Pub Date : 2025-01-01DOI: 10.1016/j.phro.2024.100691
Dirk Wagenaar, Johannes A. Langendijk, Stefan Both
The McNamara (MCN) and Wedenberg (WED) RBE weighted dose (DRBE), dose and dose-weighted average LET (LETd) were calculated in twenty brain cancer patients. A linear approximation was made for each RBE model to give best agreement to clinically relevant dosimetric parameters. Additional evaluations were done on twenty head and neck and twenty breast cancer patients.The R2 of the fits was ≥0.94 and ≥0.91 for MCN and WED respectively for α/β values ≥1.0 Gy. The graphs derived in this work can be used to convert RBE-LET slopes derived from clinical data to α/β values in the MCN or WED models.
{"title":"Linear approximation of variable relative biological effectiveness models for proton therapy","authors":"Dirk Wagenaar, Johannes A. Langendijk, Stefan Both","doi":"10.1016/j.phro.2024.100691","DOIUrl":"10.1016/j.phro.2024.100691","url":null,"abstract":"<div><div>The McNamara (MCN) and Wedenberg (WED) RBE weighted dose (D<sub>RBE</sub>), dose and dose-weighted average LET (LET<sub>d</sub>) were calculated in twenty brain cancer patients. A linear approximation was made for each RBE model to give best agreement to clinically relevant dosimetric parameters. Additional evaluations were done on twenty head and neck and twenty breast cancer patients.The R<sup>2</sup> of the fits was ≥0.94 and ≥0.91 for MCN and WED respectively for α/β values ≥1.0 Gy. The graphs derived in this work can be used to convert RBE-LET slopes derived from clinical data to α/β values in the MCN or WED models.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100691"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143068554","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100716
Josh Mason, Jack Doherty, Sarah Robinson, Meagan de la Bastide, Jack Miskell, Ruth McLauchlan
For 18 months following clinical introduction of deep-learning auto-segmentation (DLAS), an audit of organ at risk (OAR) contour editing was performed, including 1255 patients from a single institution and the majority of tumour sites. Mean surface-Dice similarity coefficient increased from 0.87 to 0.97, the number of unedited OARs increased from 21.5 % to 40 %. The audit identified changes in editing corresponding to vendor model changes, adaption of local contouring practice and reduced editing in areas of no clinical significance. The audit allowed assessment of the level and frequency of editing and identification of outlier cases.
{"title":"Auditing the clinical usage of deep-learning based organ-at-risk auto-segmentation in radiotherapy","authors":"Josh Mason, Jack Doherty, Sarah Robinson, Meagan de la Bastide, Jack Miskell, Ruth McLauchlan","doi":"10.1016/j.phro.2025.100716","DOIUrl":"10.1016/j.phro.2025.100716","url":null,"abstract":"<div><div>For 18 months following clinical introduction of deep-learning auto-segmentation (DLAS), an audit of organ at risk (OAR) contour editing was performed, including 1255 patients from a single institution and the majority of tumour sites. Mean surface-Dice similarity coefficient increased from 0.87 to 0.97, the number of unedited OARs increased from 21.5 % to 40 %. The audit identified changes in editing corresponding to vendor model changes, adaption of local contouring practice and reduced editing in areas of no clinical significance. The audit allowed assessment of the level and frequency of editing and identification of outlier cases.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100716"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130571","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}
Radiotherapy for localized prostate cancer often targets the entire prostate with a uniform dose despite the presence of high-risk dominant intraprostatic lesions (DILs). This study investigated the feasibility of focal dose-averaged linear energy transfer (LETd) boost for prostate carbon-ion radiotherapy to deposit higher LETd to DILs while ensuring desired relative biological effectiveness weighted dose coverage to targets and sparing organs at risk (OARs).
Materials and methods
A retrospective planning study was conducted on 15 localized prostate cancer cases. The DILs were identified on multiparametric MRI and used to define the boost target (PTVboost). Two treatment plans were designed for each patient: 1) conventional plan optimized by the single-field uniform dose technique, and 2) boost plan optimized by the multifield optimization and LET painting technique, to achieve LETd boost within the PTVboost. Dose and LETd metrics of the targets and OARs were compared between the two plans.
Results
Compared to the conventional plans, the boost plans delivered clinically acceptable dose coverage (D90% and D50%) to the target (PTV2) within 1% differences while significantly increasing the minimum LETd by 16 ∼ 24 keV/μm for the PTVboost (63.9 ± 2.8 vs. 44.0 ± 1.3 keV/μm, p < 0.001). Furthermore, these improvements were consistent across all cases, irrespective of their anatomical features, including the boost volume’s size, location, and shape.
Conclusion
Focal LETd boost was a feasible strategy for prostate carbon-ion radiotherapy. This investigation demonstrated its superiority in delivering LETd boost without depending on tumor location and volume across different cases.
{"title":"Optimizing the dose-averaged linear energy transfer for the dominant intraprostatic lesions in high-risk localized prostate cancer patients","authors":"Bo Zhao , Nobuyuki Kanematsu , Shuri Aoki , Shinichiro Mori , Hideyuki Mizuno , Takamitsu Masuda , Hideyuki Takei , Hitoshi Ishikawa","doi":"10.1016/j.phro.2025.100727","DOIUrl":"10.1016/j.phro.2025.100727","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Radiotherapy for localized prostate cancer often targets the entire prostate with a uniform dose despite the presence of high-risk dominant intraprostatic lesions (DILs). This study investigated the feasibility of focal dose-averaged linear energy transfer (LET<sub>d</sub>) boost for prostate carbon-ion radiotherapy to deposit higher LET<sub>d</sub> to DILs while ensuring desired relative biological effectiveness weighted dose coverage to targets and sparing organs at risk (OARs).</div></div><div><h3>Materials and methods</h3><div>A retrospective planning study was conducted on 15 localized prostate cancer cases. The DILs were identified on multiparametric MRI and used to define the boost target (PTV<sub>boost</sub>). Two treatment plans were designed for each patient: 1) conventional plan optimized by the single-field uniform dose technique, and 2) boost plan optimized by the multifield optimization and LET painting technique, to achieve LET<sub>d</sub> boost within the PTV<sub>boost</sub>. Dose and LET<sub>d</sub> metrics of the targets and OARs were compared between the two plans.</div></div><div><h3>Results</h3><div>Compared to the conventional plans, the boost plans delivered clinically acceptable dose coverage (D<sub>90%</sub> and D<sub>50%</sub>) to the target (PTV2) within 1% differences while significantly increasing the minimum LET<sub>d</sub> by 16 ∼ 24 keV/μm for the PTV<sub>boost</sub> (63.9 ± 2.8 vs. 44.0 ± 1.3 keV/μm, p < 0.001). Furthermore, these improvements were consistent across all cases, irrespective of their anatomical features, including the boost volume’s size, location, and shape.</div></div><div><h3>Conclusion</h3><div>Focal LET<sub>d</sub> boost was a feasible strategy for prostate carbon-ion radiotherapy. This investigation demonstrated its superiority in delivering LET<sub>d</sub> boost without depending on tumor location and volume across different cases.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100727"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379452","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100719
Rachael Tulip , Sebastian Andersson , Robert Chuter , Spyros Manolopoulos
Synthetic Computed Tomography (sCT) is required to provide electron density information for MR-only radiotherapy. Deep-learning (DL) methods for sCT generation show improved dose congruence over other sCT generation methods (e.g. bulk density). Using 30 female pelvis datasets to train a cycleGAN-inspired DL model, this study found mean dose differences between a deformed planning CT (dCT) and sCT were 0.2 % (D98 %). Three Dimensional Gamma analysis showed a mean of 90.4 % at 1 %/1mm. This study showed accurate sCTs (dose) can be generated from routinely available T2 spin echo sequences without the need for additional specialist sequences.
{"title":"Synthetic Computed Tomography generation using deep-learning for female pelvic radiotherapy planning","authors":"Rachael Tulip , Sebastian Andersson , Robert Chuter , Spyros Manolopoulos","doi":"10.1016/j.phro.2025.100719","DOIUrl":"10.1016/j.phro.2025.100719","url":null,"abstract":"<div><div>Synthetic Computed Tomography (sCT) is required to provide electron density information for MR-only radiotherapy. Deep-learning (DL) methods for sCT generation show improved dose congruence over other sCT generation methods (e.g. bulk density). Using 30 female pelvis datasets to train a cycleGAN-inspired DL model, this study found mean dose differences between a deformed planning CT (dCT) and sCT were 0.2 % (D98 %). Three Dimensional Gamma analysis showed a mean of 90.4 % at 1 %/1mm. This study showed accurate sCTs (dose) can be generated from routinely available T2 spin echo sequences without the need for additional specialist sequences.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100719"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143268019","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100697
Clinton Gibson, Joseph B. Schulz, Amy Yu, Piotr Dubrowski, Lawrie Skinner
This study evaluates alternative shielding materials to lead for protecting the scalp and nails during total skin electron irradiation. We tested a silicone helmet, tungsten-doped silicone mittens, and planar aluminum and copper shields. The helmet and mittens were created using 3D modeling software and fused filament fabrication printing, while the planar shields were machined and assembled with printed hardware. Transmission measurements showed transmission rates of 4.5%–6.8% for the mittens, 5.8%–9.1% for the helmet, and 7.5% for the planar shields. The silicone-based devices improve comfort and usability, and slight design changes can enhance coverage and application.
{"title":"Nontoxic generalized patient shielding devices for total skin electron therapy","authors":"Clinton Gibson, Joseph B. Schulz, Amy Yu, Piotr Dubrowski, Lawrie Skinner","doi":"10.1016/j.phro.2025.100697","DOIUrl":"10.1016/j.phro.2025.100697","url":null,"abstract":"<div><div>This study evaluates alternative shielding materials to lead for protecting the scalp and nails during total skin electron irradiation. We tested a silicone helmet, tungsten-doped silicone mittens, and planar aluminum and copper shields. The helmet and mittens were created using 3D modeling software and fused filament fabrication printing, while the planar shields were machined and assembled with printed hardware. Transmission measurements showed transmission rates of 4.5%–6.8% for the mittens, 5.8%–9.1% for the helmet, and 7.5% for the planar shields. The silicone-based devices improve comfort and usability, and slight design changes can enhance coverage and application.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100697"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428785","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100733
Baoqiang Ma , Alessia De Biase , Jiapan Guo , Lisanne V. van Dijk , Johannes A. Langendijk , Stefan Both , Peter M.A. van Ooijen , Nanna M. Sijtsema
Background and purpose
Deep learning (DL) models can extract prognostic image features from pre-treatment PET/CT scans. The study objective was to explore the potential benefits of incorporating pathologic lymph node (PL) spatial information in addition to that of the primary tumor (PT) in DL-based models for predicting local control (LC), regional control (RC), distant-metastasis-free survival (DMFS), and overall survival (OS) in oropharyngeal cancer (OPC) patients.
Materials and methods
The study included 409 OPC patients treated with definitive (chemo)radiotherapy between 2010 and 2022. Patient data, including PET/CT scans, manually contoured PT (GTVp) and PL (GTVln) structures, clinical variables, and endpoints, were collected. Firstly, a DL-based method was employed to segment tumours in PET/CT, resulting in predicted probability maps for PT (TPMp) and PL (TPMln). Secondly, different combinations of CT, PET, manual contours and probability maps from 300 patients were used to train DL-based outcome prediction models for each endpoint through 5-fold cross validation. Model performance, assessed by concordance index (C-index), was evaluated using a test set of 100 patients.
Results
Including PL improved the C-index results for all endpoints except LC. For LC, comparable C-indices (around 0.66) were observed between models trained using only PT and those incorporating PL as additional structure. Models trained using PT and PL combined into a single structure achieved the highest C-index of 0.65 and 0.80 for RC and DMFS prediction, respectively. Models trained using these target structures as separate entities achieved the highest C-index of 0.70 for OS.
Conclusion
Incorporating lymph node spatial information improved the prediction performance for RC, DMFS, and OS.
{"title":"The prognostic value of pathologic lymph node imaging using deep learning-based outcome prediction in oropharyngeal cancer patients","authors":"Baoqiang Ma , Alessia De Biase , Jiapan Guo , Lisanne V. van Dijk , Johannes A. Langendijk , Stefan Both , Peter M.A. van Ooijen , Nanna M. Sijtsema","doi":"10.1016/j.phro.2025.100733","DOIUrl":"10.1016/j.phro.2025.100733","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Deep learning (DL) models can extract prognostic image features from pre-treatment PET/CT scans. The study objective was to explore the potential benefits of incorporating pathologic lymph node (PL) spatial information in addition to that of the primary tumor (PT) in DL-based models for predicting local control (LC), regional control (RC), distant-metastasis-free survival (DMFS), and overall survival (OS) in oropharyngeal cancer (OPC) patients.</div></div><div><h3>Materials and methods</h3><div>The study included 409 OPC patients treated with definitive (chemo)radiotherapy between 2010 and 2022. Patient data, including PET/CT scans, manually contoured PT (GTVp) and PL (GTVln) structures, clinical variables, and endpoints, were collected. Firstly, a DL-based method was employed to segment tumours in PET/CT, resulting in predicted probability maps for PT (TPMp) and PL (TPMln). Secondly, different combinations of CT, PET, manual contours and probability maps from 300 patients were used to train DL-based outcome prediction models for each endpoint through 5-fold cross validation. Model performance, assessed by concordance index (C-index), was evaluated using a test set of 100 patients.</div></div><div><h3>Results</h3><div>Including PL improved the C-index results for all endpoints except LC. For LC, comparable C-indices (around 0.66) were observed between models trained using only PT and those incorporating PL as additional structure. Models trained using PT and PL combined into a single structure achieved the highest C-index of 0.65 and 0.80 for RC and DMFS prediction, respectively. Models trained using these target structures as separate entities achieved the highest C-index of 0.70 for OS.</div></div><div><h3>Conclusion</h3><div>Incorporating lymph node spatial information improved the prediction performance for RC, DMFS, and OS.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100733"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437653","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2024.100689
Michael J. Dubec , Michael Berks , James Price , Lisa McDaid , John Gaffney , Ross A. Little , Susan Cheung , Marcel van Herk , Ananya Choudhury , Julian C. Matthews , Andrew McPartlin , Geoff J.M. Parker , David L. Buckley , James P.B. O’Connor
Background and purpose
Magnetic resonance imaging – linear accelerator (MRI-linac) systems permit imaging of tumours to guide treatment. Dynamic contrast enhanced (DCE)-MRI allows investigation of tumour perfusion. We assessed the feasibility of performing DCE-MRI on a 1.5 T MRI-linac in patients with head and neck cancer (HNC) and measured biomarker repeatability and sensitivity to radiotherapy effects.
Materials and methods
Patients were imaged on a 1.5 T MRI-linac or a 1.5 T diagnostic MR system twice before treatment. DCE-MRI parameters including Ktrans were calculated, with the optimum pharmacokinetic model identified using corrected Akaike information criterion. Repeatability was assessed by within-subject coefficient of variation (wCV). Treatment effects were assessed as change measured at week 2 of radiotherapy.
Results
14 patients were recruited (6 scanned on diagnostic MR and 8 on MRI-linac), with a total of 24 lesions. Baseline Ktrans estimates were comparable on both MR systems; 0.13 [95 %CI: 0.10 to 0.16] min−1 (diagnostic MR) and 0.15 [0.12 to 0.18] min−1 (MRI-linac). wCV values were 22.6 % [95 % CI: 16.2 to 37.3 %] (diagnostic MR) and 11.7 % [8.4 to 19.3 %] (MRI-linac). Combined cohort increase in Ktrans was significant (p < 0.01). Similar results were seen for other DCE-MRI parameters.
Conclusions
DCE-MRI is feasible on a 1.5 T MRI-linac system in patients with HNC. Parameter estimates, repeatability, and sensitivity to treatment were similar to those measured on a conventional diagnostic MR system. These data support performing DCE-MRI in studies on the MRI-linac to assess treatment response and adaptive guidance based on tumour perfusion.
背景和目的：磁共振成像-线性加速器（MRI-linac）系统允许肿瘤成像指导治疗。动态对比增强(DCE)-MRI可以检查肿瘤灌注情况。我们评估了在头颈癌（HNC）患者的1.5 T mri直线上进行DCE-MRI的可行性，并测量了生物标志物的可重复性和对放疗效果的敏感性。材料和方法：患者在治疗前两次在1.5 T mri直线仪或1.5 T诊断MR系统上成像。计算包括Ktrans在内的DCE-MRI参数，并使用修正的赤池信息准则确定最佳药代动力学模型。用受试者内变异系数（wCV）评价重复性。以放射治疗第2周时测量的变化来评估治疗效果。结果：纳入14例患者（6例诊断MR扫描，8例mri直线扫描），共24个病灶。两种MR系统的基线Ktrans估计值具有可比性；0.13 [95% CI: 0.10至0.16]min-1（诊断MR）和0.15[0.12至0.18]min-1 （mri线性）。wCV值为22.6% (95% CI: 16.2 ~ 37.3%)（诊断MR）和11.7% （mri线性）（8.4 ~ 19.3%）。结论：DCE-MRI在1.5 T MRI-linac系统上对HNC患者是可行的。参数估计、可重复性和对治疗的敏感性与传统诊断MR系统测量的结果相似。这些数据支持在MRI-linac研究中使用DCE-MRI来评估治疗反应和基于肿瘤灌注的适应性指导。
{"title":"Translation of dynamic contrast-enhanced imaging onto a magnetic resonance-guided linear accelerator in patients with head and neck cancer","authors":"Michael J. Dubec , Michael Berks , James Price , Lisa McDaid , John Gaffney , Ross A. Little , Susan Cheung , Marcel van Herk , Ananya Choudhury , Julian C. Matthews , Andrew McPartlin , Geoff J.M. Parker , David L. Buckley , James P.B. O’Connor","doi":"10.1016/j.phro.2024.100689","DOIUrl":"10.1016/j.phro.2024.100689","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Magnetic resonance imaging – linear accelerator (MRI-linac) systems permit imaging of tumours to guide treatment. Dynamic contrast enhanced (DCE)-MRI allows investigation of tumour perfusion. We assessed the feasibility of performing DCE-MRI on a 1.5 T MRI-linac in patients with head and neck cancer (HNC) and measured biomarker repeatability and sensitivity to radiotherapy effects.</div></div><div><h3>Materials and methods</h3><div>Patients were imaged on a 1.5 T MRI-linac or a 1.5 T diagnostic MR system twice before treatment. DCE-MRI parameters including K<sup>trans</sup> were calculated, with the optimum pharmacokinetic model identified using corrected Akaike information criterion. Repeatability was assessed by within-subject coefficient of variation (wCV). Treatment effects were assessed as change measured at week 2 of radiotherapy.</div></div><div><h3>Results</h3><div>14 patients were recruited (6 scanned on diagnostic MR and 8 on MRI-linac), with a total of 24 lesions. Baseline K<sup>trans</sup> estimates were comparable on both MR systems; 0.13 [95 %CI: 0.10 to 0.16] min<sup>−1</sup> (diagnostic MR) and 0.15 [0.12 to 0.18] min<sup>−1</sup> (MRI-linac). wCV values were 22.6 % [95 % CI: 16.2 to 37.3 %] (diagnostic MR) and 11.7 % [8.4 to 19.3 %] (MRI-linac). Combined cohort increase in K<sup>trans</sup> was significant (p < 0.01). Similar results were seen for other DCE-MRI parameters.</div></div><div><h3>Conclusions</h3><div>DCE-MRI is feasible on a 1.5 T MRI-linac system in patients with HNC. Parameter estimates, repeatability, and sensitivity to treatment were similar to those measured on a conventional diagnostic MR system. These data support performing DCE-MRI in studies on the MRI-linac to assess treatment response and adaptive guidance based on tumour perfusion.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100689"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11721217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972457","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100714
Roel C. Kwakernaak, Victor J. Brand, Jesús Rojo-Santiago, Femke E. Froklage, Mischa S. Hoogeman, Steven J.M. Habraken, Maaike T.W. Milder
Background and purpose
Erectile dysfunction is a common side effect of radiotherapy for prostate cancer. To mitigate this toxicity, it has been suggested to limit the dose to critical nerves and vessels. We investigated the feasibility of sparing the neuro-vascular bundles (NVBs) in stereotactic body radiotherapy under the impact of realistic treatment uncertainties.
Materials and methods
Non-sparing and sparing NVB treatment plans, delivered in 5 × 7.25 Gy, were automatically generated for 20 patients. Polynomial Chaos Expansion (PCE) was used to fast and accurately model the dose against treatment errors. PCE enabled a robustness evaluation of 100.000 treatment scenarios per plan, allowing to derive scenario distributions of clinically relevant dose volume histogram parameters and population dose histograms.
Results
An average decrease of 3.7 Gy and 4.4 Gy in the median of the NVB was achieved in the patient population in the presence of realistic treatment uncertainties for non-coplanar (NC) and coplanar (C) plans respectively. Sparing NVBs decreased planning target volume coverage by 2.1 % in on average, however clinical target volume (CTV) dose remained adequate. Population dose histograms showed that, while sparing does impact dose volume histogram parameters of organs at risk (OARs), the probability of a scenario exceeding planning constraints was limited.
Conclusion
NVB sparing was maintained in the presence of treatment uncertainties without compromising CTV coverage or OAR dose. There was no significant difference in the achieved NVB dose between NC and C plans. The clinical impact of the achieved sparing is subject of ongoing clinical trials.
{"title":"Neurovascular bundle sparing in hypofractionated radiotherapy maintained with realistic treatment uncertainties","authors":"Roel C. Kwakernaak, Victor J. Brand, Jesús Rojo-Santiago, Femke E. Froklage, Mischa S. Hoogeman, Steven J.M. Habraken, Maaike T.W. Milder","doi":"10.1016/j.phro.2025.100714","DOIUrl":"10.1016/j.phro.2025.100714","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Erectile dysfunction is a common side effect of radiotherapy for prostate cancer. To mitigate this toxicity, it has been suggested to limit the dose to critical nerves and vessels. We investigated the feasibility of sparing the neuro-vascular bundles (NVBs) in stereotactic body radiotherapy under the impact of realistic treatment uncertainties.</div></div><div><h3>Materials and methods</h3><div>Non-sparing and sparing NVB treatment plans, delivered in 5 × 7.25 Gy, were automatically generated for 20 patients. Polynomial Chaos Expansion (PCE) was used to fast and accurately model the dose against treatment errors. PCE enabled a robustness evaluation of 100.000 treatment scenarios per plan, allowing to derive scenario distributions of clinically relevant dose volume histogram parameters and population dose histograms.</div></div><div><h3>Results</h3><div>An average decrease of 3.7 Gy and 4.4 Gy in the median <span><math><mrow><msub><mi>D</mi><mrow><mn>0.1</mn><mi>c</mi><msup><mrow><mi>m</mi></mrow><mn>3</mn></msup></mrow></msub></mrow></math></span> of the NVB was achieved in the patient population in the presence of realistic treatment uncertainties for non-coplanar (NC) and coplanar (C) plans respectively. Sparing NVBs decreased planning target volume coverage by 2.1 % in <span><math><mrow><msub><mi>V</mi><mrow><mn>36.25</mn><mi>G</mi><mi>y</mi></mrow></msub></mrow></math></span> on average, however clinical target volume (CTV) dose remained adequate. Population dose histograms showed that, while sparing does impact dose volume histogram parameters of organs at risk (OARs), the probability of a scenario exceeding planning constraints was limited.</div></div><div><h3>Conclusion</h3><div>NVB sparing was maintained in the presence of treatment uncertainties without compromising CTV coverage or OAR dose. There was no significant difference in the achieved NVB dose between NC and C plans. The clinical impact of the achieved sparing is subject of ongoing clinical trials.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100714"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130343","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100701
Artemis Bouzaki , Dylan Green , Marcel van Herk , Jane Shortall , Tanuj Puri , Sarah Kerns , David Azria , Marrie-Pierre Farcy-Jacquet , Jenny Chang-Claude , Ananya Choudhury , Alison Dunning , Maarten Lambrecht , Barbara Avuzzi , Dirk De Ruysscher , Petra Seibold , Elena Sperk , Christopher Talbot , Ana Vega , Liv Veldeman , Adam Webb , Alan McWilliam
Background and purpose
Growing evidence suggests that spatial dose variations across the rectal surface influence toxicity risk after radiotherapy. Existing methodologies employ a fixed, arbitrary physical extent for rectal dose mapping, limiting their analysis. We developed a method to standardise rectum contours, unfold them into 2D cylindrical surface maps, and identify subregions where higher doses increase rectal toxicities.
Materials and methods
Data of 1,048 patients with prostate cancer from the REQUITE study were used. Deep learning based automatic segmentations were generated to ensure consistency. Rectum length was standardised using linear transformations superior and inferior to the prostate. The automatic contours were validated against the manual contours through contour variation assessment with cylindrical mapping. Voxel-based analysis of the dose surface maps for the manual and automatic contours against individual rectal toxicities was performed using Student’s t permutation test and Cox Proportional Hazards Model (CPHM). Significance was defined by permutation testing.
Results
Our method enabled the analysis of 1,048 patients using automatic segmentation. Student’s t-test showed significance (p < 0.05) in the lower posterior for clinical-reported proctitis and patient-reported bowel urgency. Univariable CPHM identified a 3 % increased risk per Gy for clinician-reported proctitis and a 2 % increased risk per Gy for patient-reported bowel urgency in the lower posterior. No other endpoints were significant.
Conclusion
We developed a methodology that unfolds the rectum to a 2D surface map. The lower posterior was significant for clinician-reported proctitis and patient-reported bowel urgency, suggesting that reducing the dose in the region could decrease toxicity risk.
{"title":"New rectum dose surface mapping methodology to identify rectal subregions associated with toxicities following prostate cancer radiotherapy","authors":"Artemis Bouzaki , Dylan Green , Marcel van Herk , Jane Shortall , Tanuj Puri , Sarah Kerns , David Azria , Marrie-Pierre Farcy-Jacquet , Jenny Chang-Claude , Ananya Choudhury , Alison Dunning , Maarten Lambrecht , Barbara Avuzzi , Dirk De Ruysscher , Petra Seibold , Elena Sperk , Christopher Talbot , Ana Vega , Liv Veldeman , Adam Webb , Alan McWilliam","doi":"10.1016/j.phro.2025.100701","DOIUrl":"10.1016/j.phro.2025.100701","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Growing evidence suggests that spatial dose variations across the rectal surface influence toxicity risk after radiotherapy. Existing methodologies employ a fixed, arbitrary physical extent for rectal dose mapping, limiting their analysis. We developed a method to standardise rectum contours, unfold them into 2D cylindrical surface maps, and identify subregions where higher doses increase rectal toxicities.</div></div><div><h3>Materials and methods</h3><div>Data of 1,048 patients with prostate cancer from the REQUITE study were used. Deep learning based automatic segmentations were generated to ensure consistency. Rectum length was standardised using linear transformations superior and inferior to the prostate. The automatic contours were validated against the manual contours through contour variation assessment with cylindrical mapping. Voxel-based analysis of the dose surface maps for the manual and automatic contours against individual rectal toxicities was performed using Student’s t permutation test and Cox Proportional Hazards Model (CPHM). Significance was defined by permutation testing.</div></div><div><h3>Results</h3><div>Our method enabled the analysis of 1,048 patients using automatic segmentation. Student’s <em>t</em>-test showed significance (p < 0.05) in the lower posterior for clinical-reported proctitis and patient-reported bowel urgency. Univariable CPHM identified a 3 % increased risk per Gy for clinician-reported proctitis and a 2 % increased risk per Gy for patient-reported bowel urgency in the lower posterior. No other endpoints were significant.</div></div><div><h3>Conclusion</h3><div>We developed a methodology that unfolds the rectum to a 2D surface map. The lower posterior was significant for clinician-reported proctitis and patient-reported bowel urgency, suggesting that reducing the dose in the region could decrease toxicity risk.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100701"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130345","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}
Pub Date : 2025-01-01DOI: 10.1016/j.phro.2025.100702
Karen Chin Snyder, Salim M. Siddiqui, Parag Parikh, Kundan Thind
Background and Purpose
Online adaptive radiotherapy for fractionated intracranial stereotactic radiosurgery (FSRS) on a magnetic resonance linear accelerator (MR-L) has the potential to allow for real-time adjustments of anatomical changes during radiotherapy treatment. This study investigates the dosimetric improvements of an online-adaptive MR-L workflow and validates the dosimetry utilizing an MR-visible phantom.
Methods and materials
Twenty-six cases previously treated with a conventional C-arm linear accelerator (CA-L) were replanned to determine optimal optimization constraints and objectives for achieving comparable MR-L plans. The optimization methodology was subsequently applied to simulate an online adaptive workflow on an MR phantom, incorporating target volumes from five previously treated patients that required offline adaptation. Plan quality and normal brain dose statistics were evaluated and compared to the offline adapted CA-L plans.
Results
No significant difference was observed between the CA-L and MR-L target coverage. The normal brain dose for MR-L plans increased with target volume more rapidly than for CA-L plans. However, some outliers achieved equivalent normal brain doses, indicating potential benefits of MRIgRT for specific superficial volumes located in the frontal, occipital lobes, and cerebellum. End-to-end validation with simulated adaptive workflow on a MR phantom utilizing target volumes that previously required adaption showed acceptable difference of <2.5 % between measured and planned target dose.
Conclusion
The study shows promising results for an online adaptive workflow for the treatment of intracranial FSRS on a low-field MR-L.
{"title":"Adaptive treatment workflow and dosimetric evaluation of intracranial fractionated stereotactic radiosurgery on a low-field magnetic resonance-linear accelerator","authors":"Karen Chin Snyder, Salim M. Siddiqui, Parag Parikh, Kundan Thind","doi":"10.1016/j.phro.2025.100702","DOIUrl":"10.1016/j.phro.2025.100702","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Online adaptive radiotherapy for fractionated intracranial stereotactic radiosurgery (FSRS) on a magnetic resonance linear accelerator (MR-L) has the potential to allow for real-time adjustments of anatomical changes during radiotherapy treatment. This study investigates the dosimetric improvements of an online-adaptive MR-L workflow and validates the dosimetry utilizing an MR-visible phantom.</div></div><div><h3>Methods and materials</h3><div>Twenty-six cases previously treated with a conventional C-arm linear accelerator (CA-L) were replanned to determine optimal optimization constraints and objectives for achieving comparable MR-L plans. The optimization methodology was subsequently applied to simulate an online adaptive workflow on an MR phantom, incorporating target volumes from five previously treated patients that required offline adaptation. Plan quality and normal brain dose statistics were evaluated and compared to the offline adapted CA-L plans.</div></div><div><h3>Results</h3><div>No significant difference was observed between the CA-L and MR-L target coverage. The normal brain dose for MR-L plans increased with target volume more rapidly than for CA-L plans. However, some outliers achieved equivalent normal brain doses, indicating potential benefits of MRIgRT for specific superficial volumes located in the frontal, occipital lobes, and cerebellum. End-to-end validation with simulated adaptive workflow on a MR phantom utilizing target volumes that previously required adaption showed acceptable difference of <2.5 % between measured and planned target dose.</div></div><div><h3>Conclusion</h3><div>The study shows promising results for an online adaptive workflow for the treatment of intracranial FSRS on a low-field MR-L.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"33 ","pages":"Article 100702"},"PeriodicalIF":3.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143130572","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}
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