Author:
Mohamed Rania M.,Panthi Bikash,Adrada Beatriz E.,Boge Medine,Candelaria Rosalind P.,Chen Huiqin,Guirguis Mary S.,Hunt Kelly K.,Huo Lei,Hwang Ken-Pin,Korkut Anil,Litton Jennifer K.,Moseley Tanya W.,Pashapoor Sanaz,Patel Miral M.,Reed Brandy,Scoggins Marion E.,Son Jong Bum,Thompson Alastair,Tripathy Debu,Valero Vicente,Wei Peng,White Jason,Whitman Gary J.,Xu Zhan,Yang Wei,Yam Clinton,Ma Jingfei,Rauch Gaiane M.
Abstract
AbstractTriple-negative breast cancer (TNBC) is often treated with neoadjuvant systemic therapy (NAST). We investigated if radiomic models based on multiparametric Magnetic Resonance Imaging (MRI) obtained early during NAST predict pathologic complete response (pCR). We included 163 patients with stage I-III TNBC with multiparametric MRI at baseline and after 2 (C2) and 4 cycles of NAST. Seventy-eight patients (48%) had pCR, and 85 (52%) had non-pCR. Thirty-six multivariate models combining radiomic features from dynamic contrast-enhanced MRI and diffusion-weighted imaging had an area under the receiver operating characteristics curve (AUC) > 0.7. The top-performing model combined 35 radiomic features of relative difference between C2 and baseline; had an AUC = 0.905 in the training and AUC = 0.802 in the testing set. There was high inter-reader agreement and very similar AUC values of the pCR prediction models for the 2 readers. Our data supports multiparametric MRI-based radiomic models for early prediction of NAST response in TNBC.
Publisher
Springer Science and Business Media LLC