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Original article

Vol. 142 No. 2324 (2012)

Secondary MRI-findings, volumetric and spectroscopic measurements in mesial temporal sclerosis

  • Maria Luisa Lopez-Acevedo
  • Manuel Martinez-Lopez
  • Rafael Favila
  • Ernesto Roldan-Valadez
DOI
https://doi.org/10.4414/smw.2012.13549
Cite this as:
Swiss Med Wkly. 2012;142:w13549
Published
03.06.2012

Summary

INTRODUCTION: Primary- and secondary MR findings, volumetric measurements and MR spectroscopy data of each hippocampus represent more a dozen of variables that radiologists should consider in a quantitative MR report of temporal lobe epilepsy (TLE). There is a paucity of data about the significance of secondary MR findings simultaneously evaluated with volumetry and MR spectroscopy. We analyzed the influence of qualitative-secondary MR findings simultaneously with quantitative (volumetry and spectroscopy) data in MRI positive- and negative patients with mesial temporal sclerosis (MTS).

METHODS: Analytic and transversal study of 59 patients with TLE and suspiciousness of MTS. 13 variables were analyzed for each hippocampus: age, gender, cerebral hemisphere, temporal lobe atrophy, choroidal fissure dilatation, mamillary body atrophy, collateral white matter atrophy, fornix asymmetry; Naa/Cr, Cho/Cr, mI/Cr, Naa/(Cr+Cho); and hippocampus volume (mm3). Multivariate discriminant analysis (DA) was performed with the aim to identify specific morphologic and metabolic attributes in hippocampi with and without MTS.

RESULTS: Discriminant function significantly differentiated the hippocampi with- and without MTS (Wilks’ λ = 0.211, χ2 (11) = 116.072, p = < .001. The model explained 79.03% of the variation in the grouping variable. The pooled within-groups correlations showed the highest influence of discriminating function for the secondary MR findings over metabolite indices and hippocampal volumes, the overall predictive accuracy was 93.9%.

DISCUSSION: Due of the large number of variables (qualitative and quantitative) to which a radiologist is exposed in a conventional hippocampal MR-report, such evaluation might benefit from the use of predictive models generated by unconventional statistical methods, such as DA.

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