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Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies
Radiomics has shown promise in improving models for predicting patient outcomes. However, to maximize the information gain of the radiomics features, especially in larger patient cohorts, the variability in radiomics features owing to differences between scanners and scanning protocols must be accou...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115360/ https://www.ncbi.nlm.nih.gov/pubmed/30158540 http://dx.doi.org/10.1038/s41598-018-31509-z |
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author | Ger, Rachel B. Zhou, Shouhao Chi, Pai-Chun Melinda Lee, Hannah J. Layman, Rick R. Jones, A. Kyle Goff, David L. Fuller, Clifton D. Howell, Rebecca M. Li, Heng Stafford, R. Jason Court, Laurence E. Mackin, Dennis S. |
author_facet | Ger, Rachel B. Zhou, Shouhao Chi, Pai-Chun Melinda Lee, Hannah J. Layman, Rick R. Jones, A. Kyle Goff, David L. Fuller, Clifton D. Howell, Rebecca M. Li, Heng Stafford, R. Jason Court, Laurence E. Mackin, Dennis S. |
author_sort | Ger, Rachel B. |
collection | PubMed |
description | Radiomics has shown promise in improving models for predicting patient outcomes. However, to maximize the information gain of the radiomics features, especially in larger patient cohorts, the variability in radiomics features owing to differences between scanners and scanning protocols must be accounted for. To this aim, the imaging variability of radiomics feature values was evaluated on 100 computed tomography scanners at 35 clinics by imaging a radiomics phantom using a controlled protocol and the commonly used chest and head protocols of the local clinic. We used a linear mixed-effects model to determine the degree to which the manufacturer and individual scanners contribute to the overall variability. Using a controlled protocol reduced the overall variability by 57% and 52% compared to the local chest and head protocols respectively. The controlled protocol also reduced the relative contribution of the manufacturer to the total variability. For almost all variabilities (manufacturer, scanner, and residual with different preprocesssing), the controlled protocol scans had a significantly smaller variability than the local protocol scans did. For most radiomics features, the imaging variability was small relative to the inter-patient feature variability in non–small cell lung cancer and head and neck squamous cell carcinoma patient cohorts. From this study, we conclude that using controlled scans can reduce the variability in radiomics features, and our results demonstrate the importance of using controlled protocols in prospective radiomics studies. |
format | Online Article Text |
id | pubmed-6115360 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61153602018-09-04 Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies Ger, Rachel B. Zhou, Shouhao Chi, Pai-Chun Melinda Lee, Hannah J. Layman, Rick R. Jones, A. Kyle Goff, David L. Fuller, Clifton D. Howell, Rebecca M. Li, Heng Stafford, R. Jason Court, Laurence E. Mackin, Dennis S. Sci Rep Article Radiomics has shown promise in improving models for predicting patient outcomes. However, to maximize the information gain of the radiomics features, especially in larger patient cohorts, the variability in radiomics features owing to differences between scanners and scanning protocols must be accounted for. To this aim, the imaging variability of radiomics feature values was evaluated on 100 computed tomography scanners at 35 clinics by imaging a radiomics phantom using a controlled protocol and the commonly used chest and head protocols of the local clinic. We used a linear mixed-effects model to determine the degree to which the manufacturer and individual scanners contribute to the overall variability. Using a controlled protocol reduced the overall variability by 57% and 52% compared to the local chest and head protocols respectively. The controlled protocol also reduced the relative contribution of the manufacturer to the total variability. For almost all variabilities (manufacturer, scanner, and residual with different preprocesssing), the controlled protocol scans had a significantly smaller variability than the local protocol scans did. For most radiomics features, the imaging variability was small relative to the inter-patient feature variability in non–small cell lung cancer and head and neck squamous cell carcinoma patient cohorts. From this study, we conclude that using controlled scans can reduce the variability in radiomics features, and our results demonstrate the importance of using controlled protocols in prospective radiomics studies. Nature Publishing Group UK 2018-08-29 /pmc/articles/PMC6115360/ /pubmed/30158540 http://dx.doi.org/10.1038/s41598-018-31509-z Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ger, Rachel B. Zhou, Shouhao Chi, Pai-Chun Melinda Lee, Hannah J. Layman, Rick R. Jones, A. Kyle Goff, David L. Fuller, Clifton D. Howell, Rebecca M. Li, Heng Stafford, R. Jason Court, Laurence E. Mackin, Dennis S. Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies |
title | Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies |
title_full | Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies |
title_fullStr | Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies |
title_full_unstemmed | Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies |
title_short | Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies |
title_sort | comprehensive investigation on controlling for ct imaging variabilities in radiomics studies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115360/ https://www.ncbi.nlm.nih.gov/pubmed/30158540 http://dx.doi.org/10.1038/s41598-018-31509-z |
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