Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images

Idiopathic pulmonary fibrosis (IPF) patients have a significantly higher risk of developing lung cancer (LC). There is only limited evidence of the use of texture-based radiomics features from high-resolution computed tomography (HRCT) images for risk stratification of IPF patients for LC. We retros...

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Autores principales:	Chia-Hao Liang, Yung-Chi Liu, Yung-Liang Wan, Chun-Ho Yun, Wen-Jui Wu, Rafael López-González, Wei-Ming Huang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	idiopathic pulmonary fibrosis lung cancer radiomics risk factors Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/51402e7897d84d399505ef19d7cc5712
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spelling	oai:doaj.org-article:51402e7897d84d399505ef19d7cc57122021-11-25T17:01:22ZQuantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images10.3390/cancers132256002072-6694https://doaj.org/article/51402e7897d84d399505ef19d7cc57122021-11-01T00:00:00Zhttps://www.mdpi.com/2072-6694/13/22/5600https://doaj.org/toc/2072-6694Idiopathic pulmonary fibrosis (IPF) patients have a significantly higher risk of developing lung cancer (LC). There is only limited evidence of the use of texture-based radiomics features from high-resolution computed tomography (HRCT) images for risk stratification of IPF patients for LC. We retrospectively enrolled subjects who suffered from IPF in this study. Clinical data including age, gender, smoking status, and pulmonary function were recorded. Non-contrast chest CT for fibrotic score calculation and determination of three dimensional measures of whole-lung texture and emphysema were performed using a promising deep learning imaging platform. The results revealed that among 116 subjects with IPF (90 non-cancer and 26 lung cancer cases), the radiomics features showed significant differences between non-cancer and cancer patients. In the training cohort, the diagnostic accuracy using selected radiomics features with AUC of 0.66–0.73 (sensitivity of 80.0–85.0% and specificity of 54.2–59.7%) was not inferior to that obtained using traditional risk factors, such as gender, smoking status, and emphysema (%). In the validation cohort, the combination of radiomics features and traditional risk factors produced a diagnostic accuracy of 0.87 AUC and an accuracy of 75.0%. In this study, we found that whole-lung CT texture analysis is a promising tool for LC risk stratification of IPF patients.Chia-Hao LiangYung-Chi LiuYung-Liang WanChun-Ho YunWen-Jui WuRafael López-GonzálezWei-Ming HuangMDPI AGarticleidiopathic pulmonary fibrosislung cancerradiomicsrisk factorsNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENCancers, Vol 13, Iss 5600, p 5600 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	idiopathic pulmonary fibrosis lung cancer radiomics risk factors Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	idiopathic pulmonary fibrosis lung cancer radiomics risk factors Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Chia-Hao Liang Yung-Chi Liu Yung-Liang Wan Chun-Ho Yun Wen-Jui Wu Rafael López-González Wei-Ming Huang Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images
description	Idiopathic pulmonary fibrosis (IPF) patients have a significantly higher risk of developing lung cancer (LC). There is only limited evidence of the use of texture-based radiomics features from high-resolution computed tomography (HRCT) images for risk stratification of IPF patients for LC. We retrospectively enrolled subjects who suffered from IPF in this study. Clinical data including age, gender, smoking status, and pulmonary function were recorded. Non-contrast chest CT for fibrotic score calculation and determination of three dimensional measures of whole-lung texture and emphysema were performed using a promising deep learning imaging platform. The results revealed that among 116 subjects with IPF (90 non-cancer and 26 lung cancer cases), the radiomics features showed significant differences between non-cancer and cancer patients. In the training cohort, the diagnostic accuracy using selected radiomics features with AUC of 0.66–0.73 (sensitivity of 80.0–85.0% and specificity of 54.2–59.7%) was not inferior to that obtained using traditional risk factors, such as gender, smoking status, and emphysema (%). In the validation cohort, the combination of radiomics features and traditional risk factors produced a diagnostic accuracy of 0.87 AUC and an accuracy of 75.0%. In this study, we found that whole-lung CT texture analysis is a promising tool for LC risk stratification of IPF patients.
format	article
author	Chia-Hao Liang Yung-Chi Liu Yung-Liang Wan Chun-Ho Yun Wen-Jui Wu Rafael López-González Wei-Ming Huang
author_facet	Chia-Hao Liang Yung-Chi Liu Yung-Liang Wan Chun-Ho Yun Wen-Jui Wu Rafael López-González Wei-Ming Huang
author_sort	Chia-Hao Liang
title	Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images
title_short	Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images
title_full	Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images
title_fullStr	Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images
title_full_unstemmed	Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images
title_sort	quantification of cancer-developing idiopathic pulmonary fibrosis using whole-lung texture analysis of hrct images
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/51402e7897d84d399505ef19d7cc5712
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Quantification of Cancer-Developing Idiopathic Pulmonary Fibrosis Using Whole-Lung Texture Analysis of HRCT Images

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