Diffusion weighted imaging (DWI) characterizes cancerous tissue cellularity, particularly in breast cancer^1-4. Through DWI, biomarkers have been developed that are sensitive to microvascular flow via the intravoxel incoherent motion (IVIM) effect⁵. Using IVIM, first proposed by LeBihan, one can quantify the tumor hypervascularity and hypercellularity, and these markers have been shown in a range of breast cancer studies^6-11. Histogram analysis of the spatial distribution of IVIM parameters¹² can also provide additional information on each parameter's distributions, giving values of skewness and kurtosis^{13, 14}, for potentially enhanced characterization of the cancer microenvironment¹⁵. While it has been shown that IVIM parameters can distinguish between benign and malignant lesions^{8, 9, 11}, we hypothesize that a comprehensive evaluation of IVIM (including metrics of average, maximum, minimum, kurtosis, and skewness) can potentially have value by providing predictive biomarkers of treatment response. Here, we examine breast cancer patients using pre- and post-treatment imaging and compare the metrics from intravoxel incoherent motion (IVIM) histogram analysis with clinical response results.This IRB approved, HIPAA-compliant retrospective study observed 31 breast cancer patients with 32 lesions (31 invasive ductal carcinoma and 1 invasive lobular carcinoma). All patients underwent MRI scans during April 2011 to March 2013 followed by neoadjuvant chemo treatment (‘pre-treatment scans’). Additionally, 6 patients underwent an additional MRI scan 12-14 weeks after the initial scan and 1-2 cycles of treatment (‘post-treatment scan’). All patients underwent a standard bilateral contrast-enhanced (CE) MRI along with DWI in a 3T MRI scanner (Discovery MR750; GE Healthcare, Waukesha, WI) with a 16 channel breast coil (Sentinelle Vanguard, Sentinelle Medical, Toronto, Canada) and included fat-suppressed T2-weighted imaging, DW and post-contrast T1-weighted imaging. The DWI protocol consisted of a single shot spin echo EPI sequence (TR/TE = 4000/85.3 ms; 4 averages; FOV = 28 x 28 to 36 x 36 cm²; slice thickness: 4–5 mm; acquired matrix: 128x128, interpolated to 256x256; 19-35 slices; and 10 b values i.e. b = 0, 30, 60, 90, 120, 250, 400, 600, 800, 1000 s/mm²). Analyses for IVIM average and histogram (maximum, minimum, skewness, and kurtosis) metrics were derived from custom data analysis (Igor Pro 6, Wavemetrics, Portland, OR) using a biexponential model⁵. A single operator drew ROIs around the outer tumor border limiting IVIM analysis to the tumor region. Monoexponential analysis was performed to generate ADC maps of the entire lesion. Segmented biexponential IVIM analysis was performed to estimate D_t, f_p, and D_p. An additional filter was generated to select voxels of highly vascular tumor tissue (VTT) and exclude necrotic or normal tissue regions¹⁶, the percentage of which among all lesion voxels was labeled as VTT%. Clinical data was collected including histology of biopsy or surgical specimens as well as clinical response to treatment, defined by tumor size reduction by RECIST criteria (2 patients were excluded as there was no recorded response data). For analysis of pre-treatment IVIM-DWI parameters, we conducted Mann-Whitney tests to test for differences between responders and nonresponder. P values were not adjusted for multiple comparisons.Of all 30 lesions studied, 5 were classified as nonresponders; among the 6 patients scanned twice, only 1 did not show treatment response. Average, kurtosis, and skewness of the D_p parameters differentiate between responders and nonresponders to treatment (Table 1). Other IVIM metrics did not show any significant differences when compared to response to treatment results. In addition, we observe that IVIM parameters change when comparing between pre- and post-treatment MRI scans as seen in the parametric maps for an individual patient with invasive ductal carcinoma (Figure 1) and in all patients (Figure 2). ADC and D_t values generally increased post-treatment in responders.Among baseline measurements, D_p and VTT% were most prognostic, with high vascularity, slow and heterogeneous pseudodiffusion offering poor prognosis; analogously, decreases in D_p occurred in all dual-scanned responders. Our results showed that baseline values of ADC or D_t were not predictive of response. Low baseline ADC trended towards significance as a response predictor (p=0.074, consistent with other studies¹⁷). Also, early ADC and D_t increases were largest in dual-scanned responders, indicating a possible decline in cellularity, as previously correlated with response¹⁸. While a larger study will help to confirm these trends on a larger scale, this work suggest that both mean and heterogeneity metrics from IVIM analysis have prognostic value in the setting of neoadjuvant breast cancer therapy.