Targeting interictal low-entropy zones during epilepsy surgery predicts successful outcomes in pediatric drug-resistant epilepsy

癫痫手术中靶向发作间期低熵区可预测儿童耐药性癫痫的手术成功结局

Approximately 40% of children undergoing epilepsy surgery have postoperative seizures, underscoring the need for enhanced estimators of the epileptogenic zone (EZ). We hypothesize that visually imperceptible low-entropy activity in the interictal periods, even in the absence of conventional spikes, is a robust signature of the EZ. To test this, we mapped interictal "low-entropy zones" using intracranial electroencephalography (iEEG) in children with drug-resistant epilepsy (DRE) and assessed their value for postsurgical outcome prediction when targeted during surgery, along with their stability over prolonged periods. Surgically targeting low-entropy zones accurately predicts the postoperative seizure outcomes of children with DRE. Mapping low-entropy activity using brief iEEG segments shows consistency with using prolonged data and could enhance surgical planning in pediatric DRE.

大约40%接受癫痫手术的儿童术后仍会发作，这凸显了需要更好地评估致痫区（EZ）。我们假设，发作间期视觉上难以察觉的低熵活动，即使在没有传统棘波的情况下，也是致痫区的一个可靠特征。为了验证这一点，我们利用颅内脑电图（iEEG）对耐药性癫痫（DRE）患儿的发作间期“低熵区”进行了定位，并评估了在手术中针对这些区域时它们对术后预后的预测价值，以及它们在较长时间内的稳定性。手术中针对低熵区能够准确预测耐药性癫痫患儿的术后癫痫发作结局。利用短时间iEEG片段绘制低熵活动图与利用长时间数据绘制的结果一致，并且可以改善儿科耐药性癫痫的手术规划。

REF: Makaram N, Pesce M, Tsuboyama M, et al. Targeting interictal low-entropy zones during epilepsy surgery predicts successful outcomes in pediatric drug-resistant epilepsy. Epilepsia. 2026;67(1):33-48. doi:10.1111/epi.18636 PMID: 40974546

Spectrum of epileptogenicity in different cortical tuber radiological subtypes: A stereoelectroencephalographic study

不同皮质结节影像学亚型的致痫性谱：一项立体脑电图研究

Tuberous sclerosis complex (TSC) causes focal drug-resistant epilepsy. Prediction of which tubers are epileptogenic remains challenging. We used stereoelectroencephalography (SEEG) to investigate epileptogenic zone (EZ) organization in TSC-related epilepsy, focusing on epileptogenicity of different tuber radiological subtypes. Most TSC-related epilepsy represents focal EZ related to tubers, but focal extratuber EZ can also occur (FCD or hippocampus). Radiologically, calcified tubers (type D) and tubers with focal cortical depression and central hypointensity (type E) exhibit the highest epileptogenicity, similar to FCD type II.

结节性硬化症（TSC）可导致局灶性药物难治性癫痫。预测哪些结节具有致痫性仍具有挑战性。我们采用立体定向脑电图（SEEG）来研究TSC相关癫痫的致痫区（EZ）结构，重点关注不同结节放射学亚型的致痫性。大多数TSC相关癫痫表现为与结节相关的局灶性致痫区，但也可出现局灶性结节外致痫区（局灶性皮质发育不良或海马）。在影像学上，钙化结节（D型）和伴有局灶性皮质凹陷及中心低信号的结节（E型）致痫性最高，与II型局灶性皮质发育不良相似。

REF: Wang H, McGonigal A, Zhang B, et al. Spectrum of epileptogenicity in different cortical tuber radiological subtypes: A stereoelectroencephalographic study. Epilepsia. 2026;67(1):49-61. doi:10.1111/epi.18639 PMID: 40956290

Seizure outcomes in persons with autism spectrum disorder undergoing epilepsy surgery: A systematic review and meta-analysis

自闭症谱系障碍患者接受癫痫手术的癫痫发作结局：一项系统评价和荟萃分析

Autism spectrum disorder (ASD) and epilepsy commonly co-occur. Surgical interventions are viable treatment options for individuals with drug-resistant epilepsy. However, past research in patients with ASD and epilepsy has yielded mixed results regarding seizure outcomes following epilepsy surgery. Our study provides the most comprehensive review to date of epilepsy surgery in ASD. Based on past work, there is potential for properly selected patients with ASD and epilepsy to experience a significant reduction in seizure frequency or seizure freedom, as well as improved quality of life, following epilepsy surgery.

自闭症谱系障碍（ASD）和癫痫常同时出现。对于药物难治性癫痫患者，手术干预是可行的治疗选择。然而，以往针对患有ASD和癫痫患者的研究在癫痫手术后的癫痫发作结局方面得出了不同的结果。我们的研究是迄今为止对ASD患者癫痫手术最全面的综述。基于以往的研究，经过适当筛选的患有ASD和癫痫的患者在接受癫痫手术后，有可能显著降低癫痫发作频率或实现无癫痫发作，同时提高生活质量。

REF: Subramaniam VR, Goldstein J, Rafati A, Gorka P, Kwon CS. Seizure outcomes in persons with autism spectrum disorder undergoing epilepsy surgery: A systematic review and meta-analysis. Epilepsia. 2026;67(1):62-84. doi:10.1111/epi.18645 PMID: 41074616

Long-term memory trajectories in seizure-free patients following epilepsy surgery for hippocampal sclerosis

海马硬化癫痫手术后无癫痫发作患者的长期记忆轨迹

This study was undertaken to study long-term memory trajectories over the years in patients with temporal lobe epilepsy and unilateral hippocampal sclerosis (TLE/HS) seizure-free since surgery. Memory preservation or improvement in the first few postoperative years is usually not sustained in the long term, suggesting that disease progression surpasses plasticity over the years.

本研究旨在探讨颞叶癫痫合并单侧海马硬化（TLE/HS）患者自手术后无癫痫发作多年来的长期记忆轨迹。术后最初几年记忆得以保留或改善的情况通常无法长期维持，这表明随着时间推移，疾病进展超过了大脑的可塑性。

REF: Martins WA, Gomes R, Leal-Conceição E, et al. Long-term memory trajectories in seizure-free patients following epilepsy surgery for hippocampal sclerosis. Epilepsia. 2026;67(1):85-95. doi:10.1111/epi.18648 PMID: 41042503

Long-term outcomes of stereotactic radiofrequency ablation in hypothalamic hamartomas: A single-center experience

下丘脑错构瘤立体定向射频消融的长期疗效：单中心经验

Hypothalamic hamartomas (HHs) lead to refractory epilepsy, and minimally invasive surgical approaches are standard of care for affected patients. Stereotactic radiofrequency thermocoagulation (SRT) is one of the treatment methods recognized to achieve seizure freedom. This study reports surgical outcome from a single center reporting an ablation technique using fewer trajectories than previously reported and assesses the effect of coagulated volume on long-term seizure freedom. SRT is a minimally invasive method to successfully treat refractory seizures in patients with HH. Disconnection seems to be more important for successful treatment than volume reduction. Even large HHs can be successfully treated with small coagulation volumes.

下丘脑错构瘤（HHs）可导致难治性癫痫，对于受影响的患者，微创外科手术是标准治疗方案。立体定向射频热凝术（SRT）是公认的可实现无癫痫发作的治疗方法之一。本研究报告了单中心采用比以往报道更少进针路径的消融技术的手术结果，并评估了热凝体积对长期无癫痫发作的影响。SRT是一种成功治疗HH患者难治性癫痫发作的微创方法。对于成功治疗而言，神经离断似乎比体积缩小更为重要。即使是较大的HHs，也可以通过小体积热凝成功治疗。

REF: Reinacher PC, Jacobs J, Shah MJ, et al. Long-term outcomes of stereotactic radiofrequency ablation in hypothalamic hamartomas: A single-center experience. Epilepsia. 2026;67(1):96-108. doi:10.1111/epi.18660 PMID: 41030180

Pharmacokinetics and tolerability of single-dose Staccato® alprazolam in adolescents with epilepsy, and population pharmacokinetic analysis to support dose selection in adolescents

单剂量速释®阿普唑仑在青少年癫痫患者中的药代动力学和耐受性，以及支持青少年剂量选择的群体药代动力学分析

Staccato® alprazolam is a hand-held inhalation device that provides rapid systemic delivery of alprazolam through the intrapulmonary route. This trial explored the pharmacokinetics and tolerability of single-dose Staccato alprazolam 2 mg in adolescents with epilepsy. Pharmacokinetic data were included in a population pharmacokinetic analysis to support adolescent dose selection in the Phase 3 trials. Alprazolam was rapidly absorbed in most adolescent patients with epilepsy following administration with the Staccato device. No clinically relevant differences between body weight groups were observed on primary pharmacokinetic or safety outcomes. Staccato alprazolam 2 mg was well tolerated. Overall, the present data support the use of Staccato alprazolam 2 mg in adolescents with epilepsy (12-17 years of age).

思达可（Staccato®）阿普唑仑是一种手持式吸入装置，可通过肺内途径实现阿普唑仑的快速全身递送。本试验探究了单剂量2毫克思达可阿普唑仑在癫痫青少年患者中的药代动力学和耐受性。药代动力学数据被纳入群体药代动力学分析，以支持3期试验中青少年的剂量选择。使用思达可装置给药后，大多数癫痫青少年患者能迅速吸收阿普唑仑。在主要药代动力学或安全性结局方面，未观察到不同体重组之间存在临床相关差异。2毫克思达可阿普唑仑耐受性良好。总体而言，目前的数据支持在癫痫青少年患者（12 - 17岁）中使用2毫克思达可阿普唑仑。

REF: Klein P, Aungaroon G, Biton V, et al. Pharmacokinetics and tolerability of single-dose Staccato® alprazolam in adolescents with epilepsy, and population pharmacokinetic analysis to support dose selection in adolescents. Epilepsia. 2026;67(1):109-119. doi:10.1111/epi.18643 PMID: 41133403

Development and validation of clinico-imaging machine learning and deep learning models to predict responses to initial antiseizure medications in epilepsy

开发并验证临床影像机器学习和深度学习模型以预测癫痫患者对初始抗癫痫药物的反应

Antiseizure medications (ASMs) are the first-line treatment for epilepsy, yet they are ineffective in controlling seizures in about 40% of patients with unpredictable individual response to treatment. This study aimed to develop and validate artificial intelligence (AI) models using clinical and brain magnetic resonance imaging (MRI) data to predict responses to the first two ASMs in people with epilepsy. AI-based models incorporating brain MRI, clinical, and medication data can efficiently predict seizure freedom in recently diagnosed epilepsy. They may enhance treatment selection in epilepsy and offer a foundation for clinical decision support systems. Further validation in larger cohorts is warranted.

抗癫痫药物（ASMs）是癫痫的一线治疗方法，但约40%的患者使用这些药物无法控制癫痫发作，且个体对治疗的反应难以预测。本研究旨在利用临床和脑部磁共振成像（MRI）数据开发并验证人工智能（AI）模型，以预测癫痫患者对前两种抗癫痫药物的反应。结合脑部MRI、临床和药物数据的人工智能模型能够有效预测新诊断癫痫患者的无癫痫发作情况。这些模型可能会优化癫痫的治疗选择，并为临床决策支持系统提供基础。有必要在更大的队列中进行进一步验证。

REF: Nazem-Zadeh MR, Chang RS, Barnard S, et al. Development and validation of clinico-imaging machine learning and deep learning models to predict responses to initial antiseizure medications in epilepsy. Epilepsia. 2026;67(1):120-137. doi:10.1111/epi.18668 PMID: 41133949

An extreme type of new onset refractory status epilepticus with stimulus-induced seizures in pharmacological isoelectric states

药物性等电位状态下伴有刺激诱发癫痫发作的一种极端类型的新发难治性癫痫持续状态

Status epilepticus (SE) is a common neurological emergency associated with high morbidity and mortality. SE is classified as refractory when it persists despite benzodiazepine and second-line antiseizure medication. Managing refractory SE in the intensive care setting often requires high doses of sedative drugs, which can induce burst suppression or complete electrical suppression (amplitude < 10 μV). We aimed to investigate the characteristics of persistent epileptic seizures in patients undergoing pharmacologically induced electrical suppression for treatment of refractory SE. We report a series of seven c-NORSE patients with a rare and extremely severe presentation: persistent and stimulus-induced seizures occurring over an electrically suppressed EEG background. This hyperexcitability state may result from cellular and network alterations induced by phenobarbital in patients with central nervous system inflammation.

癫痫持续状态（SE）是一种常见的神经系统急症，具有较高的发病率和死亡率。当SE在使用苯二氮䓬类药物和二线抗癫痫药物后仍持续存在时，被归类为难治性癫痫持续状态。在重症监护环境中管理难治性SE通常需要大剂量的镇静药物，这可能会导致爆发抑制或完全电抑制（振幅 < 10 μV）。我们旨在研究因治疗难治性SE而接受药物诱导电抑制的患者中持续性癫痫发作的特征。我们报告了一系列7例伴发热性感染相关癫痫综合征（c - NORSE）患者，他们呈现出一种罕见且极其严重的表现：在脑电图电抑制背景下出现持续性和刺激诱发的癫痫发作。这种高兴奋性状态可能是由中枢神经系统炎症患者使用苯巴比妥引起的细胞和网络改变所致。

REF: Lévi-Strauss J, Nguyen-Michel VH, Ribeiro EM, et al. An extreme type of new onset refractory status epilepticus with stimulus-induced seizures in pharmacological isoelectric states. Epilepsia. 2026;67(1):138-150. doi:10.1111/epi.18601 PMID: 40847775

Selecting effective antiseizure medications for early treatment of SCN8A-related epilepsy using a machine learning approach incorporating clinician and caregiver assessments

采用结合临床医生和护理人员评估的机器学习方法，为SCN8A相关癫痫的早期治疗选择有效的抗癫痫药物

Despite rapid advances in understanding the disease spectrum and its progression, little is known about which antiseizure medications (ASMs) are likely to be beneficial or detrimental as first-line therapies for patients with SCN8A-related epilepsy (SCN8A-RE). This is a critical issue given low rates of seizure freedom and treatment resistance rates that exceed 75%. In this study, we test the hypothesis that machine learning (ML) algorithms can improve selection of ASMs that are likely to benefit patients with SCN8A-RE. The results indicate that ML algorithms can improve selection of ASMs that are likely to be beneficial in the early treatment of SCN8A-RE patients, with little risk of recommending ASMs with detrimental effects-a particular hazard for patient populations requiring long-term maintenance on polypharmacy. The results also expand the number of recommended ASMs from two sodium channel blockers (SCBs) identified in a recent consensus process to five SCBs and a γ-aminobutyric acidergic drug. The algorithm lays the groundwork for incorporating composite measures that include both seizure control and quality of life metrics.

尽管在了解该疾病谱及其进展方面取得了快速进展，但对于哪些抗癫痫药物（ASMs）作为SCN8A相关癫痫（SCN8A - RE）患者的一线治疗可能有益或有害，人们知之甚少。鉴于癫痫发作缓解率低且治疗抵抗率超过75%，这是一个关键问题。在这项研究中，我们检验了机器学习（ML）算法能否改善对可能使SCN8A - RE患者受益的抗癫痫药物的选择这一假设。结果表明，机器学习算法可以改善对在SCN8A - RE患者早期治疗中可能有益的抗癫痫药物的选择，且推荐有不良影响的抗癫痫药物的风险很小——对于需要长期接受多药治疗维持的患者群体来说，这是一个特别的风险。研究结果还将推荐的抗癫痫药物数量从最近一项共识过程中确定的两种钠通道阻滞剂（SCBs）增加到五种钠通道阻滞剂和一种γ - 氨基丁酸能药物。该算法为纳入包括癫痫发作控制和生活质量指标在内的综合指标奠定了基础。

REF: Hack JB, Hammer MF. Selecting effective antiseizure medications for early treatment of SCN8A-related epilepsy using a machine learning approach incorporating clinician and caregiver assessments. Epilepsia. 2026;67(1):151-163. doi:10.1111/epi.18632 PMID: 41034159