Download IMAGING THE DEVELOPING BRAIN

IMAGING THE DEVELOPING BRAIN
S. Mori, A. Qiu, J. T. Ratnanather, J. Pekar, P. Barker, P. van Zijl, M. I. Miller
Resource for Quantitative functional MRI
Kennedy Krieger Institute, F.M. Kirby Research Center for Functional Brain Imaging,
Johns Hopkins University; Center for Imaging Science, Dept. of Radiology.
http://mri.kennedykrieger.org/; contact: [email protected]
The Resource for Quantitative Functional Magnetic Resonance Imaging (MRI) and
Spectroscopy (MRS) is an interdepartmental and interdisciplinary laboratory combining facilities
of the F.M. Kirby Research Center for Functional Brain Imaging at the Kennedy Krieger Institute
(KKI) and the Center for Imaging Science (CIS) at Johns Hopkins University (JHU). This
resource is dedicated to using its unique expertise to design novel MRI and MRS data
acquisition and data processing technology with a special focus on clinical and neurosciencebased pediatric and neurodevelopmental applications. One of the main issues to be addressed
is the need to assess tissue properties and brain anatomical features and apparent alterations
in brain activation and/or pathology, when the brain is changing size during development. The
problem of changing brain size will be tackled by using landmark, curve, surface and volume
based brain warping technologies to be able to derive a unified and comprehensive whole-brain
anatomical reference frame for multi-modality MRI data.
Two types of imaging for which this approach is especially important are high-resolution
anatomical imaging (1x1x1mm3 true spatial resolution) and diffusion tensor imaging (DTI,
(2.2x2.2x2.2mm3 true spatial resolution), in which white matter connections can be identified.
While conventional anatomical image approaches (water density and relaxation time, T1, T2,
based) are problematic for studying development due to lack of tissue contrast within white
matter and between white and gray matter during several stages of brain development, DTI
contrast is unique in that it can distinguish such structures at any time point, allowing
identification of corresponding brain structures throughout the development process.
Currently we are collaborating with St. Luke Hospital in Belgium and Yonsei University in Korea
to establish DTI database of developing brain (www.pediatricDTI.org). Based on this database,
we are working on quantitative characterization of the normal brain development. The first level
of the analysis was performed by manually delineating corresponding structures and measuring
their size, T2, apparent diffusion constant, and diffusion anisotropy (1). In the second level of
the analysis, we used a linear normalization method to transform all the data to a common
template. After the normalization, we performed pixel-by-pixel analyses to investigate time
dependent changes in white matter anatomy. The study clearly indicates that the superior
longitudinal fasciculus is one of the tracts that emerges latest during the development. In the
third level analysis, our goal is to investigate the development of white matter via non-linear
transformation based on Large Deformation Diffeomorphic Metric Mapping (LDDMM) and tensor
statistical analysis.
(1) Hermoye, L, Saint-Martin, C., Cosnard, G., Lee, S-K, Kim, J., Nassogne, M-C., Menten, R.,
Clapuyt, P., Donohue, PK, Hua, K., Wakana, S, Jiang, H, van Zijl, PCM., Mori, S, “Pediatric
diffusion tensor imaging: Normal database and observation of the white matter maturation in
early childhood”, Neuroimage, 29, 493-504 (2006)