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 Karageorgiou
  • S. Charles Schulz
  • Randy L. Gollub
  • Nancy C. Andreasen
  • Beng-Choon Ho
  • John Lauriello
  • Vince D. Calhoun
  • H. Jeremy Bockholt
  • Scott R. Sponheim
  • Apostolos P. Georgopoulos
Article

DOI: 10.1007/s12021-010-9094-6

Cite this article as:
Karageorgiou, E., Schulz, S.C., Gollub, R.L. et al. Neuroinform (2011) 9: 321. doi:10.1007/s12021-010-9094-6

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

SchizophreniaSchizophreniformSchizoaffectivePCALDABiomarkersNeuropsychologyMRICross-validationDiagnosisMCIC

Copyright information

© Springer Science+Business Media, LLC (outside the USA) 2011

Authors and Affiliations

  • Elissaios Karageorgiou
    • 1
    • 2
    • 3
    • 4
  • S. Charles Schulz
    • 5
    • 6
  • Randy L. Gollub
    • 7
  • Nancy C. Andreasen
    • 8
  • Beng-Choon Ho
    • 8
  • John Lauriello
    • 9
  • Vince D. Calhoun
    • 6
    • 10
  • H. Jeremy Bockholt
    • 6
  • Scott R. Sponheim
    • 1
    • 5
    • 11
    • 12
  • Apostolos P. Georgopoulos
    • 1
    • 2
    • 3
    • 4
    • 5
  1. 1.Brain Sciences Center (11B)Veterans Affairs Medical CenterMinneapolisUSA
  2. 2.Department of NeuroscienceUniversity of Minnesota Medical SchoolMinneapolisUSA
  3. 3.Department of NeurologyUniversity of Minnesota Medical SchoolMinneapolisUSA
  4. 4.Center for Cognitive SciencesUniversity of Minnesota Medical SchoolMinneapolisUSA
  5. 5.Department of PsychiatryUniversity of Minnesota Medical SchoolMinneapolisUSA
  6. 6.Mind Research NetworkAlbuquerqueUSA
  7. 7.Department of PsychiatryMassachusetts General Hospital and Harvard Medical SchoolCharlestownUSA
  8. 8.Department of PsychiatryUniversity of Iowa Carver College of MedicineIowaUSA
  9. 9.Department of PsychiatryUniversity of New MexicoAlbuquerqueUSA
  10. 10.Department of Electrical and Computer EngineeringUniversity of New MexicoAlbuquerqueUSA
  11. 11.Mental Health Patient Service LineVeterans Affairs Medical CenterMinneapolisUSA
  12. 12.Department of PsychologyUniversity of Minnesota Medical SchoolMinneapolisUSA