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

Yu Jen Chen, Chih Min Liu, Yung Chin Hsu, Yu Chun Lo, Tzung Jeng Hwang, Hai Gwo Hwu, Yi Tin Lin, Wen Yih Isaac Tseng

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)575-587
Number of pages13
JournalHuman Brain Mapping
Volume39
Issue number1
DOIs
Publication statusPublished - Jan 1 2018

Fingerprint

Schizophrenia
Brain
Masks
ROC Curve
Biomarkers
Head
White Matter
Physicians
Control Groups

Keywords

  • diffusion magnetic resonance imaging
  • diffusion spectrum imaging
  • individualized prediction
  • schizophrenia
  • tract-based automatic analysis
  • white matter tracts

ASJC Scopus subject areas

  • Anatomy
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology

Cite this

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

In: Human Brain Mapping, Vol. 39, No. 1, 01.01.2018, p. 575-587.

Research output: Contribution to journalArticle

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. / Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity. In: Human Brain Mapping. 2018 ; Vol. 39, No. 1. pp. 575-587.
@article{30b3386c27fb41a9b37a829a15d82b16,
title = "Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity",
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.",
keywords = "diffusion magnetic resonance imaging, diffusion spectrum imaging, individualized prediction, schizophrenia, tract-based automatic analysis, white matter tracts",
author = "Chen, {Yu Jen} and Liu, {Chih Min} and Hsu, {Yung Chin} and Lo, {Yu Chun} and Hwang, {Tzung Jeng} and Hwu, {Hai Gwo} and Lin, {Yi Tin} and Tseng, {Wen Yih Isaac}",
year = "2018",
month = "1",
day = "1",
doi = "10.1002/hbm.23867",
language = "English",
volume = "39",
pages = "575--587",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "John Wiley and Sons Inc.",
number = "1",

}

TY - JOUR

T1 - Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity

AU - Chen, Yu Jen

AU - Liu, Chih Min

AU - Hsu, Yung Chin

AU - Lo, Yu Chun

AU - Hwang, Tzung Jeng

AU - Hwu, Hai Gwo

AU - Lin, Yi Tin

AU - Tseng, Wen Yih Isaac

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

KW - diffusion magnetic resonance imaging

KW - diffusion spectrum imaging

KW - individualized prediction

KW - schizophrenia

KW - tract-based automatic analysis

KW - white matter tracts

UR - http://www.scopus.com/inward/record.url?scp=85037153880&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85037153880&partnerID=8YFLogxK

U2 - 10.1002/hbm.23867

DO - 10.1002/hbm.23867

M3 - Article

VL - 39

SP - 575

EP - 587

JO - Human Brain Mapping

JF - Human Brain Mapping

SN - 1065-9471

IS - 1

ER -