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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.
Afiliação
  • Mai Y; Department of Neurology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Cao Z; Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Zhao L; BrainNow Research Institute, Shenzhen, China.
  • Yu Q; Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Xu J; Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Liu W; BrainNow Research Institute, Shenzhen, China.
  • Liu B; Department of Statistics, College of Liberal Art and Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.
  • Tang J; Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Luo Y; BrainNow Research Institute, Shenzhen, China.
  • Liao W; Department of Neurology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Fang W; Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Ruan Y; Department of Rehabilitation, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Lei M; Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Mok VCT; BrainNow Research Institute, Shenzhen, China.
  • Shi L; Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong, SAR, China.
  • Liu J; BrainNow Research Institute, Shenzhen, China.
CNS Neurosci Ther ; 30(4): e14492, 2024 04.
Article em En | MEDLINE | ID: mdl-37864441
ABSTRACT

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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Alzheimer / Disfunção Cognitiva Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Alzheimer / Disfunção Cognitiva Idioma: En Ano de publicação: 2024 Tipo de documento: Article