Faculty Bibliography

Evidence suggests that some structural brain abnormalities in schizophrenia are neurodevelopmental in origin. There is also growing evidence to suggest that shape deformations in brain structure may reflect abnormalities in neurodevelopment. While many magnetic resonance (MR) imaging studies have investigated brain area and volume measures in schizophrenia, fewer have focused on shape deformations. In this MR study we used a 3D shape representation technique, based on spherical harmonic functions, to analyze left and right amygdala-hippocampus shapes in each of 15 patients with schizophrenia and 15 healthy controls matched for age, gender, handedness and parental socioeconomic status. Left/right asymmetry was also measured for both shape and volume differences. Additionally, shape and volume measurements were combined in a composite analysis. There were no differences between groups in overall volume or shape. Left/right amygdala-hippocampal asymmetry, however, was significantly larger in patients than controls for both relative volume and shape. The local brain regions responsible for the left/right asymmetry differences in patients with schizophrenia were in the tail of the hippocampus (including both the inferior aspect adjacent to parahippocampal gyrus and the superior aspect adjacent to the lateral geniculate nucleus and more anteriorly to the cerebral peduncles) and in portions of the amygdala body (including the anterior-superior aspect adjacent to the basal nucleus). Also, in patients, increased volumetric asymmetry tended to be correlated with increased left/right shape asymmetry. Furthermore, a combined analysis of volume and shape asymmetry resulted in improved differentiation between groups. Classification function analyses correctly classified 70% of cases using volume, 73.3% using shape, and 87% using combined volume and shape measures. These findings suggest that shape provides important new information toward characterizing the pathophysiology of schizophrenia, and that combining volume and shape measures provides improved group discrimination in studies investigating brain abnormalities in schizophrenia. An evaluation of shape deformations also suggests local abnormalities in the amygdala-hippocampal complex in schizophrenia.

In this work, we present a unique set of 3D MRI brain data that is appropriate for testing the intra and inter-site variability of image analysis met-hods. A single subject was scanned two times within a 24 hour time window each at five different MR sites over a period of six weeks using GE and Phillips 1.5 T scanners. The imaging protocol included T1 weighted, Proton Density and T2 weighted images. We applied three quantitative image analysis methods and analyzed their results via the coefficients of variability (COV) and the intra correlation coefficient. The tested methods include two multi-channel tissue segmentation techniques based on an anatomically guided manual seeding and an atlas-based seeding. The third tested method was a single-channel semi-automatic segmentation of the hippocampus. The results show that the outcome of image analysis methods varies significantly for images from different sites and scanners. With the exception of total brain volume, which shows consistent low variability across all images, the COV's were clearly larger between sites than within sites. Also, the COV's between sits with different scanner types are slightly larger than between sites with the same scanner type. The presented existence of a significant inter-site variability requires adaptations in image methods to produce repeatable measurements. This is especially of importance in multi-site clinical research.