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Abstract #1045

Lateralization of Temporal Lobe Epilepsy Using Multimodal MRI, Decision Tree, and Random Forest Methods

Alireza Fallahi1, Neda Mohammadi-Mobarakeh2, Narges Hosseini Tabatabaei3, Mohammad Pooyan4, Jafar Mehvari-Habibabadi5, Mohammad-Reza Ay2, and Mohammad-Reza Nazem-Zadeh2
1Shahed University, Tehran, Iran (Islamic Republic of), 2Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), 3Brain and Spinal Cord Injury Research Centre, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), 4Biomedical Engineering Department, Shahed University, Tehran, Iran (Islamic Republic of),, Isfahan, Iran (Islamic Republic of)

In this study, a decision making method was developed for determination epileptogenicity in mesial temporal lobe epilepsy (mTLE) patients using different neuroimaging markers including hippocampal volume, and FLAIR (Fluid Attenuated Inversion Recovery) intensity and MD (Mean Diffusivity) value in hippocampus, FA (Fractional anisotropy) in posteroinferior cingulum, and FA in crus of fornix from MRI images of T1, FLAIR, and DTI (diffusion tensor imaging). The aim of this study is to creating an automated classification algorithm using decision tree and random forest methods. Result of applied method detected essential rules for prediction of laterality in individual mTLE patients.

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