Diffusion Weighted Imaging (DWI) offers promising enhancements to breast cancer imaging by providing detailed examinations of tissue microstructure without the need for contrast agents, potentially improving specificity compared to the current standard, Dynamic Contrast-Enhanced MRI (DCE-MRI). Despite its advantages, DWI faces challenges such as Echo Planar Imaging (EPI)-related distortions, gradient nonlinearity, and eddy currents, which compromise its diagnostic sensitivity. This thesis tackles these issues by implementing reverse polarity gradient (RPG) sequences to correct EPI distortions and applying Gradient Nonlinearity Correction (GNC) to improve the accuracy of quantitative tissue measurements calculated from DWI.Utilizing data from the I-SPY2 TRIAL, a multi-center clinical trial testing novel agents for breast cancer, this study evaluates the effectiveness of these correction techniques on a subset of 6 patients and 16 exams scanned with Diffusion Tensor Imaging (DTI) and RPG sequences. The application of RPG and GNC has shown significant improvements in the Apparent Diffusion Coefficient (ADC) and Fractional Anisotropy(FA) measurements in phantom studies, affirming the potential of these corrections to standardize clinical DWI protocols and enhance its reliability alongside DCE-MRI in breast cancer treatment evaluation. Furthermore, this thesis explores the lack of correlation between changes in ADC values and Functional Tumor Volume (FTV) measured from DCE-MRI, underscoring DWI's potential role in providing independent and complementary information for assessing biological changes and aiding treatment evaluation.