Análisis de los Casos

Most hypotheses explaining how seizures arise implicate a relative imbalance between local cortical excitatory and inhibitory influences. Over the past two decades these concepts have been refined, particularly in animal models of epilepsy arising in the limbic system and in epilepsy in man caused by hippocampal sclerosis. Other than in an animal model of chronic neocortical injury in which a sub-population of GABAergic cortical interneurons is lost [2 3 0 ], relatively little is known of the mechanisms of seizures in neocortical epilepsy.

Cortical excitability and the spread of seizure activity are strongly influenced by subcortical structures [180, 236, 241]. The current model of basal ganglia function in relation to the neocortex is complex, but permits some predictions in man concerning the control of cortical excitability by the striatum (figure 1 .1 2 )[2 4 9 ]. Neocortical input to the striatum is excitatory, and glutamatergic. The striatum also receives an inhibitory, GABAergic, input from the pallidum. The major outputs from striatum are inhibitory, GABAergic outputs to the internal portion of the globus pallidus and the substantia nigra pars reticulata. These latter areas project via GABAergic inhibitory pathways to the ventral anterior and ventral lateral nuclei of the thalamus, which in turn project, via excitatory pathways, to the cortex. Thus, inhibiting the activity of the striatum leads to increased inhibition of the thalamus and hence decreased cortical excitability.

Potentiation of inhibition is associated with an increased number of GABA^-BZRs [1 8 8 ]. Flumazenil volume of distribution (FMZVD), a parameter measurable at the voxel level with PET, is directly correlated with benzodiazepine receptor density and hence acts as an index of GABA^-BZR density.

Using the technique of Statistical Parametric Mapping (SPM), an automated and objective means of comparing groups of images, a group of 10 patients with unilateral frontal lobe epilepsy (FLE) and normal MRI was investigated in order to detect any abnormalities of FMZVD in the cortex and basal ganglia.

1 0 .2 . METHODS

1 0 . 2 . 1 . S u b je c ts

We studied 18 patients who were recruited from the epilepsy clinics of the National Hospital for Neurology and Neurosurgery, Queen Square, London, UK. Clinical details of the patients are summarised in tables 8.1 and 8.2; the individual patient findings were described in Chapter 8. All had partial seizures and had undergone a high resolution MRI protocol including II-w e ig h te d volume acquisition with 1.5mm partitions and both coronal T2-weighted and coronal proton density acquisitions covering the whole brain in contiguous 5mm slices (GE Signa 1.5T). The MRI data had been reported to be normal by an experienced neuroradiologist aware of the clinical information. The data from the same 24 normal subjects as in Chapter 5 were used.

1 0 . 2 . 2 . Scanning p ro to co l

Scans were performed using an ECAT-953B PET scanner (CTI/Siemens, Knoxville) [460]. Data were acquired in 3D mode, with the septa retracted to improve sensitivity [4 2 5 ]. Dual energy window scatter correction [427] was employed.

1 0 . 2 . 3 . D e riv a tio n o f plasm a in p u t fu n c tio n 1 0 . 2 . 4 . D a ta analysis

1 0 . 2 . 5 . P rod uction o f p a ra m e tric maps

These aspects of the method were identical to that used in Chapter 5.

1 0 . 2 . 6 . S ta tis tic a l P a ra m e tric M apping

Images from patients with a unilateral onset in the left hemisphere were flipped so that all subjects with unilateral onset had right-sided foci.

For the comparison of the patient and normal groups, the SPMjt} were transformed to the unit normal distribution (SPMjZ}) and thresholded at p<0.01, p<0.001 and p<0.0001 uncorrected. There was no a priori hypothesis defining the regions to be examined;therefore, to permit analysis of the entire brain volume a correction for multiple non-independent comparisons was made. Each focus exceeding the uncorrected threshold was then characterized in terms of spatial extent (k) [459]. The corrected

For the analysis of correlation between FMZVD and seizure frequency, seizure frequency (total number of all seizure types per month as determined from patients’ prospectively compiled diaries) was included in the model as a covariate of interest in a parametric analysis. The patient data were examined alone. Firstly, all 18 patients were examined for regions where FMZVD correlated significantly with seizure frequency; this analysis was confined to those regions found significant in the group comparison above. Therefore, the SPM{Z} was thresholded at p<0.001, uncorrected. Secondly, the 10 patients with unilateral frontal seizures were examined alone for regions where FMZVD correlated significantly with seizure frequency; this analysis was confined to the frontal cortex. Therefore, the SPM{Z} was thresholded at p<0.001, uncorrected.

The significant regions were then superimposed on an “average normalised” MRI constructed from a voxel-by-voxel mean of the normalised T1 -weighted MRIs of 8 of the normal control group.

1 0 . 3 . RESULTS

Three separate analyses were performed. Thirteen patients had unilateral seizure foci, 7 on the right and 6 on the left; five had bilateral foci or seizures not clearly lateralised. Images from patients with unilateral left-sided foci were flipped so that all unilateral foci were on the right during the group analysis.

The first analysis compared all 18 patients with the 24 normal controls. This revealed FMZVD significantly increased interictally in a number of cortical and subcortical regions. No regions of decreased FMZVD were found. The main regions of increased FMZVD were the ipsilateral motor cortex (highest Z-score in this region 5.68), ipsilateral putamen (Z = 5 .2 1 ), ipsilateral lateral premotor cortex (Z = 4 .8 ), anterior cingulate (Z =5.08), contralateral putamen (Z =4.4), contralateral lateral premotor cortex (Z =4.3 5) and contralateral motor cortex (Z = 3 .9 4 ) (figure 10.1a).

In the second analysis only the data from the 18 patients was examined, looking for regions where FMZVD correlated significantly with seizure frequency, confining attention only to those regions identified in the first analysis. FMZVD correlated negatively with seizure frequency in a number of regions. Three of these regions coincided with anatomical areas found significant in the first analysis; ipsilateral putamen (Z= 3.9 7), cingulate (Z =3.4 5) and ipsilateral premotor cortex (Z = 3.1 ) (figure 10.1b and figure 10.2). No significant positive correlations between FMZVD and seizure frequency were observed when examining all 18 patients together.

In the third analysis only the data from a subgroup of 10 patients with unilateral frontal lobe seizure foci was examined for voxels in which FMZVD correlated significantly with seizure frequency. The analysis was confined to frontal cortex. FMZVD correlated positively with seizure frequency in only one area, a region of ipsilateral frontal cortex, Z=3.76 (figure 10.1c). No significant negative correlations between seizure frequency and FMZVD were found for this subgroup.