A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast Cancer

Authors

Ken-Pin Hwang
Nabil A Elshafeey
Aikaterini Kotrotsou
Huiqin Chen
Jong Bum Son
Medine Boge
Rania M Mohamed
Abeer H Abdelhafez
Beatriz E Adrada
Bikash Panthi
Jia Sun
Benjamin C Musall
Shu Zhang
Rosalind P Candelaria
Jason B White
Elizabeth E Ravenberg
Debu Tripathy
Clinton Yam
Jennifer K Litton
Lei Huo
Alastair M Thompson
Peng Wei
Wei T Yang
Mark D Pagel
Jingfei Ma
Gaiane M Rauch

Publication Date

7-1-2023

Journal

Radiology Imaging Cancer

Abstract

Purpose

To determine if a radiomics model based on quantitative maps acquired with synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC).

Materials and Methods

In this prospective study, 181 women diagnosed with stage I–III TNBC were scanned with a SyMRI sequence at baseline and at midtreatment (after four cycles of NAST), producing T1, T2, and proton density (PD) maps. Histopathologic analysis at surgery was used to determine pathologic complete response (pCR) or non-pCR status. From three-dimensional tumor contours drawn on the three maps, 310 histogram and textural features were extracted, resulting in 930 features per scan. Radiomic features were compared between pCR and non-pCR groups by using Wilcoxon rank sum test. To build a multivariable predictive model, logistic regression with elastic net regularization and cross-validation was performed for texture feature selection using 119 participants (median age, 52 years [range, 26–77 years]). An independent testing cohort of 62 participants (median age, 48 years [range, 23–74 years]) was used to evaluate and compare the models by area under the receiver operating characteristic curve (AUC).

Results

Univariable analysis identified 15 T1, 10 T2, and 12 PD radiomic features at midtreatment that predicted pCR with an AUC greater than 0.70 in both the training and testing cohorts. Multivariable radiomics models of maps acquired at midtreatment demonstrated superior performance over those acquired at baseline, achieving AUCs as high as 0.78 and 0.72 in the training and testing cohorts, respectively.

Conclusion

SyMRI-based radiomic features acquired at midtreatment are potentially useful for identifying early NAST responders in TNBC.

Keywords

Humans, Female, Middle Aged, Triple Negative Breast Neoplasms, Neoadjuvant Therapy, Prospective Studies, Magnetic Resonance Imaging, Breast

Comments

ClinicalTrials.gov registration no. NCT02276443

Supplemental Materials

PMID: 37505106