ArticleCNS neuroscience & therapeutics2024
The role of visual rating and automated brain volumetry in early detection and differential diagnosis of Alzheimer's disease.
Article in CNS neuroscience & therapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Subtyping and staging of Alzheimer's disease from routine structural MRI with PHASE-AD.medRxiv : the preprint server for health sciences · 2026Article
- AI-Based Brain Volumetry Without MPRAGE? Evaluation of Synthetic T1-MPRAGE from 2D T2/FLAIR.Diagnostics (Basel, Switzerland) · 2026Article
- MRI approach to the patient with suspected dementia: artificial intelligence techniques and semi-quantitative rating scales compared.Frontiers in radiology · 2026Article
- Machine learning-derived biomarker cutoffs for Alzheimer's disease: Validation and application in preclinical and prodromal phases.iScience · 2025Article
- Evaluation of AccuBrain-based MRI quantitative analysis in diagnosing Alzheimer's disease and assessing behavioral and psychological symptoms of dementia.Aging clinical and experimental research · 2025Article
- The role of visual rating and automated brain volumetry in early detection and differential diagnosis of Alzheimer's disease.CNS neuroscience & therapeutics · 2024Article
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Authors and funding
17 authors.
Funding
Abstract
backgroundMedial temporal lobe atrophy (MTA) is a diagnostic marker for mild cognitive impairment (MCI) and Alzheimer's disease (AD), but the accuracy of quantitative MTA (QMTA) in diagnosing early AD is unclear. This study aimed to investigate the accuracy of QMTA and its related components (inferior lateral ventricle [ILV] and hippocampus) with MTA in the early diagnosis of MCI and AD.
methodsThis study included four groups: normal (NC), MCI stable (MCIs), MCI converted to AD (MCIs), and mild AD (M-AD) groups. Magnetic resonance image analysis software was used to quantify the hippocampus, ILV, and QMTA. MTA was rated by two experienced neurologists. Receiver operating characteristic area under the curve (AUC) analysis was performed to compare their capability in differentiating AD from NC and MCI, and optimal thresholds were determined using the Youden index.
resultsQMTA distinguished M-AD from NC and MCI with higher diagnostic accuracy than MTA, hippocampus, and ILV (AUC
conclusionsQMTA may be a better choice than the MTA scale or the associated quantitative components alone in identifying AD patients and MCI individuals with higher progression risk.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.