Abstract 3043: Quantitative MRI during neoadjuvant therapy for predicting breast cancer response in the community setting
Authors: Anna Sorace, Jack Virostko, Chengyue Wu, Angela M. Jarrett, Stephanie L. Barnes, Debra Patt, Boone Goodgame, Sarah Avery, Thomas E. Yankeelov
Journal: Cancer Research (2018)

Abstract Purpose: Quantification of accurate and early response to neoadjuvant therapy (NAT) provides the opportunity to replace an ineffective treatment with an alternative regimen, thereby potentially avoiding ineffective systemic therapy. Quantitative magnetic resonance imaging (MRI) has been shown to predict breast cancer response to treatment early during the course of NAT within academic medical centers. Integrating quantitative imaging techniques into community-based medical practices has the potential to reach a larger percentage of breast cancer patients, and allow more community center participation in clinical trials that require quantitative imaging. This study evaluated the reproducibility and accuracy of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) in the community setting and the ability to implement these techniques to predict the eventual response of breast tumors to NAT. Experiment Procedure: MRI was performed at two community imaging centers and one academic research facility using a 3T Siemens Skyra scanners equipped with a breast coil. To assess reproducibility across sites, normal subjects (N=3) were scanned at three imaging centers. Quantitative T1 (required for pharmacokinetic modeling of DCE-MRI) and apparent diffusion coefficient (ADC) maps were calculated of normal fibroglandular breast tissue. Accuracy was tested through evaluation of T1 and DW-MRI in phantoms. Women undergoing NAT for breast cancer (N=10) were scanned with DCE-MRI and DW-MRI at baseline (prior to beginning therapy) and three longitudinal time points during the course of NAT to evaluate early prediction of response to therapy. Quantitative measures of ADC (evaluating cellularity from DW-MRI) and Ktrans (evaluating vascular perfusion and permeability from DCE-MRI) were calculated for the segmented tumor volume. Imaging was compared to pathology reports at the conclusion of NAT. Results: Reproducibility scans of normal breast fibroglandular tissue yielded an average difference of 8.4% and 7.0% in T1 and ADC measurements, respectively, across sites. Phantom studies revealed accurate measurements of T1 mapping and ADC, with reproducibility measurements showing a difference of 2.8% and 1.6%, respectively. Patients achieving a pathological complete response (pCR) revealed a 13.8% ± 19.0% increase in the mean ADC values of the tumor from t1 (baseline, prior to beginning NAT) and t2 (following one round of NAT) and a 15.4% ± 40.9% decrease in mean Ktrans. Conversely, patients that did not achieve non-pCR had little change in ADC (-0.9% ± 12.6% change between t1 and t2) and a 15.3% ± 42.8% increase in Ktrans. Conclusions: Quantitative MRI has been shown to be accurate and reproducible across community medical centers. Furthermore, the preliminary results discussed above parallel those previously reported in the academic research setting. Citation Format: Anna Sorace, Jack Virostko, Chengyue Wu, Angela M. Jarrett, Stephanie L. Barnes, Debra Patt, Boone Goodgame, Sarah Avery, Thomas E. Yankeelov. Quantitative MRI during neoadjuvant therapy for predicting breast cancer response in the community setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3043.