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Multicenter Tract-Based Analysis of Microstructural Lesions within the Alzheimer's Disease Spectrum: Association with
Stefan J Teipel1,2, Jan O Kuper-Smith1, Claudia Bartels3,4
1Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.
Abstract:
Diffusion changes as determined by diffusion tensor imaging are potential indicators of microstructural lesions in people with mild cognitive impairment (MCI), prodromal Alzheimer's disease (AD), and AD dementia. Here we extended the scope of analysis toward subjective cognitive complaints as a pre-MCI at risk stage of AD. In a cohort of 271 participants of the prospective DELCODE study, including 93 healthy controls and 98 subjective cognitive decline (SCD), 45 MCI, and 35 AD dementia cases, we found reductions of fiber tract integrity in limbic and association fiber tracts in MCI and AD dementia compared with controls in a tract-based analysis (p < 0.05, family wise error corrected). In contrast, people with SCD showed spatially restricted white matter alterations only for the mode of anisotropy and only at an uncorrected level of significance. DTI parameters yielded a high cross-validated diagnostic accuracy of almost 80% for the clinical diagnosis of MCI and the discrimination of Aβ positive MCI cases from Aβ negative controls. In contrast, DTI parameters reached only random level accuracy for the discrimination between Aβ positive SCD and control cases from Aβ negative controls. These findings suggest that in prodromal stages of AD, such as in Aβ positive MCI, multicenter DTI with prospectively harmonized acquisition parameters yields diagnostic accuracy meeting the criteria for a useful biomarker. In contrast, automated tract-based analysis of DTI parameters is not useful for the identification of preclinical AD, including Aβ positive SCD and control cases.
Insights
Diffusion tensor imaging (DTI) detects microstructural changes in mild cognitive impairment (MCI) and Alzheimer's disease (AD). DTI shows promise as a biomarker for MCI but not for earlier preclinical AD stages like subjective cognitive decline.
Area of Science:
- Neuroimaging
- Neurology
- Biomarker Discovery
Background:
- Diffusion tensor imaging (DTI) detects microstructural lesions in mild cognitive impairment (MCI), prodromal Alzheimer's disease (AD), and AD dementia.
- Subjective cognitive decline (SCD) represents a potential pre-MCI stage of AD.
- Investigating DTI's utility in identifying early AD-related brain changes is crucial.
Purpose of the Study:
- To evaluate DTI's effectiveness in detecting white matter alterations across the Alzheimer's disease spectrum, from subjective cognitive decline to AD dementia.
- To assess the diagnostic accuracy of DTI parameters for identifying MCI and discriminating between Aβ-positive and Aβ-negative individuals.
- To determine if DTI can serve as a reliable biomarker for preclinical AD stages.
Main Methods:
- Analysis of DTI parameters in a cohort of 271 participants (93 controls, 98 SCD, 45 MCI, 35 AD dementia) from the DELCODE study.
- Tract-based spatial statistics were used to compare white matter integrity across diagnostic groups.
- Cross-validated diagnostic accuracy was calculated for DTI parameters in distinguishing clinical groups and Aβ-positive status.
Main Results:
- Reductions in fiber tract integrity were observed in MCI and AD dementia compared to controls.
- Subjective cognitive decline (SCD) participants showed limited white matter alterations, primarily at uncorrected significance levels.
- DTI achieved nearly 80% diagnostic accuracy for MCI and discriminating Aβ-positive MCI, but random accuracy for preclinical AD (Aβ-positive SCD).
Conclusions:
- Multicenter DTI with harmonized acquisition shows potential as a useful biomarker for prodromal AD (Aβ-positive MCI).
- Automated tract-based DTI analysis is not currently effective for identifying preclinical AD, including Aβ-positive SCD.
- Further research is needed to refine DTI applications for early Alzheimer's disease detection.
