In vivo application of MP-PCA denoising of quantitative T2* and magnetic susceptibility maps (QSM) in normal and pathological cerebral tissues

Motivation: Higher spatial resolution can increase the diagnosis quality of Quantitative Susceptibility Mapping (QSM) by improving the sensitivity to local field variations and minimizing partial volume effects, yet, at the cost of reduced signal-to-noise ratio (SNR). Goal(s): Improve the SNR of high-resolution QSM data, while preserving structural properties of the tissue. Approach: Use Marchenko-Pastur principal component analysis (MP-PCA) to denoise T­2*-weighted images, and generate quantitative T2* and QSM maps with higher SNR. Results: MP-PCA denoising was able to efficiently improve the SNR on numerical phantom and in vivo. Proof of concept is provided for healthy brain anatomy and for a patient with brain metastases. Impact: Marchenko Pastur principal component analysis can be used to enhance the SNR of T2*-weighted images, T2* maps, and QSM maps while preserving the fine details of the tissue.