Identification and Classification of Alzheimer's Disease Patients Using Novel Fractional Motion Model.
Identification and Classification of Alzheimer's Disease Patients Using Novel Fractional Motion Model.
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DOI：
10.3389/fnins.2020.00767
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发表时间：
2020
影响因子：
4.3
通讯作者：
Ma G
中科院分区：
文献类型：
--
作者：
Du L;Xu B;Zhao Z;Han X;Gao W;Shi S;Liu X;Chen Y;Wang Y;Sun S;Zhang L;Gao J;Ma G
大多数弥散磁共振成像（dMRI）技术使用单指数模型来描述水在脑中的扩散过程。然而，观察到的dMRI信号衰减曲线偏离单指数形式。为了解决这个问题，分数运动（FM）模型已经发展，这被认为是一个更合适的模型来描述复杂的扩散过程中的脑组织。FM模型在阿尔茨海默病（AD）患者的识别和分类中的应用尚不清楚。本研究的目的是探讨FM模型用于AD患者与健康对照的鉴别和AD患者分级的潜在可行性。24例AD患者和11例健康对照者被纳入。选择左侧和右侧海马作为感兴趣区域（ROI）。计算表观扩散系数（ADC）值和FM相关参数，包括Noah指数（α）、Hurst指数（H）和记忆参数（μ=H−1/α），并使用双样本t检验比较AD患者和健康对照组以及轻度AD和中度AD患者之间的差异。采用Pearson偏相关分析，比较AD患者FM相关参数α、H、μ和ADC值与简易精神状态检查量表（MMSE）和蒙特利尔认知功能评定量表（莫卡）评定的认知功能的相关性。受试者操作特征分析用于评估差异性能。我们发现FM相关参数α可以用于区分AD患者和健康对照（P < 0.05），具有更高的敏感性和特异性（左侧感兴趣区域，0.917和0.636;右侧感兴趣区域，0.917和0.727），并且分级AD患者（P < 0.05）表现出更高的敏感性和特异性（右侧感兴趣区域，0.917，0.75）。AD患者双侧海马α值与MMSE（P < 0.05）和莫卡（P < 0.05）评分呈正相关，提示双侧海马α值是AD患者疾病严重程度的潜在MRI生物标志物。这种新的扩散模型可能有助于进一步了解AD患者的神经病理变化。
Most diffusion magnetic resonance imaging (dMRI) techniques use the mono-exponential model to describe the diffusion process of water in the brain. However, the observed dMRI signal decay curve deviates from the mono-exponential form. To solve this problem, the fractional motion (FM) model has been developed, which is regarded as a more appropriate model for describing the complex diffusion process in brain tissue. It is still unclear in the identification and classification of Alzheimer’s disease (AD) patients using the FM model. The purpose of this study was to investigate the potential feasibility of FM model for differentiating AD patients from healthy controls and grading patients with AD. Twenty-four patients with AD and 11 healthy controls were included. The left and right hippocampus were selected as regions of interest (ROIs). The apparent diffusion coefficient (ADC) values and FM-related parameters, including the Noah exponent (α), the Hurst exponent (H), and the memory parameter (μ=H−1/α), were calculated and compared between AD patients and healthy controls and between mild AD and moderate AD patients using a two-sample t-test. The correlations between FM-related parameters α, H, μ, and ADC values and the cognitive functions assessed by mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scales were investigated using Pearson partial correlation analysis in patients with AD. The receiver-operating characteristic analysis was used to assess the differential performance. We found that the FM-related parameter α could be used to distinguish AD patients from healthy controls (P < 0.05) with greater sensitivity and specificity (left ROI, 0.917 and 0.636; right ROI, 0.917 and 0.727) and grade AD patients (P < 0.05) showed higher sensitivity and specificity (right ROI, 0.917, 0.75). The α was found to be positively correlated with MMSE (P < 0.05) and MoCA (P < 0.05) scores in patients with AD, indicating that the α values in the bilateral hippocampus were a potential MRI-based biomarker of disease severity in AD patients. This novel diffusion model may be useful for further understanding neuropathologic changes in patients with AD.
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影响因子：
2.9
作者：
Jensen, Jens H.;Helpern, Joseph A.
通讯作者：
Helpern, Joseph A.
影响因子：
19.7
作者：
CHENEVERT, TL;BRUNBERG, JA;PIPE, JG
通讯作者：
PIPE, JG
影响因子：
2.4
作者：
Burnecki, Krzysztof;Weron, Aleksander
通讯作者：
Weron, Aleksander
影响因子：
3.7
作者：
Acosta-Cabronero J;Williams GB;Cardenas-Blanco A;Arnold RJ;Lupson V;Nestor PJ
通讯作者：
Nestor PJ
影响因子：
3.3
作者：
Hall, Matt G.;Barrick, Thomas R.
通讯作者：
Barrick, Thomas R.