| 1. |
- Unkelbach, Jan, et al.
(författare)
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The role of computational methods for automating and improving clinical target volume definition
- 2020
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Ingår i: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 153, s. 15-25
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Tidskriftsartikel (refereegranskat)abstract
- Treatment planning in radiotherapy distinguishes three target volume concepts: the gross tumor volume(GTV), the clinical target volume (CTV), and the planning target volume (PTV). Over time, GTV definitionand PTV margins have improved through the development of novel imaging techniques and better imageguidance, respectively. CTV definition is sometimes considered the weakest element in the planning pro-cess. CTV definition is particularly complex since the extension of microscopic disease cannot be seenusing currently available in-vivo imaging techniques. Instead, CTV definition has to incorporate knowl-edge of the patterns of tumor progression. While CTV delineation has largely been considered the domainof radiation oncologists, this paper, arising from a 2019 ESTRO Physics research workshop, discusses thecontributions that medical physics and computer science can make by developing computational meth-ods to support CTV definition. First, we overview the role of image segmentation algorithms, which mayin part automate CTV delineation through segmentation of lymph node stations or normal tissues repre-senting anatomical boundaries of microscopic tumor progression. The recent success of deep convolu-tional neural networks has also enabled learning entire CTV delineations from examples. Second, wediscuss the use of mathematical models of tumor progression for CTV definition, using as example theapplication of glioma growth models to facilitate GTV-to-CTV expansion for glioblastoma that is consis-tent with neuroanatomy. We further consider statistical machine learning models to quantify lymphaticmetastatic progression of tumors, which may eventually improve elective CTV definition. Lastly, we dis-cuss approaches to incorporate uncertainty in CTV definition into treatment plan optimization as well asgeneral limitations of the CTV concept in the case of infiltrating tumors without natural boundaries.
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| 2. |
- Anastasi, Gail, et al.
(författare)
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Patterns of practice for adaptive and real-time radiation therapy (POP-ART RT) part I : Intra-fraction breathing motion management
- 2020
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Ingår i: Radiotherapy and Oncology. - : ELSEVIER IRELAND LTD. - 0167-8140 .- 1879-0887. ; 153, s. 79-87
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The POP-ART RT study aims to determine to what extent and how intra-fractional real-time respiratory motion management (RRMM) and plan adaptation for inter-fractional anatomical changes (ART), are used in clinical practice and to understand barriers to implementation. Here we report on part I: RRMM. Material and methods: A questionnaire was distributed worldwide to assess current clinical practice, wishes for expansion or new implementation and barriers to implementation. RRMM was defined as inspiration/expiration gating in free-breathing or breath-hold, or tracking where the target and the beam are continuously realigned. Results: The questionnaire was completed by 200 centres from 41 countries. RRMM was used by 68% of respondents ('users') for a median (range) of 2 (1-6) tumour sites. Eighty-one percent of users applied inspiration breath-hold in at least one tumour site (breast: 96%). External marker was used to guide RRMM by 61% of users. KV/MV imaging was frequently used for liver and pancreas (with fiducials) and for lung (with or without fiducials). Tracking was mainly performed on robotic linacs with hybrid internal-external monitoring. For breast and lung, approximately 75% of respondents used or wished to implement RRMM, which was lower for liver (44%) and pancreas (27%). Seventy-one percent of respondents wished to implement RRMM for a new tumour site. Main barriers were human/financial resources and capacity on the machine. Conclusion: Sixty-eight percent of respondents used RRMM and 71% wished to implement RRMM for a new tumour site. The main barriers to implementation were human/financial resources and capacity on treatment machines. (C) 2020 The Authors. Published by Elsevier B.V.
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| 3. |
- Bertholet, Jenny, et al.
(författare)
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Patterns of practice for adaptive and real-time radiation therapy (POP-ART RT) part II : Offline and online plan adaption for interfractional changes
- 2020
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Ingår i: Radiotherapy and Oncology. - : ELSEVIER IRELAND LTD. - 0167-8140 .- 1879-0887. ; 153, s. 88-96
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The POP-ART RT study aims to determine to what extent and how intrafractional real-time respiratory motion management (RRMM), and plan adaptation for interfractional anatomical changes (ART) are used in clinical practice and to understand barriers to implementation. Here we report on part II: ART using more than one plan per target per treatment course. Materials and methods: A questionnaire on the current practice of ART, wishes for expansion or implementation, and barriers to implementation was distributed worldwide. Four types of ART were discriminated: daily online replanning, online plan library, protocolled offline replanning (all three based on a protocol), and ad-hoc offline replanning. Results: The questionnaire was completed by 177 centres from 40 countries. ART was used by 61% of respondents (31% with protocol) for a median (range) of 3 (1-8) tumour sites. CBCT/MVCT was the main imaging modality except for online daily replanning (11 users) where 10 users used MR. Two thirds of respondents wished to implement ART for a new tumour site; 40% of these had plans to do it in the next 2 years. Human/material resources and technical limitations were the main barriers to further use and implementation. Conclusions: ART was used for a broad range of tumour sites, mainly with ad-hoc offline replanning and for a median of 3 tumour sites. There was a large interest in implementing ART for more tumour sites, mainly limited by human/material resources and technical limitations. Daily online replanning was primarily performed on MR-linacs. (C) 2020 The Authors. Published by Elsevier B.V.
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| 4. |
- Gupta, Vikas, et al.
(författare)
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Fast and robust adaptation of organs-at-risk delineations from planning scans to match daily anatomy in pre-treatment scans for online-adaptive radiotherapy of abdominal tumors
- 2018
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Ingår i: Radiotherapy and Oncology. - : ELSEVIER IRELAND LTD. - 0167-8140 .- 1879-0887. ; 127:2, s. 332-338
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To validate a novel deformable image registration (DIR) method for online adaptation of planning organ-at-risk (OAR) delineations to match daily anatomy during hypo-fractionated RT of abdominal tumors. Materials and methods: For 20 liver cancer patients, planning OAR delineations were adapted to daily anatomy using the DIR on corresponding repeat CTs. The DIRs accuracy was evaluated for the entire cohort by comparing adapted and expert-drawn OAR delineations using geometric (Dice Similarity Coefficient (DSC), Modified Hausdorff Distance (MHD) and Mean Surface Error (MSE)) and dosimetric (D-max and D-mean) measures. Results: For all OARs, DIR achieved average DSC, MHD and MSE of 86%, 2.1 mm, and 1.7 mm, respectively, within 20 s for each repeat CT. Compared to the baseline (translations), the average improvements ranged from 2% (in heart) to 24% (in spinal cord) in DSC, and 25% (in heart) to 44% (in right kidney) in MHD and MSE. Furthermore, differences in dose statistics (D-max, D-mean and D-2%) using delineations from an expert and the proposed DIR were found to be statistically insignificant (p amp;gt; 0.01). Conclusion: The validated DIR showed potential for online-adaptive radiotherapy of abdominal tumors as it achieved considerably high geometric and dosimetric correspondences with the expert-drawn OAR delineations, albeit in a fraction of time required by experts. (C) 2018 The Authors. Published by Elsevier B.V.
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| 5. |
- Wang, Yibing, et al.
(författare)
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An individualized strategy to estimate the effect of deformable registration uncertainty on accumulated dose in the upper abdomen
- 2018
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Ingår i: Physics in Medicine and Biology. - : IOP PUBLISHING LTD. - 0031-9155 .- 1361-6560. ; 63:12
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Tidskriftsartikel (refereegranskat)abstract
- In the abdomen, it is challenging to assess the accuracy of deformable image registration (DIR) for individual patients, due to the lack of clear anatomical landmarks, which can hamper clinical applications that require high accuracy DIR, such as adaptive radiotherapy. In this study, we propose and evaluate a methodology for estimating the impact of uncertainties in DIR on calculated accumulated dose in the upper abdomen, in order to aid decision making in adaptive treatment approaches. Sixteen liver metastasis patients treated with SBRT were evaluated. Each patient had one planning and three daily treatment CT-scans. Each daily CT scan was deformably registered 132 times to the planning CT-scan, using a wide range of parameter settings for the registration algorithm. A subset of realistic registrations was then objectively selected based on distances between mapped and target contours. The underlying 3D transformations of these registrations were used to assess the corresponding uncertainties in voxel positions, and delivered dose, with a focus on accumulated maximum doses in the hollow OARs, i.e. esophagus, stomach, and duodenum. The number of realistic registrations varied from 5 to 109, depending on the patient, emphasizing the need for individualized registration parameters. Considering for all patients the realistic registrations, the 99th percentile of the voxel position uncertainties was 5.6 +/- 3.3 mm. This translated into a variation (difference between 1st and 99th percentile) in accumulated Dmax in hollow OARs of up to 3.3 Gy. For one patient a violation of the accumulated stomach dose outside the uncertainty band was detected. The observed variation in accumulated doses in the OARs related to registration uncertainty, emphasizes the need to investigate the impact of this uncertainty for any DIR algorithm prior to clinical use for dose accumulation. The proposed method for assessing on an individual patient basis the impact of uncertainties in DIR on accumulated dose is in principle applicable for all DIR algorithms allowing variation in registration parameters.
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