Probabilistic landscape of seizure semiology localizing values.
Probabilistic landscape of seizure semiology localizing values.
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DOI：
10.1093/braincomms/fcac130
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发表时间：
2022
影响因子：
4.8
通讯作者：
Duncan, John S.
中科院分区：
文献类型：
--
作者：
Alim-Marvasti, Ali;Romagnoli, Gloria;Dahele, Karan;Modarres, Hadi;Perez-Garcia, Fernando;Sparks, Rachel;Ourselin, Sebastien;Clarkson, Matthew J.;Chowdhury, Fahmida;Diehl, Beate;Duncan, John S.
符号学描述了癫痫发作期间症状和体征的演变，有助于评估局灶性耐药癫痫患者的根治性切除。符号学的复杂性各不相同，从初级皮层引起的初级感觉运动发作，到分布式大脑网络出现的复杂行为和自动化。由专家癫痫专家解释的详细的符号学可能指向癫痫发作的可能位置，但这一过程是主观的。还没有研究以数据驱动的方式捕获符号学定位值的变化，以允许对所涉及的网络和节点进行客观和概率确定。我们根据系统综述和荟萃分析指南的首选报告项目，从癫痫文献中整理了一个开放的数据集，将符号学与分层的大脑定位联系起来。总共从4,643名患者的309篇文章中收集了11个 230数据点，使用基本事实(术后癫痫发作自由、成像和神经生理学的一致性、和/或侵入性脑电)和区分来自预定义皮质区域的符号学和负责产生特定符号学的神经解剖学定位的描述来标记。这使得我们能够通过过滤根据患者癫痫发作灶的先验知识预先选择患者的研究来减轻颞叶发表的偏见。使用这个数据集，我们将符号定位值的概率景观描述为七个主要大脑区域的森林地块：颞叶、额叶、扣带、顶叶、枕叶、脑岛和下丘脑，以及五个时间亚区。我们评估了任何一种符号学的内在价值，而不是所有其他发作表现。例如，如果不考虑有利于颞叶癫痫的出版物偏向，上腹部光环与颞叶有关的概率为83%。先前皮质定位分布的无偏结果将颞叶癫痫的患病率从66%修正为44%。因此，有关上腹部光环存在的知识更新了对颞叶的定位，其优势比(OR)为2.4[CI95%(1.9，2.9)；具体地说，近侧颞叶结构的OR：2.8(2.3，2.9)]，证明了上腹部光环的价值。作为进一步的例子，尽管头部定位被认为牵涉到额叶，但与先前皮质定位的分布相比，它并没有增加定位价值[OR：0.9(0.7，1.2)]。对象化12个最常见的符号学的本地化值提供了对大脑功能障碍的补充观点，这与病变缺陷映射的观点是互补的，因为不是将大脑区域与表型缺陷联系起来，而是将符号学表型与大脑来源联系起来。这项工作使癫痫的传播与发作表现相结合，以及用于定位癫痫表型的临床支持算法成为可能。Alim-Marasti等人。精选的Semio2Brain，最大的数据驱动和开放的数据集，来自对癫痫文献的系统回顾，将符号学与大脑区域联系起来。在309篇文章中，从4,643名患者中收集了大约11个 数据点。给出了癫痫符号学的绝对概率脑定位和相对概率脑定位。
Semiology describes the evolution of symptoms and signs during epileptic seizures and contributes to the evaluation of individuals with focal drug-resistant epilepsy for curative resection. Semiology varies in complexity from elementary sensorimotor seizures arising from primary cortex to complex behaviours and automatisms emerging from distributed cerebral networks. Detailed semiology interpreted by expert epileptologists may point towards the likely site of seizure onset, but this process is subjective. No study has captured the variances in semiological localizing values in a data-driven manner to allow objective and probabilistic determinations of implicated networks and nodes. We curated an open data set from the epilepsy literature, in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, linking semiology to hierarchical brain localizations. A total of 11 230 data points were collected from 4643 patients across 309 articles, labelled using ground truths (postoperative seizure-freedom, concordance of imaging and neurophysiology, and/or invasive EEG) and a designation method that distinguished between semiologies arising from a predefined cortical region and descriptions of neuroanatomical localizations responsible for generating a particular semiology. This allowed us to mitigate temporal lobe publication bias by filtering studies that preselected patients based on prior knowledge of their seizure foci. Using this data set, we describe the probabilistic landscape of semiological localizing values as forest plots at the resolution of seven major brain regions: temporal, frontal, cingulate, parietal, occipital, insula, and hypothalamus, and five temporal subregions. We evaluated the intrinsic value of any one semiology over all other ictal manifestations. For example, epigastric auras implicated the temporal lobe with 83% probability when not accounting for the publication bias that favoured temporal lobe epilepsies. Unbiased results for a prior distribution of cortical localizations revised the prevalence of temporal lobe epilepsies from 66% to 44%. Therefore, knowledge about the presence of epigastric auras updates localization to the temporal lobe with an odds ratio (OR) of 2.4 [CI95% (1.9, 2.9); and specifically, mesial temporal structures OR: 2.8 (2.3, 2.9)], attesting the value of epigastric auras. As a further example, although head version is thought to implicate the frontal lobes, it did not add localizing value compared with the prior distribution of cortical localizations [OR: 0.9 (0.7, 1.2)]. Objectification of the localizing values of the 12 most common semiologies provides a complementary view of brain dysfunction to that of lesion-deficit mappings, as instead of linking brain regions to phenotypic-deficits, semiological phenotypes are linked back to brain sources. This work enables coupling of seizure propagation with ictal manifestations, and clinical support algorithms for localizing seizure phenotypes. Alim-Marvasti et al. curated Semio2Brain, the largest data-driven and open data set from a systematic review of the epilepsy literature, linking semiology to brain regions. About 11 230 data points were collected from 4643 patients across 309 articles. The absolute and relative probabilistic cerebral localizing values of seizure semiology are presented.
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影响因子：
5.7
作者：
Chen, Rong;Herskovits, Edward H.
通讯作者：
Herskovits, Edward H.
影响因子：
5.6
作者：
Baykan, Betul;Altindag, Ebru;Noachtar, Soheyl
通讯作者：
Noachtar, Soheyl
影响因子：
5.6
作者：
Bleasel, A;Kotagal, P;Rybicki, L
通讯作者：
Rybicki, L
DOI：
10.1155/2012/751510
发表时间：
2012
期刊：
Epilepsy research and treatment
影响因子：
--
作者：
Blair RD
通讯作者：
Blair RD
影响因子：
2.3
作者：
Franca, Sara;Gupta, Deepak K.;Lhatoo, Samden D.
通讯作者：
Lhatoo, Samden D.