SU92. Implicit Socioemotional Modulation of Working Memory Brain Activity in Schizophrenia (original) (raw)

2017, Schizophrenia Bulletin

investigated differences in volumetry between manual delineation and automated segmentations derived by FreeSurfer, FSL, and MAGeT in a sample of first-episode psychosis (FEP) patients and controls. Methods: The basal ganglia and thalamus of 30 subjects (15 FEP, 15 controls) were manually defined and compared to automated methods by extracting: (1) percent volume differences between manual volumes and those derived by MAGeT/FreeSurfer/FSL, (2) between-method correlations, and (3) Bland-Altman plots to illustrate potential biases. Volume and shape differences of the basal ganglia and thalamus were also examined in a larger sample of 135 FEP patients and 88 controls across automated techniques. Results: All automated methods overestimated volumes compared to manual segmentations, with the least pronounced differences produced with MAGeT. The least between-method variability was noted for the striatum, whereas marked differences between manual labels and MAGeT compared to FreeSurfer and FSL emerged for the pallidum and thalamus. Correlations between manual segmentation and automated methods were strongest for MAGeT (range: 0.51-0.92; P < .01, corrected), whereas FreeSurfer and FSL showed moderate to strong Pearson correlations (range: 0.44-0.86; P < .05, corrected), with the exception of FreeSurfer pallidal (r = 0.31, P = .10) and FSL thalamic segmentations (r = 0.37, P = .051). Bland-Altman plots highlighted a tendency for greater volumetric differences between manual labels and automated methods at the lower end of the distribution (ie, smaller structures), which was most prominent for bilateral thalamus across automated pipelines, and left pallidum for FSL. The striatum and pallidum were significantly larger in FEP patients compared to controls bilaterally, irrespective of method. MAGeT was more sensitive to shape-based group differences, and uncovered widespread surface expansions in the striatum and pallidum bilaterally in FEP patients compared to controls, and contractions in bilateral thalamus (FDR corrected). By contrast, FSL only detected differences in the right ventral striatum (FEP > control, corrected) and one cluster of the left thalamus (Control > FEP, corrected). Conclusion: The current study provides a detailed analysis of how manual segmentations of the basal ganglia and thalamus compare against 3 automated segmentation pipelines, namely MAGeT, FreeSurfer, and FSL, in the clinical investigation of changes in subcortical structures in FEP. Results obtained with automated pipelines should be rigorously checked by a trained eye, and consistent quality control procedures are strongly encouraged when using automated segmentation methods.