A multi-scanner study of subcortical brain volume abnormalities in schizophrenia
Introduction
Schizophrenia patients show significant structural brain abnormalities when studied with magnetic resonance imaging (MRI). In vivo study of these abnormalities may aid in our understanding of etiology, pathogenesis, and treatment effects. In this study we examine whether subcortical volume alterations can be observed in prospective multi-center imaging studies despite additional between-scanner variance. We provide effect size estimates for single center (based on meta-analysis of single site effects) versus multi-center (based on mega-analysis correcting for site effects) structural imaging studies in schizophrenia.
Effect size estimates for structural brain alterations in schizophrenia are predominantly based on single center studies (Haijma et al., 2013, Shepherd et al., 2012); but for a simulation of multi-center study effect sizes, see Suckling et al. (2010). The increase in multi-scanner imaging studies, as well as increased efforts towards data sharing, emphasizes the need for effect-size estimates for multi-scanner data acquisitions. The ability to detect statistically significant differences between conditions depends on the effect size, sample size, α-level, and power of the test (Cohen, 1992). In power analyses, the researcher sets the desired α-level and power of the test. The effect size is preferably gleaned from the literature or otherwise estimated, and the sample size that will be required to observe a statistically significant effect is estimated.
The effect size for mean comparisons can be computed as the mean difference between two conditions divided by the pooled standard deviation of the measurements (Cohen, 1992) and thus depends on measurement variability. In single scanner studies, such variability depends on subject variability, between-acquisition scanner variability, and measurement-method reliability. In multi-scanner studies it also depends on between-scanner and other between-site (e.g., sample demographics) variance. Subject variability depends on the relative homogeneity or heterogeneity of the sample(s). Between-acquisition scanner variability depends on the stability over time of the MRI scanner. Brain-measurement reliabilities are estimated from multiple measurements on the same cases and include inter- and intra-scanner reliability (Jovicich et al., 2009), rater reliability (van Erp et al., 2004), and measurement-method reliability (Dewey et al., 2010, Tae et al., 2008, Wonderlick et al., 2009).
Measurements should not only be reliable but also valid. A measure is considered valid when the inferences made from it are appropriate, meaningful, and useful. The calculation of inter-method reliability in which a new method is compared to a GOLD standard, or a method that has been shown to produce valid measurements, provides one way to validate a measurement method. The more similar the measurements are (the higher the intra-class correlation), the more valid the measurements based on the new method. Nevertheless, validation should also be established by confirming that meaningful variability can be observed with the measurements.
Given between-scanner variability, the question remains as to how many additional data sets need to be collected in multi-scanner versus single scanner studies to observe differences between schizophrenia patients and controls? In this study, we compare subcortical volumes between chronic schizophrenia patients and healthy volunteers, and we report the weighted mean effect sizes as well as multi-center-based (n=7) effect sizes for subcortical volumes. Based on the effect sizes reported in meta-analyses (Haijma et al., 2013, Shepherd et al., 2012) (see Table 4), we hypothesized that we would find smaller amygdala, hippocampus, and intracranial volume and larger lateral ventricle and pallidum volumes in patients with schizophrenia compared with healthy volunteers.
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Participants
The participants comprised 186 schizophrenia patients (mean age±S.D.=38.9±11.6, 145 males) and 176 healthy volunteers (mean age±S.D.=37.5±11.2, 126 males) with similar mean age, sex, handedness, and race distributions from seven sites (Table 1; see Supplement 1, Tables 1S, for demographic data by site). Patient inclusion criteria were schizophrenia diagnosis based on the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (First et al., 2002b). All patients were clinically stable
Group effects
There were significant effects of group (schizophrenia patient, healthy volunteer) on hippocampus, pallidum, putamen, lateral ventricle, amygdala and intracranial volumes (Fig. 1A–1F), with hippocampus, amygdala, and intracranial volumes smaller and pallidum, putamen, and lateral ventricle volumes larger in schizophrenia patients compared with controls (Table 3, Fig. 1; see Supplement 1, Tables 3S for statistical results by site). The effects for hippocampus and pallidum also passed the
Discussion
The principal findings of this study are: (1) that we confirm smaller hippocampus, amygdala, and intracranial volumes and larger lateral ventricle, putamen, and pallidum volumes in patients with schizophrenia compared with healthy volunteers based on a prospective seven-site imaging study; (2) that significant site effects are present for hippocampus, putamen, thalamus, and intracranial volumes; and (3) that effect sizes for regional volume differences based on the multisite sample analysis
Acknowledgments
We are thankful to Liv McMillan for overall study coordination, Harry Mangalam, Joseph Farran, and Adam Brenner, for administering the University of California, Irvine High-Performance Computing cluster, and to the research subjects for their participation. This work was supported by the National Center for Research Resources at the National Institutes of Health (Grant nos. NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network) and NIH 1 U24 RR025736-01 (Biomedical Informatics
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