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Updated: Jul 9, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Diffusion tensor imaging parameters in the presence of optic neuritis in multiple sclerosis
Murat Baykara1, Ayça Simay Ersöz2, Buse Gündoğan1
1Haydarpasa Numune Training and Research Hospital, Hamidiye Faculty of Medicine, Radiology Department, University of Health Sciences, Istanbul, Turkey.
Objective:
This study examined how different diffusion tensor imaging (DTI) acquisition planes affect diffusion tensor indices in multiple sclerosis (MS) patients, stratified by optic neuritis (ON) history.
Materials And Methods:
Thirty-seven relapsing-remitting MS patients were prospectively enrolled: 20 with a history of ON (MSwON) and 17 without (MSwoON). Each participant underwent DTI in both axial and coronal planes using a 1.5 Tesla MRI system. Optic nerve regions of interest were drawn independently for each plane, and 18 DTI-derived parameters were compared between groups using linear mixed-effects models with False Discovery Rate correction.
Results:
No significant group effect was detected for any DTI parameter (p > 0.05), suggesting that diffusion metrics were broadly comparable between MSwON and MSwoON patients. The group × acquisition plane interaction was also non-significant across all parameters. In contrast, acquisition plane exerted a significant main effect on ten parameters following FDR correction - among them Fractional Anisotropy, Apparent Diffusion Coefficient, Mean Diffusivity, and Radial Diffusivity - with axial acquisitions consistently yielding higher diffusivity and anisotropy values than coronal ones.
Conclusion:
Optic nerve DTI parameters did not differ significantly between MSwON and MSwoON patients, a finding compatible with subclinical bilateral nerve involvement in both groups. The marked dependence of multiple DTI metrics on acquisition plane points to the non-negligible role of imaging geometry, EPI-related distortions, and partial volume contamination in small-structure DTI measurements.
Insights
Diffusion tensor imaging (DTI) of the optic nerve in multiple sclerosis (MS) patients showed no differences between those with and without optic neuritis (ON) history. However, DTI metrics varied significantly based on the acquisition plane used.
Area of Science:
- Neuroimaging
- Radiology
- Medical Physics
Background:
- Multiple sclerosis (MS) is a demyelinating disease affecting the central nervous system.
- Optic neuritis (ON) is a common initial symptom of MS, often leading to optic nerve damage.
- Diffusion Tensor Imaging (DTI) is a sensitive MRI technique for evaluating white matter integrity.
Purpose of the Study:
- To investigate the impact of different DTI acquisition planes (axial vs. coronal) on diffusion tensor indices in the optic nerve of MS patients.
- To compare DTI parameters between MS patients with a history of ON (MSwON) and those without (MSwoON).
Main Methods:
- Prospective enrollment of 37 relapsing-remitting MS patients (20 MSwON, 17 MSwoON).
- Acquisition of DTI data in both axial and coronal planes using a 1.5 Tesla MRI scanner.
- Analysis of 18 DTI parameters in optic nerve regions of interest, with comparisons between groups and acquisition planes using linear mixed-effects models and False Discovery Rate (FDR) correction.
Main Results:
- No significant differences in DTI parameters were found between MSwON and MSwoON groups.
- A significant main effect of acquisition plane was observed for ten DTI parameters, including Fractional Anisotropy, Apparent Diffusion Coefficient, Mean Diffusivity, and Radial Diffusivity.
- Axial acquisitions consistently yielded higher diffusivity and anisotropy values compared to coronal acquisitions.
Conclusions:
- Optic nerve DTI parameters do not significantly differ between MS patients with and without ON history, suggesting potential subclinical involvement in both groups.
- DTI metric variability is significantly influenced by the acquisition plane, highlighting the importance of imaging geometry, EPI distortions, and partial volume effects in small-structure DTI analysis.
