Cargando…

Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades

(1) Background: Lymphangioleiomyomatosis is a genetic disease that affects mostly women of childbearing age. In the lungs, it manifests as the progressive formation of air-filled cysts and is associated with a decline in lung function. With a median survival of 29 years after the onset of symptoms,...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Simone, Lebron, Alfredo, Matthew, Brianna, Moss, Joel, Wen, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669375/
https://www.ncbi.nlm.nih.gov/pubmed/38002379
http://dx.doi.org/10.3390/bioengineering10111255
_version_ 1785139681853177856
author Lee, Simone
Lebron, Alfredo
Matthew, Brianna
Moss, Joel
Wen, Han
author_facet Lee, Simone
Lebron, Alfredo
Matthew, Brianna
Moss, Joel
Wen, Han
author_sort Lee, Simone
collection PubMed
description (1) Background: Lymphangioleiomyomatosis is a genetic disease that affects mostly women of childbearing age. In the lungs, it manifests as the progressive formation of air-filled cysts and is associated with a decline in lung function. With a median survival of 29 years after the onset of symptoms, computed-tomographic monitoring of cystic changes in the lungs is a key part of the management of the disease. However, the current standard method to measure cyst burdens from CT is semi-automatic and requires manual adjustments from trained operators to obtain consistent results due to variabilities in CT technology and imaging conditions over the long course of the disease. This can be impractical for longitudinal studies involving large numbers of scans and is susceptible to subjective biases. (2) Methods: We developed an automated method of pulmonary cyst segmentation for chest CT images incorporating novel graphics processing algorithms. We assessed its performance against the gold-standard semi-automated method performed by experienced operators who were blinded to the results of the automated method. (3) Results: the automated method had the same consistency over time as the gold-standard method, but its cyst scores were more strongly correlated with concurrent pulmonary function results from the physiology laboratory than those of the gold-standard method. (4) Conclusions: The automated cyst segmentation is a competent replacement for the gold-standard semi-automated process. It is a solution for saving time and labor in clinical studies of lymphangioleiomyomatosis that may involve large numbers of chest CT scans from diverse scanner platforms and protocols.
format Online
Article
Text
id pubmed-10669375
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-106693752023-10-27 Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades Lee, Simone Lebron, Alfredo Matthew, Brianna Moss, Joel Wen, Han Bioengineering (Basel) Article (1) Background: Lymphangioleiomyomatosis is a genetic disease that affects mostly women of childbearing age. In the lungs, it manifests as the progressive formation of air-filled cysts and is associated with a decline in lung function. With a median survival of 29 years after the onset of symptoms, computed-tomographic monitoring of cystic changes in the lungs is a key part of the management of the disease. However, the current standard method to measure cyst burdens from CT is semi-automatic and requires manual adjustments from trained operators to obtain consistent results due to variabilities in CT technology and imaging conditions over the long course of the disease. This can be impractical for longitudinal studies involving large numbers of scans and is susceptible to subjective biases. (2) Methods: We developed an automated method of pulmonary cyst segmentation for chest CT images incorporating novel graphics processing algorithms. We assessed its performance against the gold-standard semi-automated method performed by experienced operators who were blinded to the results of the automated method. (3) Results: the automated method had the same consistency over time as the gold-standard method, but its cyst scores were more strongly correlated with concurrent pulmonary function results from the physiology laboratory than those of the gold-standard method. (4) Conclusions: The automated cyst segmentation is a competent replacement for the gold-standard semi-automated process. It is a solution for saving time and labor in clinical studies of lymphangioleiomyomatosis that may involve large numbers of chest CT scans from diverse scanner platforms and protocols. MDPI 2023-10-27 /pmc/articles/PMC10669375/ /pubmed/38002379 http://dx.doi.org/10.3390/bioengineering10111255 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Simone
Lebron, Alfredo
Matthew, Brianna
Moss, Joel
Wen, Han
Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades
title Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades
title_full Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades
title_fullStr Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades
title_full_unstemmed Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades
title_short Automated Segmentation and Measurements of Pulmonary Cysts in Lymphangioleiomyomatosis across Multiple CT Scanner Platforms over a Period of Two Decades
title_sort automated segmentation and measurements of pulmonary cysts in lymphangioleiomyomatosis across multiple ct scanner platforms over a period of two decades
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669375/
https://www.ncbi.nlm.nih.gov/pubmed/38002379
http://dx.doi.org/10.3390/bioengineering10111255
work_keys_str_mv AT leesimone automatedsegmentationandmeasurementsofpulmonarycystsinlymphangioleiomyomatosisacrossmultiplectscannerplatformsoveraperiodoftwodecades
AT lebronalfredo automatedsegmentationandmeasurementsofpulmonarycystsinlymphangioleiomyomatosisacrossmultiplectscannerplatformsoveraperiodoftwodecades
AT matthewbrianna automatedsegmentationandmeasurementsofpulmonarycystsinlymphangioleiomyomatosisacrossmultiplectscannerplatformsoveraperiodoftwodecades
AT mossjoel automatedsegmentationandmeasurementsofpulmonarycystsinlymphangioleiomyomatosisacrossmultiplectscannerplatformsoveraperiodoftwodecades
AT wenhan automatedsegmentationandmeasurementsofpulmonarycystsinlymphangioleiomyomatosisacrossmultiplectscannerplatformsoveraperiodoftwodecades