Accelerated Brain Aging in Amnestic Mild Cognitive Impairment: Relationships with Individual Cognitive Decline, Risk Factors for Alzheimer Disease, and Clinical Progression.

PURPOSE: To determine whether a brain age prediction model could quantify individual deviations from a healthy brain-aging trajectory (predicted age difference [PAD]) in patients with amnestic mild cognitive impairment (aMCI) and to determine if PAD was associated with individual cognitive impairment.
MATERIALS AND METHODS: In this retrospective study, a machine learning approach was trained to determine brain age based on T1-weighted MRI scans. Two datasets were used for model training and testing-the Beijing Aging Brain Rejuvenation Initiative (BABRI) (616 healthy controls and 80 patients with aMCI, 2010-2018) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (589 healthy controls and 144 patients with aMCI, 2010-2018). A total of 974 healthy controls were used for model training (490 from BABRI and 484 from ADNI; age range, 49-95 years). The trained model was then tested on both healthy controls (126 from BABRI and 105 from ADNI) and patients with aMCI (80 from BABRI and 144 from ADNI) to estimate PAD (predicted age - actual age). Furthermore, the associations between PAD with cognitive impairment, genetic risk factors and pathologic markers of Alzheimer disease (AD), and clinical progression in patients with aMCI were examined using a partial correlation analysis, a two-way analysis of covariance, and a general linear model, respectively.
RESULTS: Based on the prediction model, patients with aMCI were found to have higher PADs than those of healthy controls (BABRI: 2.65 ± 4.91 [standard deviation] vs 0.18 ± 4.79 [P < .001]; ADNI: 1.68 ± 5.28 vs 0.05 ± 4.41 [P < .001]). Moreover, the PAD was significantly associated with individual cognitive impairment in several cognitive domains in patients with aMCI (P < .05, corrected). When considering different AD-related risk factors, apolipoprotein E ε4 allele carriers were observed to have higher PADs than noncarriers (3.76 ± 4.82 vs 0.10 ± 5.05; P = .017), and patients with amyloid-positive aMCI were observed to have higher PADs than patients with amyloid-negative status (2.40 ± 5.25 vs 0.93 ± 5.20; P = .003). Finally, PAD combined with other markers of AD at baseline for differentiating between progressive and stable aMCI resulted in an area under the curve value of 0.87.
CONCLUSION: The PAD is a sensitive imaging marker related to individual cognitive differences in patients with aMCI.Keywords: MR Imaging, Brain/Brain Stem, Brain Age, Machine Learning, Mild Cognitive Impairment, Structural MRI Supplemental material is available for this article. © RSNA, 2021. 2021 by the Radiological Society of North America, Inc.