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

Research output: ResearchJournal article

White matter tract integrity (WMTI) can be used to characterize tissue microstructure in areas with axisymmetric 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. In a clinical setting, however, the diffusion kurtosis imaging (DKI) protocol utilized as part of WMTI imaging may be prohibitively long. Consequently, the diagnostic value of the WMTI parameters is rarely explored outside of dedicated animal studies and clinical studies of slowly progressing diseases. 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 to those from axially symmetric DKI and to parameters calculated analytically from the axially symmetric tensors. We also assess the effect of the imposed symmetry on the kurtosis fractional anisotropy (KFA). We employ numerical simulations, as well as data from fixed rat spinal cord and whole human brain in vivo. 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 $\mu$m isotropic resolution with whole brain coverage in a one hour acquisition). This approach may help introduce the WMTI technique into a wider range of settings, including preclinical research and the clinical evaluation of patients who suffered traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders.
Original languageEnglish
Article number1610.02783
JournalarXiv preprint
StatePublished - 10 Oct 2016

Bibliographical note

36 pages, 11 figures, 1 table, 3 supplementary figures. Submitted to Neuroimage

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ID: 110168938