White matter biomarkers from fast protocols using axially symmetric diffusion kurtosis imaging

• Published in: NMR in biomedicine Vol. 30; no. 9
• Main Authors: Hansen, Brian, Khan, Ahmad R., Shemesh, Noam, Lund, Torben E., Sangill, Ryan, Eskildsen, Simon F., Østergaard, Leif, Jespersen, Sune N.
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.09.2017
• Subjects: Animals; Biological products; Biomarkers; Biomarkers - analysis; Biophysical Phenomena; biophysics; Brain; Brain injury; Computer Simulation; Data acquisition; Datasets; diffusion; Diffusion rate; Diffusion Tensor Imaging - methods; Disorders; Experimental methods; Humans; In vivo methods and tests; Inflammation; Kurtosis; Medical imaging; MRI; Neurodevelopmental disorders; Neuroimaging; Numerical Analysis, Computer-Assisted; Parameter estimation; Rats, Long-Evans; Signs and symptoms; Spinal cord; Substantia alba; Therapeutic applications; white matter; White Matter - metabolism; WMTI; white matter; diffusion; WMTI; kurtosis; MRI; biophysics
• ISSN: 0952-3480; 1099-1492; 1099-1492
• DOI: 10.1002/nbm.3741

White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development and aging, as well as in a number of brain disorders. Currently, WMTI is mostly used in dedicated animal studies and clinical studies of slowly progressing diseases, and has not yet emerged as a routine clinical tool. To this end, a less data intensive experimental method would be beneficial by enabling high resolution validation studies, and ease clinical applications by speeding up data acquisition compared with typical diffusion kurtosis imaging (DKI) protocols utilized as part of WMTI imaging. Here, we evaluate WMTI based on recently introduced axially symmetric DKI, which has lower data demand than conventional DKI. We compare WMTI parameters derived from conventional DKI with those calculated analytically from axially symmetric DKI. We employ numerical simulations, as well as data from fixed rat spinal cord (one sample) and in vivo human (three subjects) and rat brain (four animals). Our analysis shows that analytical WMTI based on axially symmetric DKI with sparse data sets (19 images) produces WMTI metrics that correlate strongly with estimates based on traditional DKI data sets (60 images or more). We demonstrate the preclinical potential of the proposed WMTI technique in in vivo rat brain (300 μm isotropic resolution with whole brain coverage in a 1 h acquisition). WMTI parameter estimates are subject to a duality leading to two solution branches dependent on a sign choice, which is currently debated. Results from both of these branches are presented and discussed throughout our analysis. The proposed fast WMTI approach may be useful for preclinical research and e.g. clinical evaluation of patients with traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders. Detailed white matter evaluation (WMTI) from scarce diffusion kurtosis data sets and axial kurtosis is presented and evaluated. Our analysis employs extensive numerical simulations and experimental evaluation based on data from fixed spinal cord, normal human brain, and in vivo rat brain. Strong correlations to standard estimation methods are found even with analysis based on only 19 images. The fast WMTI method may be useful for high resolution preclinical studies or for clinical settings where scan time is a constraint.