MRI-based Alzheimer’s disease-resemblance atrophy index in the detection of preclinical and prodromal Alzheimer’s disease
| Autor: | Jill Abrigo, Bonnie Y.K. Lam, Yishan Luo, Chi-Lai Ho, Winnie Cw Chu, Adrian Wong, Sirong Chen, Anthea Yee Tung Ng, Simon Ho Man Wong, Alzheimer’s Disease Neuroimaging Initiative, Wanting Liu, Vincent Mok, Ho Ko, Pauline Wing Lam Kwan, Alexander Y.L. Lau, Lin Shi, Hon Wing Ma, Lisa Wing Chi Au, Eric Y.L. Leung, Xiang Fan |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Oncology Aging medicine.medical_specialty Prodromal Symptoms Disease prodromal Alzheimer's disease Hippocampus Cohort Studies Atrophy Alzheimer Disease hemic and lymphatic diseases Internal medicine mental disorders preclinical Alzheimer’s disease medicine Humans Dementia Cognitive Dysfunction Cognitive impairment Aged business.industry Prodromal Stage Cell Biology Middle Aged medicine.disease Magnetic Resonance Imaging amyloid and tau PET Temporal Lobe Hippocampal volume Biomarker (medicine) Csf analysis Female business volumetric segmentation tool Research Paper MRI |
| Zdroj: | Aging (Albany NY) |
| ISSN: | 1945-4589 |
| Popis: | Alzheimer’s Disease-resemblance atrophy index (AD-RAI) is an MRI-based machine learning derived biomarker that was developed to reflect the characteristic brain atrophy associated with AD. Recent study showed that AD-RAI (≥0.5) had the best performance in predicting conversion from mild cognitive impairment (MCI) to dementia and from cognitively unimpaired (CU) to MCI. We aimed to validate the performance of AD-RAI in detecting preclinical and prodromal AD. We recruited 128 subjects (MCI=50, CU=78) from two cohorts: CU-SEEDS and ADNI. Amyloid (A+) and tau (T+) status were confirmed by PET (11C-PIB, 18F-T807) or CSF analysis. We investigated the performance of AD-RAI in detecting preclinical and prodromal AD (i.e. A+T+) among MCI and CU subjects and compared its performance with that of hippocampal measures. AD-RAI achieved the best metrics among all subjects (sensitivity 0.74, specificity 0.91, accuracy 85.94%) and among MCI subjects (sensitivity 0.92, specificity 0.81, accuracy 86.00%) in detecting A+T+ subjects over other measures. Among CU subjects, AD-RAI yielded the best specificity (0.95) and accuracy (85.90%) over other measures, while hippocampal volume achieved a higher sensitivity (0.73) than AD-RAI (0.47) in detecting preclinical AD. These results showed the potential of AD-RAI in the detection of early AD, in particular at the prodromal stage. |
| Databáze: | OpenAIRE |
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