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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
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Fractional anisotropy alterations in individuals born preterm: a diffusion tensor imaging meta-analysis
Ke Li1, Zeguang Sun, Yingping Han
1Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, China; School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Developmental Medicine and Child Neurology
|November 1, 2014
Summary
Individuals born preterm show significant white matter abnormalities, particularly in the corpus callosum, persisting into adulthood. Fractional anisotropy changes vary with developmental stage and imaging parameters.
Area of Science:
- Neuroimaging
- Developmental Neuroscience
- Radiology
Background:
- Preterm birth can lead to long-term neurodevelopmental challenges.
- White matter integrity is crucial for cognitive function and is often affected by preterm birth.
Purpose of the Study:
- To meta-analyze cerebral microstructural changes in individuals born preterm using fractional anisotropy (FA) from diffusion tensor imaging (DTI).
- To identify specific brain regions with white matter abnormalities in preterm individuals.
Main Methods:
- Utilized the activation likelihood estimate (ALE) meta-analysis method.
- Analyzed fractional anisotropy (FA) data from diffusion tensor imaging (DTI) studies.
- Quantitatively assessed FA changes in corpus callosum subregions.
Main Results:
- Identified 11 regions with decreased FA and 4 regions with increased FA in preterm individuals.
- Observed the most significant FA decrease in the splenium of the corpus callosum (SMD=-0.75).
- Found substantial FA decreases in the body (SMD=-0.73) and genu (SMD=-0.65) of the corpus callosum.
Conclusions:
- Preterm birth is associated with persistent white matter abnormalities from childhood to young adulthood.
- Mechanisms of FA alterations may differ across developmental stages.
- Study variability is influenced by participant age at scanning and MRI field strength.
