Cancer Management and Research (Oct 2020)
MRI-Based Radiomic Signature as a Prognostic Biomarker for HER2-Positive Invasive Breast Cancer Treated with NAC
Abstract
Qin Li,1,2,* Qin Xiao,2,3,* Jianwei Li,3,4 Shaofeng Duan,5 He Wang,6 Yajia Gu2,3 1Shanghai Institute of Medical Imaging, Shanghai, China; 2Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China; 3Department of Oncology, Fudan University Shanghai Cancer Center, Shanghai, China; 4Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China; 5PDx, GE Healthcare, Shanghai, China; 6Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China*These authors contributed equally to this workCorrespondence: Yajia GuDepartment of Radiology, Fudan University Shanghai Cancer Center, No. 270 Dongan Road, Shanghai 200032, China, Tel +8618017312040Fax +862164174774Email [email protected]: To identify MRI-based radiomics signature (Rad-score) as a biomarker of risk stratification for disease-free survival (DFS) in patients with HER2-positive invasive breast cancer treated with trastuzumab-based neoadjuvant chemotherapy (NAC) and establish a radiomics-clinicoradiologic-based nomogram that combines Rad-score, MRI findings, and clinicopathological variables for DFS estimation.Patients and Methods: A total of 127 patients were divided into a training set and testing set according to the ratio of 7:3. Radiomic features were extracted from multiphase CE-MRI (CEm). Rad-score was calculated using the LASSO (least absolute shrinkage and selection operator) regression analysis. The cutoff point of Rad-score to divide the patients into high- and low-risk groups was determined by receiver operating characteristic curve analysis. A Kaplan–Meier survival curves and the Log rank test were used to investigate the association of the Rad-score with DFS. Univariate and multivariate Cox proportional hazards model were used to determine the association of Rad-score, MRI features, and clinicopathological variables with DFS. A radiomics-clinicoradiologic-based nomogram combining the Rad-score, MRI features, and clinicopathological findings was plotted to validate the radiomic signatures for DFS estimation.Results: The Rad-score stratified patients into high- and low-risk groups for DFS in the training set (P< 0.0001) and was validated in the testing set (P=0.002). The radiomics-clinicoradiologic-based nomogram estimated DFS (training set: C-index=0.974, 95% confidence interval (CI)= 0.954– 0.994; testing set: C-index=0.917, 95% CI= 0.842– 0.991) better than the clinicoradiologic-based nomogram (training set: C-index=0.855, 95% CI= 0.739– 0.971; testing set: C-index=0.831, 95% CI=0.643– 0.999).Conclusion: The Rad-score is an independent biomarker for the estimation of DFS in invasive HER2-positive breast cancer with NAC and the radiomics-clinicoradiologic-based nomogram improved individualized DFS estimation.Keywords: radiomics, breast cancer, prognosis, magnetic resonance imaging
