Hippocampal Magnetic Resonance Imaging Research Articles

The association between childhood adversity and hippocampal volumes is moderated by romantic relationship experiences

AbstractReduced hippocampal volumes are a feature of many mental disorders. Childhood maltreatment is a known risk factor for the development of psychopathology and has consistently been linked to hippocampal volume reductions in adults, but not in children and adolescents. We propose that maltreatment‐related difficulties in coping with developmental tasks in adolescence and young adulthood might underlie the delayed emergence of hippocampal volume reductions in maltreated individuals. In a study with 196 healthy young adults (mean age [years]: 24.0 ± 3.2, 50% female, 20.6% living with a partner (missings: n = 2)), we investigated the interaction between childhood maltreatment (Childhood Trauma Screener) and the breakup of a steady romantic relationship (List of Threatening Experiences Questionnaire) on hippocampal magnetic resonance imaging grey matter volumes. The experience of a romantic relationship breakup moderated the association between childhood maltreatment and bilateral hippocampal volumes, revealing more negative associations with hippocampal volumes in participants with at least one breakup compared to those with no breakup experience (right hippocampus: β = − 0.05 ± 0.02, p = 0.031, p (FDR) = 0.031; left hippocampus: β = −0.06 ± 0.02, p = 0.005, p (FDR) = 0.009). Moreover, our findings provide some evidence that childhood maltreatment is related to smaller bilateral hippocampal volumes only in those adults who suffered from a relationship breakup (right hippocampus: β = −0.23 ± 0.10, p = 0.018, p (FDR) = 0.018; left hippocampus: β = −0.24 ± 0.10, p = 0.016, p (FDR) = 0.018;). Our study highlights the interaction of adult social bonds with early adversity on vulnerability to psychopathology.

Exploring the cognitive assessment potential of MRI-based volumetric hippocampal segmentation in Parkinson's disease.

To investigate the potential of magnetic resonance imaging (MRI)-based total and segmental hippocampus volume analysis in the assessment of cognitive status in Parkinson's disease (PD). We divided participants into three groups Group A-Parkinson patients (Pp) with normal cognitive status (n=25), Group B-Pp with dementia (n=17), and Group C-healthy controls (n=37). Three-dimensional T1W Fast Spoiled Gradient Recalled Echo images were used for Volbrain hippocampus subfield segmentation. We used the "Winterburn" protocol, which divides the hippocampus into five segments, Cornu Ammonis (CA),CA2/CA3, CA4/dentate gyrus, stratum radiatum, lacunosum, and moleculare, and subiculum. A total of 79 participants were included in the study, consisting of 42 individuals with PD (64.2% male) and 37 healthy controls (54.1% male). The mean age of PD was 60.9±10.7 years and the mean age of control group was 59.27±12.3 years. Significant differences were found in total hippocampal volumes between Group A and B (p=.047. Statistically significant group differences were found in total, right, and left CA1 volumes (analysis of variance [ANOVA]: F(2,76)=8.098, p=.001; F(2,76)=7.628, p=.001; F(2,76)=5.084, p=.008, respectively), as well as in total subiculum volumes (ANOVA: F(2,76)=4.368, p=.016). Post hoc tests showed that total subiculum volume was significantly lower in individuals with normal cognitive status (0.474±0.116cm3) compared to healthy controls (0.578±0.151cm3, p=.013). Volumetric hippocampal MRI can be used to assess the cognitive status of Pp. Longitudinal studies that evaluate Pp who progress from normal cognition to dementia are required to establish a causal relationship.

Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease

Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = -0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = -0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.

Genetic dissection of Hippocampal sclerosis MRI surrogates

AbstractBackgroundHippocampal sclerosis of aging (HS) is one of the most predominant causes of dementia in elder populations and it is often misdiagnosed as Alzheimer’s disease (AD). HS has recently been found to show a hippocampal atrophy pattern that might be key for the differentiation of this pathology from AD in the early stages of dementia.MethodIn this study, we aimed to find SNPs associated with AD diagnosis that might be related to HS. To that end, we calculated a polygenic risk score (PRS) combining SNPs associated with AD by Bellenguez et al. (2022) and assessed their relation with HS‐by‐proxy based on magnetic resonance imaging (MRI) data of hippocampal subfield volumes from 1,130 individuals without dementia syndrome.ResultOur results show a significant association of AD‐PRS with fimbria and hippocampal body and head volumes. Association with these hippocampal subfields was also observed on the individual effects of the AD‐related variants in the SHARPIN (rs34173062) and TNIP1 (rs871269) genes. Besides, these loci remained consistently associated to HS‐aging after increasing the sample size by including an independent cohort of healthy individuals (N = 729).ConclusionThe results presented in this study suggest that some SNPs that have recently been identified as AD variants might be closely related to atrophy in hippocampal subfields instead of AD, and hence, could be instrumental to refine AD and HS pathways, their interrelationships, and to elaborate specific treatment for each condition.

3D Pre-Processing Algorithm for MRI Images of Different Stages of AD

Alzheimer’s disease (AD) is a degenerative neuronal brain disorder resulting in memory loss, skills, and cognitive changes. The disorder’s primary diagnostic tests are defined as total brain atrophy and hippocampal atrophy. Early diagnosis is significant, and automatic systems design is necessary for this disorder. Potential biomarkers for AD are described using a hippocampal magnetic resonance imaging volumetry system with certain limitations. For the definite identification of the hippocampus region, pre-processing of the 3D MRI images of AD is necessary. The filtering and histogram-based pre-processing techniques enhance the region of interest, which helps in effectively segmenting the biomarker, the hippocampus. The median and eight histogram clippings are defined to be 98% efficient pre-processing techniques with the comparison of image quality parameters and statistical analysis. Thus an algorithm for pre-processing of the 3D MRI images of stages of AD is designed for the further process of identification.

Predicting Alzheimer's Disease and Quantifying Asymmetric Degeneration of the Hippocampus Using Deep Learning of Magnetic Resonance Imaging Data.

In order to quantify lateral asymmetric degeneration of the hippocampus for early predicting Alzheimer's disease (AD), we develop a deep learning (DL) model to learn informative features from the hippocampal magnetic resonance imaging (MRI) data for predicting AD conversion in a time-to-event prediction modeling framework. The DL model is trained on unilateral hippocampal data with an autoencoder based regularizer, facilitating quantification of lateral asymmetry in the hippocampal prediction power of AD conversion and identification of the optimal strategy to integrate the bilateral hippocampal MRI data for predicting AD. Experimental results on MRI scans of 1307 subjects (817 for training and 490 for validation) have demonstrated that the left hippocampus can better predict AD than the right hippocampus, and an integration of the bilateral hippocampal data with the instance based DL method improved AD prediction, compared with alternative predictive modeling strategies.

Study of the human hippocampal formation: a method for histological and magnetic resonance correlation in perinatal cases.

Little information is available on the magnetic resonance imaging (MRI) determination of the hippocampal formation (HF) during the perinatal period. However, this exploration is increasingly used, which requires defining visible HF landmarks on MRI images, validated through histological analysis. This study aims to provide a protocol to identify HF landmarks on MRI images, followed by histological validation through serial sections of the temporal lobe of the samples examined, to assess the longitudinal extent of the hippocampus during the perinatal period. We examined ex vivo MRI images from nine infant control brain samples. Histological validation of the hippocampal formation MRI images was obtained through serial sectioning and examination of Nissl-stained sections at 250μm intervals along the entire length of the hippocampal formation. Up to six landmarks were identified both in MRI images and the serial histological sections. Proceeding in an anterior to posterior (rostrocaudal) direction, these were as follows: 1) the limen insulae (fronto-temporal junction); 2) the beginning of the amygdaloid complex; 3) the beginning of the lateral ventricle; 4) the caudal limit of the uncus, indicated by the start of the lateral geniculate nucleus (at the level of the gyrus intralimbicus); 5) the end of the lateral geniculate nucleus (beginning of the pulvinar); and 6) the beginning of the fornix. After histological validation of each of these landmarks, the full longitudinal length of the hippocampal formation and distances between landmarks were calculated. No statistically significant differences were found in total length or between landmarks. While the HF is anatomically organized at birth, its annotation is particularly challenging to perform. The histological validation of HF landmarks allows a better understanding of MRI images. The proposed protocol could be useful to assess MRI hippocampal quantification in children and possible variations due to different neurological diseases.

Changes in Measures of Vestibular and Balance Function and Hippocampus Volume in Alzheimer's Disease and Mild Cognitive Impairment.

To test the hypotheses that people with Alzheimer's disease and mild cognitive impairment have increased frequency of vestibular impairments and decreased hippocampal volume compared with healthy age-matched controls. Retrospective, with some historical controls. Out-patient, tertiary care center. People with mild to moderate dementia diagnosed with Alzheimer's disease and with mild cognitive impairment. Main Outcome Measures: A standard clinical battery of objective tests of the vestibular system, and screening for balance; available clinical diagnostic magnetic resonance imaging (MRIs) were reviewed and postprocessed to quantify the left and right hippocampal volumes utilizing both manual segmentation and computer automated segmentation. Study subjects (N = 26) had significantly more vestibular impairments, especially on Dix-Hallpike maneuvers and cervical vestibular evoked myogenic potentials (cVEMP), than historical controls. No differences were found between mild and moderate dementia subjects. Independence on instrumental activities of daily living in subjects with age-normal balance approached statistical differences from subjects with age-abnormal balance. MRI data were available for 11 subjects. Subjects with abnormal cVEMP had significantly reduced left hippocampal MRIs using manual segmentation compared with subjects with normal cVEMP. The data from this small sample support and extend previous evidence for vestibular impairments in this population. The small MRI sample set should be considered preliminary evidence, and suggests the need for further research, with a more robust sample and high-resolution MRIs performed for the purpose of hippocampal analysis.

Hippocampal magnetic resonance imaging in focal onset seizure with impaired awareness\u2014descriptive study from tertiary care centre in southern part of India

BackgroundTemporal lobe epilepsy is the most common type of focal onset seizure. Focal onset seizure with impaired awareness, previously known as complex partial seizure (CPS), account for 18–40% of all seizure types. Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy, which produces focal onset seizure with impaired awareness. It may be detected in MRI visually, but bilateral abnormalities are better identified using volumetric analysis.We aimed to compare hippocampal volume in patients with focal onset seizure with impaired awareness visually and quantitatively.MethodologyThis cross-sectional study includes clinically diagnosed cases of 56 focal onset seizure with impaired awareness undergoing MRI at a tertiary teaching hospital in the southern part of India for a duration of 18 months from February 2018 to August 2019.ResultsOut of 53 patients studied using 1.5 T MRI brain with seizure protocols, hippocampal atrophy was identified visually in 13 (24.5%) on the right side, 9 (16.98%) on the left side, and in 6 (11.32%) bilaterally. However, with volumetry, hippocampal atrophy (not taking T2 signal change) was detected in 15 (28.30%) on the right side, 10 (18.86%) on the left side, and in 7 (13.20%) bilaterally. Hippocampal volumes between ipsilateral and contralateral seizure focus were found to have no significant difference (p-0.84).ConclusionsThough visual analysis is efficient in the diagnosis of pathology, MR volumetry may be used as an expert eye in cases of subtle volume loss.

Toward individualized prediction of seizure recurrence: Hippocampal neuroimaging features in a cohort of patients from a first seizure clinic

PurposeWe performed an exploratory analysis of electroencephalography (EEG) and neuroimaging data from a cohort of 51 patients with first seizure (FS) and new-onset epilepsy (NOE) to identify variables, or combinations of variables, that might discriminate between clinical trajectories over a one-year period and yield potential biomarkers of epileptogenesis. MethodsPatients underwent EEG, hippocampal and whole brain structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS) within six weeks of the index seizure, and repeat neuroimaging one year later. We classified patients with FS as having had a single seizure (FS-SS) or having converted to epilepsy (FS-CON) after one year and performed logistic regression to identify combinations of variables that might discriminate between FS-SS and FS-CON, and between FS-SS and the combined group FS-CON + NOE. We performed paired t-tests to assess changes in quantitative variables over time. ResultsSeveral combinations of variables derived from hippocampal structural MRI, DTI, and MRS provided excellent discrimination between FS-SS and FS-CON in our sample, with areas under the receiver operating curve (AUROC) ranging from 0.924 to 1. They also provided excellent discrimination between FS-SS and the combined group FS-CON + NOE in our sample, with AUROC ranging from 0.902 to 1. After one year, hippocampal fractional anisotropy (FA) increased bilaterally, hippocampal radial diffusivity (RD) decreased on the side with the larger initial measurement, and whole brain axial diffusivity (AD) increased in patients with FS-SS; hippocampal volume decreased on the side with the larger initial measurement, hippocampal FA increased bilaterally, hippocampal RD decreased bilaterally and whole brain AD, FA and mean diffusivity increased in the combined group FS-CON + NOE (corrected threshold for significance, q = 0.017). ConclusionWe propose a prospective, multicenter study to develop and test models for the prediction of seizure recurrence in patients after a first seizure, based on hippocampal neuroimaging. Further longitudinal neuroimaging studies in patients with a first seizure and new-onset epilepsy may provide clues to the microstructural changes occurring at the earliest stages of epilepsy and yield biomarkers of epileptogenesis.

CLASSIFICATION OF PROGRESSIVE STAGES OF ALZHEIMER’S DISEASE IN MRI HIPPOCAMPAL REGION

Alzheimer’s disease (AD) is a type of neuronal brain disorder that is degenerative and results in memory loss, skills and cognitive changes. The primary diagnostic tests for the disorder are defined to be total brain atrophy and hippocampal atrophy. Early diagnosis is significant and the design of automatic systems is necessary for this disorder. A potential biomarker for AD is described using a hippocampal magnetic resonance imaging volumetry system that possesses certain limitations. This paper aims to analyze the transition of stages from normal cognition to different forms that ultimately leads to Alzheimer’s disease. The magnetic resonance imaging (MRI) images of different stages are derived from the standard database for the segregation of hippocampal region. Later, the morphological and radiomic features are extracted from the hippocampal regions of different stages, since the hippocampus plays a major role in memory. Classification of extracted features was performed using machine learning algorithms like ensemble tree classifiers. The classification results based on performance parameters specify that the bagged tree classifier is more efficient. The 4-way classification has an accuracy of 95.6% indicating certain misclassification between the two classes MCI and PMCI. To categorize these two classes, a 2-way classification is described that has an accuracy of 98.6%. With these results, an effective method is defined for the analysis and identification of the different progressive stages of Alzheimer’s disease.

Volumetric alterations in the hippocampal subfields of subjects at increased risk of dementia

The hippocampus is one of the first regions to demonstrate atrophy during the prodromal stage of Alzheimer's disease. Volumetric analysis of its individual subfields could provide biomarkers with higher sensitivity than whole hippocampal volume during an earlier disease stage. We quantified the hippocampal subfields volume in a large cohort comprising healthy participants (aged 40–59) with dementia family history (FH) and controls (without FH), examined at 2 time points across 2 years. Subfield volumes were quantified using both a T1-weighted and a high-resolution T2 hippocampal magnetic resonance imaging acquisition with Freesurfer. The participants were stratified based on dementia FH, APOE genotype, and CAIDE (Cardiovascular Risk Factors, Aging and Dementia) risk score. Whole hippocampal volume did not differ between the groups. The volume of the molecular layer was lower in participants with an APOE ε4 genotype, but there were no differences between subjects with and without dementia FH or with an increasing CAIDE score. The molecular layer may be the first hippocampal region to demonstrate volumetric alterations in subjects at risk of dementia.

Hippocampal profiling: Localized magnetic resonance imaging volumetry and T2 relaxometry for hippocampal sclerosis.

ObjectiveHippocampal sclerosis (HS) is the most common cause of drug‐resistant temporal lobe epilepsy, and its accurate detection is important to guide epilepsy surgery. Radiological features of HS include hippocampal volume loss and increased T2 signal, which can both be quantified to help improve detection. In this work, we extend these quantitative methods to generate cross‐sectional area and T2 profiles along the hippocampal long axis to improve the localization of hippocampal abnormalities.MethodsT1‐weighted and T2 relaxometry data from 69 HS patients (32 left, 32 right, 5 bilateral) and 111 healthy controls were acquired on a 3‐T magnetic resonance imaging (MRI) scanner. Automated hippocampal segmentation and T2 relaxometry were performed and used to calculate whole‐hippocampal volumes and to estimate quantitative T2 (qT2) values. By generating a group template from the controls, and aligning this so that the hippocampal long axes were along the anterior‐posterior axis, we were able to calculate hippocampal cross‐sectional area and qT2 by a slicewise method to localize any volume loss or T2 hyperintensity. Individual patient profiles were compared with normative data generated from the healthy controls.ResultsProfiling of hippocampal volumetric and qT2 data could be performed automatically and reproducibly. HS patients commonly showed widespread decreases in volume and increases in T2 along the length of the affected hippocampus, and focal changes may also be identified. Patterns of atrophy and T2 increase in the left hippocampus were similar between left, right, and bilateral HS. These profiles have potential to distinguish between sclerosis affecting volume and qT2 in the whole or parts of the hippocampus, and may aid the radiological diagnosis in uncertain cases or cases with subtle or focal abnormalities where standard whole‐hippocampal measurements yield normal values.SignificanceHippocampal profiling of volumetry and qT2 values can help spatially localize hippocampal MRI abnormalities and work toward improved sensitivity of subtle focal lesions.

A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data

IntroductionIt is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia. MethodsA deep learning method is developed and validated based on magnetic resonance imaging scans of 2146 subjects (803 for training and 1343 for validation) to predict MCI subjects' progression to AD dementia in a time-to-event analysis setting. ResultsThe deep-learning time-to-event model predicted individual subjects' progression to AD dementia with a concordance index of 0.762 on 439 Alzheimer's Disease Neuroimaging Initiative testing MCI subjects with follow-up duration from 6 to 78 months (quartiles: [24, 42, 54]) and a concordance index of 0.781 on 40 Australian Imaging Biomarkers and Lifestyle Study of Aging testing MCI subjects with follow-up duration from 18 to 54 months (quartiles: [18, 36, 54]). The predicted progression risk also clustered individual subjects into subgroups with significant differences in their progression time to AD dementia (P < .0002). Improved performance for predicting progression to AD dementia (concordance index = 0.864) was obtained when the deep learning–based progression risk was combined with baseline clinical measures. DiscussionOur method provides a cost effective and accurate means for prognosis and potentially to facilitate enrollment in clinical trials with individuals likely to progress within a specific temporal period.

Contourlet-based hippocampal magnetic resonance imaging texture features for multivariant classification and prediction of Alzheimer's disease.

The study is aimed to assess whether the addition of contourlet-based hippocampal magnetic resonance imaging (MRI) texture features to multivariant models improves the classification of Alzheimer's disease (AD) and the prediction of mild cognitive impairment (MCI) conversion, and to evaluate whether Gaussian process (GP) and partial least squares (PLS) are feasible in developing multivariant models in this context. Clinical and MRI data of 58 patients with probable AD, 147 with MCI, and 94 normal controls (NCs) were collected. Baseline contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters based on MRI, and regional CMgl measurement based on fluorine-18 fluorodeoxyglucose-positron emission tomography were included to develop GP and PLS models to classify different groups of subjects. GPR1 model, which incorporated MRI texture features and was based on GPG, performed better in classifying different groups of subjects than GPR2 model, which used the same algorithm and had the same data as GPR1 except that MRI texture features were excluded. PLS model, which included the same variables as GPR1 but was based on the PLS algorithm, performed best among the three models. GPR1 accurately predicted 82.2% (51/62) of MCI convertors confirmed during the 2-year follow-up period, while this figure was 53 (85.5%) for PLS model. GPR1 and PLS models accurately predicted 58 (79.5%) vs. 61 (83.6%) of 73 patients with stable MCI, respectively. For seven patients with MCI who converted to NCs, PLS model accurately predicted all cases (100%), while GPR1 predicted six (85.7%) cases. The addition of contourlet-based MRI texture features to multivariant models can effectively improve the classification of AD and the prediction of MCI conversion to AD. Both GPR and LPS models performed well in the classification and predictive process, with the latter having significantly higher classification and predictive accuracies. Advances in knowledge: We combined contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters, and regional CMgl measurement to develop models using GP and PLS algorithms to classify AD patients.

Association of Hippocampal Magnetic Resonance Imaging With Learning and Memory Deficits in HIV-1-Seropositive Patients.

To investigate the relationship between cognitive impairment and hippocampal morphological and functional changes in HIV-seropositive patients. Thirty HIV+ patients who complain of memory decrease and 15 healthy volunteers were recruited. Performances of learning and memory were assessed using Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R). Bilateral hippocampal volume, apparent diffusion coefficient (ADC) value, fractional anisotropy value, and magnetic resonance spectroscopy variables of bilateral hippocampus and parahippocampal gyrus were detected by 3.0 T magnetic resonance scanner. We found significant differences in all cognitive outcomes but one between HIV+ and HIV- patients. There was a difference in the ADC value of left parahippocampal gyrus between mild-impairment group and severe-impairment group (P = 0.018). We found differences in the choline (Cho), Cho/creatinine (Cr), and N-acetylaspartate/Cr of left hippocampus (P = 0.002, P = 0.008, P = 0.002) and the Cho/Cr of right parahippocampal gyrus (P = 0.023) between HIV+ and HIV- patients and in the myoinositol of left hippocampus (P = 0.003) and the glutamate and glutamine of right hippocampus (P < 0.001) between mild-impairment group and severe-impairment group. We found significant positive correlations between N-acetylaspartate/Cr of left hippocampus and outcomes of HVLT-R and BVMT-R. There were significant negative correlations between ADC values of hippocampus and parahippocampal gyrus and outcomes of HVLT-R and BVMT-R and between Cho and Cho/Cr of hippocampus and parahippocampal gyrus and outcomes of HVLT-R and BVMT-R. The performance of verbal learning and visual memory was significantly decreased in HIV-1-seropositive patients. The cognitive impairment of HIV infection was associated with conductive function and metabolic changes of hippocampus and parahippocampal gyrus in this study.

Mesio-temporal ictal semiology as an indicator for surgical treatment of epilepsies with large multilobar cerebral lesions

PurposeMesio-temporal ictal semiology is sometimes observed in patients with large multilobar lesion. In this situation, surgery is often discarded because of the lesion size and/or suspicion of extended or multifocal epileptogenic areas. In this retrospective study we evaluated the surgical outcome of such patients in order to assess whether the electro-clinical presentation of seizures could be a prognostic marker of surgical outcome. MethodsAmong the temporal lobe epilepsy population explored in our department between 2000 and 2011 (240 patients), we identified 7 patients who presented an extensive lesion on brain Magnetic Resonance Imaging (MRI) (multilobar in four, hemispheric in two, and bilateral in one). All patients underwent 18Fluorodeoxyglucose Positron Emission Tomography, which showed large, hemispheric or multilobar, areas of glucose hypometabolism. Because of the large lesion size, all patients were explored by stereoelectroencephalography (SEEG) before taking a decision regarding surgical indication. ResultsSEEG confirmed the temporal origin of the seizures and discarded the possibility of multiple epileptogenic zones. A temporal lobectomy, tailored on the basis of SEEG data, was proposed to the seven patients. The seven patients are classified Engel class I after the surgery (mean follow-up: 37.4±22.1 months). ConclusionOur data thus suggest that, even in the absence of hippocampal MRI abnormality, ictal symptoms compatible with a temporal origin of seizures should be considered as a reliable indicator for surgery eligibility regardless of MRI lesion size. On the basis of our findings, the mesio-temporal semiology of seizures appears as one of the most reliable markers of operability in patients with large MRI lesions. These patients should not be excluded a priori from invasive exploration and surgical treatment, even if a large portion of their lesion is likely to be left in place after surgery.

The relationship between the apolipoprotein E e4 allele and hippocampal magnetic resonance imaging volume in community-dwelling individuals with mild Alzheimer's disease.

The degree of hippocampal magnetic resonance imaging (MRI) volume loss in Alzheimer's disease (AD) is commonly accepted as a marker of disease severity, yet remains expensive, unavailable, or not tolerated by many patients. To examine whether the presence of one or more apolipoprotein E (ApoE) e4 alleles is associated with smaller hippocampal MRI volumes in a population of early AD patients. A total of 88 consecutive patients attending a community-based memory disorders clinic who had both mild dementia on the Clinical Dementia Rating scale and Diagnostic and Statistical Manual of Mental Disorders criteria for probable AD were recruited. We examined the relationship between ApoE e4 allele load and hippocampal atrophy on MRI volumes. There was no association between the ApoE e4 load and hippocampal volume in this cohort. This study suggests that the presence of one or more ApoE e4 alleles cannot be used to estimate pathological disease load in early AD.

Hippocampal Magnetic Resonance Imaging Abnormalities in Cardiac Arrest are Associated with Poor Outcome

The role of neuroimaging in assessing prognosis in comatose cardiac survivors appears promising, but little is known regarding the import of particular spatial patterns. We report a specific spatial imaging abnormality on magnetic resonance imaging (MRI) that portends a poor prognosis: bilateral hippocampal hyperintensities on diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences. Eighty sequential comatose cardiac arrest patients underwent MRI scans. Qualitative and quantitative regional analyses were performed. Patients were categorized as HIPPO(+) (n = 18) or HIPPO(-) (n = 62) based on whether they had bilateral hippocampal hyperintensities. Poor outcome was defined by a modified Rankin Scale (mRS) score ≥4 at 6 months. Patients with bilateral hippocampal abnormalities had a higher frequency of poor outcome (P = .032). HIPPO(+) patients suffered more severe cerebral injury, with lower whole brain apparent diffusion coefficient values (P = .043) and a greater number of affected regions on DWI (P = .001) and FLAIR (P = .001) than HIPPO(-) patients. The hippocampal approach was 100% specific for a poor prognosis; only 1 patient survived and remained in a vegetative state. Bilateral hippocampal hyperintensities on MRI may be a specific imaging finding that is indicative of poor prognosis in patients who suffer global hypoxic-ischemic injury. More research on the prognostic significance of this and similar neuroimaging patterns is indicated.

Different structural correlates for verbal memory impairment in temporal lobe epilepsy with and without mesial temporal lobe sclerosis

Memory impairment is one of the most prominent cognitive deficits in temporal lobe epilepsy (TLE). The overall goal of this study was to explore the contribution of cortical and hippocampal (subfield) damage to impairment of auditory immediate recall (AIMrecall), auditory delayed recall (ADMrecall), and auditory delayed recognition (ADMrecog) of the Wechsler Memory Scale III (WMS-III) in TLE with (TLE-MTS) and without hippocampal sclerosis (TLE-no). It was hypothesized that volume loss in different subfields determines memory impairment in TLE-MTS and temporal neocortical thinning in TLE-no. T1 whole brain and T2-weighted hippocampal magnetic resonance imaging and WMS-III were acquired in 22 controls, 18 TLE-MTS, and 25 TLE-no. Hippocampal subfields were determined on the T2 image. Free surfer was used to obtain cortical thickness averages of temporal, frontal, and parietal cortical regions of interest (ROI). MANOVA and stepwise regression analysis were used to identify hippocampal subfields and cortical ROI significantly contributing to AIMrecall, ADMrecall, and ADMrecog. In TLE-MTS, AIMrecall was associated with cornu ammonis 3 (CA3) and dentate (CA3&DG) and pars opercularis, ADMrecall with CA1 and pars triangularis, and ADMrecog with CA1. In TLE-no, AIMrecall was associated with CA3&DG and fusiform gyrus (FUSI), and ADMrecall and ADMrecog were associated with FUSI. The study provided the evidence for different structural correlates of the verbal memory impairment in TLE-MTS and TLE-no. In TLE-MTS, the memory impairment was mainly associated by subfield-specific hippocampal and inferior frontal cortical damage. In TLE-no, the impairment was associated by mesial-temporal cortical and to a lesser degree hippocampal damage.