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Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

Authors :
Chen, Yu‐Jen
Liu, Chih‐Min
Hsu, Yung‐Chin
Lo, Yu‐Chun
Hwang, Tzung‐Jeng
Hwu, Hai‐Gwo
Lin, Yi‐Tin
Tseng, Wen‐Yih Isaac
Source :
Human Brain Mapping. Jan2018, Vol. 39 Issue 1, p575-587. 13p.
Publication Year :
2018

Abstract

Background A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity. Methods The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis. Results The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients. Conclusions The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10659471
Volume :
39
Issue :
1
Database :
Academic Search Index
Journal :
Human Brain Mapping
Publication Type :
Academic Journal
Accession number :
126586634
Full Text :
https://doi.org/10.1002/hbm.23867