Title: Can CT-based Radiomics Signature Predict KRAS/NRAS/BRAF Mutations in Colorectal Cancer?
Authors: Yang, L; Dong, D; Fang, MJ; Zhu, YB; Zang, YL; Liu, ZY; Zhang, HM; Ying, JM; Zhao, XM; Tian, J
Author Full Names: Yang, Lei; Dong, Di; Fang, Mengjie; Zhu, Yongbei; Zang, Yali; Liu, Zhenyu; Zhang, Hongmei; Ying, Jianming; Zhao, Xinming; Tian, Jie
Source: EUROPEAN RADIOLOGY, 28 (5):2058-2067; 10.1007/s00330-017-5146-8 MAY 2018
Language: English
Abstract: To investigate whether CT-based radiomics signature can predict KRAS/NRAS/BRAF mutations in colorectal cancer (CRC). This retrospective study consisted of a primary cohort (n = 61) and a validation cohort (n = 56) with pathologically confirmed CRC. Patients underwent KRAS/NRAS/BRAF mutation tests and contrast-enhanced CT before treatment. A total of 346 radiomics features were extracted from portal venous-phase CT images of the entire primary tumour. Associations between the genetic mutations and clinical background, tumour staging, and histological differentiation were assessed using univariate analysis. RELIEFF and support vector machine methods were performed to select key features and build a radiomics signature. The radiomics signature was significantly associated with KRAS/NRAS/BRAF mutations (P < 0.001). The area under the curve, sensitivity, and specificity for predicting KRAS/NRAS/BRAF mutations were 0.869, 0.757, and 0.833 in the primary cohort, respectively, while they were 0.829, 0.686, and 0.857 in the validation cohort, respectively. Clinical background, tumour staging, and histological differentiation were not associated with KRAS/NRAS/BRAF mutations in both cohorts (P > 0.05). The proposed CT-based radiomics signature is associated with KRAS/NRAS/BRAF mutations. CT may be useful for analysis of tumour genotype in CRC and thus helpful to determine therapeutic strategies. aEuro cent Key features were extracted from CT images of the primary colorectal tumour. aEuro cent The proposed radiomics signature was significantly associated with KRAS/NRAS/BRAF mutations. aEuro cent In the primary cohort, the proposed radiomics signature predicted mutations. aEuro cent Clinical background, tumour staging, and histological differentiation were unable to predict mutations.
ISSN: 0938-7994
eISSN: 1432-1084
IDS Number: GB5KY
Unique ID: WOS:000429104200030
PubMed ID: 29335867