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Deep Convolutional Networks for Automated Detection of Epileptogenic Brain Malformations

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11072)

Abstract

Focal cortical dysplasia (FCD) is a prevalent surgically-amenable epileptogenic malformation of cortical development. On MRI, FCD typically presents with cortical thickening, hyperintensity, and blurring of the gray-white matter interface. These changes may be visible to the naked eye, or subtle and be easily overlooked. Despite advances in MRI analytics, current surface-based algorithms fail to detect FCD in 50% of cases. Moreover, arduous data pre-processing and specialized expertise preclude widespread use. Here we propose a novel algorithm that harnesses feature-learning capability of convolutional neural networks (CNNs) with minimal data pre-processing. Our classifier, trained on a patch-based augmented dataset derived from patients with histologically-validated FCD operates directly on MRI voxels to distinguish the lesion from healthy tissue. The algorithm was trained and cross-validated on multimodal MRI data from a single site (S1) and evaluated on independent data from S1 and six other sites worldwide (S2–S7; 3 scanner manufacturers and 2 field strengths) for a total of 107 subjects. The classifier showed excellent sensitivity (S1: 87%, 35/40 lesions detected; S2–S7: 91%, 61/67 lesions detected) and specificity (S1: 95%, no findings in 36/38 healthy controls; 90%, no findings in 57/63 disease controls). Easy implementation, minimal pre-processing, high performance and generalizability make this classifier an ideal platform for large-scale clinical use, particularly in “MRI-negative” FCD.

Keywords

Magnetic resonance imaging Clinical diagnostics Epilepsy Deep learning Classification 

Notes

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging CenterMontreal Neurological InstituteMontrealCanada
  2. 2.Multimodal Imaging and Connectome Laboratory, McConnell Brain Imaging CenterMontreal Neurological InstituteMontrealCanada
  3. 3.Children’s Hospital A. Meyer-University of FlorenceFlorenceItaly
  4. 4.Freiburg Epilepsy Center, University Medical CenterFreiburgGermany
  5. 5.University of CampinasCampinasBrazil
  6. 6.Istituto Neurologico Carlo BestaMilanItaly
  7. 7.The Florey Institute of Neuroscience and Mental Health and the University of MelbourneMelbourneAustralia
  8. 8.Aix-Marseille Univ, INSMarseilleFrance
  9. 9.Aix-Marseille Univ, CNRSMarseilleFrance
  10. 10.Siemens Medical Solutions, Medical Imaging TechnologiesPrincetonUSA

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