Anatomically weighted second-order total variation reconstruction of 23Na MRI using prior information from 1H MRI

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2015-01, Vol.105, p.452-461
• Main Authors: Gnahm, Christine, Nagel, Armin M.
• Format: Article
• Language: English
• Subjects: Adult; Algorithms; Anatomical prior knowledge; Assessments; Compressed sensing; Computer simulation; Humans; Image Processing, Computer-Assisted - methods; Iterative reconstruction; Magnetic Resonance Spectroscopy - methods; Male; Multiple sclerosis; Multiple Sclerosis - pathology; Non-proton MRI; Patients; Projection reconstruction; Proton Magnetic Resonance Spectroscopy - methods; Reconstruction; Sodium; Sodium - metabolism; Sodium MRI; Three dimensional; Total variation
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2014.11.006

Sodium (23Na) MRI is a noninvasive tool to assess cell viability, which is linked to the total tissue sodium concentration (TSC). However, due to low in vivo concentrations, 23Na MRI suffers from low signal-to-noise ratio (SNR) and limited spatial resolution. As a result, image quality is compromised by Gibbs ringing artifacts and partial volume effects. An iterative reconstruction algorithm that incorporates prior information from 1H MRI is developed to reduce partial volume effects and to increase the SNR in non-proton MRI. Anatomically weighted second-order total variation (AnaWeTV) is proposed as a constraint for compressed sensing reconstruction of 3D projection reconstruction (3DPR) data. The method is evaluated in simulations and a MR measurement of a multiple sclerosis (MS) patient by comparing it to gridding and other reconstruction techniques. AnaWeTV increases resolution of known structures and reduces partial volume effects. In simulated MR brain data (nominal resolution Δx3=3×3×3mm3), the intensity error of four small MS lesions was reduced from (6.9±3.8)% (gridding) to (2.8±1.4)% (AnaWeTV with T2-weighted reference images). Compared to gridding, a substantial SNR increase of 130% was found in the white matter of the MS patient. The algorithm is robust against misalignment of the prior information on the order of the 23Na image resolution. Features without prior information are still reconstructed with high contrast. AnaWeTV allows a more precise quantification of TSC in structures with prior knowledge. Thus, the AnaWeTV algorithm is in particular beneficial for the assessment of tissue structures that are visible in both 23Na and 1H MRI. •We propose an iterative reconstruction algorithm that incorporates prior knowledge for 23Na MRI.•We develop an anatomically weighted second-order total variation constraint (AnaWeTV).•Anatomical weighting factors are calculated from high-resolution 1H MRI.•AnaWeTV increases SNR and reduces partial volume effects.•AnaWeTV performs superiorly compared to rival reconstruction techniques.