*9th International Conference on Human Brain Mapping, New York City, U.S.A., June 18-22, 2003*

### Dynamic Programming Definition of Boundaries of the Planum Temporale

**
Nayoung Lee**^{}, J. Tilak Ratnanather^{}, Patrick Barta^{}, Monica K. Hurdal^{}, Michael I. Miller^{}

^{}Dept of Biomedical Engineering, Johns Hopkins University,
Baltimore, MD 21218

^{}Center for Imaging Science, Johns Hopkins University, MD 21218

^{}Dept of Psychiatry, Johns Hopkins University School of Medicine, MD 21205

^{}Dept of Mathematics, Florida State University, Tallahassee, FL
32306

**Abstract**

Dynamic programming was used to define boundaries of cortical submanifolds
with focus on the planum temporale (PT) of the superior temporal gyrus
(STG), a region implicated in a variety of neuropsychiatric disorders. To
this end, automated methods were used to generate the cortical surface of
PT from 10 high resolution MRI subvolume encompassing the STG. Bayesian
segmentation was then used to segment the subvolumes into cerebrospinal
fluid, gray matter (GM) and white matter (WM). 3D isocontouring using the
intensity value at which there is equal probability of GM and WM is used
to reconstruct the triangulated graph representing the STG cortical
surface, enabling principal curvature at each point on the graph to be
computed. Dynamic programming was used to delineate the PT cortical
surface by tracking principal curves from the retro-insular end of the
Heschl's Gyrus (HG) to the STG, along the posterior STG up to the start of
the ramus and back to the retro-insular end of the HG. A coordinate system
was then defined on the PT cortical surface. The origin was defined by the
retro-insular end of the HG and the y-axis passes through the point on the
posterior STG where the ramus begins.
Automated labelling of GM in the STG is robust with probability of
misclassification of gray matter voxels between Bayesian and manual
segmentation in the range 0.001-0.12 (n=20). PT reconstruction is also
robust with 90% of the vertices of the reconstructed PT within 1 mm (n=20)
from semi-automated contours. Finally, the inter-rater reliability for the
surface area derived from repeated reconstructions was 0.96 for the left
PT and 0.94 for the right PT, thus demonstrating the robustness of dynamic
programming in defining a coordinate system on the PT. It provides a
method with potential significance in the study of neuropsychiatric
disorders.

Joint work with N. Honeycutt and G. Pearlson. Research supported by NIH
P41-RR15241, MH 43775, MH 60504 and MH 52886 and NSF FRG DMS-0101329.

*NeuroImage, Volume 19, Number 2, Supplement 1, Page S45, CD-Rom Abstract 875, 2003*