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Paul Yarowsky

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
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3

YNIMG Journal 2006 Journal Article

White and gray matter development in human fetal, newborn and pediatric brains

  • Hao Huang
  • Jiangyang Zhang
  • Setsu Wakana
  • Weihong Zhang
  • Tianbo Ren
  • Linda J. Richards
  • Paul Yarowsky
  • Pamela Donohue

Brain anatomy is characterized by dramatic growth from the end of the second trimester through the neonatal stage. The characterization of normal axonal growth of the white matter tracts has not been well-documented to date and could provide important clues to understanding the extensive inhomogeneity of white matter injuries in cerebral palsy (CP) patients. However, anatomical studies of human brain development during this period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor magnetic resonance imaging (DTMRI) can reveal detailed anatomy of white matter. We acquired diffusion tensor images (DTI) of postmortem fetal brain samples and in vivo neonates and children. Neural structures were annotated in two-dimensional (2D) slices, segmented, measured, and reconstructed three-dimensionally (3D). The growth status of various white matter tracts was evaluated on cross-sections at 19–20 gestational weeks, and compared with 0-month-old neonates and 5- to 6-year-old children. Limbic, commissural, association, and projection white matter tracts and gray matter structures were illustrated in 3D and quantitatively characterized to assess their dynamic changes. The overall pattern of the time courses for the development of different white matter is that limbic fibers develop first and association fibers last and commissural and projection fibers are forming from anterior to posterior part of the brain. The resultant DTMRI-based 3D human brain data will be a valuable resource for human brain developmental study and will provide reference standards for diagnostic radiology of premature newborns.

YNIMG Journal 2005 Journal Article

Mapping postnatal mouse brain development with diffusion tensor microimaging

  • Jiangyang Zhang
  • Michael I. Miller
  • Celine Plachez
  • Linda J. Richards
  • Paul Yarowsky
  • Peter van Zijl
  • Susumu Mori

While mouse brain development has been extensively studied using histology, quantitative characterization of morphological changes is still a challenging task. This paper presents how developing brain structures can be quantitatively characterized with magnetic resonance diffusion tensor microimaging coupled with techniques of computational anatomy. High resolution diffusion tensor images of ex vivo postnatal mouse brains provide excellent contrasts to reveal the evolutions of mouse forebrain structures. Using anatomical landmarks defined on diffusion tensor images, tissue level growth patterns of mouse brains were quantified. The results demonstrate the use of these techniques to three-dimensionally and quantitatively characterize brain growth.

YNIMG Journal 2003 Journal Article

Three-dimensional anatomical characterization of the developing mouse brain by diffusion tensor microimaging

  • Jiangyang Zhang
  • Linda J Richards
  • Paul Yarowsky
  • Hao Huang
  • Peter C.M van Zijl
  • Susumu Mori

Investigation of three-dimensional (3D) morphometry of developing brains has been hindered by a lack of imaging modalities that can monitor the 3D evolution of various anatomical structures without sectioning and staining processes. In this study, we combined magnetic resonance microimaging and diffusion tensor imaging techniques to accomplish such visualization. The application of this approach to developing mouse embryos revealed that it could clearly delineate early critical structures such as neuroepithelium, cortical plate, and various axonal structures, and follow their developmental evolution. The technique was applied to the study of the Netrin-1 mutant, allowing verification of its anatomical phenotype.

v2026.09.13