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MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients

BACKGROUND AND PURPOSE: Locally advanced rectal cancer (LARC) is a heterogeneous disease with little information about KRAS status and image features. The purpose of this study was to analyze the association between T2 magnetic resonance imaging (MRI) radiomics features and KRAS status in LARC patie...

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Autores principales: Zhang, ZhiYuan, Shen, LiJun, Wang, Yan, Wang, Jiazhou, Zhang, Hui, Xia, Fan, Wan, JueFeng, Zhang, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138318/
https://www.ncbi.nlm.nih.gov/pubmed/34026605
http://dx.doi.org/10.3389/fonc.2021.614052
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author Zhang, ZhiYuan
Shen, LiJun
Wang, Yan
Wang, Jiazhou
Zhang, Hui
Xia, Fan
Wan, JueFeng
Zhang, Zhen
author_facet Zhang, ZhiYuan
Shen, LiJun
Wang, Yan
Wang, Jiazhou
Zhang, Hui
Xia, Fan
Wan, JueFeng
Zhang, Zhen
author_sort Zhang, ZhiYuan
collection PubMed
description BACKGROUND AND PURPOSE: Locally advanced rectal cancer (LARC) is a heterogeneous disease with little information about KRAS status and image features. The purpose of this study was to analyze the association between T2 magnetic resonance imaging (MRI) radiomics features and KRAS status in LARC patients. MATERIAL AND METHODS: Eighty-three patients with KRAS status information and T2 MRI images between 2012.05 and 2019.09 were included. Least absolute shrinkage and selection operator (LASSO) regression was performed to assess the associations between features and gene status. The patients were divided 7:3 into training and validation sets. The C-index and the average area under the receiver operator characteristic curve (AUC) were used for performance evaluation. RESULTS: The clinical characteristics of 83 patients in the KRAS mutant and wild-type cohorts were balanced. Forty-two (50.6%) patients had KRAS mutations, and 41 (49.4%) patients had wild-type KRAS. A total of 253 radiomics features were extracted from the T2-MRI images of LARC patients. One radiomic feature named X.LL_scaled_std, a standard deviation value of scaled wavelet-transformed low-pass channel filter, was selected from 253 features (P=0.019). The radiomics-based C-index values were 0.801 (95% CI: 0.772-0.830) and 0.703 (95% CI: 0.620-0.786) in the training and validation sets, respectively. CONCLUSION: Radiomics features could differentiate KRAS status in LARC patients based on T2-MRI images. Further validation in a larger dataset is necessary in the future.
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spelling pubmed-81383182021-05-22 MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients Zhang, ZhiYuan Shen, LiJun Wang, Yan Wang, Jiazhou Zhang, Hui Xia, Fan Wan, JueFeng Zhang, Zhen Front Oncol Oncology BACKGROUND AND PURPOSE: Locally advanced rectal cancer (LARC) is a heterogeneous disease with little information about KRAS status and image features. The purpose of this study was to analyze the association between T2 magnetic resonance imaging (MRI) radiomics features and KRAS status in LARC patients. MATERIAL AND METHODS: Eighty-three patients with KRAS status information and T2 MRI images between 2012.05 and 2019.09 were included. Least absolute shrinkage and selection operator (LASSO) regression was performed to assess the associations between features and gene status. The patients were divided 7:3 into training and validation sets. The C-index and the average area under the receiver operator characteristic curve (AUC) were used for performance evaluation. RESULTS: The clinical characteristics of 83 patients in the KRAS mutant and wild-type cohorts were balanced. Forty-two (50.6%) patients had KRAS mutations, and 41 (49.4%) patients had wild-type KRAS. A total of 253 radiomics features were extracted from the T2-MRI images of LARC patients. One radiomic feature named X.LL_scaled_std, a standard deviation value of scaled wavelet-transformed low-pass channel filter, was selected from 253 features (P=0.019). The radiomics-based C-index values were 0.801 (95% CI: 0.772-0.830) and 0.703 (95% CI: 0.620-0.786) in the training and validation sets, respectively. CONCLUSION: Radiomics features could differentiate KRAS status in LARC patients based on T2-MRI images. Further validation in a larger dataset is necessary in the future. Frontiers Media S.A. 2021-05-07 /pmc/articles/PMC8138318/ /pubmed/34026605 http://dx.doi.org/10.3389/fonc.2021.614052 Text en Copyright © 2021 Zhang, Shen, Wang, Wang, Zhang, Xia, Wan and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Zhang, ZhiYuan
Shen, LiJun
Wang, Yan
Wang, Jiazhou
Zhang, Hui
Xia, Fan
Wan, JueFeng
Zhang, Zhen
MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
title MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
title_full MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
title_fullStr MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
title_full_unstemmed MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
title_short MRI Radiomics Signature as a Potential Biomarker for Predicting KRAS Status in Locally Advanced Rectal Cancer Patients
title_sort mri radiomics signature as a potential biomarker for predicting kras status in locally advanced rectal cancer patients
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138318/
https://www.ncbi.nlm.nih.gov/pubmed/34026605
http://dx.doi.org/10.3389/fonc.2021.614052
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