Partial Least Squares - Diffusion Tensor Imaging (PLS-DTI): A novel approach for biomarker imaging in breast cancer

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Currently, magnetic resonance imaging is the most sensitive imaging technique for detecting cancer processes in early stages. Regarding breast cancer, due to the characteristics of the tissue as it is formed by ducts (tubular structure), anisotropic diffusion should be considered instead of general isotropic Diffusion Weighted Imaging (DWI). Anisotropic diffusion is studied by applying a technique called Diffusion Tensor Imaging (DTI), where the diffusion gradient is applied with several different directions, calculated by Ordinary Least Squares (OLS) in clinical practice. In this paper, we propose a new DTI calculation method based on Partial Least Squares (PLS), which has some advantages over the traditional OLS calculation: i) the PLS model provides valid biomarkers (non-negative eigenvalues) in a larger percentage of pixels, improving the traditional OLS calculation and reducing the effect of noisier images; ii) OLS tensors are calculated pixel-by-pixel, whereas the PLS method calculates only one model taking advantage of the correlation structure between pixels with similar characteristics, obtaining more reliable estimations; iii) PLS performance is quite reliable when lowering the number of directions of the magnetic field, while this is not the case of OLS. PLS keeps providing a good solution even with low functional resolution equipment, reducing costs and acquisition times, which is an important advantage for its widespread use in value-based medicine-oriented clinical practice.