Abstract Introduction Quantitative dynamic parameters including Ktrans can predict for both response and outcome in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Quantitative methods are time-consuming to calculate in practice, requiring expensive additional software and expertise. For diagnostic purposes, signal intensity-time curves (SITC) are used for tissue characterisation. In this study we compared NAC-related changes in SITC with the quantitative DCE-MRI biomarker Ktrans (wash-in rate) and response and outcomes. Methods 73 women with histologically-proven primary breast cancer underwent DCE-MRI studies before and after two cycles of NAC. Patients received anthracycline and/or docetaxel based chemotherapy. At completion of NAC, patients had surgery, radiotherapy and endocrine therapy / trastuzumab if ER/ HER2 positive. SITCs for each of the paired DCE-MRI studies were visually scored using a published pattern recognition schema consisting of 5 distinct patterns encompassing wash-in and wash-out phases and compared to the endpoints of OS, DFS and pathologic response. Results 58 patients completed the study and were evaluable. Median age was 45 years (range 22 to 70), 41 patients were ER/ PR +ve, 12 Her-2 +ve and 13 triple negative. At baseline the majority of patients (n = 28, 48%) had a curve shape of 4 (Table 1). Linear regression analyses showed that curve shapes were significantly related to ktrans values both before (r2 = 0.465, p<0.0001) and after 2 cycles of NAC (r2 = 0.615, p<0.0001). 37 of 58 patients (64%) had changes in curve shape in response to NAC; 35 (95%) had decreases in curve shape and two (5%) had increases. Decreases in curve shape of 1 point were seen in 15 (43%), 12 patients had decreases in shape of 2 (34%), and eight had decreases of 3 (23%). Changes in curve shapes were significantly related to changes in ktrans (r2 = 0.576, p<0.0001). Changes in curve shape were significantly correlated with clinical (p = 0.005) and pathologic response (p = 0.034). Reduction in curve shape of ≥2 points was significant for overall survival using Kaplan-Meier analysis with a 5 year OS of 80.9% vs 68.6% (p = 0.048). Table 1: Signal Intensity time curves (n = 58)Signal intensity time curve typeBaselinePost 2 cycles of NAC10 (0%)0 (0%)21 (1.7%)26 (44.8%)312 (20.7%)10 (17.2%)428 (48.3%)18 (31%)517 (29.3%4 (6.9%) Conclusions These data suggest that SITCs are closely related to the quantitative DCE-MRI biomarker Ktrans and that change in curve shape can be used to predict clinical and pathologic benefit as well as survival. In clinical practice, the use of SITC which needs no special software to generate, provides a useful method of assessing the effectiveness of NAC for primary breast cancer. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-01-08.