Abstract PD2-09: Association of quantitative MRI features with tumor infiltrating lymphocytes and treatment response prediction in HER2 positive subtype of breast cancer

Abstract

Objectives: To evaluate associations between qualitative and quantitative MRI features and tumor infiltrating lymphocytes (TIL) levels in HER2+ subtype of breast cancer, as potential prognostic non-invasive imaging markers for treatment response prediction. Materials and Methods: Retrospective review of breast cancer patients who had MRI at staging, neoadjuvant chemotherapy and surgery from January 1, 2008 through December 31, 2015 was performed. BI-RADS lexicon was used for lesion evaluation. Demographic, imaging, and pathologic data including TIL levels were documented. Quantitative MRI texture analysis was performed using 3 types of textural features (TF): local binary patterns (LBP), gray-level co-occurrence matrix (GLCM), and threshold adjacency statistics (TAS). Associations between MRI quantitative TF, TIL levels, and pathologic complete response (pCR) were evaluated by Pearson correlation and logistic regression. Results: There were 50 HER2+ patients (median age 51 years, range 29-59) with pretreatment MRI and TIL status for analysis; 27 patients had pCR at surgery. Qualitative MRI analysis showed that mass rim-enhancement (p<0. 05) and fast early enhancement kinetics (p<0.01) were associated with higher TIL levels. No association between qualitative MRI features and pCR was found. Nine TF significantly correlated with pCR (p<0.05): angular 2nd moment (GLCM), 75 percentile (LBP), standard deviation (GLCM), adjacency 0-5 (TAS). This is indicative of association of tumor heterogeneity with pCR. Three TF were significantly associated with high TIL levels (p<0.05): standard deviation, adjacency 1 and 2. Additional four TF had high association with TIL (p<0.1): sum entropy, adjacency 0, 3 and 4. These findings showed that increased heterogeneity, complexity and entropy were associated with high TIL level. Three TF were significantly associated with both, pCR and TIL (p<0.05): 75 percentile, standard deviation, adjacency 8. Conclusion: Quantitative tumor texture analysis based on statistical modeling showed specific nine TF indicative of tumor heterogeneity associated with pCR; and seven TF indicative of increased heterogeneity, complexity, and entropy associated with high TIL levels in HER2+ breast cancer. Analysis of associations of MRI quantitative TF with pCR and TIL in HER2+ breast cancer may help to develop prognostic non-invasive imaging markers for treatment response prediction. Citation Format: Rauch GM, Zhu H, Li H, Adrada BE, Santiago L, Candelaria RP, Wang H, Leung J, Litton J, Wu Y, Murthy R, Mittendorf EA, Yang W. Association of quantitative MRI features with tumor infiltrating lymphocytes and treatment response prediction in HER2 positive subtype of breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD2-09.

MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer

“…Our data suggest that radiomic intratumour heterogeneity does not equal pathologic intratumour heterogeneity but can be used in prediction models as a valuable parameter. This finding is supported by Rauch et al who also demonstrated that radiomic intratumoural heterogeneity seems to be different from pathological intratumuor heterogeneity, in this case with respect to the level of tumour infiltrating lymphocytes, and was shown to be associated with achievement of pCR [26].…”