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  4. Current Clinical Applications of Diffusion-Tensor Imaging in Neurological Disorders

Current Clinical Applications of Diffusion-Tensor Imaging in Neurological Disorders

J Clin Neurol, 2018 · DOI: 10.3988/jcn.2018.14.2.129 · Published: April 1, 2018

NeuroimagingNeurologyMedical Imaging

Simple Explanation

Diffusion-tensor imaging (DTI) is a noninvasive medical imaging tool used to investigate the structure of white matter. The signal contrast in DTI is generated by differences in the Brownian motion of the water molecules in brain tissue. Postprocessed DTI scalars can be used to evaluate changes in the brain tissue caused by disease, disease progression, and treatment responses, which has led to an enormous amount of interest in DTI in clinical research. This review article provides insights into DTI scalars and the biological background of DTI as a relatively new neuroimaging modality.

Study Duration
Not specified
Participants
Not specified
Evidence Level
Review Article

Key Findings

  • 1
    DTI scalars like FA, AD, RD, MD, and MO can be correlated with clinical information to reveal abnormalities associated with neurological diseases.
  • 2
    Advanced DTI postprocessing techniques have yielded novel anatomical and structural pathway information about the brain.
  • 3
    Improvements in DTI acquisition techniques and standardization of postprocessing methods will guarantee the utilization of DTI in clinical research and even as a diagnostic tool.

Research Summary

Diffusion-tensor imaging (DTI) is a noninvasive medical imaging tool used to investigate the structure of white matter. The signal contrast in DTI is generated by differences in the Brownian motion of the water molecules in brain tissue. This review article provides insights into DTI scalars and the biological background of DTI as a relatively new neuroimaging modality. Further, it summarizes the clinical role of DTI in various disease processes Apart from selecting appropriate DTI scalars, sophisticated clinical research also requires suitable DTI postprocessing tools. Advanced robust postprocessing techniques have yielded novel anatomical and structural pathway information about the brain.

Practical Implications

Improved Diagnosis

DTI can potentially serve as a diagnostic tool for various neurological disorders by identifying microstructural changes in the brain.

Treatment Monitoring

DTI can be used to monitor the effectiveness of treatments by evaluating changes in brain tissue caused by disease progression and treatment responses.

Personalized Medicine

DTI findings can be correlated with clinical information to provide insights into individual abnormalities associated with neurological diseases, leading to personalized treatment approaches.

Study Limitations

  • 1
    The semiquantitative nature of DTI data analysis remains a significant limitation.
  • 2
    Measurement protocol and processing of image data need to be standardized.
  • 3
    Technical difficulties of acquiring qualified images due to small and mobile structures limit clinical applications of DTI.

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