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.

Subjects 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.

Fig. 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.

[1] Joshi, M. et al. 1999. NeuroImage 9:461-476.
[2] Miller, M.I. et al. 2002. NeuroImage 12:i676-687.
[3] Collins, C.R. and K. Stephenson, K. To appear. Computational Geometry: Theory and Application.
[4] Hurdal, M.K. et al. 1999. Lecture Notes in Computer Science 1679:279-286.

This 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