An MRI-based parcellation method for the temporal lobe

Citation
Jj. Kim et al., An MRI-based parcellation method for the temporal lobe, NEUROIMAGE, 11(4), 2000, pp. 271-288
Citations number
61
Categorie Soggetti
Neurosciences & Behavoir
Journal title
NEUROIMAGE
ISSN journal
10538119 → ACNP
Volume
11
Issue
4
Year of publication
2000
Pages
271 - 288
Database
ISI
SICI code
1053-8119(200004)11:4<271:AMPMFT>2.0.ZU;2-V
Abstract
The temporal lobe has long been a focus of attention with regard to the und erlying pathology of several major psychiatric illnesses. Previous postmort em and imaging studies describing regional volume reductions or perfusion d efects in temporal subregions have shown inconsistent findings, which are i n part due to differences in the definition of the subregions and the metho dology of measurement. The development of precise reproducible parcellation systems on magnetic resonance images may help improve uniformity of result s in volumetric MR studies and unravel the complex activation patterns seen in functional neuroimaging studies. The present study describes detailed g uidelines for the parcellation of the temporal neocortex. It parcels the en tire temporal neocortex into 16 subregions: temporal pole, heschl's gyrus, planum temporale, planum polare, superior temporal gyrus (rostral and cauda l), middle temporal gyrus (rostral, intermediate, and caudal), inferior tem poral gyrus (rostral, intermediate, and caudal), occipitotemporal gyrus (ro stral and caudal), and parahippocampal gyrus (rostral and caudal). Based up on topographic landmarks of individual sulci, every subregion was consecuti vely traced on a set of serial coronal slices. In spite of the huge variabi lity of sulcal topography, the sulcal landmarks could be identified reliabl y due to the simultaneous display of three orthogonal (transaxial, coronal, and sagittal) planes, triangulated gray matter isosurface, and a 3-D-rende red image. The reliability study showed that the temporal neocortex could b e parceled successfully and reliably; intraclass correlation coefficient fo r each subregion ranged from 0.62 to 0.99. Ultimately, this method will per mit us to detect subtle morphometric impairments or to find abnormal patter ns of functional activation in the temporal subregions that might reflect u nderlying neuropathological processes in psychiatric illnesses such as schi zophrenia. (C) 2000 Academic Press.