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Detecting focal cortical dysplasia lesions from FLAIR-negative images based on cortical thickness.
Feng, Cuixia; Zhao, Hulin; Tian, Maoyu; Lu, Miaomiao; Wen, Junhai.
Afiliación
  • Feng C; Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China. 786733550@qq.com.
  • Zhao H; Sixth Medical Center of PLA General Hospital, Beijing, China.
  • Tian M; Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China.
  • Lu M; Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China.
  • Wen J; Department of Biomedical Engineering, School of Life Science, Beijing Institute of Technology, Beijing, China. wenjh@bit.edu.cn.
Biomed Eng Online ; 19(1): 13, 2020 Feb 22.
Article en En | MEDLINE | ID: mdl-32087703
ABSTRACT

BACKGROUND:

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.

METHODS:

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.

RESULTS:

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%).

CONCLUSION:

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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Imagen por Resonancia Magnética / Malformaciones del Desarrollo Cortical Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: Biomed Eng Online Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Encéfalo / Imagen por Resonancia Magnética / Malformaciones del Desarrollo Cortical Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male Idioma: En Revista: Biomed Eng Online Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2020 Tipo del documento: Article País de afiliación: China