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Combining brain metabolic and neuropsychological measures best predicts conversion to Alzheimer's disease in Mild Cognitive Impairment.

Introduction. Patients with mild cognitive impairment (MCI) are clinically characterized by a cognitive dysfunction that does not significantly disrupt activities of daily living (no dementia). Most patients progress to dementia in the following years. An important avenue for research concerns the prediction of conversion from MCI to AD on the basis of the initial examination. Previous studies have shown that, among neuropsychological tests, cued episodic memory recall as measured by the RI48 test was the best predictor of the outcome of MCI patients (Ivanoiu et al., 2005). Moreover, FDG-PET measures (and more precisely hypometabolism of the right temporoparietal cortex) predicted global cognitive decline in MCI better than did episodic memory, semantic autobiographical memory and word fluency (Chetelat et al., 2005). The current study aimed at evaluating the ability to predict conversion from MCI to AD of two known robust predictors (RI48 performance and brain metabolism) considered either alone or in combination. Methods. 50 MCI patients underwent a FDG-PET at rest and performed the cuedrecall RI48 test, as well as the MMSE. They were followed-up for 36 months. At the end of the follow-up, 28 patients converted to AD and 22 remained stable. AD converters and stable MCI were compared in terms of brain metabolism and cognitive performance. Then, discriminant analyses were used to assess the classification value of age, MMS score, metabolic and memory measures taken individually and of various combinations of measures. Results. Compared with stable MCI, AD converters showed a significant decrease in metabolic activity in bilateral middle temporal cortices, the right inferior parietal cortex and in the left precuneus. AD converters performed more poorly than stable MCI on the RI48 test. Taken individually, the different measures showed equivalent classification accuracy (metabolism of right temporoparietal cortex and left precuneus= 76%, RI48 = 76%). Age and MMS scores were poor predictors (classification accuracy = 62% and 66% respectively). Combining age, metabolic measures and RI48 scores best predicted progression to AD (88%). Conclusion. The results suggest that the optimal strategy for identifying MCI patients who are most likely to progress to AD consists in combining measures of brain metabolism and performance on a highly sensitive memory test.