Abstract
Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of pharmacoresistant epilepsy. Small FCD lesions are difficult to distinguish from normal cortex and remain often overlooked on radiological MRI inspection. This paper presents a method to detect small FCD lesions on T1-MRI relying on surface-based features that model their textural and morphometric characteristics. The automatic detection was performed by a two step classification. First, a vertex-wise classifier based on a neural-network bagging trained on manual labels. Then, a cluster-wise classification designed to remove false positive clusters. The method was tested on 19 patients with small FCD. At the first classification step, 18/19 (95%) lesions were detected. The second classification step kept 13/19 (68%) lesions and decreased efficiently the amount of false positive. This new approach may assist the presurgical evaluation of patients with intractable epilepsy, especially those with unremarkable MRI findings.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Taylor, D.C., Falconer, M.A., Bruton, C.J., Corsellis, J.A.N.: Focal Dysplasia of the Cerebral Cortex in Epilepsy. J. Neurol. Neurosurg. Psychiatry 34, 369–387 (1971)
Sisodiya, S.M.: Surgery for Malformations of Cortical Development Causing Epilepsy. Brain 123, 1075–1091 (2000)
Tassi, L., Colombo, N., Garbelli, R., Francione, S., Lo, R.G., Mai, R., Cardinale, F., Cossu, M., Ferrario, A., Galli, C., Bramerio, M., Citterio, A., Spreafico, R.: Focal Cortical Dysplasia: Neuropathological Subtypes, EEG, Neuroimaging and Surgical Outcome. Brain 125, 1719–1732 (2002)
Antel, S.B., Collins, D.L., Bernasconi, N., Andermann, F., Shinghal, R., Kearney, R.E., Arnold, D.L., Bernasconi, A.: Automated Detection of Focal Cortical Dysplasia Lesions Using Computational Models of their MRI Characteristics and Texture Analysis. Neuroimage 19, 1748–1759 (2003)
Wilke, M., Kassubek, J., Ziyeh, S., Schulze-Bonhage, A., Huppertz, H.J.: Automated Detection of Gray Matter Malformations Using Optimized Voxel-Based Morphometry: a Systematic Approach. Neuroimage 20, 330–343 (2003)
Colliot, O., Bernasconi, N., Khalili, N., Antel, S.B., Naessens, V., Bernasconi, A.: Individual Voxel-Based Analysis of Gray Matter in Focal Cortical Dysplasia. Neuroimage 29, 162–171 (2006)
Colliot, O., Antel, S.B., Naessens, V.B., Bernasconi, N., Bernasconi, A.: In Vivo Profiling of Focal Cortical Dysplasia on High-Resolution MRI with Computational Models. Epilepsia 47, 134–142 (2006)
Besson, P., Bernasconi, A.: Small FCD Lesions are Located at the Bottom of a Sulcus. Epilepsia 47, 16 (2006)
Kim, J.S., Singh, V., Lee, J.K., Lerch, J., Ad-Dab’bagh, Y., MacDonald, D., Lee, J.M., Kim, S.I., Evans, A.C.: Automated 3-D Extraction and Evaluation of the Inner and Outer Cortical Surfaces Using a Laplacian Map and Partial Volume Effect Classification. NeuroImage 27, 210–221 (2005)
Dale, A.M., Fischl, B., Sereno, M.I.: Cortical Surface-Based Analysis. I. Segmentation and Surface Reconstruction. Neuroimage 9, 179–194 (1999)
Salat, D.H., Buckner, R.L., Snyder, A.Z., Greve, D.N., Desikan, R.S.R., Busa, E., Morris, J.C., Dale, A.M., Fischl, B.: Thinning of the Cerebral Cortex in Aging. Cereb. Cortex 14, 721–730 (2004)
Lerch, J.P., Pruessner, J.C., Zijdenbos, A., Hampel, H., Teipel, S.J., Evans, A.C.: Focal Decline of Cortical Thickness in Alzheimer’s Disease Identified by Computational Neuroanatomy. Cereb. Cortex 15, 995–1001 (2005)
Luders, E., Narr, K.L., Thompson, P.M., Rex, D.E., Jancke, L., Steinmetz, H., Toga, A.W.: Gender Differences in Cortical Complexity. Nat. Neurosci. 7, 799–800 (2004)
Thompson, P.M., Woods, R.P., Mega, M.S., Toga, A.W.: Mathematical/Computational Challenges in Creating Deformable and Probabilistic Atlases of the Human Brain. Hum. Brain Mapp. 9, 81–92 (2000)
Lyttelton, O., Boucher, M., Robbins, S., Evans, A.: An Unbiased Iterative Group Registration Template for Cortical Surface Analysis. NeuroImage 34, 1535–1544 (2007)
Sled, J.G., Zijdenbos, A.P., Evans, A.C.: A Nonparametric Method for Automatic Correction of Intensity Nonuniformity in MRI Data. IEEE Trans. Med. Imaging 17, 87–97 (1998)
Collins, D.L., Neelin, P., Peters, T.M., Evans, A.C.: Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space. J. Comput. Assist. Tomogr. 18, 192–205 (1994)
Zijdenbos, A.P., Forghani, R., Evans, A.C.: Automatic Quantification of MS Lesions in 3D MRI Brain Data Sets: Validation of INSECT. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 439–448. Springer, Heidelberg (1998)
Lerch, J.P., Evans, A.C.: Cortical Thickness Analysis Examined through Power Analysis and a Population Simulation. NeuroImage 24, 163–173 (2005)
Colliot, O., Mansi, T., Bernasconi, N., Naessens, V., Klironomos, D., Bernasconi, A.: Segmentation of Focal Cortical Dysplasia Lesions on MRI Using Level Set Evolution. Neuroimage 32, 1621–1630 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Besson, P., Bernasconi, N., Colliot, O., Evans, A., Bernasconi, A. (2008). Surface-Based Texture and Morphological Analysis Detects Subtle Cortical Dysplasia. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008. MICCAI 2008. Lecture Notes in Computer Science, vol 5241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85988-8_77
Download citation
DOI: https://doi.org/10.1007/978-3-540-85988-8_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85987-1
Online ISBN: 978-3-540-85988-8
eBook Packages: Computer ScienceComputer Science (R0)