Automated MRI brain image analysis techniques, such as voxel-based morphometry (VBM) (Ashburner & Friston, 2000), offer advantages over subjective techniques (e.g., visual inspection) and have been employed to detect subtle anatomical anomalies in individual neurological patients compared to healthy controls (Bernasconi et al., 2004; Mehta, Grabowski, Trivedi, & Damasio, 2003; Wilke, Kassubek, Ziyeh, Schulze-Bonhage, & Huppertz, 2003). Morphometric analysis of structural MRI has become a widely used and established approach to study normal brain development and neurological diseases. T1-weighted images are primarily used to study gray matter properties, whereas diffusion tensor imaging (DTI) is employed in the investigation of white matter features.

Whereas most conventional clinical MRI review is performed by visual inspection of images slice by slice, quantitative MRI involves 3D image acquisition and systematic quantification of brain morphology, typically across the entire brain. Brain structures may be traced manually for volumetric estimation; however, as this is very labor-intensive, it is not feasible in a clinical setting and therefore largely constrained to research studies. The availability of increased computing power and advancements in signal processing in medical imaging has enabled automatic quantification of brain structures with minimal user intervention and, crucially, within reasonable time frames. Importantly, quantitative MRI has the potential to detect subtle abnormalities in an individual patient by comparing metrics derived from a single scan to large normal control data sets.

VBM investigations have identified widespread cortical and subcortical abnormalities associated with temporal lobe epilepsy that are not apparent upon visual inspection. In addition to hippocampal atrophy (Bernasconi et al., 2003; Salmenperä, Kälviäinen, Partanen, & Pitkänen, 2001), structural abnormalities are found in the entorhinal cortex (Bonilha et al., 2007), fornix (Kuzniecky et al., 1999), parahippocampal gyrus (Bernasconi et al., 2003), amygdala (Bernasconi et al., 2003; Salmenperä et al., 2001), basal ganglia (Dreifuss et al., 2001), thalamus (DeCarli et al., 1998), lateral temporal lobe (Jutila et al., 2001; J. W. Lee et al., 1998; Moran, Lemieux, Kitchen, Fish, & Shorvon, 2001), and cerebellum (Sandok, O’Brien, Jack, & So, 2000). As summarized in a comprehensive review of VBM group studies comparing patients with TLE to healthy controls (Keller & Roberts, 2008), hippocampal atrophy ipsilateral to the seizure focus and bilateral thalamic atrophy are common findings; however, several neocortical abnormalities can also be observed. Such findings are consistent with the diverse cognitive deficits demonstrated in TLE outside of memory impairment (Hermann, Lin, Jones, & Seidenberg, 2009). However, widespread neocortical atrophy associated with seizure burden must be differentiated from the presence of dual pathology, as the presence of extratemporal structural abnormalities is associated with a reduction in the likelihood of seizure freedom following a mesial temporal resection (Sisodiya et al., 1997).

VBM methods have also been applied to the characterization of focal cortical abnormalities in individuals with visually apparent malformations of cortical development. In one study, VBM identified gray matter abnormalities in 79 % of visually identified FCDs, as well as abnormalities extending beyond the known lesion (Colliot et al., 2006). In another investigation, 9 out of 11 patients showed significant gray matter concentration excess that was correspondent to the visually detected FCD (Leonardo Bonilha et al., 2006). VBM methods have also reliably identified regions of increased T2 signal that correspond to visually identified MCDs in 18 out of 20 patients (Rugg-Gunn, Boulby, Symms, Barker, & Duncan, 2005). Importantly, all of these studies identified additional gray matter abnormalities that were not apparent to the visual eye. However, the epileptogenic potential of such putatively occult lesions was not demonstrated, and the detection of so-called “MRI-negative” lesions remains an active area of research.

Consistent with VBM studies, surface-based methods have identified widespread neocortical abnormalities associated with mesial temporal lobe epilepsy (MTLE), particularly cortical thinning of the frontal and lateral temporal regions (Lin et al., 2007; McDonald et al., 2008b). Greater asymmetries in cortical thickness have been observed in the medial temporal cortex of MTLE patients relative to controls, with more abnormalities in the regions ipsilateral to the seizure focus (Bernhardt et al., 2008; Lin et al., 2007; McDonald et al., 2008b). Ipsilateral abnormalities are also apparent in frontal regions (Bernhardt et al., 2008). However, both cortical thinning and reduction in cortical complexity are found in bilateral extratemporal regions, even in the case of unilateral seizure foci (Lin et al., 2007). Interestingly, differential patterns of neocortical thinning are observed in TLE with MTS (TLE-MTS) and TLE without MTS (TLE-no), with more thinning in the inferior medial and posterior temporal regions in TLE-MTS and more thinning in lateral temporal and opercular regions in TLE-no (Mueller et al., 2009). This suggests that surface features can help to distinguish whether differential epileptogenic networks might be involved in TLE with and without MTS. An exciting area for further research would be to determine whether there is a relationship between these differential patterns of cortical thinning and different patterns of performance on neuropsychological tests (e.g., greater memory deficits associated with MTS and greater word-finding difficulties associated with MTS-no).

Studies on the relationship between surface-based measures of neocortical abnormalities and cognitive dysfunction in TLE are only beginning to emerge. A relationship between cortical thinning and general cognitive phenotypical patterns has been recently demonstrated. Increasing abnormalities in temporal and extratemporal cortical thickness were found to distinguish between different cognitive phenotypes (minimally impaired; memory impaired; memory, executive function, and speed impaired) in a stepwise fashion, with the most cognitively impaired group demonstrating the most significant cortical thinning (Dabbs, Jones, Seidenberg, & Hermann, 2009).

Also consistent with VBM studies, surface-based methods can be used to detect cortical abnormalities associated with MCDs. Surface-based methods have identified that areas of focal cortical dysplasia can be preferentially located at the bottom of abnormally deep sulci (Besson, Andermann, Dubeau, & Bernasconi, 2008), a finding which may be used to direct the search for developmental abnormalities, particularly when MRI features are only mildly abnormal or absent. Uniquely, surface-based methods can characterize subtle surface features, such as cortical thickening, blurred gray-white matter boundary, and hyperintense T1 signal (Besson, Bernasconi, Colliot, Evans, & Bernasconi, 2008). These characteristic features, particularly in combination, can be used to detect subtle abnormalities that escape visual detection. Figure 7.2 shows an example of a 38-year-old female patient who had suffered from epilepsy all her life. Several past MRIs showed no sign of a focal lesion until she was referred to our epilepsy center, and a small T2-FLAIR abnormality was discovered in her right mesial frontal lobe. Quantitative comparison revealed significant thickening and blurring in the same region, imaging features consistent with focal cortical dysplasia. The epileptogenic character of the region was subsequently confirmed by intracranial electrophysiology, as well as pathology and outcome after resection.

Automatic subcortical segmentation methods have had as high as a 74 % accuracy rate in the lateralization of epilepsy through hippocampal volumetric comparisons, compared to 78 % with manual segmentation methods (Akhondi-Asl, Jafari-Khouzani, Elisevich, & Soltanian-Zadeh, 2010). Reductions in hippocampal volumes ipsilateral to seizure focus in MTLE have been identified, along with bilateral reductions in thalamic and cerebellar gray matter volumes (McDonald et al., 2008a). Some companies, like San Diego-based CorTechs, Inc., offer FDA-approved user-friendly processing and visualization of quantitative MRI morphometry with automatic report generation, which are reimbursable by insurance companies. An example where quantitative analysis offered increased accuracy compared to visual inspection alone is shown by a patient evaluated at our center for presurgical evaluation and who had undergone a full epilepsy MRI protocol. The clinical MRI report indicated right hippocampal atrophy. However, when a subcortical segmentation was performed and the patient’s hippocampal volumes were compared to 40 normal controls, it was evident that both hippocampi were severely atrophied, with more atrophy seen in the right hemisphere (Fig. 7.3).

A general decrease in white matter volume in chronic TLE has been well documented; however, DTI allows for the investigation of specific fiber tract integrity. Bilateral symmetrical reduction in fractional anisotropy (FA) is observed in the fornix and cingulum of patients with TLE (Concha, Beaulieu, & Gross, 2005), as well as frontotemporal white matter tracts (arcuate fasciculus and uncinate fasciculus) (Lin, Riley, Juranek, & Cramer, 2008; Matsumoto et al., 2008; Rodrigo et al., 2007), temporal-occipital connections (inferior longitudinal fasciculus), frontal-occipital connections (inferior frontal-occipital fasciculus) (Ahmadi et al., 2009), and the corpus callosum (Arfanakis et al., 2002; Concha, Beaulieu, Collins, & Gross, 2009). Patients with left TLE have greater, more diffuse changes in FA values across multiple fiber tracts, whereas patients with right TLE showed changes that are primarily ipsilateral to the side of seizure onset (Ahmadi et al., 2009).

Consistent with cortical abnormalities found in TLE, whole-brain voxelwise analysis of DTI data has revealed extensive bilateral white matter diffusion abnormalities in the frontal and temporal lobes, with more involvement in the hemisphere ipsilateral to seizure onset (Shon et al., 2010; Thivard et al., 2005). In TLE patients with left- and right-sided resective surgery, widespread tract degradation was observed in the uncinate fasciculus, the fronto-occipital fasciculus, the superior longitudinal fasciculus, the corpus callosum, and the corticospinal tract (Schoene-Bake et al., 2009). Furthermore, tract degradation has been shown to be associated with memory and language impairments in TLE patients (McDonald et al., 2008), suggesting that DTI can provide important information for predicting cognitive status in individuals with epilepsy (Table 7.2).