Abstract Introduction: Early response assessment to neoadjuvant therapy (NAT) for locally advanced breast cancer would allow for more accurate prognosis and provide the opportunity to replace an ineffective treatment with an alternative regimen. This could potentially increase systemic treatment efficacy and avoid unnecessary side effects from ineffective therapies. Quantitative MRI has been shown to be beneficial in predicting breast tumor response to treatment early during the course of NAT within many academic environments. Importantly, integrating quantitative imaging techniques into the community-based setting has the potential to reach a large percentage of breast cancer patients, as most patients receive their care at private practice or community hospitals. This study evaluated the ability to implement quantitative dynamic contrast enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) data in the community setting to predict the eventual response of breast tumors to NAT. Experimental Design: Women undergoing NAT for breast cancer (N=16) were scanned with DCE-MRI and DW-MRI at baseline (prior to beginning therapy, t1) and three longitudinal time points during the course of NAT to evaluate early response to therapy (t2, t3, t4). MRI was performed at two community imaging centers using a 3T Siemens Skyra scanners equipped with 8- or 16-channel breast coils. DW-MRI was acquired with a spin echo sequence with TR/TE = 3000/52 ms, b-values of 200, 800 s/mm2 and used to compute the apparent diffusion coefficient (ADC) values for every voxel. DCE-MRI data was collected (following a pre-contrast T1 map) with TR/TE/α = 7.02 ms/4.60 ms/6o, and a temporal resolution of 7.27 sec for eight minutes. A catheter placed within an antecubital vein delivered gadolinium-based contrast agent (0.1 mmol/kg of Multihance or 10 mL of Gadovist) at 2 mL/sec via a power injector after the acquisition of the first minute of dynamic scans (baseline).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:The patients (n = 6) achieving a pathological complete response (pCR) revealed a 12.9% ± 19.1% increase in the mean ADC values of the tumor from t1 and t2. Conversely, patients (n = 10) that had residual disease burden after NAT (i.e., a non-pCR) had a decreased ADC, revealing a -8.0% ± 19.2% change between t1 and t2 (p = 0.06). The mean Ktrans values of the tumor decreased showing a change of -61.4% ± 18.2% from t1 to t2 in the pCR patients. Conversely, non-pCR patients had a 10.2% ± 80.4% increase in Ktrans between t1 and t2 (p = 0.14) Conclusion:Preliminary evidence reveals that quantitative DCE-MRI and DW-MRI can be implemented in community-based imaging settings to predict the response of breast tumors to NAT. Thus, our results provide evidence that quantitative DW-MRI and DCE-MRI can be disseminated across community imaging facilities, thereby dramatically increasing the patient population for which these techniques can serve. We acknowledge the support of CPRIT RR160005. Citation Format: Sorace AG, Virostko J, Wu C, Jarrett AM, Barnes SL, Ekrut D, Patt D, Goodgame B, Avery S, Yankeelov TE. Quantitative breast MRI to predict response to neoadjuvant therapy in community imaging centers: Preliminary results [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-01-02.