the MU per CP with artificial intelligence (AI).</div></div><div><h3>Materials and methods</h3><div>The 40/68/88 treatment plans of consecutive patients treated between 01/2019 and 06/2024 at our institution for metastatic cancer to the liver/bone/lung were included. Two approaches were considered to maximise the sample size. In one approach, the samples of each anatomical site were extensively augmented to predict the MU per CP from the dose distribution per CP, providing the MU per beam and meterset weight per CP. In the other approach, all samples from all anatomical sites were combined for training. The number of achieved clinical goals based on dose-volume calculation metrics in AI radiotherapy plans (AI-RTPlan) was compared with the number of achieved clinical goals in the clinical plans.</div></div><div><h3>Results</h3><div>The mean absolute percentage error between predicted and clinical MU per beam/meterset weight per CP was less than 6.2%. All AI-RTPlans were generated in less than 5 s. At least 90%/5% of patients had the same, or more, achieved clinical goals with AI-RTPlans. Target coverage and dose to organs at risk metrics were within ± 2% and ± 2.3 Gy of the clinical value in all patients, respectively.</div></div><div><h3>Conclusions</h3><div>Augmenting data extensively and combining anatomical sites were equivalent and proficient strategies to predict machine settings for radiotherapy planning of oligometastatic cancer.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"37 ","pages":"Article 100890"},"PeriodicalIF":3.3,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145760658","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}
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