Alzheimer's disease (AD) is one of the most common neurological disorders affecting older adults, with approximately 7.2 million cases only in the United States. This number is projected to increase to 13.8 million in the United States by 2060, leading to increased expenditures for healthcare, long-term care and hospice services. Consequently, great emphasis is placed on prevention and the development of early diagnosis techniques, which can lead to timely treatment and the prevention of the consequences of full-blown disease. In this review, we analyze the potential diagnostic value of biomarkers derived from a multimodal approach based on magnetic resonance spectroscopy, diffusion tensor imaging, and magnetic resonance imaging, capable of detecting metabolic, microstructural, and anatomical changes, respectively, that precede the cognitive and behavioral changes observed in AD by years. The primary aim is to evaluate whether the combined and complementary use of these methods can identify early biomarkers useful for recognizing AD in its early stages, predicting progression from MCI to AD, supporting patient stratification, and monitoring cognitive decline or response to treatment. We identified regions more susceptible to metabolic alterations (PCC and hippocampus) and trajectories of structural brain alterations (atrophy or diffusivity abnormalities). The assessment of such imaging biomarkers may serve as the foundation for future prospective studies aimed at developing differential diagnostic methods, a crucial goal within the broader context of dementias, by adopting standardized multimodal MRI protocols. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 1.
Zecca et al. (Thu,) studied this question.
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