Physics and Imaging in Radiation Oncology最新文献

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Feasibility and potential clinical benefit of dose de-escalation in stereotactic ablative radiotherapy for lung cancer lesions with ground glass opacities 立体定向消融放疗剂量递减治疗肺癌磨玻璃混浊的可行性及潜在临床效益。
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100681
Carla Cases , Meritxell Mollà , Marcelo Sánchez , Mariana Benegas , Marc Ballestero , Sergi Serrano-Rueda , Gabriela Antelo , Carles Gomà
{"title":"Feasibility and potential clinical benefit of dose de-escalation in stereotactic ablative radiotherapy for lung cancer lesions with ground glass opacities","authors":"Carla Cases ,&nbsp;Meritxell Mollà ,&nbsp;Marcelo Sánchez ,&nbsp;Mariana Benegas ,&nbsp;Marc Ballestero ,&nbsp;Sergi Serrano-Rueda ,&nbsp;Gabriela Antelo ,&nbsp;Carles Gomà","doi":"10.1016/j.phro.2024.100681","DOIUrl":"10.1016/j.phro.2024.100681","url":null,"abstract":"<div><h3>Introduction</h3><div>Treatment of neoplasic lung nodules with ground glass opacities (GGO) faces two primary challenges. First, the standard practice of treating GGOs as solid nodules, which effectively controls the tumor locally, but might increase associated toxicities. The second is the potential for dose calculation errors related to increased heterogeneity. This study addresses the optimization of a dose de-escalation regime for stereotactic ablative radiotherapy (SABR) for GGO lesions.</div></div><div><h3>Materials and Methods</h3><div>We used the CT scans of 35 patients (40 lesions) with some degree of GGO component treated at our institution between 2017 and 2021. We first assessed the dose calculation accuracy as a function of the GGO component of the lesion. We then analysed the advantages of a dose de-escalation regime in terms of lung dose reduction (Dmean, V20Gy and V300GyBED3) and plan robustness.</div></div><div><h3>Results</h3><div>We found a positive correlation between the presence of GGO and the dose calculation errors in a phantom scenario. These differences are reduced for patient data and in the presence of breathing motion. When using a de-escalation regime, significant reductions were achieved in mean lung dose, V20Gy and V300GyBED3. This study also revealed that lower doses in GGO areas lead to more stable fluence patterns, increasing treatment robustness.</div></div><div><h3>Conclusions</h3><div>The study lays the foundation for an eventual use of dose de-escalation in SABR for treating lung lesions with GGO, potentially leading to equivalent local control while reducing associated toxicities. These findings lay the groundwork for future clinical trials.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100681"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11663960/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883145","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}
引用次数: 0
Feasibility of quantitative relaxometry for prostate target localization and response assessment in magnetic resonance-guided online adaptive stereotactic body radiotherapy 磁共振引导在线自适应立体定向放射治疗中前列腺靶标定位和反应评估的定量松弛法的可行性。
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100678
Ergys Subashi , Eve LoCastro , Sarah Burleson , Aditya Apte , Michael Zelefsky , Neelam Tyagi
{"title":"Feasibility of quantitative relaxometry for prostate target localization and response assessment in magnetic resonance-guided online adaptive stereotactic body radiotherapy","authors":"Ergys Subashi ,&nbsp;Eve LoCastro ,&nbsp;Sarah Burleson ,&nbsp;Aditya Apte ,&nbsp;Michael Zelefsky ,&nbsp;Neelam Tyagi","doi":"10.1016/j.phro.2024.100678","DOIUrl":"10.1016/j.phro.2024.100678","url":null,"abstract":"<div><h3>Purpose</h3><div>Multiparametric magnetic resonance imaging (MRI) is known to provide predictors for malignancy and treatment outcome. The inclusion of these datasets in workflows for online adaptive planning remains under investigation. We demonstrate the feasibility of longitudinal relaxometry in online MR-guided adaptive stereotactic body radiotherapy (SBRT) to the prostate and dominant intra-prostatic lesion (DIL).</div></div><div><h3>Methods</h3><div>Fifty patients with intermediate-risk prostate cancer were included in the study. The clinical target volume (CTV) was defined as the prostate gland plus 1 cm of seminal vesicles. The gross tumor volume (GTV) was defined as the DIL identified on multiparametric MRI. Online adaptive radiotherapy was delivered in a 1.5 T MR-Linac using a prescription of 800 cGy/900 cGy × 5 fractions to the CTV + 3 mm/GTV + 2 mm. Relaxometry and diffusion-weighted imaging were implemented using clinically available sequences. Test-retest measurements were performed in eight patients, at each treatment fraction. Bias and uncertainty in relaxometry measurements were also assessed using a reference phantom.</div></div><div><h3>Results</h3><div>The bias in longitudinal/transverse relaxation times was negligible while uncertainty was within 3 %. Test-retest measurements demonstrate that bias/uncertainty in patient T1 and T2 were comparable to bias/uncertainty estimated in the phantom. Mean T1 and T2 relaxation were significantly different between the prostate and DIL. The correlation between T1, T2, and diffusion was significant in the DIL, but not in the prostate. During treatment, mean T1 in the DIL approaches mean T1 in the prostate.</div></div><div><h3>Conclusions</h3><div>Longitudinal relaxometry for online MR-guided adaptive SBRT is feasible in a high-field MR-Linac and may provide complementary information for target delineation and response assessment.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100678"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11665667/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883148","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}
引用次数: 0
Pro-active risk analysis of an in-house developed deep learning based autoplanning tool for breast Volumetric Modulated Arc Therapy 内部开发的基于深度学习的乳房体积调制弧线治疗自动规划工具的主动风险分析。
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100677
Liesbeth Vandewinckele , Chahrazad Benazzouz , Laurence Delombaerde , Laure Pape , Truus Reynders , Aline Van der Vorst , Dylan Callens , Jan Verstraete , Adinda Baeten , Caroline Weltens , Wouter Crijns
{"title":"Pro-active risk analysis of an in-house developed deep learning based autoplanning tool for breast Volumetric Modulated Arc Therapy","authors":"Liesbeth Vandewinckele ,&nbsp;Chahrazad Benazzouz ,&nbsp;Laurence Delombaerde ,&nbsp;Laure Pape ,&nbsp;Truus Reynders ,&nbsp;Aline Van der Vorst ,&nbsp;Dylan Callens ,&nbsp;Jan Verstraete ,&nbsp;Adinda Baeten ,&nbsp;Caroline Weltens ,&nbsp;Wouter Crijns","doi":"10.1016/j.phro.2024.100677","DOIUrl":"10.1016/j.phro.2024.100677","url":null,"abstract":"<div><h3>Background and Purpose:</h3><div>With the increasing amount of in-house created deep learning models in radiotherapy, it is important to know how to minimise the risks associated with the local clinical implementation prior to clinical use. The goal of this study is to give an example of how to identify the risks and find mitigation strategies to reduce these risks in an implemented workflow containing a deep learning based planning tool for breast Volumetric Modulated Arc Therapy.</div></div><div><h3>Materials and Methods:</h3><div>The deep learning model ran on a private Google Cloud environment for adequate computational capacity and was integrated into a workflow that could be initiated within the clinical Treatment Planning System (TPS). A proactive Failure Mode and Effect Analysis (FMEA) was conducted by a multidisciplinary team, including physicians, physicists, dosimetrists, technologists, quality managers, and the research and development team. Failure modes categorised as ‘Not acceptable’ and ‘Tolerable’ on the risk matrix were further examined to find mitigation strategies.</div></div><div><h3>Results:</h3><div>In total, 39 failure modes were defined for the total workflow, divided over four steps. Of these, 33 were deemed ‘Acceptable’, five ‘Tolerable’, and one ‘Not acceptable’. Mitigation strategies, such as a case-specific Quality Assurance report, additional scripted checks and properties, a pop-up window, and time stamp analysis, reduced the failure modes to two ‘Tolerable’ and none in the ‘Not acceptable’ region.</div></div><div><h3>Conclusions:</h3><div>The pro-active risk analysis revealed possible risks in the implemented workflow and led to the implementation of mitigation strategies that decreased the risk scores for safer clinical use.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100677"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11697787/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142932913","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}
引用次数: 0
Monte Carlo simulated correction factors for high dose rate brachytherapy postal dosimetry audit methodology 蒙特卡罗模拟高剂量率近距离放射邮政剂量测定审计方法的校正系数
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100657
Krzysztof Chelminski , Alexis Dimitriadis , Roua Abdulrahim , Pavel Kazantsev , Evelyn Granizo-Roman , Jonathan Kalinowski , Shirin Abbasi Enger , Godfrey Azangwe , Mauro Carrara , Jamema Swamidas
{"title":"Monte Carlo simulated correction factors for high dose rate brachytherapy postal dosimetry audit methodology","authors":"Krzysztof Chelminski ,&nbsp;Alexis Dimitriadis ,&nbsp;Roua Abdulrahim ,&nbsp;Pavel Kazantsev ,&nbsp;Evelyn Granizo-Roman ,&nbsp;Jonathan Kalinowski ,&nbsp;Shirin Abbasi Enger ,&nbsp;Godfrey Azangwe ,&nbsp;Mauro Carrara ,&nbsp;Jamema Swamidas","doi":"10.1016/j.phro.2024.100657","DOIUrl":"10.1016/j.phro.2024.100657","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Full-scatter conditions in water are impractical for postal dosimetry audits in brachytherapy. This work presents a method to obtain correction factors that account for deviations from full-scatter water-equivalent conditions for a small plastic phantom.</div></div><div><h3>Material and Methods</h3><div>A 16 × 8 × 3 cm phantom (PMMA) with a radiophotoluminescent dosimeter (RPLD) at the centre and two catheters on either side was simulated using Monte Carlo (MC) to calculate correction factors accounting for the lack of scatter, non-water equivalence of the RPLD and phantom, source model and backscatter for HDR <sup>60</sup>Co and <sup>192</sup>Ir sources.</div></div><div><h3>Results</h3><div>The correction factors for non-water equivalence, lack of full scatter, and the use of PMMA were 1.062 ± 0.013, 1.059 ± 0.008 and 0.993 ± 0.009 for <sup>192</sup>Ir and 1.129 ± 0.005, 1.009 ± 0.005 and 1.005 ± 0.005 for <sup>60</sup>Co respectively. Water-equivalent backscatter thickness of 5 cm was found to be adequate and increasing thickness of backscatter did not have an influence on the RPLD dose. The mean photon energy in the RPLD for four HDR <sup>192</sup>Ir sources was 279 ± 2 keV in full scatter conditions and 295 ± 1 keV in the audit conditions. For <sup>60</sup>Co source the corresponding mean energies were 989 ± 1 keV and 1022 ± 1 keV respectively.</div></div><div><h3>Conclusions</h3><div>Correction factors were obtained through the MC simulations for conditions deviating from TG-43, including the amount of back scatter, and the optimum audit set up. Additionally, the influence of different source models on the correction factors was negligible and demonstrates their generic applicability.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100657"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560794","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}
引用次数: 0
External validation of a multimodality deep-learning normal tissue complication probability model for mandibular osteoradionecrosis trained on 3D radiation distribution maps and clinical variables 根据三维辐射分布图和临床变量训练的下颌骨骨坏死多模态深度学习正常组织并发症概率模型的外部验证
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100668
Laia Humbert-Vidan , Christian R. Hansen , Vinod Patel , Jørgen Johansen , Andrew P. King , Teresa Guerrero Urbano
{"title":"External validation of a multimodality deep-learning normal tissue complication probability model for mandibular osteoradionecrosis trained on 3D radiation distribution maps and clinical variables","authors":"Laia Humbert-Vidan ,&nbsp;Christian R. Hansen ,&nbsp;Vinod Patel ,&nbsp;Jørgen Johansen ,&nbsp;Andrew P. King ,&nbsp;Teresa Guerrero Urbano","doi":"10.1016/j.phro.2024.100668","DOIUrl":"10.1016/j.phro.2024.100668","url":null,"abstract":"<div><h3>Background and purpose</h3><div>While the inclusion of spatial dose information in deep learning (DL)-based normal-tissue complication probability (NTCP) models has been the focus of recent research studies, external validation is still lacking. This study aimed to externally validate a DL-based NTCP model for mandibular osteoradionecrosis (ORN) trained on 3D radiation dose distribution maps and clinical variables.</div></div><div><h3>Methods and materials</h3><div>A 3D DenseNet-40 convolutional neural network (3D-mDN40) was trained on clinical and radiation dose distribution maps on a retrospective class-balanced matched cohort of 184 subjects. A second model (3D-DN40) was trained on dose maps only and both DL models were compared to a logistic regression (LR) model trained on DVH metrics and clinical variables. All models were externally validated by means of their discriminative ability and calibration on an independent dataset of 82 subjects.</div></div><div><h3>Results</h3><div>No significant difference in performance was observed between models. In internal validation, these exhibited similar Brier scores around 0.2, Log Loss values of 0.6–0.7 and ROC AUC values around 0.7 (internal) and 0.6 (external). Differences in clinical variable distributions and their effect sizes were observed between internal and external cohorts, such as smoking status (0.6 vs. 0.1) and chemotherapy (0.1 vs. −0.5), respectively.</div></div><div><h3>Conclusion</h3><div>To our knowledge, this is the first study to externally validate a multimodality DL-based ORN NTCP model. Utilising mandible dose distribution maps, these models show promise for enhancing spatial risk assessment and guiding dental and oncological decision-making, though further research is essential to address overfitting and domain shift for reliable clinical use.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100668"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142660813","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}
引用次数: 0
Accuracy, repeatability, and reproducibility of water-fat magnetic resonance imaging in a phantom and healthy volunteer 模型和健康志愿者的水脂磁共振成像的准确性、可重复性和再现性
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100651
Anouk Corbeau , Pien van Gastel , Piotr A. Wielopolski , Nick de Jong , Carien L. Creutzberg , Uulke A. van der Heide , Stephanie M. de Boer , Eleftheria Astreinidou
{"title":"Accuracy, repeatability, and reproducibility of water-fat magnetic resonance imaging in a phantom and healthy volunteer","authors":"Anouk Corbeau ,&nbsp;Pien van Gastel ,&nbsp;Piotr A. Wielopolski ,&nbsp;Nick de Jong ,&nbsp;Carien L. Creutzberg ,&nbsp;Uulke A. van der Heide ,&nbsp;Stephanie M. de Boer ,&nbsp;Eleftheria Astreinidou","doi":"10.1016/j.phro.2024.100651","DOIUrl":"10.1016/j.phro.2024.100651","url":null,"abstract":"<div><div>Bone marrow (BM) damage due to chemoradiotherapy can increase BM fat in cervical cancer patients. Water-fat magnetic resonance (MR) scans were performed on a phantom and a healthy female volunteer to validate proton density fat fraction accuracy, reproducibility, and repeatability across different vendors, field strengths, and protocols. Phantom measurements showed a high accuracy, high repeatability, and excellent reproducibility. Volunteer measurements had an excellent intra- and interreader reliability, good repeatability, and moderate to good reproducibility. Water-fat MRI show potential for quantification of longitudinal vertebral BM fat changes. Further studies are needed to validate and extend these findings for broader clinical applicability.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100651"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533614","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}
引用次数: 0
Comparing robust proton versus online adaptive photon radiotherapy for short-course treatment of rectal cancer 比较用于直肠癌短程治疗的强质子放疗和在线自适应光子放疗
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100663
Johanna A. Hundvin , Unn Hege Lilleøren , Alexander Valdman , Bruno Sorcini , John Alfred Brennsæter , Camilla G. Boer , Helge E.S. Pettersen , Kathrine R. Redalen , Inger Marie Løes , Sara Pilskog
{"title":"Comparing robust proton versus online adaptive photon radiotherapy for short-course treatment of rectal cancer","authors":"Johanna A. Hundvin ,&nbsp;Unn Hege Lilleøren ,&nbsp;Alexander Valdman ,&nbsp;Bruno Sorcini ,&nbsp;John Alfred Brennsæter ,&nbsp;Camilla G. Boer ,&nbsp;Helge E.S. Pettersen ,&nbsp;Kathrine R. Redalen ,&nbsp;Inger Marie Løes ,&nbsp;Sara Pilskog","doi":"10.1016/j.phro.2024.100663","DOIUrl":"10.1016/j.phro.2024.100663","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Image-guided proton beam therapy (IG-PBT) and cone-beam CT (CBCT)-based online adaptive photon radiotherapy (oART) have potentials to restrict radiation toxicity. They are both hypothesised to reduce therapy limiting bowel toxicity in the multimodality treatment of locally advanced rectal cancer (LARC). This study aimed to quantify the difference in relevant dose-volume metrics for these modalities.</div></div><div><h3>Material and Methods</h3><div>Six-degrees-of-freedom IG-PBT and oART short-course radiotherapy (SCRT) were simulated for 18 LARC patients. Relative biological effectiveness (RBE) was 1.1 for IG-PBT. Delivered dose was evaluated using post-CBCTs. Target coverage was considered robust if average dose to 99% of the clinical target volume was <span><math><mrow><mo>≥</mo></mrow></math></span> 95% of the prescription. Organ at risk (OAR) doses were compared using dose-volume histograms and severe bowel toxicity estimated using dose–response modelling.</div></div><div><h3>Results</h3><div>Target coverage was robust in all patients for oART and all but one patient for IG-PBT. For the main OARs, IG-PBT increased the volume exposed to <span><math><mrow><mo>≥</mo></mrow></math></span> 15 Gy (RBE), but reduced volumes exposed to lower doses. Both low- and high-dose exposure to bowel loops were significantly different between the modalities (median (interquartile range) IG-PBT-V<sub>8.9Gy(RBE)</sub> = 92 (51–156) cm<sup>3</sup>, oART-V<sub>8.9Gy(RBE)</sub> = 166 (107–234) cm<sup>3</sup>, p &lt; 0.001; IG-PBT-V<sub>23Gy(RBE)</sub> = 62 (25–106) cm<sup>3</sup>, oART-V<sub>23Gy(RBE)</sub> = 38 (18–75) cm<sup>3</sup>, p &lt; 0.001), translating into similar total grade ≥ 3 bowel toxicity risk.</div></div><div><h3>Conclusion</h3><div>IG-PBT and oART delivered comparable and satisfying target coverage in SCRT for LARC with similar estimated risk of severe bowel toxicity. Volumes of OAR exposed to 15 Gy (RBE) or more were reduced by oART, while IG-PBT reduced the volumes receiving doses below this level.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100663"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593793","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}
引用次数: 0
Magnetic resonance-guided stereotactic body radiation therapy for pancreatic oligometastases from renal cell carcinoma 磁共振引导下的立体定向体放射治疗肾细胞癌胰腺寡转移瘤。
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100683
Jonna K. van Vulpen , Hidde Eijkelenkamp , Guus Grimbergen , Frank J. Wessels , Sasja F. Mulder , Gert J. Meijer , Martijn P.W. Intven
{"title":"Magnetic resonance-guided stereotactic body radiation therapy for pancreatic oligometastases from renal cell carcinoma","authors":"Jonna K. van Vulpen ,&nbsp;Hidde Eijkelenkamp ,&nbsp;Guus Grimbergen ,&nbsp;Frank J. Wessels ,&nbsp;Sasja F. Mulder ,&nbsp;Gert J. Meijer ,&nbsp;Martijn P.W. Intven","doi":"10.1016/j.phro.2024.100683","DOIUrl":"10.1016/j.phro.2024.100683","url":null,"abstract":"<div><div>Stereotactic body radiation therapy (SBRT) may be a non-invasive strategy to treat patients with pancreatic oligometastases from renal cell carcinoma (RCC). We analyzed 11 patients treated with MR-guided SBRT to 31 pancreatic oligometastases. At a median follow-up of 31.6 months, 1-year and 2-year freedom from local progression was 100 % and 95 % (95 % CI 86–100 %), respectively. Moreover, 1-year and 2-year freedom from systemic therapy was 91 % (95 %CI 75–100 %) and 82 % (95 % CI 62–100 %), respectively. MR-guided SBRT may be a safe and effective treatment option for pancreatic oligometastases from RCC.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100683"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11650256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142847867","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}
引用次数: 0
The influence of cardiac substructure dose on survival in a large lung cancer stereotactic radiotherapy cohort using a robust personalized contour analysis 在一个大型肺癌立体定向放疗队列中,心脏亚结构剂量对生存的影响采用了稳健的个性化轮廓分析。
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100686
Luuk H.G. van der Pol , Jacquelien Pomp , Firdaus A.A. Mohamed Hoesein , Bas W. Raaymakers , Joost J.C. Verhoeff , Martin F. Fast
{"title":"The influence of cardiac substructure dose on survival in a large lung cancer stereotactic radiotherapy cohort using a robust personalized contour analysis","authors":"Luuk H.G. van der Pol ,&nbsp;Jacquelien Pomp ,&nbsp;Firdaus A.A. Mohamed Hoesein ,&nbsp;Bas W. Raaymakers ,&nbsp;Joost J.C. Verhoeff ,&nbsp;Martin F. Fast","doi":"10.1016/j.phro.2024.100686","DOIUrl":"10.1016/j.phro.2024.100686","url":null,"abstract":"<div><div>Background/Purpose: Radiation-induced cardiac toxicity in lung cancer patients has received increased attention since RTOG 0617. However, large cohort studies with accurate cardiac substructure (CS) contours are lacking, limiting our understanding of the potential influence of individual CSs. Here, we analyse the correlation between CS dose and overall survival (OS) while accounting for deep learning (DL) contouring uncertainty, <span><math><mrow><mi>α</mi><mtext>/</mtext><mi>β</mi></mrow></math></span> uncertainty and different modelling approaches. Materials/Methods: This single institution, retrospective cohort study includes 730 patients (early-stage tumours (I or II). All treated: 2009–2019), who received stereotactic body radiotherapy (≥ 5 Gy per fraction). A DL model was trained on 70 manually contoured patients to create 12 cardio-vascular structures. Structures with median dice score above 0.8 and mean surface distance (MSD) &lt;2 mm during testing, were further analysed. Patientspecific CS dose was used to find the correlation between CS dose and OS with elastic net and random survival forest models (with and without confounding clinical factors). The influence of delineation-induced dose uncertainty on OS was investigated by expanding/contracting the DL-created contours using the MSD ± 2 standard deviations. Results: Eight CS contours met the required performance level. The left atrium (LA) mean dose was significant for OS and an LA mean dose of 3.3 Gy (in EQD2) was found as a significant dose stratum. Conclusion: Explicitly accounting for input parameter uncertainty in lung cancer survival modelling was crucial in robustly identifying critical CS dose parameters. Using this robust methodology, LA mean dose was revealed as the most influential CS dose parameter.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100686"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11663986/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883152","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}
引用次数: 0
Development and international multicentre pilot testing of a postal dosimetry audit methodology for high dose rate brachytherapy 高剂量率近距离放射治疗邮寄剂量测量审计方法的开发和国际多中心试点测试
IF 3.4
Physics and Imaging in Radiation Oncology Pub Date : 2024-10-01 DOI: 10.1016/j.phro.2024.100665
Alexis Dimitriadis, Anna Becker, Krzysztof Chelminski, Pavel Kazantsev, Egor Titovich, Godfrey Azangwe, Liset de la Fuente Rosales, Benjamin Kellogg, Mauro Carrara, Jamema Swamidas
{"title":"Development and international multicentre pilot testing of a postal dosimetry audit methodology for high dose rate brachytherapy","authors":"Alexis Dimitriadis,&nbsp;Anna Becker,&nbsp;Krzysztof Chelminski,&nbsp;Pavel Kazantsev,&nbsp;Egor Titovich,&nbsp;Godfrey Azangwe,&nbsp;Liset de la Fuente Rosales,&nbsp;Benjamin Kellogg,&nbsp;Mauro Carrara,&nbsp;Jamema Swamidas","doi":"10.1016/j.phro.2024.100665","DOIUrl":"10.1016/j.phro.2024.100665","url":null,"abstract":"<div><h3>Background and Purpose</h3><div>Dosimetry audits are essential for reducing errors in brachytherapy. A postal dosimetry audit methodology was developed and tested in an international multicentre pilot, to assess the accuracy of the Reference Air Kerma Rate of <sup>192</sup>Ir and <sup>60</sup>Co brachytherapy sources.</div></div><div><h3>Materials and Methods</h3><div>A compact phantom made of polymethyl methacrylate was developed to accommodate two catheters, a radiophotoluminescence dosimeter (RPLD) for dose measurements and a Gafchromic (RTQA2) film strip for source position verification. Deviations of the audit setup from TG-43 conditions were quantified experimentally and compared to previous Monte Carlo (MC) simulations. A measurement uncertainty budget was estimated for the RPLD analysis. The methodology was tested in an international pilot study consisting of 59 dosimeter sets among 48 centres from 11 countries.</div></div><div><h3>Results</h3><div>The experimental correction factors showed good agreement with previous MC simulations, and the total correction factor accounting for non-water equivalence, lack of scatter and beam quality was found to be 1.029 ± 0.009 for <sup>192</sup>Ir and 1.059 ± 0.007 for <sup>60</sup>Co sources, to be employed in audit measurement. The total uncertainty budget was estimated to be 2.24 % (k = 1). In the multicentre study, the ratio between measured and reported user dose ranged from 0.968 to 1.049, with all irradiated dosimeter sets within ± 5 %, and 54 out of 59 within ± 3 %.</div></div><div><h3>Conclusions</h3><div>The methodology was tested in an international multicentre pilot study and has shown good performance validating the uncertainty budget.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"32 ","pages":"Article 100665"},"PeriodicalIF":3.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593791","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}
引用次数: 0
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