Article

Neuroinformatics

, Volume 9, Issue 4, pp 321-333

Neuropsychological Testing and Structural Magnetic Resonance Imaging as Diagnostic Biomarkers Early in the Course of Schizophrenia and Related Psychoses

  • Elissaios KarageorgiouAffiliated withBrain Sciences Center (11B), Veterans Affairs Medical CenterDepartment of Neuroscience, University of Minnesota Medical SchoolDepartment of Neurology, University of Minnesota Medical SchoolCenter for Cognitive Sciences, University of Minnesota Medical School
  • , S. Charles SchulzAffiliated withDepartment of Psychiatry, University of Minnesota Medical SchoolMind Research Network
  • , Randy L. GollubAffiliated withDepartment of Psychiatry, Massachusetts General Hospital and Harvard Medical School
  • , Nancy C. AndreasenAffiliated withDepartment of Psychiatry, University of Iowa Carver College of Medicine
  • , Beng-Choon HoAffiliated withDepartment of Psychiatry, University of Iowa Carver College of Medicine
  • , John LaurielloAffiliated withDepartment of Psychiatry, University of New Mexico
  • , Vince D. CalhounAffiliated withBrain Sciences Center (11B), Veterans Affairs Medical CenterMind Research NetworkDepartment of Electrical and Computer Engineering, University of New Mexico
  • , H. Jeremy BockholtAffiliated withMind Research Network
  • , Scott R. SponheimAffiliated withBrain Sciences Center (11B), Veterans Affairs Medical CenterDepartment of Psychiatry, University of Minnesota Medical SchoolMental Health Patient Service Line, Veterans Affairs Medical CenterDepartment of Psychology, University of Minnesota Medical School
    • , Apostolos P. GeorgopoulosAffiliated withBrain Sciences Center (11B), Veterans Affairs Medical CenterDepartment of Neuroscience, University of Minnesota Medical SchoolDepartment of Neurology, University of Minnesota Medical SchoolCenter for Cognitive Sciences, University of Minnesota Medical SchoolDepartment of Psychiatry, University of Minnesota Medical School Email author 

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Abstract

Making an accurate diagnosis of schizophrenia and related psychoses early in the course of the disease is important for initiating treatment and counseling patients and families. In this study, we developed classification models for early disease diagnosis using structural MRI (sMRI) and neuropsychological (NP) testing. We used sMRI measurements and NP test results from 28 patients with recent-onset schizophrenia and 47 healthy subjects, drawn from the larger sample of the Mind Clinical Imaging Consortium. We developed diagnostic models based on Linear Discriminant Analysis (LDA) following two approaches; namely, (a) stepwise (STP) LDA on the original measurements, and (b) LDA on variables created through Principal Component Analysis (PCA) and selected using the Humphrey-Ilgen parallel analysis. Error estimation of the modeling algorithms was evaluated by leave-one-out external cross-validation. These analyses were performed on sMRI and NP variables separately and in combination. The following classification accuracy was obtained for different variables and modeling algorithms. sMRI only: (a) STP-LDA: 64.3% sensitivity and 76.6% specificity, (b) PCA-LDA: 67.9% sensitivity and 72.3% specificity. NP only: (a) STP-LDA: 71.4% sensitivity and 80.9% specificity, (b) PCA-LDA: 78.5% sensitivity and 91.5% specificity. Combined sMRI-NP: (a) STP-LDA: 64.3% sensitivity and 83.0% specificity, (b) PCA-LDA: 89.3% sensitivity and 93.6% specificity. (i) Maximal diagnostic accuracy was achieved by combining sMRI and NP variables. (ii) NP variables were more informative than sMRI, indicating that cognitive deficits can be detected earlier than volumetric structural abnormalities. (iii) PCA-LDA yielded more accurate classification than STP-LDA. As these sMRI and NP tests are widely available, they can increase accuracy of early intervention strategies and possibly be used in evaluating treatment response.

Keywords

Schizophrenia Schizophreniform Schizoaffective PCA LDA Biomarkers Neuropsychology MRI Cross-validation Diagnosis MCIC