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Madesta F, Sentker T, Gauer T, Werner R. Self‐contained deep learning‐based boosting of 4D cone‐beam CT reconstruction. Med Phys 2020; 47:5619-5631. [DOI: 10.1002/mp.14441] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 06/02/2020] [Accepted: 07/16/2020] [Indexed: 12/25/2022] Open
Affiliation(s)
- Frederic Madesta
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
| | - Thilo Sentker
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
| | - René Werner
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
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Meschini G, Seregni M, Molinelli S, Vai A, Phillips J, Sharp GC, Pella A, Valvo F, Ciocca M, Riboldi M, Paganetti H, Baroni G. Validation of a model for physical dose variations in irregularly moving targets treated with carbon ion beams. Med Phys 2019; 46:3663-3673. [PMID: 31206718 DOI: 10.1002/mp.13662] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 06/07/2019] [Accepted: 06/07/2019] [Indexed: 12/14/2022] Open
Abstract
PURPOSE In particle therapy, conventional treatment planning systems rely on an imaging representation of the irradiated region to compute the dose. For irregular breathing, when an imaging dataset describing the actual motion is not available, a different approach for dose estimation is needed. To this aim, we validate a method for the estimation of physical dose variations in gated carbon ion treatments, providing also a demonstration of the feasibility of physical dose metrics to assess the method performance. Finally, we describe a sample use case, in which this method is used to assess plan robustness with respect to undetected irregular tumor motion. METHODS The method entails the definition of a patient- and beam-specific water equivalent depth (WED) space, the simulation of motion as a translation equal to tumor displacement, and the reconstruction of the altered dose. We validated the approach using four-dimensional computed tomographies (4DCTs) and clinical plans in 12 patients, treated with respiratory gated carbon ion beams at the National Centre for Oncological Hadrontherapy (Pavia, Italy). Using the end-exhale CT and dose distribution as a reference, the physical dose delivered at the end-inhale tumor position was estimated and compared to the ground-truth dose recalculation on the end-inhale CT. Biologically effective and physical dose variations between the plan and the recalculation were compared as well. As a use case, we evaluated dose changes caused by simulated irregular tumor motion, that is, linear and nonlinear baseline shifts and/or amplitude variations with hysteresis. RESULTS The ratio between biologically effective and physical equivalent uniform dose (EUD) variations due to end-exhale to end-inhale motion was less than one for 96% of investigated structures. In the validation study, we found a median error corresponding to a 14% EUD overestimation for the tumor and 4% EUD underestimation for a subgroup of organs at risk, together with a high EUD variation due to motion [median 352% EUD variation between end-exhale and end-inhale doses in the planning tumor volume (PTV)]. Considering relevant dose-volume histogram (DVH) metrics, the median difference between estimated and ground truth doses was ≤ 4%. Gamma analysis between estimated and recalculated dose distributions resulted in a pass rate > 80% for 83% of the target volumes. For the two patients selected for the sample use case, a patient-specific assessment of the method performance was performed on the 4DCT and it was possible to relate EUD variations of both tumor and organs at risk to the simulated target motion. CONCLUSIONS The physical dose distribution was found to be more sensitive to motion with respect to the biologically effective one, suggesting the suitability of the physical dose metrics for the WED-space method validation. We showed that the method can compensate for intra-fractional tumor motion with proper accuracy in the selected patient group, although its use is recommended when limited deformations are expected. In conclusion, the WED-space method can provide simulations of dose alteration due to irregular breathing when imaging data are lacking, and, once integrated with relative biological effectiveness (RBE) modeling, it would be useful in evaluating the robustness of carbon ion treatment plans.
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Affiliation(s)
| | | | | | - Alessandro Vai
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Justin Phillips
- Alexian Brothers Medical Center, Elk Grove Village, IL, 60007, USA
| | | | - Andrea Pella
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Francesca Valvo
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Mario Ciocca
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Marco Riboldi
- Ludwig-Maximilians-Universität, Munich, 80539, Germany
| | | | - Guido Baroni
- Politecnico di Milano, Milan, 20133, Italy.,Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
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Werner R, Sentker T, Madesta F, Gauer T, Hofmann C. Intelligent 4D CT sequence scanning (i4DCT): Concept and performance evaluation. Med Phys 2019; 46:3462-3474. [DOI: 10.1002/mp.13632] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 04/30/2019] [Accepted: 05/22/2019] [Indexed: 12/20/2022] Open
Affiliation(s)
- René Werner
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
| | - Thilo Sentker
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
| | - Frederic Madesta
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
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Mogadas N, Sothmann T, Knopp T, Gauer T, Petersen C, Werner R. Influence of deformable image registration on 4D dose simulation for extracranial SBRT: A multi-registration framework study. Radiother Oncol 2018; 127:225-232. [PMID: 29606523 DOI: 10.1016/j.radonc.2018.03.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 03/14/2018] [Accepted: 03/14/2018] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE To evaluate the influence of deformable image registration approaches on correspondence model-based 4D dose simulation in extracranial SBRT by means of open source deformable image registration (DIR) frameworks. MATERIAL AND METHODS Established DIR algorithms of six different open source DIR frameworks were considered and registration accuracy evaluated using freely available 4D image data. Furthermore, correspondence models (regression-based correlation of external breathing signal measurements and internal structure motion field) were built and model accuracy evaluated. Finally, the DIR algorithms were applied for motion field estimation in radiotherapy planning 4D CT data of five lung and five liver lesion patients, correspondence model formation, and model-based 4D dose simulation. Deviations between the original, statically planned and the 4D-simulated VMAT dose distributions were analyzed and correlated to DIR accuracy differences. RESULTS Registration errors varied among the DIR approaches, with lower DIR accuracy translating into lower correspondence modeling accuracy. Yet, for lung metastases, indices of 4D-simulated dose distributions widely agreed, irrespective of DIR accuracy differences. In contrast, liver metastases 4D dose simulation results strongly vary for the different DIR approaches. CONCLUSIONS Especially in treatment areas with low image contrast (e.g. the liver), DIR-based 4D dose simulation results strongly depend on the applied DIR algorithm, drawing resulting dose simulations and indices questionable.
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Affiliation(s)
- Nik Mogadas
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | - Thilo Sothmann
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany; Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Germany.
| | - Tobias Knopp
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Germany
| | - Cordula Petersen
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Germany
| | - René Werner
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
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