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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

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Published on: July 28, 2013

Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study.

Daniel S Tylee¹, Zora Kikinis², Thomas P Quinn³

¹Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA; Department of Psychiatry and Behavioral Sciences; SUNY Upstate Medical University, Syracuse, NY, USA.

Neuroimage. Clinical

|August 2, 2017

Summary

Researchers identified new white matter abnormalities in chromosome 22q11.2 deletion syndrome (22q11.2DS) using advanced imaging analysis. These findings in the middle longitudinal fascicle and extreme capsule may explain overlooked neurodevelopmental and psychiatric symptoms.

Keywords:

(-fp), fronto-parietal aspect (-to), temporo-occipital aspect (-tp), temporo-parietal aspect (22q11.2DS), 22q11.2 deletion syndrome (AD), axial diffusivity (DTI), diffusion tensor imaging (DWI), diffusion weighted image (EmC), extreme capsule (FA), fractional anisotropy (FOV), field of view (GDS), Gordon Diagnostic Systems (ILF), inferior longitudinal fasciculus (MdLF), middle longitudinal fascicle (RD), radial diffusivity (ROI), region of interest (SIPS), Structured Interview for Prodromal Syndromes (SRS), Social Responsiveness Scale (STG), superior temporal gyrus (SVM), support vector machine (UKF), Unscented Kalman Filter (WAIS-III), Wechsler Adult Intelligence Scale – 3rd edition (WMQL), white matter query language (dTP), dorsal temporal pole 22q11.2 deletion syndrome Callosal asymmetry Diffusion tensor imaging Extreme capsule Inferior longitudinal fasciculus Machine-learning Middle longitudinal fascicle Support vector machine Velocardiofacial syndrome White matter query language

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Area of Science:

Neuroimaging
Genetics
Neurodevelopmental Disorders

Background:

Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic disorder impacting brain development and increasing psychiatric risk.
Previous studies suggest white matter abnormalities in 22q11.2DS, but specific tracts affected remain incompletely understood.

Purpose of the Study:

To identify novel white matter microstructural abnormalities in 22q11.2DS using a discovery-based approach.
To correlate imaging findings with clinical symptoms in individuals with 22q11.2DS.

Main Methods:

Utilized white matter query language to parcellate brain white matter into 34 bilateral cortical connection tracts.
Applied support vector machine learning to diffusion imaging data to identify features distinguishing 22q11.2DS from comparison subjects.
Analyzed diffusion imaging characteristics of white matter tracts.

Main Results:

Confirmed previously identified abnormalities in the inferior longitudinal fasciculus (ILF) in 22q11.2DS.
Discovered novel 22q11.2DS-related anomalies in the middle longitudinal fascicle and extreme capsule.
Found significant associations between ILF metrics and positive prodromal psychosis symptoms in 22q11.2DS participants.

Conclusions:

The study identified novel white matter abnormalities in 22q11.2DS, expanding understanding beyond previously known affected tracts.
These findings highlight the potential of advanced neuroimaging techniques for uncovering subtle neuroanatomical differences in genetic syndromes.
The association between ILF abnormalities and psychosis symptoms warrants further investigation into the neurobiological underpinnings of psychiatric manifestations in 22q11.2DS.