Abstract PD6-08: DCE-MRI derived imaging features for characterizing invasive lobular breast cancer and predicting recurrence-free survival after neoadjuvant therapy

Abstract

Abstract Background With current imaging technologies, assessing response to neoadjuvant chemotherapy (NAC) or neoadjuvant endocrine therapy (NET) remains a challenge for patients with invasive lobular carcinoma (ILC). Therefore, we evaluated imaging features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) before and after neoadjuvant therapy in a cohort of patients with ILC, including the longest tumor diameter (LD), functional tumor volume (FTV), and peak signal enhancement ratio (SER). FTV is the sum of all image voxels enhancing above a set threshold within a defined region, and has been validated as a predictor of recurrence-free survival (RFS) for breast cancer. SER is a measure of contrast wash-in and wash-out and reflects neovascularity of tumors. We determined whether baseline and post-treatment imaging features differed by type of neoadjuvant therapy and if they were associated with RFS in neoadjuvantly treated ILC regardless of treatment type. Methods With institutional review board approval, a retrospective analysis of pre- and post-treatment breast DCE-MRI was performed on a cohort of ILC patients receiving neoadjuvant therapy between 1998 and 2017. We compared pre-treatment, post-treatment, and percent reduction (α) in LD, FTV, and peak SER by neoadjuvant treatment type (i.e. NAC or NET) using the Wilcoxon rank-sum test. Univariate t-tests, Chi-squared tests, analysis of variance, and Spearmen’s correlation were used to evaluate associations of clinicopathologic features and treatment type. Univariate and multivariate associations with RFS in the entire neoadjuvantly treated cohort adjusting for treatment type were evaluated using the log-rank test and Cox proportional hazards models. Results A cohort of 76 patients with pre- and post-treatment MRI were included in this study, of whom 42 (55.3%) received NAC and 34 (44.7%) received NET. The NAC group was significantly younger (55 vs. 60 years, p=0.013), less likely to have stage 1 disease (26.2% vs. 73.5%, p<0.001), and showed a trend of having more human epidermal growth factor 2 receptor-positive (HER2) tumors. The mean follow up time was 4.9 years with no difference between treatment groups. Patients in the NAC group had significantly larger pre-treatment LD and FTV but no difference was found in pre-treatment peak SER between groups. Post-treatment LD, FTV, and peak SER did not differ between treatment groups (Table 1). Those receiving NAC had significantly greater reduction in FTV compared to those receiving NET; αLD and α peak SER did not differ. In a multivariate Cox proportional hazards model including all patients in the cohort, higher pre-treatment peak SER was significantly associated with worse RFS regardless of neoadjuvant treatment type when adjusting for age, stage, receptor subtype, and tumor grade (hazard ratio 1.3, p=0.005, 95% CI 1.1-1.6). Neither LD nor FTV were associated with RFS on multivariate analysis. ConclusionPre-treatment peak SER measured by MRI may provide prognostic information beyond standard clinicopathologic variables in patients with ILC receiving either neoadjuvant chemotherapy or endocrine therapy. Further evaluation in a larger ILC cohort is needed to validate our initial findings. Table 1. Comparison of MR imaging features of ILC patients receiving neoadjuvant chemotherapy and neoadjuvant endocrine therapy.Overall(n=76)NAC(n=42)NET(n=34)P-valuePre-treatment (median, IQR)LD (cm)2.7, 1.6-5.44.6, 2.5-71.8, 1.4-3.20.0006FTV (cc)5.8, 2.2-16.48.7, 4.1-24.23.0, 0.9-80.0004SER0.9, 0.8-1.00.9, 0.9-1.00.9, 0.8-1.10.8335Post-treatment (median, IQR)LD (cm)1.1, 0-1.91.0, 0-1.81.3, 0-1.90.6071FTV (cc)0.5, 0.1-1.80.3, 0.1-1.80.7, 0.3-1.80.2196SER0.9, 0.8-1.00.8, 0.8-1.00.9, 0.8-1.10.2321Percent reduction (%)LD44.6, 15.1-10079.6, 33.8-10033.8, 10.1-1000.0958FTV93, 72.5-97.495.8, 90.7-99.172.6, 43.1-94.5<0.0001SER8.5, -11.1-19.710.7, -6.0-21.81.9, -15.1-17.90.3041 Citation Format: Geraldine Tran, Ella Jones, Wen Li, Kelly Fahrner-Scott, David Newitt, Bonnie Joe, Laura Esserman, Nola Hylton, Rita Mukhtar. DCE-MRI derived imaging features for characterizing invasive lobular breast cancer and predicting recurrence-free survival after neoadjuvant therapy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD6-08.