Dataset Information

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

ABSTRACT:

Purpose

To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE).

Materials and methods

This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration-cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus.

Results

Quantitative MR imaging-derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%-89.5%) and specificity (92.2%-94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies.

Conclusion

Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice.

SUBMITTER: Farid N

PROVIDER: S-EPMC3401351 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Publications

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

Farid Nikdokht N Girard Holly M HM Kemmotsu Nobuko N Smith Michael E ME Magda Sebastian W SW Lim Wei Y WY Lee Roland R RR McDonald Carrie R CR

Radiology 20120621 2

<h4>Purpose</h4>To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE).<h4>Materials and methods</h4>This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated ...[more]

PMID: 22723496

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Project description:Background and purposeUnilateral mesial temporal lobe epilepsy and hippocampal sclerosis have structural and functional abnormalities in the mesial temporal regions. To gain insight into the pathophysiology of the epileptic network in mesial temporal lobe epilepsy with hippocampal sclerosis, we aimed to clarify the relationships between hippocampal atrophy and the altered connection between the hippocampus and the posterior cingulate cortex in patients with mesial temporal lobe epilepsy with hippocampal sclerosis.Materials and methodsFifteen patients with left mesial temporal lobe epilepsy with hippocampal sclerosis and 15 healthy controls were included in the study. Multicontrast MR imaging, including high-resolution T1WI, diffusion spectrum imaging, and resting-state fMRI, was performed to measure the hippocampal volume, structural connectivity of the inferior cingulum bundle, and intrinsic functional connectivity between the hippocampus and the posterior cingulate cortex, respectively.ResultsCompared with controls, patients had decreased left hippocampal volume (volume ratio of the hippocampus and controls, 0.366% ± 0.029%; patients, 0.277% ± 0.063%, corrected P = .002), structural connectivity of the bilateral inferior cingulum bundle (generalized fractional anisotropy, left: controls, 0.234 ± 0.020; patients, 0.193 ± 0.022, corrected P = .0001, right: controls, 0.226 ± 0.022; patients, 0.208 ± 0.017, corrected P = .047), and intrinsic functional connectivity between the left hippocampus and the left posterior cingulate cortex (averaged z-value: controls, 0.314 ± 0.152; patients, 0.166 ± 0.062). The left hippocampal volume correlated with structural connectivity positively (standardized β = 0.864, P = .001), but it had little correlation with intrinsic functional connectivity (standardized β = -0.329, P = .113). On the contralesional side, the hippocampal volume did not show any significant correlation with structural connectivity or intrinsic functional connectivity (F2,12 = 0.284, P = .757, R2 = 0.045).ConclusionsIn left mesial temporal lobe epilepsy with hippocampal sclerosis, the left inferior cingulum bundle undergoes degeneration in tandem with the left hippocampal volume, whereas intrinsic functional connectivity seems to react by compensating the loss of connectivity. Such insight might be helpful in understanding the development of the epileptic network in left mesial temporal lobe epilepsy with hippocampal sclerosis.

Project description:BackgroundHippocampal sclerosis (HS) is associated with post-surgery outcome in patients with temporal lobe epilepsy (TLE), and an automated method that quantifies HS severity is still lacking. Here, we aim to propose an MRI-based HS index (HSI) that integrates hippocampal volume and FLAIR signal to measure the severity of HS.MethodsForty-two pre-surgery TLE patients were included retrospectively, with T1-weighted (T1W) and FLAIR images acquired from each subject. Two experienced neurosurgeons (W.D. and C.S.) and one neurologist (Q.L.) rated HS severity with a four-class grading scale (normal, mild, moderate and severe) based on both hippocampal volume loss and increased FLAIR signal. A consensus of HS severity for each subject was made by voting among the three visual rating results. Regarding the automatic quantification, the hippocampal volume was quantified by AccuBrain on T1W image, and the FLAIR signal of hippocampus was calculated as the mean intensity of hippocampal region on the FLAIR image (normalized by the mean intensity of gray matter). To fit the HSI from visual rating, we applied ordinal regression with the voted visual rating as the dependent variable, and hippocampal volume and FLAIR signal as the independent variables. The HSI was calculated by weighting the predicted probabilities of the four-class grading scales from ordinal regression.ResultsThe intra-class correlation coefficient (single measure) of the three raters was 0.806. The generated HSI was significantly correlated with the visual rating scales of the three raters (W.D.: 0.823, Q.L.: 0.817, C.S.: 0.717). HSI scores well differentiated the different HS categories as defined by the agreed HS visual rating (normal vs. mild: p < 0.001, mild vs. moderate: p < 0.001, moderate vs. severe: p = 0.001).ConclusionsThe proposed HSI was consistent with visual rating scales from epileptologists and sensitive to HS severity. This MRI-based index may help to evaluate HS severity in clinical practice. Further validations are needed to associate HSI with post-surgery outcomes.

Project description:ObjectiveTo provide a multi-atlas framework for automated hippocampus segmentation in temporal lobe epilepsy (TLE) and clinically validate the results with respect to surgical lateralization and post-surgical outcome.MethodsWe retrospectively identified 47 TLE patients who underwent surgical resection and 12 healthy controls. T1-weighted 3 T MRI scans were acquired for all subjects, and patients were identified by a neuroradiologist with regards to lateralization and degree of hippocampal sclerosis (HS). Automated segmentation was implemented through the Joint Label Fusion/Corrective Learning (JLF/CL) method. Gold standard lateralization was determined from the surgically resected side in Engel I (seizure-free) patients at the two-year timepoint. ROC curves were used to identify appropriate thresholds for hippocampal asymmetry ratios, which were then used to analyze JLF/CL lateralization.ResultsThe optimal template atlas based on subject images with varying appearances, from normal-appearing to severe HS, was demonstrated to be composed entirely of normal-appearing subjects, with good agreement between automated and manual segmentations. In applying this atlas to 26 surgically resected seizure-free patients at a two-year timepoint, JLF/CL lateralized seizure onset 92% of the time. In comparison, neuroradiology reads lateralized 65% of patients, but correctly lateralized seizure onset in these patients 100% of the time. When compared to lateralized neuroradiology reads, JLF/CL was in agreement and correctly lateralized all 17 patients. When compared to nonlateralized radiology reads, JLF/CL correctly lateralized 78% of the nine patients.SignificanceWhile a neuroradiologist's interpretation of MR imaging is a key, albeit imperfect, diagnostic tool for seizure localization in medically-refractory TLE patients, automated hippocampal segmentation may provide more efficient and accurate epileptic foci localization. These promising findings demonstrate the clinical utility of automated segmentation in the TLE MR imaging pipeline prior to surgical resection, and suggest that further investigation into JLF/CL-assisted MRI reading could improve clinical outcomes. Our JLF/CL software is publicly available at https://www.nitrc.org/projects/ashs/.

Dataset Information

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

Purpose

Materials and methods

Results

Conclusion

Publications

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

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