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基于形态学影像后处理技术在局灶性皮质发育不良诊治中的研究进展

Advances in morphology-based image post-processing techniques in the diagnosis and management of focal cortical dysplasia
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摘要 局灶性皮质发育不良(focal cortical dysplasia,FCD)是导致药物难治性癫痫(drug-resistant epilepsy,DRE)最常见的病因之一,其神经影像学特征是临床评估的重要组成部分。因为只有部分类型FCD在MRI表现异常,对于MRI阴性的FCD,诊断和治疗仍存在诸多困难。基于形态学的影像后处理技术发展日新月异,各种辅助诊断和治疗的影像后处理工具如Matlab、3D slicer、SinoPlan、MRIcro等越来越受到广大癫痫外科学者的青睐,不仅可将MRI显示的异常病灶进行剥离并三维重建,同时还可辅助显现出肉眼难以辨识的潜在异常部位,大大提高了FCD病灶检出率,进一步满足了临床对精准诊断和治疗FCD的需要,为难治性癫痫的诊治创造了新的思路和方法,也为临床更加全面科学的诊断和治疗提供了更多的参考。 Focal cortical dysplasia(FCD) is one of the most common etiologies leading to drug-resistant epilepsy(DRE), and its neuroimaging features are an important part of clinical evaluation. Only some types of FCD can show abnormalities on MRI, and there are still many difficulties in the diagnosis and treatment of MRI-negative FCD.Morphology-based image post-processing technology is developing rapidly, and various image post-processing tools to assist diagnosis and treatment, such as Matlab, 3D slicer, SinoPlan, MRIcro, etc., are increasingly favored by the majority of scholars in epilepsy surgery, which can not only strip and 3D reconstruct abnormal lesions shown by MRI, but also assist in the appearance of potential abnormal sites which are difficult to recognize with the naked eye. This has greatly improved the detection rate of FCD foci and further met the demand for accurate diagnosis and treatment of FCD, thereby creating new ideas and methods for the diagnosis and treatment of intractable epilepsy, and providing more references for more comprehensive and scientific clinical diagnosis and treatment.
作者 王仁 王小强 史雪峰 张新定 WANG Ren;WANG Xiaoqiang;SHI Xuefeng;ZHANG Xinding(Department of Neurosurgery,The Second Hospital of Lanzhou University,Lanzhou 730030,China)
出处 《中国神经精神疾病杂志》 CAS CSCD 北大核心 2024年第3期178-182,共5页 Chinese Journal of Nervous and Mental Diseases
基金 甘肃省自然科学基金项目(编号:22JR5RA977,23JRRA1629)。
关键词 局灶性皮质发育不良 影像后处理技术 MRI阳性 MRI阴性 人工神经网络 Focal cortical dysplasia Image post-processing technology MRI-positive MRI-negative Artificial neural network
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