Quantitative Predictors of Response to Neoadjuvant Chemotherapy on Dynamic Contrast-enhanced 3T Breast MRI

Wakana Murakami; Hyung Won Choi; Melissa M Joines; Anne Hoyt; Laura Doepke; Kelly E McCann; Noriko Salamon; James Sayre; Stephanie Lee-Felker

doi:10.1093/jbi/wbab095

Quantitative Predictors of Response to Neoadjuvant Chemotherapy on Dynamic Contrast-enhanced 3T Breast MRI

J Breast Imaging. 2022 Apr 15;4(2):168-176. doi: 10.1093/jbi/wbab095.

Authors

Wakana Murakami^{1

2}, Hyung Won Choi¹, Melissa M Joines¹, Anne Hoyt¹, Laura Doepke¹, Kelly E McCann³, Noriko Salamon¹, James Sayre⁴, Stephanie Lee-Felker¹

Affiliations

¹ University of California at Los Angeles David Geffen School of Medicine, Department of Radiological Sciences, Los Angeles, CA, USA.
² Showa University Graduate School of Medicine, Department of Radiology, Shinagawa-ku, Tokyo, Japan.
³ University of California at Los Angeles David Geffen School of Medicine, Department of Medicine, Los Angeles, CA, USA.
⁴ University of California at Los Angeles Fielding School of Public Health, Department of Biostatistics, Los Angeles, CA, USA.

PMID: 38422427
DOI: 10.1093/jbi/wbab095

Abstract

Objective: To assess whether changes in quantitative parameters on breast MRI better predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer than change in volume.

Methods: This IRB-approved retrospective study included women with newly diagnosed breast cancer who underwent 3T MRI before and during NAC from January 2013 to December 2019 and underwent surgery at our institution. Clinical data such as age, histologic diagnosis and grade, biomarker status, clinical stage, maximum index cancer dimension and volume, and surgical pathology (presence or absence of in-breast pCR) were collected. Quantitative parameters were calculated using software. Correlations between clinical features and MRI quantitative measures in pCR and non-pCR groups were assessed using univariate and multivariate logistic regression.

Results: A total of 182 women with a mean age of 52 years (range, 26-79 years) and 187 cancers were included. Approximately 45% (85/182) of women had pCR at surgery. Stepwise multivariate regression analysis showed statistical significance for changes in quantitative parameters (increase in time to peak and decreases in peak enhancement, wash out, and Kep [efflux rate constant]) for predicting pCR. These variables in combination predicted pCR with 81.2% accuracy and an area under the curve (AUC) of 0.878. The AUCs of change in index cancer volume and maximum dimension were 0.767 and 0.613, respectively.

Conclusion: Absolute changes in quantitative MRI parameters between pre-NAC MRI and intra-NAC MRI could help predict pCR with excellent accuracy, which was greater than changes in index cancer volume and maximum dimension.

Keywords: MRI; breast cancer; neoadjuvant chemotherapy; pathologic complete response; quantitative analysis.