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Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom

We studied the reliability of radiomic features on abdominal computed tomography (CT) images reconstructed with multiple CT image acquisition settings using the ACR (American College of Radiology) CT Phantom. Twenty-four sets of CT images of the ACR CT phantom were attained from a GE Discovery 750HD...

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Autores principales: Lu, Lin, Liang, Yongguang, Schwartz, Lawrence H., Zhao, Binsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Grapho Publications, LLC 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403036/
https://www.ncbi.nlm.nih.gov/pubmed/30854461
http://dx.doi.org/10.18383/j.tom.2019.00005
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author Lu, Lin
Liang, Yongguang
Schwartz, Lawrence H.
Zhao, Binsheng
author_facet Lu, Lin
Liang, Yongguang
Schwartz, Lawrence H.
Zhao, Binsheng
author_sort Lu, Lin
collection PubMed
description We studied the reliability of radiomic features on abdominal computed tomography (CT) images reconstructed with multiple CT image acquisition settings using the ACR (American College of Radiology) CT Phantom. Twenty-four sets of CT images of the ACR CT phantom were attained from a GE Discovery 750HD scanner using 24 different image acquisition settings, combinations of 4 tube currents (25, 50, 100, 200 Effective mAs), 3 slice thicknesses (1.25, 2.5, 5 mm), and 2 convolution kernels (STANDARD and SOFT). Polyethylene (−95 HU) and acrylic (120 HU) of the phantom model were selected for calculating real feature value; a noise-free, computer-generated phantom image series that reproduced the 2 objects and the background was used for calculating reference feature value. Feature reliability was defined as the degree of predicting reference feature value from real feature value. Radiomic features mean, std, skewness, kurtosis, gray-level co-occurrence matrix (GLCM)-energy, GLCM-contrast, GLCM-correlation, GLCM-homogeneity were investigated. The value of R(2) ≥ 0.85 was considered to be of high reliability. The reliability of mean and std were high across all image acquisition settings. At 200 Effective mAs, all features except GLCM-homogeneity showed high reliability, whereas at 25 Effective mAs, most features (except mean and std) showed low reliability. From high to low, reliability was ranked in the following order: mean, std, skewness, kurtosis, GLCM-energy, correlation, contrast and homogeneity. CT image acquisition settings affected the reliability of radiomic features. High reliable features were attained from images reconstructed at high tube current and thick slice thickness.
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spelling pubmed-64030362019-03-08 Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom Lu, Lin Liang, Yongguang Schwartz, Lawrence H. Zhao, Binsheng Tomography Research Articles We studied the reliability of radiomic features on abdominal computed tomography (CT) images reconstructed with multiple CT image acquisition settings using the ACR (American College of Radiology) CT Phantom. Twenty-four sets of CT images of the ACR CT phantom were attained from a GE Discovery 750HD scanner using 24 different image acquisition settings, combinations of 4 tube currents (25, 50, 100, 200 Effective mAs), 3 slice thicknesses (1.25, 2.5, 5 mm), and 2 convolution kernels (STANDARD and SOFT). Polyethylene (−95 HU) and acrylic (120 HU) of the phantom model were selected for calculating real feature value; a noise-free, computer-generated phantom image series that reproduced the 2 objects and the background was used for calculating reference feature value. Feature reliability was defined as the degree of predicting reference feature value from real feature value. Radiomic features mean, std, skewness, kurtosis, gray-level co-occurrence matrix (GLCM)-energy, GLCM-contrast, GLCM-correlation, GLCM-homogeneity were investigated. The value of R(2) ≥ 0.85 was considered to be of high reliability. The reliability of mean and std were high across all image acquisition settings. At 200 Effective mAs, all features except GLCM-homogeneity showed high reliability, whereas at 25 Effective mAs, most features (except mean and std) showed low reliability. From high to low, reliability was ranked in the following order: mean, std, skewness, kurtosis, GLCM-energy, correlation, contrast and homogeneity. CT image acquisition settings affected the reliability of radiomic features. High reliable features were attained from images reconstructed at high tube current and thick slice thickness. Grapho Publications, LLC 2019-03 /pmc/articles/PMC6403036/ /pubmed/30854461 http://dx.doi.org/10.18383/j.tom.2019.00005 Text en © 2019 The Authors. Published by Grapho Publications, LLC http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Articles
Lu, Lin
Liang, Yongguang
Schwartz, Lawrence H.
Zhao, Binsheng
Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom
title Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom
title_full Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom
title_fullStr Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom
title_full_unstemmed Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom
title_short Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom
title_sort reliability of radiomic features across multiple abdominal ct image acquisition settings: a pilot study using acr ct phantom
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403036/
https://www.ncbi.nlm.nih.gov/pubmed/30854461
http://dx.doi.org/10.18383/j.tom.2019.00005
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