Multiparametric MRI-based classification algorithms improve classification of dementia over single measure classifications. Yet, how accurate these algorithms are in identifying subjects with mild cognitive impairment (MCI) in a general population is unclear. We evaluated single and multiparametric algorithms that include structural and diffusion tensor MRI in their potential to accurately differentiate MCI from normal aging subjects in a community-dwelling population. While highest classification rates were observed for multiparametric algorithms, overall classification performance was low (AUC: 0.524-0.631). Our results suggest that accurate MRI-based single subject detection of MCI within a population-based setting may be difficult to achieve using MR imaging alone.
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