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Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data

BACKGROUND: Biologically-based models that utilize 3D radiation dosimetry data to estimate the risk of late cardiac effects could have significant utility for planning radiotherapy in young patients. A major challenge arises from having only 2D treatment planning data for patients with long-term fol...

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Autores principales: Ng, Angela, Nguyen, Thao-Nguyen, Moseley, Joanne L, Hodgson, David C, Sharpe, Michael B, Brock, Kristy K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398341/
https://www.ncbi.nlm.nih.gov/pubmed/22257738
http://dx.doi.org/10.1186/1756-6649-12-1
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author Ng, Angela
Nguyen, Thao-Nguyen
Moseley, Joanne L
Hodgson, David C
Sharpe, Michael B
Brock, Kristy K
author_facet Ng, Angela
Nguyen, Thao-Nguyen
Moseley, Joanne L
Hodgson, David C
Sharpe, Michael B
Brock, Kristy K
author_sort Ng, Angela
collection PubMed
description BACKGROUND: Biologically-based models that utilize 3D radiation dosimetry data to estimate the risk of late cardiac effects could have significant utility for planning radiotherapy in young patients. A major challenge arises from having only 2D treatment planning data for patients with long-term follow-up. In this study, we evaluate the accuracy of an advanced deformable image registration (DIR) and navigator channels (NC) adaptation technique to reconstruct 3D heart volumes from 2D radiotherapy planning images for Hodgkin's Lymphoma (HL) patients. METHODS: Planning CT images were obtained for 50 HL patients who underwent mediastinal radiotherapy. Twelve image sets (6 male, 6 female) were used to construct a male and a female population heart model, which was registered to 23 HL "Reference" patients' CT images using a DIR algorithm, MORFEUS. This generated a series of population-to-Reference patient specific 3D deformation maps. The technique was independently tested on 15 additional "Test" patients by reconstructing their 3D heart volumes using 2D digitally reconstructed radiographs (DRR). The technique involved: 1) identifying a matching Reference patient for each Test patient using thorax measurements, 2) placement of six NCs on matching Reference and Test patients' DRRs to capture differences in significant heart curvatures, 3) adapting the population-to-Reference patient-specific deformation maps to generate population-to-Test patient-specific deformation maps using linear and bilinear interpolation methods, 4) applying population-to-Test patient specific deformation to the population model to reconstruct Test-patient specific 3D heart models. The percentage volume overlap between the NC-adapted reconstruction and actual Test patient's true heart volume was calculated using the Dice coefficient. RESULTS: The average Dice coefficient expressed as a percentage between the NC-adapted and actual Test model was 89.4 ± 2.8%. The modified NC adaptation technique made significant improvements to the population deformation heart models (p = 0.01). As standard evaluation, the residual Dice error after adaptation was comparable to the volumetric differences observed in free-breathing heart volumes (p = 0.62). CONCLUSIONS: The reconstruction technique described generates accurate 3D heart models from limited 2D planning data. This development could potentially be used to retrospectively calculate delivered dose to the heart for historically treated patients and thereby provide a better understanding of late radiation-related cardiac effects.
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spelling pubmed-33983412012-07-18 Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data Ng, Angela Nguyen, Thao-Nguyen Moseley, Joanne L Hodgson, David C Sharpe, Michael B Brock, Kristy K BMC Med Phys Research Article BACKGROUND: Biologically-based models that utilize 3D radiation dosimetry data to estimate the risk of late cardiac effects could have significant utility for planning radiotherapy in young patients. A major challenge arises from having only 2D treatment planning data for patients with long-term follow-up. In this study, we evaluate the accuracy of an advanced deformable image registration (DIR) and navigator channels (NC) adaptation technique to reconstruct 3D heart volumes from 2D radiotherapy planning images for Hodgkin's Lymphoma (HL) patients. METHODS: Planning CT images were obtained for 50 HL patients who underwent mediastinal radiotherapy. Twelve image sets (6 male, 6 female) were used to construct a male and a female population heart model, which was registered to 23 HL "Reference" patients' CT images using a DIR algorithm, MORFEUS. This generated a series of population-to-Reference patient specific 3D deformation maps. The technique was independently tested on 15 additional "Test" patients by reconstructing their 3D heart volumes using 2D digitally reconstructed radiographs (DRR). The technique involved: 1) identifying a matching Reference patient for each Test patient using thorax measurements, 2) placement of six NCs on matching Reference and Test patients' DRRs to capture differences in significant heart curvatures, 3) adapting the population-to-Reference patient-specific deformation maps to generate population-to-Test patient-specific deformation maps using linear and bilinear interpolation methods, 4) applying population-to-Test patient specific deformation to the population model to reconstruct Test-patient specific 3D heart models. The percentage volume overlap between the NC-adapted reconstruction and actual Test patient's true heart volume was calculated using the Dice coefficient. RESULTS: The average Dice coefficient expressed as a percentage between the NC-adapted and actual Test model was 89.4 ± 2.8%. The modified NC adaptation technique made significant improvements to the population deformation heart models (p = 0.01). As standard evaluation, the residual Dice error after adaptation was comparable to the volumetric differences observed in free-breathing heart volumes (p = 0.62). CONCLUSIONS: The reconstruction technique described generates accurate 3D heart models from limited 2D planning data. This development could potentially be used to retrospectively calculate delivered dose to the heart for historically treated patients and thereby provide a better understanding of late radiation-related cardiac effects. BioMed Central 2012-01-18 /pmc/articles/PMC3398341/ /pubmed/22257738 http://dx.doi.org/10.1186/1756-6649-12-1 Text en Copyright ©2012 Ng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ng, Angela
Nguyen, Thao-Nguyen
Moseley, Joanne L
Hodgson, David C
Sharpe, Michael B
Brock, Kristy K
Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
title Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
title_full Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
title_fullStr Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
title_full_unstemmed Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
title_short Navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
title_sort navigator channel adaptation to reconstruct three dimensional heart volumes from two dimensional radiotherapy planning data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398341/
https://www.ncbi.nlm.nih.gov/pubmed/22257738
http://dx.doi.org/10.1186/1756-6649-12-1
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