Abstract P1-01-09: Optimization of magnetic resonance imaging predictive performance by breast cancer subtypes for predicting response to neoadjuvant chemotherapy

Objective: Change in functional tumor volume (FTV) measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), has been shown to be associated with response to neoadjuvant chemotherapy (NACT) for patients with stage II/III breast cancer. FTV reflects the vascularized volume of tumor and is calculated by applying minimum thresholds PE t for the initial percent enhancement and SER t for the early-to-late signal enhancement ratio following gadolinium contrast injection. In this retrospective study, we investigate the association of FTV influenced by PE t and SER t values with recurrence-free survival (RFS) in breast cancer subtypes defined by hormone receptor (HR) and HER2 status. Materials and Methods: 64 patients with locally advanced breast cancer were imaged by DCE-MRI before treatment (MRI 1 ), after one cycle of adriamycin-cytoxan (AC) therapy (MRI 2 ), inter-regimen (MRI 3 , taxane receivers only) and at the completion of chemotherapy prior to surgery (MRI 4 ). Because treatment length and regimen varied among patients, the MRI exam performed after all NACT and before surgery was designated as final MRI (MRI f ). FTV was calculated with varying PE t (30–200% in steps of 10%) and SER t (0–2 in steps of 0.2) values. A Cox proportional hazard model was used to analyze association with RFS, defined as the time between surgery and disease recurrence or last disease-free follow-up, for the following imaging predictors: early percent change in FTV (ΔFTV2: MRI 1 vs. MRI 2 ), final percent change (ΔFTV f : MRI 1 vs. MRI f ), and final FTV in MRI f (FTV f ). RFS association was evaluated for the full cohort and within subsets defined by tumor subtype (HR+/HER2-, HER2+, triple negative). Estimated hazard ratios per unit change in predictors, associated 95% confidence intervals (CI) and p-values were evaluated. The cutoff of p t /SER t values with higher predictive performance. Results: For the full cohort, FTV f showed the most robust association with RFS among the three predictors, with p t /SER t . The PE t /SER t combination with smallest p-value was found for PE=30% and SER=0.2, with hazard ratio 1.09 (95% CI 1.06−1.13, p f predictor was found for the full range of SER t values tested, but was mostly confined to PE t in 30−110% range; ΔFTV 2 resulted in p t /SER t combinations. When analyzed by tumor subtypes, different prediction profiles were observed. FTV f showed p t range only in the HER2+ (n=15) and triple-negative (n=11) groups. A limited number of PE t /SER t pairs showed p f and ΔFTV 2 , with the exception of the ΔFTV f in the triple-negative group, for which p t /SER t combinations in the low PE t range. Conclusions: This study was undertaken to explore the significance of FTV for predicting breast cancer recurrence following NACT. While this study is retrospective in nature and had small sample size, the findings nevertheless suggest that performance of imaging predictors based on FTV may be improved if threshold optimization is performed separately for the clinically-relevant subtypes defined by HR and HER2 receptor expression. Citation Format: Wen Li, Wei-Ching Lo, Ella F Jones, David C Newitt, John Kornak, Lisa J Wilmes, Nola M Hylton. Optimization of magnetic resonance imaging predictive performance by breast cancer subtypes for predicting response to neoadjuvant chemotherapy [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-01-09.