期刊文献+

磁共振FLAIR序列表现阴性的局灶性皮质发育不良病灶检测的研究进展 被引量:2

Research progress of focal cortical dysplasia with FLAIR-negative of magnetic resonance imaging
下载PDF
导出
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的常见原因之一,Ⅰ型在FCD中的占比为38.3%,而Ⅱ型占比为61.7%。手术是治疗FCD的有效方式。术前发现病灶并精准定位是决定手术方式及预后的重要因素。目前对于FCD的诊断主要依赖MRI检查,但是,高达40%的Ⅱ型FCD和85%的Ⅰ型FCD病灶在常规MRI上表现为阴性,给诊断和手术带来极大的难度。随着MRI硬件、软件及后处理技术的发展,极大提高了FCD在常规MRI表现为阴性的检出率(综合诊断增益率为31%),对病灶准确定位、指导手术、降低术后癫痫发作具有重要意义。因此本文就提高常规MRI表现为阴性的FCD检出率的方法进行综述。 Focal cortical dysplasia(FCD)is one of the common causes of drug refractory epilepsy.TypeⅠaccounts for 38.3%of the FCD lesions,while typeⅡaccounts for 61.7%.Surgery is an effective way for the treatment of FCD.Preoperative detection and accurate localization of the lesions are important factors affecting the mode of operation and prognosis.At present,the diagnosis of FCD mainly depends on MRI.However,up to 40%of typeⅡFCD and 85%of typeⅠFCD lesions are negative on conventional MRI,which brings great difficulty to diagnosis and operation.With the development of MRI hardware,software and post-processing technology,the negative detection rate of FCD in conventional MRI is greatly improved(overall diagnostic gain rate 31%).Which is great significance for accurate location of lesions,guiding surgery and reducing postoperative seizures.Therefore,this paper reviews the research progress of improving the detection methods of FCD negative on conventional MRI.
作者 俱京涛 陈楠 JU Jingtao;CHEN Nan(Department of Radiology and Nulear Medicine,Xuanwu Hospital,Capital Medical University,Beijing 100053,China)
出处 《磁共振成像》 CAS CSCD 北大核心 2022年第7期164-166,170,共4页 Chinese Journal of Magnetic Resonance Imaging
关键词 磁共振成像 局灶性皮质发育不良 脑磁图 癫痫 三维容积液体衰减反转恢复序列 双反转恢复序列 液体和白质抑制序列 三维边缘增强梯度回波序列 基于体素的形态学分析 形态学分析程序 基于表面形态学技术 卷积神经网络 magnetic resonance imaging focal cortical dysplasia magnetoencephalography epilepsy three-dimensional fluid attenuated inversion recover double inversion recovery sequences fluid and white matter suppression sequence three-dimensional edge-enhancing gradient echo sequence voxel-based morphometry morphometric analysis program surface-based morphometry convolutional neural network
  • 相关文献

同被引文献33

引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部