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DOI 10.1111/cns.14492

Медицинская библиотека · CNS neuroscience & therapeutics · 2023

The role of visual rating and automated brain volumetry in early detection and differential diagnosis of Alzheimer's disease.

Mai Yingren, Cao Zhiyu, Zhao Lei, Yu Qun, Xu Jiaxin, Liu Wenyan, Liu Bowen, Tang Jingyi, Luo Yishan, Liao Wang, Fang Wenli, Ruan Yuting, Lei Ming, Mok Vincent C T, Shi Lin, Liu Jun, Alzheimer's Disease Neuroimaging Initiative

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Аннотация

BACKGROUND

Medial 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.

METHODS

This 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.

RESULTS

QMTA distinguished M-AD from NC and MCI with higher diagnostic accuracy than MTA, hippocampus, and ILV (AUCNC = 0.976, AUCMCI = 0.836, AUCMCIs = 0.894, AUCMCIc = 0.730). The diagnostic accuracy of QMTA was superior to that of MTA, the hippocampus, and ILV in differentiating MCI from AD. The diagnostic accuracy of QMTA was found to remain the best across age, sex, and pathological subgroups analyzed. The sensitivity (92.45%) and specificity (90.64%) were higher in this study when a cutoff value of 0.635 was chosen for QMTA.

CONCLUSIONS

QMTA 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.

Для цитирования: Mai Yingren, Cao Zhiyu, Zhao Lei, Yu Qun, Xu Jiaxin, Liu Wenyan, Liu Bowen, Tang Jingyi, Luo Yishan, Liao Wang, Fang Wenli, Ruan Yuting, Lei Ming, Mok Vincent C T, Shi Lin, Liu Jun, Alzheimer's Disease Neuroimaging Initiative. The role of visual rating and automated brain volumetry in early detection and differential diagnosis of Alzheimer's disease.. CNS neuroscience & therapeutics. 2023. DOI: 10.1111/cns.14492.

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