Study participants (N = 115) included patients with temporal lobe epilepsy (n = 53) and healthy controls (n = 62). Initial selection criteria for the epilepsy patients included the following: (a) chronologic age from 14 to 60 years, (b) complex partial seizures of definite or probable temporal lobe origin, (c) absence of MRI abnormalities other than atrophy on clinical reading, and (d) no other neurologic disorder. A board-certified neurologist with special expertise in epileptology (P.R., R.S., K.R.) reviewed patients' medical records. This review, blinded to all quantitative imaging and cognitive data, included seizure semiology, previous EEGs, clinical neuroimaging reports, and all available medical records. Based on this review, each patient was classified as having complex partial seizures of definite, probable, or possible temporal lobe origin. Definite temporal lobe epilepsy was defined by continuous video-EEG monitoring of spontaneous seizures demonstrating temporal lobe onset; probable temporal lobe epilepsy was determined by review of clinical semiology with features reported to identify reliably complex partial seizures of temporal lobe origin versus onset in other regions (e.g., frontal) in conjunction with interictal EEGs, neuroimaging findings, and developmental and clinical history. Only those meeting criteria for definite and probable temporal lobe epilepsy proceeded to recruitment for study participation; patients with possible temporal lobe epilepsy were excluded.
There were no significant differences between patients with definite versus probable temporal lobe epilepsy in regard to demographic characteristics (age, gender, education), core clinical seizure features (age at onset, duration of epilepsy), quantitative MRI volumetric measurements (total tissue volume, total gray- and white-matter volume, total lobar volumes, total hippocampal volumes), or neuropsychological test performance across the administered battery. They were therefore combined for comparison with healthy controls. The results of MRI and cognitive comparisons between healthy controls and temporal lobe patients who underwent ictal monitoring are nonetheless reported in the Results section, in that the latter represent the gold standard for localization of seizure onset.
Selection criteria for healthy controls included the following: (a) chronologic age from 14 to 60 years, (b) either a friend or family member of the patient, (c) no current substance abuse or medical or acute psychiatric condition that could affect cognitive functioning, and (d) no psychotropic medications, loss of consciousness (LOC) >5 min, or history of developmental learning disorder. Chronologic age was closely comparable in the epilepsy and controls groups including means (33.4 vs. 34.1), medians (31.0 vs. 33.8), ranges (14–59 in both groups), and 95% confidence intervals (30.2–36.6 vs. 31.1–37.1). Other distributional characteristics (e.g., skewness, kurtosis) also were comparable, and we could find no evidence of asymmetric distributions or extreme outliers. The project was reviewed and approved by the University of Wisconsin Human Subjects Committee. All subjects were fully informed regarding the nature and purpose of the investigation, questions were answered, and signed consent was obtained.
Patients were interviewed, in the presence of a friend or family member whenever possible, regarding details of their epilepsy history and clinical course. Medical records were requested concerning all previous epilepsy-related hospitalizations, and records were requested from physicians who had treated the patients' epilepsy on an outpatient basis. These records were reviewed and abstracted by an individual blinded to the MRI and neuropsychological findings.
All participants underwent comprehensive neuropsychological assessment and high-resolution MRI with quantitative volumetric processing. Epilepsy patients were initially dichotomized into early (n = 37) and late (n = 16) age at onset groups based on a median split of epilepsy onset age (14 years) in the larger database of temporal lobe epilepsy patients from which this sample was selected. This resulted in groups with very disparate ages of seizure onset (mean early onset, 7.8 years; mean late onset, 23.3 years). The current consecutive sample was selected for study because quantitative MRI volumetric processing had been completed. Late age-at-onset patients with clear histories of early initial precipitating injuries (n = 7) were not included, as we were interested specifically in the effects of age at onset of recurrent seizures on brain structure and cognition. However, secondary analyses examined the potential relevance of early initial precipitating injuries.
Table 1 provides basic demographic and clinical seizure features of the subjects. Patients with childhood-onset temporal lobe epilepsy and healthy controls did not differ in chronologic age (p = 0.43), but both were significantly (p < 0.05) younger than late-onset patients. Early-onset temporal lobe epilepsy patients had significantly (p < 0.05) less education than both healthy controls and late-onset patients. Comparing the temporal lobe epilepsy groups, early-onset patients had a significantly earlier age at onset, as expected (7.8 vs. 23.3 years; p ≤ 0.001), and both temporal lobe epilepsy groups had chronic epilepsy, as evident from the long duration of seizures in each group (23.6 and 16.2 years), with significantly longer duration in the early-onset patients (p = 0.04). There was no significant difference in gender distribution across the groups (p = 0.39). The analyses to be described controlled for these demographic and clinical characteristics.
Table 1. Demographic and clinical characteristics of epilepsy patients and healthy controls
|Age (yr)||33.4 (12.6)||31.4 (11.6)||39.6 (10.5)|
|Education (yr)||13.6 (2.4)||12.4 (2.0)||13.7 (2.3)|
|Age at onset (yr)||—||7.8 (3.6)||23.3 (7.3)|
|Duration of epilepsy (yr)||—||23.6 (12.5)||16.2 (10.0)|
Images were obtained on a 1.5-Tesla GE Signa MRI scanner. Sequences acquired for each subject included (a) T1-weighted, three-dimensional SPGR acquired with the following parameters: TE = 5, TR = 24, flip angle = 40, NEX = 2, FOV = 26, slice thickness = 1.5 mm, slice plane = coronal, matrix = 256 × 192; (b) proton density (PD); and (c) T2-weighted images acquired with the following parameters: TE = 36 ms (for PD) or 96 ms (for T2), TR = 3,000 ms, NEX = 1, FOV = 26, slice thickness = 3.0 mm, slice plane = coronal, matrix = 256 × 192, and an echo train length = 8.
MRIs were acquired at the University of Wisconsin and transferred to the Image Processing Laboratory of the Mental Health Clinical Research Center at the University of Iowa, where they were processed by using a semiautomated software package [i.e., Brain Research: Analysis of Images, Networks, and Systems (BRAINS)](29–31). University of Iowa staff were blinded to the clinical and sociodemographic characteristics of the subjects. The T1-weighted images were spatially normalized so that the anterior–posterior axis of the brain was realigned parallel to the ACPC line, and the interhemispheric fissure was aligned on the other two axes. A 6-point linear transformation was used to warp the standard Talairach atlas space onto the resampled image. Images from the three pulse sequences were then co-registered by using a local adaptation of automated image registration software (32). After alignment of the image sets, the PD and T2 images were resampled into 1-mm cubic voxels, after which an automated algorithm classified each voxel into gray matter, white matter, CSF, blood, or “other”(33). The brains were then “removed” from the skull by using a neural network application that had been trained on a set of manual traces (31). Manual inspection and correction of the output of the neural network tracing was conducted. A stereotaxic method based on the Talairach atlas (34) yields measures of left and right frontal, temporal, parietal, and occipital lobes and cerebellum (35). The BRAINS software and procedures have been shown to be of high interrater reliability, intrarater reliability, and scan–rescan reproducibility, particularly for the MRI indices that are the focus of this study (29–31,33). MRI regions of interest for this investigation included total (supratentorial) cerebrum tissue volume including segmented gray- and white-matter volumes and total CSF. Total lobar tissue volumes and segmented gray- and white-matter volumes also were examined.
Patients and healthy controls were administered a comprehensive test battery that included standard clinical measures of intelligence (36), language [naming (37), fluency (38)], visuoperceptual/spatial skills [facial discrimination, spatial orientation (39)], memory [verbal (40) and nonverbal (41)], and executive functions [novel problem solving (42) and speeded psychomotor processing (43)]. Table 2 depicts the cognitive domains and specific abilities assessed as well as the test measures.
Table 2. Neuropsychological test battery
|WAIS-III Verbal IQ |
WAIS-III Performance IQ
WAIS-III Full-scale IQ
|Language||Confrontation naming |
|Boston Naming Testa|
Controlled Oral Word Fluencya
|Visuoperceptual||Facial discrimination |
|Facial Recognition Testa|
Judgment of Line Orientationa
|Memory||Verbal memory |
|Verbal Selective Reminding Testb|
Nonverbal Selective Reminding Testb
|Executive function||Problem solving |
Speeded psychomotor processing
|Wisconsin Card-Sorting Testc|
Trail-making Tests A and Bd
Data were analyzed primarily by multivariate analyses of covariance to control for pertinent clinical and demographic differences, as well as to minimize the possibility of Type 1 error. Post hoc pair-wise comparisons were tested at p = 0.05 by using two-tailed tests.