9th International Conference on Human Brain Mapping, New York City, U.S.A., June 18-22, 2003
Investigating the Medial Prefrontal Cortex with Cortical Flat Mappings
Monica K. Hurdal, Agatha Lee, J. Tilak Ratnanather, Tomoyuki Nishino, Michael I. Miller, Kelly Botteron1
Department of Mathematics, Florida State University, Tallahassee, U.S.A.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, U.S.A.
Center for Imaging Science, Johns Hopkins University, Baltimore, U.S.A.
Department of Psychiatry, Washington University School of Medicine, St. Louis, U.S.A.
1Department of Radiology, Washington University School of Medicine, St. Louis, U.S.A.
We are using a pipeline of tools, including cortical flat mapping, to
process ventral medial prefrontal and orbital frontal cortical regions. There
has been accumulating evidence of the role these cortical regions have in
depression. Specific limbic circuits involving the medial and prefrontal
cortex have been implicated in affective disorders such as major depressive
disorder or bipolar affective disorder. Structural and functional changes
in these regions have been reported as grey matter volume reduction and differences
in blood flow and glucose metabolism. The highly curved geometry and complicated
folding patterns of the MPFC make it an ideal region to process using cortical
flat mapping. Focusing cortical flat mapping efforts on smaller regions of
cortex, such as the medial prefrontal cortex (MPFC), will reduce the large
distortions that result from flattening a cortical hemisphere.
were young adult female twins who are participants in a larger epidemiological
twin imaging study investigating major depression. We performed a number
of automated processing steps that form the processing pipeline. Here we
report the results of this processing pipeline as applied to the left and
right MPFC for three twin pairs.
After data acquisition, a subvolume
of the MPFC was extracted for each subject to which all subsequent processing
methods were performed. We applied a Bayesian segmentation algorithm [1,2]
to each of these subvolumes so that the grey matter/white matter cortical
surfaces could be reconstructed and subsequently extracted. The surface topology
for each surface was corrected as required and we then applied the Circle
Packing quasi-conformal flat mapping algorithm [3,4]. The resulting cortical
flat maps were then used to track sulci and gyri and identify anatomical
boundaries on the MPFC.
Results and Conclusions
|Fig. 1: Top row is left/right MPFC cortical surfaces for twin pair 1A and
1B - MPFC-1A-L, MPFC-1A-R, MPFC-1B-L, MPFC-1B-R; bottom row is
corresponding cortical flat maps of cortical surfaces.|
1 illustrates left and right MPFC cortical surfaces for one twin pair and
the corresponding quasi-conformal flat maps. Surfaces are colored according
mean curvature. Focusing on smaller regions of cortex enable us to use cortical
flat mapping to identify and demarcate specific regions of interest (ROIs)
in the medial prefrontal cortex (MPFC) while reducing the large distortions
that result from flattening a cortical hemisphere. Cortical flat maps are
also permitting us use curvature and geodesics to track sulci and gyri with
greater ease and reproducibility. The highly curved geometry and complicated
folding patterns of the MPFC make morphometric analysis and visualization
difficult, making cortical flat mapping an ideal choice for preliminary investigations
of this region.
 Joshi, M. et al. 1999. NeuroImage 9:461-476.
 Miller, M.I. et al. 2002. NeuroImage 12:i676-687.
 Collins, C.R. and K. Stephenson, K. To appear. Computational Geometry: Theory and Application.
 Hurdal, M.K. et al. 1999. Lecture Notes in Computer Science 1679:279-286.
work is supported in part by NSF grants DMS-0101329, NPACI; NIH grants MH57180,
R01 MH62626-01 and P41-RR15241 and FSU grant FYAP-2002.
NeuroImage, Volume 19, Number 2, Supplement 1, Page S44, CD-Rom Abstract 856, 2003