Objective: The multicenter prospective cohort study (Japan Cooperative SPECT Study on Assessment of Mild Impairment of Cognitive Function: J-COSMIC) aimed to examine the value of (123)I-N-isopropyl-4-iodoamphetamine cerebral blood flow (IMP-CBF) SPECT in regards to early diagnosis of Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI).
Methods: Three hundred and nineteen patients with amnestic MCI at 41 participating institutions each underwent clinical and neuropsychological examinations and (123)I-IMP-CBF SPECT at baseline. Subjects were followed up periodically for 3 years, and progression to dementia was evaluated. SPECT images were classified as AD/DLB (dementia with Lewy bodies) pattern and non-AD/DLB pattern by central image interpretation and automated region of interest (ROI) analysis, respectively. Logistic regression analyses were used to assess whether baseline (123)I-IMP-CBF SPECT was predictive of longitudinal clinical outcome.
Results: Ninety-nine of 216 amnestic MCI patients (excluding 3 cases with epilepsy (n = 2) or hydrocephalus (n = 1) and 100 cases with incomplete follow-up) converted to AD within the observation period. Central image interpretation and automated ROI analysis predicted conversion to AD with 56 and 58 % overall diagnostic accuracy (sensitivity, 76 and 81 %; specificity, 39 and 37 %), respectively. Multivariate logistic regression analysis identified SPECT as a predictor, which distinguished AD converters from non-converters. The odds ratio for a positive SPECT to predict conversion to AD with automated ROI analysis was 2.5 and combining SPECT data with gender and mini-mental state examination (MMSE) further improved classification (joint odds ratio 20.08).
Conclusions: (123)I-IMP-CBF SPECT with both automated ROI analysis and central image interpretation was sensitive but relatively nonspecific for prediction of clinical outcome during the 3-year follow-up in individual amnestic MCI patients. A combination of statistically significant predictors, both SPECT with automated ROI analysis and neuropsychological evaluation, may increase predictive utility.