A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection.
A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection.
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DOI：
10.3389/fnins.2017.00669
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发表时间：
2017
影响因子：
4.3
通讯作者：
Vannucci M
中科院分区：
文献类型：
--
作者：
Chiang S;Guindani M;Yeh HJ;Dewar S;Haneef Z;Stern JM;Vannucci M
我们开发了一个综合贝叶斯预测模型框架，该框架根据氟脱氧葡萄糖正电子发射断层扫描（PET）成像生物标志物的选择来识别个体病理性大脑状态，并评估这些状态与临床结果的关联。我们考虑了一项针对随后接受前颞叶切除术的颞叶癫痫（TLE）患者的研究数据。我们的建模框架将 PET 中观察到的区域葡萄糖代谢概况视为潜在个体病理状态的表型表现，假设该状态在人群中存在差异。我们采用的建模策略允许识别以与感兴趣的临床结果差异相关的潜在病理为特征的患者亚组。它还可以识别表征受试者病理状态的成像生物标志物。在数据应用中，我们确定了前颞叶切除术后癫痫复发高风险的 TLE 患者亚组，以及一组可用于区分潜在亚组的区分性大脑区域。我们表明，所提出的方法在预测术后癫痫复发方面具有较高的交叉验证准确性。
We develop an integrative Bayesian predictive modeling framework that identifies individual pathological brain states based on the selection of fluoro-deoxyglucose positron emission tomography (PET) imaging biomarkers and evaluates the association of those states with a clinical outcome. We consider data from a study on temporal lobe epilepsy (TLE) patients who subsequently underwent anterior temporal lobe resection. Our modeling framework looks at the observed profiles of regional glucose metabolism in PET as the phenotypic manifestation of a latent individual pathologic state, which is assumed to vary across the population. The modeling strategy we adopt allows the identification of patient subgroups characterized by latent pathologies differentially associated to the clinical outcome of interest. It also identifies imaging biomarkers characterizing the pathological states of the subjects. In the data application, we identify a subgroup of TLE patients at high risk for post-surgical seizure recurrence after anterior temporal lobe resection, together with a set of discriminatory brain regions that can be used to distinguish the latent subgroups. We show that the proposed method achieves high cross-validated accuracy in predicting post-surgical seizure recurrence.
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图理论指标在功能连通性分析中的时间依赖性。
影响因子：
5.7
作者：
Chiang S;Cassese A;Guindani M;Vannucci M;Yeh HJ;Haneef Z;Stern JM
通讯作者：
Stern JM
影响因子：
2.7
作者：
Franaszczuk, PJ;Bergey, GK
通讯作者：
Bergey, GK
影响因子：
2.7
作者：
Chiang, Sharon;Haneef, Zulfi;Engel, Jerome
通讯作者：
Engel, Jerome
影响因子：
5.7
作者：
Bonilha, L;Rorden, C;Li, LM
通讯作者：
Li, LM
DOI：
10.1016/j.clinph.2014.04.004
发表时间：
2014-07
期刊：
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
影响因子：
--
作者：
Chiang S;Haneef Z
通讯作者：
Haneef Z