An MRI study of spatial probability brain map differences between first-episode schizophrenia and normal controls
Introduction
Most structural and functional neuroimaging studies have been based on a stereotaxic coordinate system of Talairach and Tournoux (Talairach and Tournoux, 1988), which has provided an anatomical reference for intersubject or intergroup consistency, and makes it possible to integrate findings across laboratories. For functional neuroimaging studies, anatomical variations are regarded as confounding factors that should be removed. Hence, spatial normalization to a stereotaxic space using several nonlinear warping techniques is a common step for such an analysis. However, such spatial normalization also rejects information concerning the effect of idiosyncratic anatomical morphology on functional activation in each individual. In the study of pathological groups, where functional abnormalities cannot easily be separated from abnormal morphology, a better understanding of functional activation may require comprehensive knowledge of the anatomical variability in the population.
Studies on the spatial distribution of subregions in normal subjects' brains have shown high interindividual variability Amunts et al., 1999, Amunts et al., 2000, Paus et al., 1996. Additionally, interindividual variability in certain anatomical landmarks Hunton et al., 1996, Steinmetz et al., 1989, Van Essen and Drury, 1997 has been reported to be of the order of centimeters even after Talairach transformation, which normalizes global size, position, and orientation. Such variations in specific regions of interests (ROIs) may include differences in shape, location, and orientation, in addition to mean volume.
Probabilistic atlases are thought to provide information about the neuroanatomic complexity and interindividual variability within a specific population in a common stereotaxic coordinate system Mazziotta et al., 1995, Mazziotta et al., 2001a, Mazziotta et al., 2001b, Roland and Zilles, 1994, Toga et al., 2001. Accordingly, many groups have noted the importance of probabilistic atlases and have made probability maps using different modalities and different methodologies. Probability maps for subregions of normal brains have been reported Amunts et al., 1999, Amunts et al., 2000, Kennedy et al., 1998, Leonard et al., 1998, Loftus et al., 1995, Paus et al., 1996, Penhune et al., 1996, Rademacher et al., 2001a, Rademacher et al., 2001b, Rademacher et al., 2002, Thompson et al., 1996a, Tomaiuolo et al., 1999, Varnavas and Grand, 1999, Westbury et al., 1999, White et al., 1997.
Probability maps may also reveal abnormalities in brain morphology specific to neurodevelopmental or neurodegenerative processes in distinct pathological populations (Toga et al., 2001). Thus, the investigation of anatomical distribution and variation according to pathology is one of the major aims for using a probabilistic atlas approach. However, relatively few pathology-specific probability maps have been created Narr et al., 2001, Thompson et al., 1997, Thompson et al., 2001. Instead of using probability maps, pathology-specific variations have been investigated using shape analysis of specific ROIs Csernansky et al., 1998, Shenton et al., 2002, but shape analysis does not provide information on spatial distribution, especially the relative location of ROIs together with neighboring brain regions.
The probabilistic atlas approach provides a new way to examine the pathology of schizophrenia using magnetic resonance imaging (MRI). Most MRI studies investigating structural abnormalities in schizophrenia have been based on a comparison of the difference in volume in manually parcellated brain regions. Here, volumetric methods include the precise definition of ROIs for consistent research among laboratories and normalization of volumes by intracranial volume to remove subject-specific global variations (for an example of this approach in subregions of the temporal lobe, see Kim et al., 2000). However, volumetric methods, which provide group comparison in gross neuroanatomy, tend to oversimplify the pathology-related characteristics and interindividual variations that anatomical experts often detect. Considering that brain development is processed in three-dimensional space, the variability of the developmental process can be explored by the distribution of specific ROIs in such a space in relation with neighboring regions. Therefore, probability maps of schizophrenia can be a useful tool for understanding better disease-specific abnormalities.
In the present study, we created and compared probability maps for first-episode schizophrenic patients and normal controls using ROIs that had previously been manually delineated. ROIs included temporal and parietal lobe subregions, prefrontal and insula (INSL) gray matter, ventricles, and the caudate nucleus (CAUD). Though all of these ROIs may have importance for understanding schizophrenia, we mainly focused on the temporal lobe where primary and secondary association cortices mediate various sensory functions such as auditory and visual processing and where components of the limbic lobe mediate memory and emotion. We subdivided the temporal lobe into the superior temporal gyrus (STG), middle temporal gyrus (MTG), inferior temporal gyrus (ITG), fusiform gyrus (FG), parahippocampal gyrus (PHG), hippocampus (HIPP), and amygdala (AMYG). For subregions of the STG, we also created probability maps of Heschl's gyrus (HG), where the primary auditory cortex is located, and planum temporale (PT), which is thought to be a neurological substrate for language.
Due to the importance of the temporal lobe in sensory and cognitive processing, interindividual anatomical variability has previously been explored for parts of the temporal lobe in psychiatrically well individuals using probability maps. Probability maps of planum temporale and primary auditory cortex, using MRI parcellations (Penhune et al., 1996), and primary auditory cortex, using cytoarchitectonic parcellations (Rademacher et al., 2001b), have been published for normal control subjects. However, little is known of the anatomical and distributional abnormalities in these areas and, to our knowledge, no probability maps have been created based on manually delineated ROIs in first-episode schizophrenia.
The initial goal of this study was to investigate the spatial distribution and spatial variability specific to first-episode schizophrenic patients using probability maps. Because first-episode schizophrenic patients are relatively free of confounds such as the long-term effects of neuroleptic medications and illness chronicity, spatial distribution of ROIs in this group may indicate disease-specific abnormalities more directly than would be the case for a sample of chronic schizophrenic patients.
Additionally, we examined potential problems with spatial normalization, especially in functional neuroimaging studies of this pathological group in comparison with a control group. It has been noted that imperfect spatial normalization, for example, due to topological variability between groups, can cause spurious results such that the significance difference may reflect an anatomic difference rather than a functional group difference Steinmetz and Seitz, 1991, Woods, 1996. Therefore, we believe it is important to understand the spatial extent of anatomical variability of ROIs in schizophrenia compared with normal controls after spatial normalization. For this purpose, we created probability maps using a widely used method of nonlinear spatial normalization and investigated how the extent of anatomical variability can vary according to ROI. We also examined how nonlinear registration differentially affects spatial normalization of ROIs in a pathological group compared to controls.
Section snippets
Subjects and parcellations of region of interests
To create probability maps, we used ROIs from schizophrenic subjects and normal controls that had previously been manually parcellated by our group for different structural MRI studies of first-episode schizophrenia (Hirayasu et al., 1998, Hirayasu et al., 1999, Hirayasu et al., 2000a, Hirayasu et al., 2000b, Hirayasu et al., 2001, Lee et al., 2002; Levitt et al., personal communication).
Patients were tested at their first hospitalization. Patients and control subjects were matched for age
Results
Sixteen ROIs of individual subjects were manually delineated by experts. To illustrate some of the ROIs, both a coronal slice and a three-dimensional rendering of the lateral and medial temporal lobe gyri are displayed in Fig. 1; this includes STG, MTG, ITG, FG, PHG, and HIPP ROI.
Table 1 gives a summary of statistics for each ROI including the number of subjects in each group used for composing probability maps, the mean volume, and the mean center of gravity in Talairach space for each ROI.
Probability maps of first-episode schizophrenia
Many researches have shown individual variability in the anatomy of the normal brain Amunts et al., 1999, Amunts et al., 2000, Kennedy et al., 1998, Leonard et al., 1998, Loftus et al., 1995, Paus et al., 1996, Penhune et al., 1996, Rademacher et al., 2001a, Rademacher et al., 2001b, Rademacher et al., 2002, Thompson et al., 1996a, Tomaiuolo et al., 1999, Varnavas and Grand, 1999, Westbury et al., 1999, White et al., 1997. We examined here for the first time the spatial distribution of brain
Conclusion
In the present study, we addressed statistical probability maps of 16 ROIs in first-episode schizophrenia and in matched normal controls. Probability maps showed different spatial distributions in first-episode schizophrenia compared with normal controls. The distribution patterns are also specific to ROIs, which imply that the focal activations that are found in functional neuroimaging studies have limitations in the direct comparison of a pathological group, such as schizophrenia, with
Acknowledgements
We gratefully acknowledge the support of the Post-doctoral Fellowship Program of Korea Science & Engineering Foundation (KOSEF) (HJP), William F. Milton Fund (JJL), National Alliance for Research on Schizophrenia and Depression (MK), the National Institutes of Health (K02 MH 01110 and R01 MH 50747 to MES, and R01 MH 58704 to DFS, R01 MH 40799 to RWM), the Department of Veterans Affairs Merit Awards (MES, RWM), the MIND Institute (Albuquerque, RWM), and the National Center for Research Resources
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