立体脑电图
皮质发育不良
前瞻性队列研究
癫痫
算法
病变
医学
磁共振成像
四分位间距
放射科
癫痫外科
外科
计算机科学
精神科
作者
Ajai Chari,Sophie Adler,Konrad Wagstyl,Kiran K. Seunarine,Muhammad Zubair Tahir,Friederike Moeller,Rachel Thornton,Stewart Boyd,Krishna Das,Gerald Cooray,Stuart Smith,Felice D‘Arco,Torsten Baldeweg,Christin Eltze,J. Helen Cross,Martin Tisdall
摘要
Abstract Aim To evaluate a lesion detection algorithm designed to detect focal cortical dysplasia (FCD) in children undergoing stereoelectroencephalography (SEEG) as part of their presurgical evaluation for drug‐resistant epilepsy. Method This was a prospective, single‐arm, interventional study (Idea, Development, Exploration, Assessment, and Long‐Term Follow‐Up phase 1/2a). After routine SEEG planning, structural magnetic resonance imaging sequences were run through an FCD lesion detection algorithm to identify putative clusters. If the top three clusters were not already sampled, up to three additional SEEG electrodes were added. The primary outcome measure was the proportion of patients who had additional electrode contacts in the SEEG‐defined seizure‐onset zone (SOZ). Results Twenty patients (median age 12 years, range 4–18 years) were enrolled, one of whom did not undergo SEEG. Additional electrode contacts were part of the SOZ in 1 out of 19 patients while 3 out of 19 patients had clusters that were part of the SOZ but they were already implanted. A total of 16 additional electrodes were implanted in nine patients and there were no adverse events from the additional electrodes. Interpretation We demonstrate early‐stage prospective clinical validation of a machine learning lesion detection algorithm used to aid the identification of the SOZ in children undergoing SEEG. We share key lessons learnt from this evaluation and emphasize the importance of robust prospective evaluation before routine clinical adoption of such algorithms. What this paper adds The focal cortical dysplasia detection algorithm collocated with the seizure‐onset zone (SOZ) in 4 out of 19 patients. The algorithm changed the resection boundaries in 1 of 19 patients undergoing stereoelectroencephalography for drug‐resistant epilepsy. The patient with an altered resection due to the algorithm was seizure‐free 1 year after resective surgery. Overall, the algorithm did not increase the proportion of patients in whom SOZ was identified.
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