Detection of hippocampal atrophy in patients with temporal lobe epilepsy: a 3-Tesla MRI shape

Chronic Visual Abnormality in an Elderly Patient With Temporal Lobe Epilepsy

A 79-year-old woman visited our department for chronic visual field abnormalities with a floating sensation for two months. Neurological and ophthalmologic examinations yielded normal results, except for brain MRI indicating left hippocampal atrophy. Cognitive function tests were normal. EEG revealed frequent spikes and slow waves in the left frontotemporal region, corroborated by reduced accumulation in 123I-iomazenil single photon emission computed tomography. A diagnosis of temporal lobe epilepsy was established, and treatment with lacosamide resulted in a remarkable improvement in symptoms and EEG findings. Mild focal seizures from the temporal region might cause mild impaired awareness, resulting in the patient's report as a sensation of uncertainty between the self and the outside world, mimicking ophthalmologic abnormalities. The repeated nature of the seizures contributed to the absence of the term "transient" in symptom description. Diagnosing epilepsy in the elderly proves challenging due to nonspecific complaints.

Duration-dependent extensive volume and shape changes of mesolimbic structures in surgically treated unilateral patients with temporal lobe epilepsy

PURPOSE

Although surgical treatment of drug-resistant mesial temporal lobe epilepsy (MTLE) has proven efficacy, surgical referrals are often delayed. Knowledge of the abnormalities of mesolimbic structures beyond the hippocampus may be important for patients with MTLE because of its usefulness in the understanding of progressive disabilities in affected structures. This study aimed to identify volume and shape changes of mesolimbic structures in surgically treated patients with unilateral MTLE and their correlation with various clinical parameters.

METHODS

Twenty-four patients with unilateral MTLE (12 with left MTLE [LMTLE] and 12 with right MTLE [RMTLE]) who were surgically treated with standard temporal lobectomy, including amygdalohippocampectomy, and 24 age- and sex-matched healthy individuals were enrolled. Preoperatively, volumetric analysis using magnetic resonance imaging (MRI) of 27 mesolimbic substructures (11 from each hemisphere and 5 from the midline) was performed. We also investigated the three-dimensional morphometric differences of the mesolimbic structures between the unilateral MTLE and control groups using shape analyses.

RESULTS

Patients with LMTLE showed significant volume reductions in various ipsilateral mesolimbic (72.7%, 8/11) and contralateral structures (27.3%, 3/11). Patients with RMTLE had also significant reduced volumes in ipsilateral (63.6%, 7/11) and contralateral structures (73.3%, 3/11). Among the clinical parameters, only the duration of epilepsy had a statistically significant inverse correlation with the volumes of the hippocampus, parahippocampus, entorhinal cortex, cingulate, and corpus callosum. In the shape analysis of the bilateral hippocampus, amygdala, parahippocampus, and entorhinal cortex, after accounting for the effects of age and total intracranial volume, significant shape changes in the anterolateral area of the ipsilateral hippocampus were noted, which corresponds to the cornu ammonis (CA)1 and subiculum of the hippocampus.

CONCLUSIONS

The extensive volume reductions in the multiple mesolimbic structures and the substantial inverse correlation between the duration of epilepsy and the volumes of the various mesolimbic structures in our study supports that MTLE is not restricted to the hippocampus, but it progressively involves extensive mesolimbic structures. The duration-dependent atrophic changes in multiple subcortical structures seen in this study also suggest a positive role of early surgical intervention for patients with drug-resistant TLE.

Remodeling of brain morphology in temporal lobe epilepsy

BACKGROUND

Mesial temporal lobe epilepsy (TLE) is one of the most widespread neurological network disorders. Computational anatomy MRI studies demonstrate a robust pattern of cortical volume loss. Most statistical analyses provide information about localization of significant focal differences in a segregationist way. Multivariate Bayesian modeling provides a framework allowing inferences about inter-regional dependencies. We adopt this approach to answer following questions: Which structures within a pattern of dynamic epilepsy-associated brain anatomy reorganization best predict TLE pathology. Do these structures differ between TLE subtypes?

METHODS

We acquire clinical and MRI data from TLE patients with and without hippocampus sclerosis (n = 128) additional to healthy volunteers (n = 120). MRI data were analyzed in the computational anatomy framework of SPM12 using classical mass-univariate analysis followed by multivariate Bayesian modeling.

RESULTS

After obtaining TLE-associated brain anatomy pattern, we estimate predictive power for disease and TLE subtypes using Bayesian model selection and comparison. We show that ipsilateral para-/hippocampal regions contribute most to disease-related differences between TLE and healthy controls independent of TLE laterality and subtype. Prefrontal cortical changes are more discriminative for left-sided TLE, whereas thalamus and temporal pole for right-sided TLE. The presence of hippocampus sclerosis was linked to stronger involvement of thalamus and temporal lobe regions; frontoparietal involvement was predominant in absence of sclerosis.

CONCLUSIONS

Our topology inferences on brain anatomy demonstrate a differential contribution of structures within limbic and extralimbic circuits linked to main effects of TLE and hippocampal sclerosis. We interpret our results as evidence for TLE-related spatial modulation of anatomical networks.

Identifying Morphological Patterns of Hippocampal Atrophy in Patients With Mesial Temporal Lobe Epilepsy and Alzheimer Disease

Purpose: Mesial temporal lobe epilepsy (MTLE) and Alzheimer's disease (AD) are two distinct neurological disorders associated with hippocampal atrophy. Our goal is to analyze the morphologic patterns of hippocampal atrophy to better understand the underlying pathological and clinical characteristics of the two conditions.

Methods: Twenty-five patients with AD and 20 healthy controls with matched age and gender were recruited into the AD group. Twenty-three MTLE patients and 28 healthy controls with matched age and gender were recruited into the MTLE group. All subjects were scanned on 3T-MRI scanner. Automated volumetric analysis was applied to measure and compare the hippocampal volume of the two respective groups. Vertex-based morphologic analysis was applied to characterize the morphologic patterns of hippocampal atrophy within and between groups, and a correlation analysis was performed.

Results: Volumetric analysis revealed significantly decreased hippocampal volume in both AD and MTLE patients compared to the controls. In the patients with AD, the mean total hippocampal volume was 32.70% smaller than that of healthy controls, without a significant difference between the left and the right hippocampus (p < 0.05). In patients with MTLE, a significant reduction in unilateral hippocampal volume was observed, with a mean volume reduction of 28.38% as compared with healthy controls (p < 0.05). Vertex-based morphologic analysis revealed a generalized shrinkage of the hippocampi in AD patients, especially in bilateral medial and lateral regions. In MTLE group, atrophy was seen in the ipsilateral head, ipsilateral lateral body and slightly contralateral tail of the hippocampus (FWE-corrected, p < 0.05).

Conclusions: MTLE and AD have distinctive morphologic patterns of hippocampal atrophy, which provide new insight into the radiology-pathology correlation in these diseases.

Automated detection of hippocampal sclerosis using clinically empirical and radiomics features

OBJECTIVE

Temporal lobe epilepsy is a common form of epilepsy that might be amenable to surgery. However, magnetic resonance imaging (MRI)-negative hippocampal sclerosis (HS) can hamper early diagnosis and surgical intervention for patients in clinical practice, resulting in disease progression. Our aim was to automatically detect and evaluate the structural alterations of HS.

METHODS

Eighty patients with pharmacoresistant epilepsy and histologically proven HS and 80 healthy controls were included in the study. Two automated classifiers relying on clinically empirical and radiomics features were developed to detect HS. Cross-validation was implemented on all participants, and specificity was assessed in the 80 controls. The performance, robustness, and clinical utility of the model were also evaluated. Structural analysis was performed to investigate the morphological abnormalities of HS.

RESULTS

The computational model based on clinical empirical features showed excellent performance, with an area under the curve (AUC) of 0.981 in the primary cohort and 0.993 in the validation cohort. One of the features, gray-white matter boundary blurring in the temporal pole, exhibited the highest weight in model performance. Another model based on radiomics features also showed satisfactory performance, with AUC of 0.997 in the primary cohort and 0.978 in the validation cohort. In particular, the model improved the detection rate of MRI-negative HS to 96.0%. The novel feature of cortical folding complexity of the temporal pole not only played a crucial role in the classifier but also had significant correlation with disease duration.

SIGNIFICANCE

Machine learning with quantitative clinical and radiomics features is shown to improve HS detection. HS-related structural alterations were similar in the MRI-positive and MRI-negative HS patient groups, indicating that misdiagnosis originates mainly from empirical interpretation. The cortical folding complexity of the temporal pole is a potentially valuable feature for exploring the nature of HS.

MRI morphology of the hippocampus in drug-resistant temporal lobe epilepsy: Shape inflation of left hippocampus and correlation of right-sided hippocampal volume and shape with visuospatial function in patients with right-sided TLE

We sought to quantify the morphology in vivo of hippocampi in patients with drug resistant temporal lobe epilepsy (TLE) via magnetic resonance imaging (MRI), prior to temporal lobe resection, and the correlation of surface-based shape analysis of morphology and clinical cognitive function. Thirty patients with drug-resistant TLE and twenty healthy controls underwent clinical neuropsychological testing, and brain MRI at Lund University Hospital prior to hippocampal resection. A neuroradiologist categorised radiological findings into normal hippocampus, subtle changes or definite hippocampal sclerosis. We manually segmented MRI of the hippocampus of participants using ANALYZE 11.0 software; and analysed hippocampal shape using SPHARM-PDM software. For radiologist visual-ratings of definite left hippocampal sclerosis in those with left-sided TLE, hippocampal volumes were significantly smaller compared to normal controls. In right-sided TLE we found contralateral shape inflation of the left hippocampus, partially confirming previous shape analytic studies of the hippocampus in TLE. We found significant correlation of volume and surface deflation of the right hippocampus in right-sided TLE with reduced performance on the two right-lateralised visuospatial memory tests, the Rey Complex Figure Test (Immediate and Delayed recall) and the Recognition Memory Test for faces. Decreased hippocampal volume was correlated with poorer performance on these tasks. The morphology of the hippocampus can be quantified via neuroimaging shape analysis in TLE. Contralateral shape inflation of the left hippocampus in right-sided TLE is intriguing, and may result from functional compensation and/or abnormal tissue. In right-sided TLE, hippocampal structural integrity, quantified as hippocampal shape, is correlated with lateralised visuospatial function.

Neuroimaging methods in Epilepsy of Temporal Origin

Background:

Temporal Lobe Epilepsy (TLE) comprises the most common form of symptomatic refractory focal epilepsy in adults. Accurate lateralization and localization of the epileptogenic focus are a significant prerequisite for determining surgical candidacy once the patient has been deemed medically intractable. Structural MR imaging, clinical, electrophysiological, and neurophysiological data have an established role in the localization of the epileptogenic foci. Nevertheless, hippocampal sclerosis cannot be detected on MR images in more than 30% of patients with TLE, and the presurgical assessment remains controversial. </P><P> Discussion: In the last years, advanced MR imaging techniques, such as 1H-MRS, DWI, DTI, DSCI, and fMRI, may provide valuable additional information regarding the physiological and metabolic characterization of brain tissue. MR imaging has shifted towards functional and molecular imaging, thus, promising to improve the accuracy regarding the lateralization and the localization of the epileptogenic focus. Additionally, nuclear medicine studies, such as SPECT and PET imaging modalities, have become an asset for the decoding of brain function and activity, and can be diagnostically helpful as well, since they provide valuable data regarding the altered metabolic activity of the seizure foci.

Conclusion:

Overall, advanced MRI, SPECT, and PET imaging techniques are increasingly becoming an essential part of TLE diagnostics, when the epileptogenic area is not identified on structural MRI or when structural MRI, clinical, and electrophysiological findings are not in concordance.

Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis

Purpose: Magnetic resonance imaging (MRI) and positron emission tomography (PET) with ¹⁸F-fluorodeoxyglucose (¹⁸FDG) are valuable tools for evaluating hippocampal sclerosis (HS); however, bias may arise during visual analyses. The aim of this study was to evaluate and compare MRI and PET post-processing techniques, automated quantitative hippocampal volume (Q-volume), and fluid-attenuated inversion-recovery (FLAIR) signal (Q-FLAIR) and glucose metabolism (Q-PET) analyses in patients with HS.

Methods: We collected MRI and ¹⁸FDG-PET images from 54 patients with HS and 22 healthy controls and independently performed conventional visual analyses (CVA) of PET (CVA-PET) and MRI (CVA-MRI) images. During the subsequent quantitative analyses, the hippocampus was segmented from the 3D T1 image, and the mean volumetric, FLAIR intensity and standardized uptake value ratio (SUVR) values of the left and right hippocampus were assessed in each subject. Threshold confidence levels calculated from the mean volumetric, FLAIR intensity and SUVR values of the controls were used to identify healthy subjects or subjects with HS. The performance of the three methods was assessed using receiver operating characteristic (ROC) curves, and the detection rates of CVA-MRI, CVA-PET, Q-volume, Q-FLAIR, and Q-PET were statistically compared.

Results: The areas under the curves (AUCs) for the Q-volume, Q-FLAIR, and Q-PET ROC analyses were 0.88, 0.41, and 0.98, which suggested a diagnostic method with moderate, poor, and high accuracy, respectively. Although Q-PET had the highest detection rate among the two CVA methods and three quantitative methods, the difference between Q-volume and Q-PET did not reach statistical significance. Regarding the HS subtypes, CVA-MRI, CVA-PET, Q-volume, and Q-PET had similar detection rates for type 1 HS, and Q-PET was the most sensitive method for detecting types 2 and 3 HS.

Conclusions: In MRI or ¹⁸FDG-PET images that have been visually assessed by experts, the quantification of hippocampal volume or glucose uptake can increase the detection of HS and appear to be additional valuable diagnostic tools for evaluating patients with epilepsy who are suspected of having HS.

The hippocampal network model: A transdiagnostic metaconnectomic approach

Purpose

The hippocampus plays a central role in cognitive and affective processes and is commonly implicated in neurodegenerative diseases. Our study aimed to identify and describe a hippocampal network model (HNM) using trans-diagnostic MRI data from the BrainMap® database. We used meta-analysis to test the network degeneration hypothesis (NDH) (Seeley et al., 2009) by identifying structural and functional covariance in this hippocampal network.

Methods

To generate our network model, we used BrainMap's VBM database to perform a region-to-whole-brain (RtWB) meta-analysis of 269 VBM experiments from 165 published studies across a range of 38 psychiatric and neurological diseases reporting hippocampal gray matter density alterations. This step identified 11 significant gray matter foci, or nodes. We subsequently used meta-analytic connectivity modeling (MACM) to define edges of structural covariance between nodes from VBM data as well as functional covariance using the functional task-activation database, also from BrainMap. Finally, we applied a correlation analysis using Pearson's r to assess the similarities and differences between the structural and functional covariance models.

Key findings

Our hippocampal RtWB meta-analysis reported consistent and significant structural covariance in 11 key regions. The subsequent structural and functional MACMs showed a strong correlation between HNM nodes with a significant structural-functional covariance correlation of r = .377 (p = .000049).

Significance

This novel method of studying network covariance using VBM and functional meta-analytic techniques allows for the identification of generalizable patterns of functional and structural abnormalities pertaining to the hippocampus. In accordance with the NDH, this framework could have major implications in studying and predicting spatial disease patterns using network-based assays.

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We derived regions that structurally co-vary with the hippocampus in a network model using a transdiagnostic meta-analytic approach.

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We used meta-analytic connectivity mapping to assess inter-regional connectivity from BrainMap's structural and functional databases.

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We tested the network degeneration hypothesis by identifying network correlations between structural and functional networks.

Volumetric Changes in Hippocampal Subregions and Memory Performance in Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis

In the present study we explored the different patterns of volumetric atrophy in hippocampal subregions of patients with left and right mesial temporal lobe epilepsy with hippocampal sclerosis (TLE-HS). Meanwhile, the memory impairment patterns in Chinese-speaking TLE-HS patients and potential influencing factors were also determined. TLE-HS patients (21 left and 17 right) and 21 healthy controls were recruited to complete T2-weighted imaging and verbal/nonverbal memory assessment. The results showed that both left and right TLE-HS patients had overall reduced hippocampal subregion volumes on the sclerotic side, and cornu ammonis sectors (CA1) exhibited maximum atrophy. The verbal memory of left TLE-HS patients was significantly impaired (P < 0.001) and was not associated with the volumes of the left hippocampal subregions. Verbal or nonverbal memory impairment was not found in the patients with right TLE-HS. These results suggested that the atrophy of hippocampal subregion volumes cannot account for the verbal memory impairment, which might be related to the functional network.

Progression of gray matter atrophy in seizure-free patients with temporal lobe epilepsy

OBJECTIVES

To investigate the presence and progression of gray matter (GM) reduction in seizure-free patients with temporal lobe epilepsy (TLE).

METHODS

We enrolled 39 consecutive TLE patients, seizure-free for at least 2 years--20 with magnetic resonance imaging (MRI) signs of hippocampal sclerosis (TLE-HS), 19 with normal MRI (TLE-NL), and 74 healthy controls. For longitudinal analysis, we included individuals who had a second MRI with minimum interval of 18 months: 21 patients (10 TLE-HS, 11 TLE-NL) and 11 controls. Three-dimensional (3D) T1 -weighted images acquired in 3 Tesla MRI were analyzed with voxel-based morphometry (VBM). The images of patients with right-sided interictal epileptogenic zone (EZ) were right-left flipped, as well as a comparable proportion of controls. Cross-sectional analysis: The patients' images from each group were compared to controls to investigate differences in GM volumes. Longitudinal analysis: The first and second images were compared in each group to look for decreased GM volume.

RESULTS

Cross-sectional analysis: Patients with TLE-HS had diffuse GM atrophy, including hippocampus and parahippocampal gyrus, insula, frontal, and occipital lobes ipsilateral to EZ, bilateral thalamus and contralateral orbitofrontal gyrus, and caudate. In contrast, TLE-NL group did not present significant differences compared to controls. Longitudinal analysis: TLE-HS presented progressive GM reduction in ipsilateral insula and occipital lobe, contralateral motor area, and bilateral temporal and frontal lobes. TLE-NL had GM progression in ipsilateral hypothalamus and parietal lobe, contralateral cerebellum, and bilateral temporal lobe. Controls did not show changes in GM volume between MRIs.

SIGNIFICANCE

Diffuse extrahippocampal GM atrophy is present in seizure-free patients with TLE-HS. In addition, there is progressive GM atrophy in patients with and without HS. These results demonstrate that not only ongoing seizures are involved in the progression of GM atrophy. An underlying pathologic mechanism could be responsible for progressive brain volume loss in TLE patients even in seizure-free periods.

3-T magnetic resonance imaging simultaneous automated multimodal approach improves detection of ambiguous visual hippocampal sclerosis

BACKGROUND AND PURPOSE

To evaluate if an automatic magnetic resonance imaging (MRI) processing system may improve detection of hippocampal sclerosis (Hs) in patients with mesial temporal lobe epilepsy (MTLE).

METHODS

Eighty consecutive patients with a diagnosis of MTLE and 20 age- and sex-matched controls were prospectively recruited and included in our study. The entire group had 3-T MRI visual assessment of Hs analysed by two blinded imaging epilepsy experts. Logistic regression was used to evaluate the performances of neuroradiologists and multimodal analysis.

RESULTS

The multimodal automated tool gave no evidence of Hs in all 20 controls and classified the 80 MTLE patients as follows: normal MRI (54/80), left Hs (14/80), right Hs (11/80) and bilateral Hs (1/80). Of note, this multimodal automated tool was always concordant with the side of MTLE, as determined by a comprehensive electroclinical evaluation. In comparison with standard visual assessment, the multimodal automated tool resolved five ambiguous cases, being able to lateralize Hs in four patients and detecting one case of bilateral Hs. Moreover, comparing the performances of the three logistic regression models, the multimodal approach overcame performances obtained with a single image modality for both the hemispheres, reaching a global accuracy value of 0.97 for the right and 0.98 for the left hemisphere.

CONCLUSIONS

Multimodal quantitative automated MRI is a reliable and useful tool to depict and lateralize Hs in patients with MTLE, and may help to lateralize the side of MTLE especially in subtle and uncertain cases.