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Reproducibility of diffusion tensor imaging in normal subjects: an evaluation of different gradient sampling schemes
Xin Liu1, Yong Yang, Jubao Sun
1Key Laboratory of Biomedical Information Engineering of Education Ministry, Institute of Biomedical Engineering, Xi'an Jiaotong University, No. 28, Xianning West Road, Xi'an, Shaanxi, 710049, People's Republic of China.
Neuroradiology
|March 11, 2014
Summary
Diffusion tensor imaging (DTI) measurements show high reproducibility. Increasing diffusion-encoding directions and using tensor-based registration improve accuracy and consistency for clinical applications.
Area of Science:
- Neuroimaging
- Medical Physics
- Biomedical Engineering
Background:
- Diffusion tensor imaging (DTI) is crucial for assessing white matter integrity in aging and neurological conditions.
- Evaluating DTI reproducibility across different protocols and analyses is vital for clinical study design.
Purpose of the Study:
- To assess the reproducibility of DTI measurements in healthy subjects.
- To compare inter- and intrasession test-retest reliability.
- To investigate the impact of diffusion-encoding directions and registration algorithms on DTI reproducibility.
Main Methods:
- Intraclass correlation coefficient (ICC) and coefficient of variation (CV) were used to quantify DTI reproducibility in regions-of-interest.
- Test-retest reproducibility was evaluated across different sessions.
- The influence of the number of diffusion-encoding directions (NDED) and registration algorithms was analyzed.
Main Results:
- DTI measurements demonstrated high reproducibility (ICC ≥ 0.70, within-subject CV ≤ 10.00%).
- Increasing NDED enhanced DTI accuracy and reproducibility.
- Tensor-based deformable registration provided the most reproducible results.
Conclusions:
- DTI acquisition protocols and post-processing methods significantly affect measurement accuracy and reproducibility.
- Careful consideration of these factors is essential for reliable clinical DTI applications.
