Automated detection of white matter signal abnormality using T2 relaxometry: application to brain segmentation on term MRI in very preterm infants

Neuroimage. 2013 Jan 1:64:328-40. doi: 10.1016/j.neuroimage.2012.08.081. Epub 2012 Sep 6.

Abstract

Hyperintense white matter signal abnormalities, also called diffuse excessive high signal intensity (DEHSI), are observed in up to 80% of very preterm infants on T2-weighted MRI scans at term-equivalent age. DEHSI may represent a developmental stage or diffuse microstructural white matter abnormalities. Automated quantitative assessment of DEHSI severity may help resolve this debate and improve neonatal brain tissue segmentation. For T2-weighted sequence without fluid attenuation, the signal intensity distribution of DEHSI greatly overlaps with that of cerebrospinal fluid (CSF) making its detection difficult. Furthermore, signal intensities of T2-weighted images are susceptible to magnetic field inhomogeneity. Increased signal intensities caused by field inhomogeneity may be confused with DEHSI. To overcome these challenges, we propose an algorithm to detect DEHSI using T2 relaxometry, whose reflection of the rapid changes in free water content provides improved distinction between CSF and DEHSI over that of conventional T2-weighted imaging. Moreover, the parametric transverse relaxation time T2 is invulnerable to magnetic field inhomogeneity. We conducted computer simulations to select an optimal detection parameter and to validate the proposed method. We also demonstrated that brain tissue segmentation is further enhanced by incorporating DEHSI detection for both simulated preterm infant brain images and in vivo in very preterm infants imaged at term-equivalent age.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Artificial Intelligence
  • Brain / pathology*
  • Diffusion Tensor Imaging / methods*
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Infant, Extremely Premature*
  • Male
  • Nerve Fibers, Myelinated / pathology*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity