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Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification.

Abstract：

:Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI-based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild-AD, and moderate-AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population-based cohort with 48 MCI and 617 normal aging subjects. Each model's ability to detect MCI was quantified using area under the receiver operating characteristic curve (AUC) and compared with an MCI detection model trained and applied to the population-based cohort. The AD-model and mild-AD identified MCI from controls better than chance level (AUC = 0.600, p = 0.025; AUC = 0.619, p = 0.008). In contrast, the moderate-AD-model was not able to separate MCI from normal aging (AUC = 0.567, p = 0.147). The MCI-model was able to separate MCI from controls better than chance (p = 0.014) with mean AUC values comparable with the AD-model (AUC = 0.611, p = 1.0). Within our population-based cohort, classification models detected MCI better than chance. Nevertheless, classification performance rates were moderate and may be insufficient to facilitate robust MRI-based MCI detection on an individual basis. Our data indicate that multiparametric MRI-based classification algorithms, that are effective in clinical cohorts, may not straightforwardly translate to applications in a general population.

journal_name

Hum Brain Mapp

journal_title

Human brain mapping

authors

Bouts MJRJ,van der Grond J,Vernooij MW,Koini M,Schouten TM,de Vos F,Feis RA,Cremers LGM,Lechner A,Schmidt R,de Rooij M,Niessen WJ,Ikram MA,Rombouts SARB

doi

10.1002/hbm.24554

subject

Has Abstract

pub_date

2019-06-15 00:00:00

pages

2711-2722

issue

eissn

1065-9471

issn

1097-0193

journal_volume

pub_type

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Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification.