Proton MR Spectroscopy in Patients with Structural MRI-Negative Temporal Lobe Epilepsy

2015 ◽  
Vol 25 (6) ◽  
pp. 1030-1037 ◽  
Author(s):  
Michael Y. Xu ◽  
Erhan Ergene ◽  
Michael Zagardo ◽  
Patrick T. Tracy ◽  
Huaping Wang ◽  
...  
1998 ◽  
Vol 170 (3) ◽  
pp. 771-776 ◽  
Author(s):  
J E Thompson ◽  
M Castillo ◽  
L Kwock ◽  
B Walters ◽  
R Beach

2012 ◽  
Vol 9 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Hasan Aydin ◽  
Nilay Aydin Oktay ◽  
Volkan Kizilgoz ◽  
Elif Altin ◽  
Idil Tatar ◽  
...  

2014 ◽  
Vol 108 (3) ◽  
pp. 517-525 ◽  
Author(s):  
Rebecca Anne Pope ◽  
Maria Centeno ◽  
Dominique Flügel ◽  
Mark Robert Symms ◽  
Matthias Koepp ◽  
...  

2004 ◽  
Vol 101 (4) ◽  
pp. 613-620 ◽  
Author(s):  
Aaron A. Cohen-Gadol ◽  
Jullie W. Pan ◽  
Jung H. Kim ◽  
Dennis D. Spencer ◽  
Hoby H. Hetherington

Object. Proton magnetic resonance (MR) spectroscopy imaging of the ratio of N-acetylaspartate (NAA) to creatine (Cr) has proved efficacious as a localizing tool in demonstrating the metabolic changes associated with temporal lobe epilepsy. To analyze the significance of these MR spectroscopy findings further, the authors explored the relationship between regional alterations in the NAA/Cr ratio in hippocampi measured preoperatively and histopathological findings in hippocampi resected in patients with intractable mesial temporal lobe epilepsy (MTLE). Methods. Twelve patients in whom the diagnosis of MTLE had been made and 12 healthy volunteers with no known history of neurological disease underwent high-resolution 1H MR spectroscopy imaging of NAA and Cr (0.64 cm3 nominal voxel resolution) in five voxels spanning the anteroposterior length of the hippocampus. The authors correlated the NAA/Cr ratio with neuropathological findings in resected hippocampi, specifically glial fibrillary acidic protein (GFAP) immunoreactivity and pyramidal neuronal loss. A linear regression analysis of the ipsilateral NAA/Cr ratio revealed a statistically significant relation to the extent of hippocampal neuronal loss in only the CA2 sector (correlation coefficient [r] = −0.66, p < 0.03). The ipsilateral NAA/Cr ratio displayed significant regressions with GFAP immunoreactivity from all the CA sectors (r values ranged from −0.69 and p < 0.01 for the CA4 sector to −0.88 and p < 0.001 for the CA2 sector) except for the CA1. The extent of neuronal cell loss in every hippocampal subfield (r = 0.71−0.74, p < 0.007), except the CA2 (p = 0.08), correlated to the extent of neuronal cell loss in the dentate gyrus. There was no significant relationship between the duration or frequency of seizures and the mean ipsilateral NAA/Cr ratio; however, the mean density of GFAP-immunopositive cells correlated with seizure frequency (p < 0.03). Conclusions. The NAA/Cr ratio may not measure the full extent of hippocampal neuronal cell loss. The significant association of the NAA/Cr ratio with the GFAP immunoreactivity of most CA sectors indicates that the NAA/Cr ratio may provide a more accurate measurement of recent neuronal injury caused by epileptic activity. The coupling between neuronal impairment and astroglial GFAP expression may indicate the close association between neuronal and glial dysfunction in patients with epilepsy.


Author(s):  
Ezequiel Gleichgerrcht ◽  
Brent Munsell ◽  
Simon Keller ◽  
Daniel L Drane ◽  
Jens H Jensen ◽  
...  

Abstract Temporal lobe epilepsy is associated with magnetic resonance imaging (MRI) findings reflecting underlying mesial temporal sclerosis. Identifying these MRI features is critical for the diagnosis and management of temporal lobe epilepsy. To date, this process relies on visual assessment by highly trained human experts (e.g. neuroradiologists, epileptologists). Artificial intelligence is increasingly recognized as a promising aid in the radiological evaluation of neurological diseases, yet its applications in temporal lobe epilepsy have been limited. Here, we applied a convolutional neural networks to assess the classification accuracy of temporal lobe epilepsy based on structural MRI. We demonstrate that convoluted neural networks can achieve high accuracy in the identification of unilateral temporal lobe epilepsy cases even when the MRI had been originally interpreted as normal by experts. We show that accuracy can be potentiated by employing smoothed gray matter maps and a direct acyclic graphs approach. We further discuss the foundations for the development of computer-aided tools to assist with the diagnosis of epilepsy.


2018 ◽  
Vol 6 (3) ◽  
pp. 79-82
Author(s):  
Arunan Murali ◽  
◽  
T Bhasker Raj ◽  
Venkata Sai ◽  
Sheila Elangovan ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document