Denoising and spatial resolution enhancement of 4D flow MRI using proper orthogonal decomposition and lasso regularization

Mojtaba F Fathi; Ali Bakhshinejad; Ahmadreza Baghaie; David Saloner; Raphael H Sacho; Vitaliy L Rayz; Roshan M D'Souza

doi:10.1016/j.compmedimag.2018.07.003

Denoising and spatial resolution enhancement of 4D flow MRI using proper orthogonal decomposition and lasso regularization

Comput Med Imaging Graph. 2018 Dec:70:165-172. doi: 10.1016/j.compmedimag.2018.07.003. Epub 2018 Aug 7.

Authors

Mojtaba F Fathi¹, Ali Bakhshinejad², Ahmadreza Baghaie³, David Saloner⁴, Raphael H Sacho⁵, Vitaliy L Rayz⁶, Roshan M D'Souza⁷

Affiliations

¹ Department of Mechanical Engineering, University of Wisconsin-Milwaukee, United States. Electronic address: fathifi2@uwm.edu.
² Department of Mechanical Engineering, University of Wisconsin-Milwaukee, United States; Departments of Neurosurgery, Medical College of Wisconsin, United States. Electronic address: bakhshi3@uwm.edu.
³ Department of Biomedical Engineering, Purdue University, United States. Electronic address: abaghaie@purdue.edu.
⁴ Department of Radiology, College of Medicine, University of California, San Francisco, United States. Electronic address: david.saloner@ucsf.edu.
⁵ Departments of Neurosurgery, Medical College of Wisconsin, United States. Electronic address: rsacho@mcw.edu.
⁶ Department of Biomedical Engineering, Purdue University, United States. Electronic address: vrayz@purdue.edu.
⁷ Department of Mechanical Engineering, University of Wisconsin-Milwaukee, United States. Electronic address: dsouza@uwm.edu.

PMID: 30423501
DOI: 10.1016/j.compmedimag.2018.07.003

Abstract

4D-Flow MRI has emerged as a powerful tool to non-invasively image blood velocity profiles in the human cardio-vascular system. However, it is plagued by issues such as velocity aliasing, phase offsets, acquisition noise, and low spatial and temporal resolution. In imaging small blood vessel malformations such as intra-cranial aneurysms, the spatial resolution of 4D-Flow is often inadequate to resolve fine flow features. In this paper, we address the problem of low spatial resolution and noise by combining 4D-Flow MRI and patient specific computational fluid dynamics using Least Absolute Shrinkage and Selection Operator. Extensive experiments using numerical phantoms of two actual intra-cranial aneurysms geometries show the applicability of the proposed method in recovering the flow profile. Comparisons with the state-of-the-art denoising methods for 4D-Flow show lower error metrics. This method can enable more accurate computation of flow derived patho-physiological parameters such as wall shear stresses, pressure gradients, and viscous dissipation.

Keywords: 4D-Flow MRI; 4D-PCMR; Computational fluid dynamics; Flow reconstruction; Lasso regularization.

MeSH terms

Algorithms
Blood Flow Velocity
Humans
Hydrodynamics*
Imaging, Three-Dimensional / methods*
Intracranial Aneurysm / diagnostic imaging*
Magnetic Resonance Imaging / methods*
Phantoms, Imaging*
Signal-To-Noise Ratio*