Back to Search Start Over

Predicting Microsatellite Instability Status in Colorectal Cancer Based on Triphasic Enhanced Computed Tomography Radiomics Signatures: A Multicenter Study

Authors :
Yuntai Cao
Guojin Zhang
Jing Zhang
Yingjie Yang
Jialiang Ren
Xiaohong Yan
Zhan Wang
Zhiyong Zhao
Xiaoyu Huang
Haihua Bao
Junlin Zhou
Source :
Frontiers in Oncology, Vol 11 (2021)
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

BackgroundThis study aimed to develop and validate a computed tomography (CT)-based radiomics model to predict microsatellite instability (MSI) status in colorectal cancer patients and to identify the radiomics signature with the most robust and high performance from one of the three phases of triphasic enhanced CT.MethodsIn total, 502 colorectal cancer patients with preoperative contrast-enhanced CT images and available MSI status (441 in the training cohort and 61 in the external validation cohort) were enrolled from two centers in our retrospective study. Radiomics features of the entire primary tumor were extracted from arterial-, delayed-, and venous-phase CT images. The least absolute shrinkage and selection operator method was used to retain the features closely associated with MSI status. Radiomics, clinical, and combined Clinical Radiomics models were built to predict MSI status. Model performance was evaluated by receiver operating characteristic curve analysis.ResultsThirty-two radiomics features showed significant correlation with MSI status. Delayed-phase models showed superior predictive performance compared to arterial- or venous-phase models. Additionally, age, location, and carcinoembryonic antigen were considered useful predictors of MSI status. The Clinical Radiomics nomogram that incorporated both clinical risk factors and radiomics parameters showed excellent performance, with an AUC, accuracy, and sensitivity of 0.898, 0.837, and 0.821 in the training cohort and 0.964, 0.918, and 1.000 in the validation cohort, respectively.ConclusionsThe proposed CT-based radiomics signature has excellent performance in predicting MSI status and could potentially guide individualized therapy.

Details

Language :
English
ISSN :
2234943X
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.3d95aef1cb0a4b5eb64044dda42632cc
Document Type :
article
Full Text :
https://doi.org/10.3389/fonc.2021.687771