Related Experiment Video
Updated: Feb 19, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by
Gyula Gyebnár1, Ádám Szabó1, Enikő Sirály2
1Magnetic Resonance Research Centre, Semmelweis University, Budapest, Hungary.
Abstract:
Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.
Insights
Diffusion tensor imaging (DTI) using diffusion-weighted MRI (DWI) can differentiate subtypes of mild cognitive impairment (MCI). DTI metrics aid in the early detection of Alzheimer Disease (AD) and other dementias.
Area of Science:
- Neuroimaging
- Neurology
- Radiology
Background:
- Mild cognitive impairment (MCI) is a precursor to dementia, with amnestic MCI (aMCI) having a higher conversion rate to Alzheimer Disease (AD).
- Differentiating MCI subtypes is crucial for early diagnosis and intervention.
- Diffusion-weighted MRI (DWI) and diffusion tensor imaging (DTI) offer insights into white matter integrity.
Purpose of the Study:
- To investigate the utility of DTI metrics in distinguishing between aMCI, non-amnestic MCI (naMCI), and healthy controls.
- To explore the relationship between DTI findings and cognitive performance.
- To assess the potential of DTI in improving the diagnostic accuracy of MCI subtypes.
Main Methods:
- Acquisition of high-resolution 3D T1-weighted and DWI images at 3T from patients with aMCI (n=18), naMCI (n=20), and controls (n=27).
- Processing of imaging data using ExploreDTI and SPM software.
- Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) using ANCOVA, with logistic regression for diagnostic discrimination.
Main Results:
- Higher mean diffusivity (MD) in aMCI compared to controls and naMCI, particularly in temporal lobe grey and white matter regions.
- Lower fractional anisotropy (FA) in white matter regions, such as the left Cingulum, in aMCI.
- Significant correlations between DTI metrics and cognitive functions (verbal fluency, memory).
- Combined FA of the crus of fornix and grey matter volumetry improved aMCI discrimination from naMCI.
Conclusions:
- DTI metrics can effectively differentiate between MCI subtypes and healthy individuals.
- DTI analysis provides valuable information for the preclinical detection of AD.
- DTI may aid in the early identification of non-Alzheimer dementias.
