Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China.
Sixth Medical Center of PLA General Hospital, Beijing, China.
Biomed Eng Online. 2020 Feb 22;19(1):13. doi: 10.1186/s12938-020-0757-8.
Focal cortical dysplasia (FCD) is a neuronal migration disorder and is a major cause of drug-resistant epilepsy. However, many focal abnormalities remain undetected during routine visual inspection, and many patients with histologically confirmed FCD have normal fluid-attenuated inversion recovery (FLAIR-negative) images. The aim of this study was to quantitatively evaluate the changes in cortical thickness with magnetic resonance (MR) imaging of patients to identify FCD lesions from FLAIR-negative images.
We first used the three-dimensional (3D) Laplace method to calculate the cortical thickness for individuals and obtained the cortical thickness mean image and cortical thickness standard deviation (SD) image based on all 32 healthy controls. Then, a cortical thickness extension map was computed by subtracting the cortical thickness mean image from the cortical thickness image of each patient and dividing the result by the cortical thickness SD image. Finally, clusters of voxels larger than three were defined as the FCD lesion area from the cortical thickness extension map.
The results showed that three of the four lesions that occurred in non-temporal areas were detected in three patients, but the detection failed in three patients with lesions that occurred in the temporal area. The quantitative analysis of the detected lesions in voxel-wise on images revealed the following: specificity (99.78%), accuracy (99.76%), recall (67.45%), precision (20.42%), Dice coefficient (30.01%), Youden index (67.23%) and area under the curve (AUC) (83.62%).
Our studies demonstrate an effective method to localize lesions in non-temporal lobe regions. This novel method automatically detected FCD lesions using only FLAIR-negative images from patients and was based only on cortical thickness feature. The method is noninvasive and more effective than a visual analysis for helping doctors make a diagnosis.
局灶性皮质发育不良（FCD）是一种神经元迁移障碍，是耐药性癫痫的主要原因。然而，在常规视觉检查中，许多局灶性异常仍未被发现，许多组织学证实的 FCD 患者具有正常的液体衰减反转恢复（FLAIR 阴性）图像。本研究旨在通过磁共振（MR）成像定量评估皮质厚度的变化，从 FLAIR 阴性图像中识别 FCD 病变。
我们首先使用三维（3D）拉普拉斯法计算个体的皮质厚度，根据所有 32 名健康对照者获得皮质厚度平均值图像和皮质厚度标准偏差（SD）图像。然后，通过从每位患者的皮质厚度图像中减去皮质厚度平均值图像，并将结果除以皮质厚度 SD 图像，计算皮质厚度扩展图。最后，从皮质厚度扩展图中定义大于三个体素的体素簇作为 FCD 病变区域。
在四个非颞叶区域发生的病变中，有三个在三个患者中被检测到，但在三个颞叶区域发生病变的患者中检测失败。对图像中以体素为单位检测到的病变进行定量分析，结果如下：特异性（99.78%）、准确性（99.76%）、召回率（67.45%）、精密度（20.42%）、Dice 系数（30.01%）、Youden 指数（67.23%）和曲线下面积（AUC）（83.62%）。
我们的研究证明了一种在非颞叶区域定位病变的有效方法。这种新方法仅使用来自患者的 FLAIR 阴性图像并基于皮质厚度特征自动检测 FCD 病变。该方法是非侵入性的，比视觉分析更有助于医生做出诊断。
