PMID- 23235270
OWN - NLM
STAT- MEDLINE
DCOM- 20130801
LR  - 20211021
IS  - 1095-9572 (Electronic)
IS  - 1053-8119 (Print)
IS  - 1053-8119 (Linking)
VI  - 68
DP  - 2013 Mar
TI  - Regional characterization of longitudinal DT-MRI to study white matter maturation 
      of the early developing brain.
PG  - 236-47
LID - S1053-8119(12)01152-4 [pii]
LID - 10.1016/j.neuroimage.2012.11.040 [doi]
AB  - The human brain undergoes rapid and dynamic development early in life. Assessment 
      of brain growth patterns relevant to neurological disorders and disease requires 
      a normative population model of growth and variability in order to evaluate 
      deviation from typical development. In this paper, we focus on maturation of 
      brain white matter as shown in diffusion tensor MRI (DT-MRI), measured by 
      fractional anisotropy (FA), mean diffusivity (MD), as well as axial and radial 
      diffusivities (AD, RD). We present a novel methodology to model temporal changes 
      of white matter diffusion from longitudinal DT-MRI data taken at discrete time 
      points. Our proposed framework combines nonlinear modeling of trajectories of 
      individual subjects, population analysis, and testing for regional differences in 
      growth pattern. We first perform deformable mapping of longitudinal DT-MRI of 
      healthy infants imaged at birth, 1 year, and 2 years of age, into a common 
      unbiased atlas. An existing template of labeled white matter regions is 
      registered to this atlas to define anatomical regions of interest. Diffusivity 
      properties of these regions, presented over time, serve as input to the 
      longitudinal characterization of changes. We use non-linear mixed effect (NLME) 
      modeling where temporal change is described by the Gompertz function. The 
      Gompertz growth function uses intuitive parameters related to delay, rate of 
      change, and expected asymptotic value; all descriptive measures which can answer 
      clinical questions related to quantitative analysis of growth patterns. Results 
      suggest that our proposed framework provides descriptive and quantitative 
      information on growth trajectories that can be interpreted by clinicians using 
      natural language terms that describe growth. Statistical analysis of regional 
      differences between anatomical regions which are known to mature differently 
      demonstrates the potential of the proposed method for quantitative assessment of 
      brain growth and differences thereof. This will eventually lead to a prediction 
      of white matter diffusion properties and associated cognitive development at 
      later stages given imaging data at early stages.
CI  - Copyright (c) 2012 Elsevier Inc. All rights reserved.
FAU - Sadeghi, Neda
AU  - Sadeghi N
AD  - Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, 
      UT 84112, USA. neda@sci.utah.edu
FAU - Prastawa, Marcel
AU  - Prastawa M
FAU - Fletcher, P Thomas
AU  - Fletcher PT
FAU - Wolff, Jason
AU  - Wolff J
FAU - Gilmore, John H
AU  - Gilmore JH
FAU - Gerig, Guido
AU  - Gerig G
LA  - eng
GR  - R01 HD067731/HD/NICHD NIH HHS/United States
GR  - U54 EB005149/EB/NIBIB NIH HHS/United States
GR  - P50 MH064065/MH/NIMH NIH HHS/United States
GR  - R01 MH070890/MH/NIMH NIH HHS/United States
GR  - R01 HD055741/HD/NICHD NIH HHS/United States
GR  - MH064065/MH/NIMH NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20121209
PL  - United States
TA  - Neuroimage
JT  - NeuroImage
JID - 9215515
SB  - IM
MH  - Brain/*growth & development
MH  - Brain Mapping/*methods
MH  - Child, Preschool
MH  - Diffusion Tensor Imaging
MH  - Female
MH  - Humans
MH  - Image Processing, Computer-Assisted
MH  - Infant
MH  - Infant, Newborn
MH  - Male
MH  - Nerve Fibers, Myelinated/*ultrastructure
PMC - PMC3693970
MID - NIHMS427821
EDAT- 2012/12/14 06:00
MHDA- 2013/08/02 06:00
PMCR- 2014/03/01
CRDT- 2012/12/14 06:00
PHST- 2012/07/27 00:00 [received]
PHST- 2012/10/21 00:00 [revised]
PHST- 2012/11/15 00:00 [accepted]
PHST- 2012/12/14 06:00 [entrez]
PHST- 2012/12/14 06:00 [pubmed]
PHST- 2013/08/02 06:00 [medline]
PHST- 2014/03/01 00:00 [pmc-release]
AID - S1053-8119(12)01152-4 [pii]
AID - 10.1016/j.neuroimage.2012.11.040 [doi]
PST - ppublish
SO  - Neuroimage. 2013 Mar;68:236-47. doi: 10.1016/j.neuroimage.2012.11.040. Epub 2012 
      Dec 9.