Pontificia Universidad Católica de Chile Pontificia Universidad Católica de Chile
Bustin A., Lima da Cruz G., Jaubert O., Lopez K., Botnar R.M., Prieto C. (2020)

High-dimensionality undersampled patch-based reconstruction (HD-PROST) for accelerated multi-contrast MRI

Revista : Magnetic Resonance in Medicine
Volumen : 81
Número : 6
Páginas : 3705-3719
Tipo de publicación : ISI Ir a publicación


PURPOSE:To develop a new high-dimensionality undersampled patch-based reconstruction (HD-PROST) for highly accelerated 2D and 3D multi-contrast MRI.METHODS:HD-PROST jointly reconstructs multi-contrast MR images by exploiting the highly redundant information, on a local and non-local scale, and the strong correlation shared between the multiple contrast images. This is achieved by enforcing multi-dimensional low-rank in the undersampled images. 2D magnetic resonance fingerprinting (MRF) phantom and in vivo brain acquisitions were performed to evaluate the performance of HD-PROST for highly accelerated simultaneous T1 and T2 mapping. Additional in vivo experiments for reconstructing multiple undersampled 3D magnetization transfer (MT)-weighted images were conducted to illustrate the impact of HD-PROST for high-resolution multi-contrast 3D imaging.RESULTS:In the 2D MRF phantom study, HD-PROST provided accurate and precise estimation of the T1 and T2 values in comparison to gold standard spin echo acquisitions. HD-PROST achieved good quality maps for the in vivo 2D MRF experiments in comparison to conventional low-rank inversion reconstruction. T1 and T2 values of white matter and gray matter were in good agreement with those reported in the literature for MRF acquisitions with reduced number of time point images (500 time point images, ~2.5 s scan time). For in vivo MT-weighted 3D acquisitions (6 different contrasts), HD-PROST achieved similar image quality than the fully sampled reference image for an undersampling factor of 6.5-fold.CONCLUSION:HD-PROST enables multi-contrast 2D and 3D MR images in a short acquisition time without compromising image quality. Ultimately, this technique may increase the potential of conventional parameter mapping.