Tract Based Spatial Statistical Analysis of Diffusion Parameters in Temporal Lobe Epilepsy

Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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ICBME16_008

تاریخ نمایه سازی: 11 تیر 1388

Abstract:

Temporal lobe epilepsy (TLE) is a neurological disease that involves parts of the brain. Majority of TLE patients suffer from refractory seizures . There fore , determining damaged areas of the brain and the seizure focus are important in TLE. The purpose of this paper is to estimate the level of damage in the brain fiber tracts using diffusion tensor magnetic resonance imaging (DT-MRT). For the evaluation of the fiber tracts, a variety of diffusion anisotropy indices ( DAI's) are proposed such as fractional anisotropy (FA), mean diffusivity (MD), and ellipsoidal area ration (EAR). Here in addition to the widely used index (FA), a newly proposed index (EAR) is also estimates because of its higher contrast to noise ratio (CNR) and signal to noise ratio (SNR) compared with the other DAI's in the high noise levels that occur in practice . Tract based spatial statistics (TBSS) method is employed for the evaluation of the fiber tracts throughout the brain based on the above DT-MRI indices .This method is applies to five patients with TLE in comparison with five normal control subjects . In the patient group, significant reduction of FA and EAR in temporal lobes is found . Also, abnormality is observed in the corpus callo sum and inferior frontal gyrus, In addition decreased FA and the hippocampus is marginally detected in conclusion , DT-MRI indices provide complimentary information for the diagnosis of TLE where EAR provides a higher sensitivity than FA.

Keywords:

Diffusion Tensor Magnetic Resonance Imaging , Temporal Lobe Epilepsy , Ellipsoidal Area Ratio , Tract Based Spatial Statistics

Authors

Maryam Afzaly

Control and Intelligent Processing Center of Excellence (CIPCE) , School of Electrical and Computer Engineering , University of Tehran , Tehran , Iran

Hamid Soltanian zadeh

Control and Intelligent Processing Center of Excellence (CIPCE) , School of Electrical and Computer Engineering , University of Tehran , Tehran , Iran