Frontiers in Neurology (Apr 2020)

Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain

  • Manuel Blesa,
  • Paola Galdi,
  • Gemma Sullivan,
  • Emily N. Wheater,
  • David Q. Stoye,
  • Gillian J. Lamb,
  • Alan J. Quigley,
  • Michael J. Thrippleton,
  • Michael J. Thrippleton,
  • Mark E. Bastin,
  • James P. Boardman,
  • James P. Boardman

DOI
https://doi.org/10.3389/fneur.2020.00235
Journal volume & issue
Vol. 11

Abstract

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Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10−4. PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life.

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