Improved Risk Stratification for Progression from Mild Cognitive Impairment to Alzheimer's Disease with a Multi-Analytical Evaluation of Amyloid-β Positron Emission Tomography

Background: Amyloid-beta (A beta) accumulation in brain of patients with suspected Alzheimer's disease (AD) can be assessed by positron emission tomography (PET) in vivo. While visual classification prevails in the clinical routine, semiquantitative PET analyses may enable more reliable evaluation of cases with a visually uncertain, borderline A beta accumulation. Objective: We evaluated different analysis approaches (visual/semiquantitative) to find the most accurate and sensitive interpretation of A beta-PET for predicting risk of progression from mild cognitive impairment (MCI) to AD. Methods: Based on standard uptake value (SUV) ratios of a cortical-composite volume of interest of F-18-AV45-PET from MCI subjects (n= 396, ADNI database), we compared three different reference region (cerebellar grey matter, CBL; brainstem, BST; white matter, WM) normalizations and the visual read by receiver operator characteristics for calculating a hazard ratio (HR) for progression to Alzheimer's disease dementia (ADD). Results: During a mean follow-up time of 45.6 +/- 13.0 months, 28% of the MCI cases (110/396) converted to ADD. Among the tested methods, the WM reference showed best discriminatory power and progression-risk stratification (HRWM of 4.4 [2.6-7.6]), but the combined results of the visual and semiquantitative analysis with all three reference regions showed an even higher discriminatory power. Conclusion: A multi-analytical composite of visual and semiquantitative reference tissue analyses of F-18-AV45-PET gave improved risk stratification for progression from MCI to ADD relative to performance of single read-outs. This optimized approach is of special interest for prospective treatment trials, which demand a high accuracy.