Brain Tissue Classification to Detect Focal Cortical Dysplasia in Magnetic Resonance Imaging

  • Fabricio Simozo Universidade de São Paulo
  • Marcos Oliveira Universidade de São Paulo
  • Luiz Murta-Junior FFCLRP-USP


Focal cortical dysplasia (FCD) is a local malformation of the cortex, the main cause of refractory epilepsy in childhood and one of the most common causes in adults. The surgery decision and planning depend on the FCD localization. Although recent studies have successfully detected FCD through artificial intelligence, no study investigates the relevance and prevalence of cortical features on FCD identification and the performance of different machine learning techniques. In this study, the proposed method constructed a voxel-based set of features, e.g., texture measure, border definition, cortical thickness.

Palavras-chave: Brain Tissue Classification, Focal Cortical Dysplasia, Magnetic Resonance Imaging


Adler, S., Wagstyl, K., Gunny, R., Ronan, L., Carmichael, D., Cross, J. H., … Baldeweg, T. (2017). Novel surface features for automated detection of focal cortical dysplasias in pediatric epilepsy. NeuroImage: Clinical, 14, 18–27.

Ahmed, B., Brodley, C. E., Blackmon, K. E., Kuzniecky, R., Barash, G., Carlson, C., … Thesen, T. (2015). Cortical feature analysis and machine learning improves detection of MRI-negative focal cortical dysplasia. Epilepsy & Behavior, 48, 21–28.

Antel, S. B., Collins, D. L., Bernasconi, N., Andermann, F., Shinghal, R., Kearney, R. E., … Bernasconi, A. (2003). Automated detection of focal cortical dysplasia lesions using computational models of their MRI characteristics and texture analysis. NeuroImage, 19(4), 1748–1759.

Bergo, F., & Falcao, A. (2008). FCD segmentation using texture asymmetry of MR-T1 images of the brain. 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 424–427. Retrieved from

Bernasconi, A., Antel, S. B., Collins, D. L., Bernasconi, N., Olivier, A., Dubeau, F., … Arnold, D. L. (2001). Texture analysis and morphological processing of magnetic resonance imaging assist detection of focal cortical dysplasia in extra-temporal partial epilepsy. Ann Neurol, 49(6), 770–775.

Blümcke, I., Aronica, E., Miyata, H., Sarnat, #harvey B, Thom, M., Roessler, K., … Spreafico, R. (2016). International recommendation for a comprehensive neuropathologic workup of epilepsy surgery brain tissue: A consensus Task Force report from the ILAE Commission on Diagnostic Methods. Epilepsia, 57(3), 348– 358.

Blümcke, I., Thom, M., & Aronica, E. (2011). The clinicopathologic spectrum of focal cortical dysplasias: A consensus classification proposed by an ad hoc Task Force of the ILAE Diagnostic Methods. …, 52(1), 158–174.

Cantor-Rivera, D., Khan, A. R., Goubran, M., Mirsattari, S. M., & Peters, T. M. (2015). Detection of temporal lobe epilepsy using support vector machines in multiparametric quantitative MR imaging. Computerized Medical Imaging and Graphics, 41, 14–28.

Carass, A., Roy, S., Jog, A., Cuzzocreo, J. L., Magrath, E., Gherman, A., … Pham, D. L. (2017). Longitudinal multiple sclerosis lesion segmentation: Resource and challenge. NeuroImage, 148, 77–102.

Colombo, N., Tassi, L., Galli, C., Citterio, A., Lo Russo, G., Scialfa, G., & Spreafico, R. (2003). Focal cortical dysplasias: MR imaging, histopathologic, and clinical correlations in surgically treated patients with epilepsy. AJNR. American Journal of Neuroradiology, 24(4), 724–33. Retrieved from

Duncan, J. S., Winston, G. P., Koepp, M. J., Ourselin, S., John, P., Frcp, S. D., … Ourselin, P. S. (2016). Brain imaging in the assessment for epilepsy surgery. The Lancet Neurology, 15(4), 420–433.

Fauser, S., Schulze-Bonhage, A., Honegger, J., Carmona, H., Huppertz, H.-J., Pantazis, G., … Zentner, J. (2004). Focal cortical dysplasias: surgical outcome in 67 patients in relation to histological subtypes and dual pathology. Brain : A Journal of Neurology, 127(Pt 11), 2406–18.

Fisher, R. S., Acevedo, C., Arzimanoglou, A., Bogacz, A., Cross, J. H., Elger, C. E., … Wiebe, S. (2014). A practical clinical definition of epilepsy. Epilepsia, 55(4), 475– 482.

Fisher, R. S., Cross, J. H., French, J. A., Higurashi, N., Hirsch, E., Jansen, F. E., … Zuberi, S. M. (2017). Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 58(4), 522–530.

Francione, S., Vigliano, P., Tassi, L., Cardinale, F., Mai, R., Lo Russo, G., & Munari, C. (2003). Surgery for drug resistant partial epilepsy in children with focal cortical dysplasia: anatomical-clinical correlations and neurophysiological data in 10 patients. Journal of Neurology, Neurosurgery, and Psychiatry, 74(11), 1493–501.

Hatt, M., Laurent, B., Ouahabi, A., Fayad, H., Tan, S., Li, L., … Visvikis, D. (2018). The first MICCAI challenge on PET tumor segmentation. Medical Image Analysis, 44, 177–195.

Hildebrandt, M., Pieper, T., Winkler, P., Kolodziejczyk, D., Holthausen, H., Blümcke, I., & Blu, I. (2005). Neuropathological spectrum of cortical dysplasia in children with severe focal epilepsies. Acta Neuropathologica, 110(1), 1–11.

Hong, S. J., Kim, H., Schrader, D., Bernasconi, N., Bernhardt, B. C., & Bernasconi, A. (2014). Automated detection of cortical dysplasia type II in MRI-negative epilepsy. Neurology, 83(1), 48–55.

Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, 24(6), 417–441.

Huppertz, H.-J. (2013). Morphometric MRI Analysis. In Dysphagia (Vol. 39, pp. 73– 84).

Kini, L. G., Gee, J. C., & Litt, B. (2016). Computational analysis in epilepsy neuroimaging: A survey of features and methods. NeuroImage: Clinical, 11(1), 515– 529. Statistical Mechanics; Mathematical Physics; Mathematical Physics.

Krsek, P., Maton, B., Korman, B., Pacheco-Jacome, E., Jayakar, P., Dunoyer, C., … Duchowny, M. (2008). Different features of histopathological subtypes of pediatric focal cortical dysplasia. Annals of Neurology, 63(6), 758–69.

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., … Van Leemput, K. (2015). The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Transactions on Medical Imaging, 34(10), 1993–2024.

Pearson, K. (1901). LIII. On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 2(11), 559–572.

Ramli, N., Rahmat, K., Lim, K. S., & Tan, C. T. (2015). Neuroimaging in refractory epilepsy. Current practice and evolving trends. European Journal of Radiology, 84(9), 1791–1800.

Roy, H., Lippé, S., Lussier, F., Sauerwein, H. C., Lortie, A., Lacroix, J., & Lassonde, M. (2011). Developmental outcome after a single episode of status epilepticus. Epilepsy & Behavior : E&B, 21(4), 430–6.

Sheppard, E., & Lippé, S. (2012). Cognitive outcome of status epilepticus in children. Epilepsy Research and Treatment, 2012, 984124.
Como Citar

Selecione um Formato
SIMOZO, Fabricio; OLIVEIRA, Marcos; MURTA-JUNIOR, Luiz. Brain Tissue Classification to Detect Focal Cortical Dysplasia in Magnetic Resonance Imaging. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 17. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 615-625. DOI: