Diffusion tensor imaging (DTI) may provide additional information on tissue characteristics over dynamic contrast enhanced (DCE) MRI, however there are conflicting results regarding its utility. Our study evaluated DCE and DTI features of histologically proven breast lesions on 3T MRI. Using a machine learning-based LASSO approach for multivariate regression and bootstrap-based internal validation, the model incorporating DCE and DTI parameters demonstrated significantly better performance in differentiating malignant and benign lesions compared to models using DCE or DTI parameters alone. These findings suggest that the addition of DTI sequences to DCE MRI may improve diagnostic performance.
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