Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment.
Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment.
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DOI：
10.1016/j.neuroimage.2011.01.050
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发表时间：
2011-05-01
期刊：
影响因子：
5.7
通讯作者：
Simmons, Andrew
中科院分区：
文献类型：
--
作者：
Costafreda, Sergi G.;Dinov, Ivo D.;Tu, Zhuowen;Shi, Yonggang;Liu, Cheng-Yi;Kloszewska, Iwona;Mecocci, Patrizia;Soininen, Hilkka;Tsolaki, Magda;Vellas, Bruno;Wahlund, Lars-Olof;Spenger, Christian;Toga, Arthur W.;Lovestone, Simon;Simmons, Andrew
海马参与导致阿尔茨海默病（AD）的神经病理学通路的发病。轻度认知障碍（MCI）的个体患AD的风险增加。海马体积已被证明可以预测哪些MCI受试者将转化为AD。我们本研究的目标是建立一种完全自动化的预后程序，可扩展到高通量临床和研究应用，用于使用3D海马形态预测MCI转化为AD。我们使用自动分析从结构磁共振扫描中提取和映射海马，以提取3D海马形状形态，然后应用机器学习分类来预测从MCI到AD的转换。我们调查了103名MCI受试者（平均年龄74.1岁）从纵向AddNeuroMed研究预测的准确性。我们的模型正确预测MCI在一年内转化为痴呆症，准确率为80%（灵敏度77%，特异性80%），这一性能与以前依赖于手动测量的预测模型具有竞争力。根据海马形态学对MCI受试者进行分类，发现相对于预测保持稳定的受试者，预测发展为痴呆的受试者在MMSE评分（p < 0.01）和CERAD言语记忆（p < 0.01）方面的认知恶化更快。与转换风险增加相关的萎缩模式表明，在角氨1（CA1）海马亚区的前部出现初始变性。我们的结论是，自动形状分析产生敏感的测量早期神经退行性变，早于痴呆症的发作，从而提供了一个预后的生物标志物MCI转换为AD。
The hippocampus is involved at the onset of the neuropathological pathways leading to Alzheimer’s disease (AD). Individuals with Mild Cognitive Impairment (MCI) are at increased risk of AD. Hippocampal volume has been shown to predict which MCI subjects will convert to AD. Our aim in the present study was to produce a fully automated prognostic procedure, scalable to high throughput clinical and research applications, for the prediction of MCI conversion to AD using 3D hippocampal morphology. We used an automated analysis for the extraction and mapping of the hippocampus from structural magnetic resonance scans to extract 3D hippocampal shape morphology, and we then applied machine learning classification to predict conversion from MCI to AD. We investigated the accuracy of prediction in 103 MCI subjects (mean age 74.1 years) from the longitudinal AddNeuroMed study. Our model correctly predicted MCI conversion to dementia within a year at an accuracy of 80% (sensitivity 77%, specificity 80%), a performance which is competitive with previous predictive models dependent on manual measurements. Categorization of MCI subjects based on hippocampal morphology revealed more rapid cognitive deterioration in MMSE scores (p < 0.01) and CERAD verbal memory (p < 0.01) in those subjects who were predicted to develop dementia relative to those predicted to remain stable. The pattern of atrophy associated with increased risk of conversion demonstrated initial degeneration in the anterior part of the cornus ammonis 1 (CA1) hippocampal subregion. We conclude that automated shape analysis generates sensitive measurements of early neurodegeneration which predates the onset of dementia and thus provides a prognostic biomarker for conversion of MCI to AD.
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影响因子：
10.6
作者：
Fu, Cynthia H. Y.;Mourao-Miranda, Janaina;Brammer, Michael J.
通讯作者：
Brammer, Michael J.
影响因子：
38.1
作者：
Frisoni, Giovanni B.;Fox, Nick C.;Jack, Clifford R., Jr.;Scheltens, Philip;Thompson, Paul M.
通讯作者：
Thompson, Paul M.
影响因子：
4.2
作者：
Dickerson, BC;Goncharova, I;deToledo-Morrell, L
通讯作者：
deToledo-Morrell, L
影响因子：
9.9
作者：
Jack, CR;Petersen, RC;Kokmen, E
通讯作者：
Kokmen, E
影响因子：
4
作者：
Ferrarini, Luca;Frisoni, Giovanni B.;Milles, Julien
通讯作者：
Milles, Julien