Multi-Modal Approaches to Alzheimer’s Diagnosis: Combining Cognitive assessments with Biomarkers and Imaging

Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that significantly impairs memory, cognition, and daily functioning. Early and accurate diagnosis is essential for timely intervention and effective disease management. While PET-CT imaging is considered the gold standard for detecting Alzheimer’s pathology, its high cost and limited accessibility necessitates the exploration of alternative diagnostic tools. Cognitive assessments, serum biomarkers, EEG, and MRI each offer unique insights into the disease process. When used in combination, these modalities may enhance diagnostic accuracy and provide a more comprehensive understanding of Alzheimer’s progression. Results: Among 384 participants, PET-CT confirmed Alzheimer’s in 192 cases (50%). Serum biomarkers showed the highest individual sensitivity (77.60%), followed by MRI (69.79%), EEG (66.67%), and cognitive tests (62.50%). All modalities had a specificity of 84.90%. When combined using the addition rule of probability, diagnostic sensitivity increased to 99.15% and specificity to 99.95%. ROC curve analysis showed serum biomarkers and MRI had the highest diagnostic accuracy. The multi-modal approach significantly improved early diagnostic performance compared to single modalities. Conclusion: Individual diagnostic accuracy after serum biomarkers and MRI was the best, whereas when all four modalities were combined, sensitivity (up to 99.15%) and specificity (up to 99.95%) showed a significant increment through the addition rule. The evidence used will provide greater early detection and decision-making in Alzheimer's disease that promotes the employment of a multi-modal diagnostic strategy.