NDLI: Diffusion Tensor Imaging Reliably Differentiates Patients With Schizophrenia from Healthy Volunteers

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Diffusion Tensor Imaging Reliably Differentiates Patients With Schizophrenia from Healthy Volunteers

Content Provider	PubMed Central
Author	Ardekani, Babak A. Ali, Tabesh Sevy, Serge Robinson, Delbert G. Bilder, Robert M. Szeszko, Philip R.
Abstract	The objective of this research was to determine whether fractional anisotropy (FA) and mean diffusivity (MD) maps derived from diffusion tensor imaging (DTI) of the brain are able to reliably differentiate patients with schizophrenia from healthy volunteers. DTI and high resolution structural magnetic resonance scans were acquired in 50 patients with schizophrenia and 50 age- and sex-matched healthy volunteers. FA and MD maps were estimated from the DTI data and spatially normalized to the Montreal Neurologic Institute standard stereotactic space. Individuals were divided randomly into two groups of 50, a training set and a test set, each comprising 25 patients and 25 healthy volunteers. A pattern classifier was designed using Fisher’s linear discriminant analysis based on the training set of images to categorize individuals in the test set as either patients or healthy volunteers. Using the FA maps the classifier correctly identified 94% of the cases in the test set (96% sensitivity and 92% specificity). The classifier achieved 98% accuracy (96% sensitivity and 100% specificity) when using the MD maps as inputs to distinguish schizophrenia patients from healthy volunteers in the test dataset. Utilizing FA and MD data in combination did not significantly alter the accuracy (96% sensitivity and specificity). Patterns of water self-diffusion in the brain as estimated by DTI can be used in conjunction with automated pattern recognition algorithms to reliably distinguish between patients with schizophrenia and normal control subjects.
Related Links	http://dx.doi.org/10.1002/hbm.20995
Ending Page	9
Page Count	9
Starting Page	1
File Format	PDF
ISSN	10659471
e-ISSN	10970193
Journal	Human brain mapping
Issue Number	1
Volume Number	32
Language	English
Publisher Date	2011-01-01
Access Restriction	Open
Subject Keyword	Anatomy Radiological and Ultrasound Technology Radiology Nuclear Medicine and imaging Neurology Clinical Neurology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Anatomy Neurology Radiology, Nuclear Medicine and Imaging Neurology (clinical) Radiological and Ultrasound Technology

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