Lateralization of temporal lobe epilepsy (TLE) and discrimination of TLE from extra-TLE using pattern analysis of magnetic resonance spectroscopic and volumetric data

Citation
Lm. Li et al., Lateralization of temporal lobe epilepsy (TLE) and discrimination of TLE from extra-TLE using pattern analysis of magnetic resonance spectroscopic and volumetric data, EPILEPSIA, 41(7), 2000, pp. 832-842
Citations number
50
Categorie Soggetti
Neurosciences & Behavoir
Journal title
EPILEPSIA
ISSN journal
00139580 → ACNP
Volume
41
Issue
7
Year of publication
2000
Pages
832 - 842
Database
ISI
SICI code
0013-9580(200007)41:7<832:LOTLE(>2.0.ZU;2-0
Abstract
Purpose: To examine whether or not pattern analysis of magnetic resonance v olumetric (MRVol) and proton magnetic resonance spectroscopic imaging (H-1- MRSI) data would enable (a) the accurate lateralization of temporal lobe ep ilepsy (TLE) and (b) the discrimination of TLE from extratemporal epilepsy (E-TLE). Methods: For lateralization analysis, we used data from 150 nonforeign tiss ue lesional TLE patients [88 left-sided (L-TLE), 46 right-sided (R-TLE)], a nd 16 bilateral (Bi-TLE)I. For the discrimination of TLE from E-TLE, we use d data from 174 patients (145 with unilateral TLE, 14 with unilateral E-TLE , and 15 with widespread epileptogenic zones involving both the TL and extr a-TL regions-multilobar epilepsy). A series of "leave-one-out" cross-valida ted linear discriminant analyses were performed using the MRVol and H-1-MRS I data sets to lateralize TLE and discriminate it from E-TLE. Results: Lateralization: The leave-one-out linear discriminant analyses wer e able to correctly lateralize (with a posterior probability >0.50) 120 (90 %) of the 134 L-TLE and R-TLE patients. Imposing higher posterior probabili ty (>0.95) increased accuracy of lateralization to 98%, with only two disco rdant cases who underwent surgery on the side of electroencephalogram, and both had bad outcome. Discrimination: the leave-one-out linear discriminant analyses were able to correctly classify (with a posterior probability >0. 50) 142 (89%) of the 159 TLE and E-TLE patients. Accuracy increased slightl y as higher posterior probability cutoffs were imposed, with fewer patients being classified. Conclusions: Pattern analysis of H-1-MRSI and MRVol data can accurately lat eralize TLE. Discriminating TLE from E-TLE was less accurate, probably due to the presence of temporal lobe damage in some patients with E-TLE reflect ing dual pathology.