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Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT

BACKGROUND: Functional volumes computed from (68)Ga-ventilation/perfusion (V/Q) PET/CT, which we have shown to correlate with pulmonary function test parameters (PFTs), have potential diagnostic utility in a variety of clinical applications, including radiotherapy planning. An automatic segmentation...

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Autores principales: Le Roux, Pierre-Yves, Siva, Shankar, Callahan, Jason, Claudic, Yannis, Bourhis, David, Steinfort, Daniel P., Hicks, Rodney J., Hofman, Michael S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5634989/
https://www.ncbi.nlm.nih.gov/pubmed/29019109
http://dx.doi.org/10.1186/s13550-017-0332-x
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author Le Roux, Pierre-Yves
Siva, Shankar
Callahan, Jason
Claudic, Yannis
Bourhis, David
Steinfort, Daniel P.
Hicks, Rodney J.
Hofman, Michael S.
author_facet Le Roux, Pierre-Yves
Siva, Shankar
Callahan, Jason
Claudic, Yannis
Bourhis, David
Steinfort, Daniel P.
Hicks, Rodney J.
Hofman, Michael S.
author_sort Le Roux, Pierre-Yves
collection PubMed
description BACKGROUND: Functional volumes computed from (68)Ga-ventilation/perfusion (V/Q) PET/CT, which we have shown to correlate with pulmonary function test parameters (PFTs), have potential diagnostic utility in a variety of clinical applications, including radiotherapy planning. An automatic segmentation method would facilitate delineation of such volumes. The aim of this study was to develop an automated threshold-based approach to delineate functional volumes that best correlates with manual delineation. Thirty lung cancer patients undergoing both V/Q PET/CT and PFTs were analyzed. Images were acquired following inhalation of Galligas and, subsequently, intravenous administration of (68)Ga-macroaggreted-albumin (MAA). Using visually defined manual contours as the reference standard, various cutoff values, expressed as a percentage of the maximal pixel value, were applied. The average volume difference and Dice similarity coefficient (DSC) were calculated, measuring the similarity of the automatic segmentation and the reference standard. Pearson’s correlation was also calculated to compare automated volumes with manual volumes, and automated volumes optimized to PFT indices. RESULTS: For ventilation volumes, mean volume difference was lowest (− 0.4%) using a 15%max threshold with Pearson’s coefficient of 0.71. Applying this cutoff, median DSC was 0.93 (0.87–0.95). Nevertheless, limits of agreement in volume differences were large (− 31.0 and 30.2%) with differences ranging from − 40.4 to + 33.0%. For perfusion volumes, mean volume difference was lowest and Pearson’s coefficient was highest using a 15%max threshold (3.3% and 0.81, respectively). Applying this cutoff, median DSC was 0.93 (0.88–0.93). Nevertheless, limits of agreement were again large (− 21.1 and 27.8%) with volume differences ranging from − 18.6 to + 35.5%. Using the 15%max threshold, moderate correlation was demonstrated with FEV1/FVC (r = 0.48 and r = 0.46 for ventilation and perfusion images, respectively). No correlation was found between other PFT indices. CONCLUSIONS: To automatically delineate functional volumes with (68)Ga-V/Q PET/CT, the most appropriate cutoff was 15%max for both ventilation and perfusion images. However, using this unique threshold systematically provided unacceptable variability compared to the reference volume and relatively poor correlation with PFT parameters. Accordingly, a visually adapted semi-automatic method is favored, enabling rapid and quantitative delineation of lung functional volumes with (68)Ga-V/Q PET/CT.
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spelling pubmed-56349892017-10-11 Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT Le Roux, Pierre-Yves Siva, Shankar Callahan, Jason Claudic, Yannis Bourhis, David Steinfort, Daniel P. Hicks, Rodney J. Hofman, Michael S. EJNMMI Res Original Research BACKGROUND: Functional volumes computed from (68)Ga-ventilation/perfusion (V/Q) PET/CT, which we have shown to correlate with pulmonary function test parameters (PFTs), have potential diagnostic utility in a variety of clinical applications, including radiotherapy planning. An automatic segmentation method would facilitate delineation of such volumes. The aim of this study was to develop an automated threshold-based approach to delineate functional volumes that best correlates with manual delineation. Thirty lung cancer patients undergoing both V/Q PET/CT and PFTs were analyzed. Images were acquired following inhalation of Galligas and, subsequently, intravenous administration of (68)Ga-macroaggreted-albumin (MAA). Using visually defined manual contours as the reference standard, various cutoff values, expressed as a percentage of the maximal pixel value, were applied. The average volume difference and Dice similarity coefficient (DSC) were calculated, measuring the similarity of the automatic segmentation and the reference standard. Pearson’s correlation was also calculated to compare automated volumes with manual volumes, and automated volumes optimized to PFT indices. RESULTS: For ventilation volumes, mean volume difference was lowest (− 0.4%) using a 15%max threshold with Pearson’s coefficient of 0.71. Applying this cutoff, median DSC was 0.93 (0.87–0.95). Nevertheless, limits of agreement in volume differences were large (− 31.0 and 30.2%) with differences ranging from − 40.4 to + 33.0%. For perfusion volumes, mean volume difference was lowest and Pearson’s coefficient was highest using a 15%max threshold (3.3% and 0.81, respectively). Applying this cutoff, median DSC was 0.93 (0.88–0.93). Nevertheless, limits of agreement were again large (− 21.1 and 27.8%) with volume differences ranging from − 18.6 to + 35.5%. Using the 15%max threshold, moderate correlation was demonstrated with FEV1/FVC (r = 0.48 and r = 0.46 for ventilation and perfusion images, respectively). No correlation was found between other PFT indices. CONCLUSIONS: To automatically delineate functional volumes with (68)Ga-V/Q PET/CT, the most appropriate cutoff was 15%max for both ventilation and perfusion images. However, using this unique threshold systematically provided unacceptable variability compared to the reference volume and relatively poor correlation with PFT parameters. Accordingly, a visually adapted semi-automatic method is favored, enabling rapid and quantitative delineation of lung functional volumes with (68)Ga-V/Q PET/CT. Springer Berlin Heidelberg 2017-10-10 /pmc/articles/PMC5634989/ /pubmed/29019109 http://dx.doi.org/10.1186/s13550-017-0332-x Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research
Le Roux, Pierre-Yves
Siva, Shankar
Callahan, Jason
Claudic, Yannis
Bourhis, David
Steinfort, Daniel P.
Hicks, Rodney J.
Hofman, Michael S.
Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
title Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
title_full Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
title_fullStr Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
title_full_unstemmed Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
title_short Automatic delineation of functional lung volumes with (68)Ga-ventilation/perfusion PET/CT
title_sort automatic delineation of functional lung volumes with (68)ga-ventilation/perfusion pet/ct
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5634989/
https://www.ncbi.nlm.nih.gov/pubmed/29019109
http://dx.doi.org/10.1186/s13550-017-0332-x
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