Automatic hippocampal segmentation in temporal lobe epilepsy: impact of developmental abnormalities

Medial positioning of the hippocampus and hippocampal fissure volume in developmental topographical disorientation

Developmental topographical disorientation (DTD) refers to the lifelong inability to orient by means of cognitive maps in familiar surroundings despite otherwise well-preserved general cognitive functions, and the absence of any acquired brain injury or neurological condition. While reduced functional connectivity between the hippocampus and other brain regions has been reported in DTD individuals, no structural differences in gray matter tissue for the whole brain neither for the hippocampus were detected. Considering that the human hippocampus is the main structure associated with cognitive map-based navigation, here, we investigated differences in morphological and morphometric hippocampal features between individuals affected by DTD (N = 20) and healthy controls (N = 238). Specifically, we focused on a developmental anomaly of the hippocampus that is characterized by the incomplete infolding of hippocampal subfields during fetal development, giving the hippocampus a more round or pyramidal shape, called incomplete hippocampal inversion (IHI). We rated IHI according to standard criteria and extracted hippocampal subfield volumes after FreeSurfer's automatic segmentation. We observed similar IHI prevalence in the group of individuals with DTD with respect to the control population. Neither differences in whole hippocampal nor major hippocampal subfield volumes have been observed between groups. However, when assessing the IHI independent criteria, we observed that the hippocampus in the DTD group is more medially positioned comparing to the control group. In addition, we observed bigger hippocampal fissure volume for the DTD comparing to the control group. Both of these findings were stronger for the right hippocampus comparing to the left. Our results provide new insights regarding the hippocampal morphology of individuals affected by DTD, highlighting the role of structural anomalies during early prenatal development in line with the developmental nature of the spatial disorientation deficit.

Incomplete hippocampal inversion: diagnostic criteria and effect on epilepsy, seizure localization and therapeutic outcome in children

PURPOSE

Elaborate a simple Magnetic Resonance Imaging (MRI)-based score to define Incomplete Hippocampal Inversion (IHI) in children (Phase 1), and evaluate the relation of IHI with (A) epilepsy, (B) seizure localization and (C) therapeutic response in a paediatric population (Phase 2).

METHODS

In Phase 1, incompletely inverted hippocampi were matched to completely inverted hippocampi. Multiple qualitative and quantitative hippocampal and extra-hippocampal features were evaluated in coronal-oblique T1-weighted (T1W) and coronal T2-weighted (T2W) images. Multivariate analysis was performed to elaborate the MRI-based score to define IHI. In Phase 2, epilepsy patients were matched to controls, and the T1W and T2W scores were applied. Multivariate analysis was performed to assess the relation of IHI and epilepsy, seizure localization and therapeutic response.

RESULTS

The hippocampal diameter ratio and parahippocampal angle in the coronal-oblique T1-weighted images, and the hippocampal diameter ratio and collateral sulcus depth in the coronal T2-weighted images predicted IHI in Phase 1. Simple and practical imaging-based scores were developed and are available on the website: https://ihiscore.netlify.app/. The Area Under the Receiver Operating Characteristic Curve of the T1W and T2W scores were, respectively, 0.965 and 0.983. In Phase 2, IHI independently predicted epilepsy (OR = 3.144, 95% CI = 1.981-4.991, p < 0.001), temporal lobe epilepsy (OR = 4.237, 95% CI = 1.586-11.318, p = 0.004), and drug resistant epilepsy (OR = 7.000, 95% CI = 2.800-17.500, p < 0.001).

CONCLUSION

The association between IHI and temporal lobe epilepsy (and the lack of association with extra-temporal epilepsy) favours the possibility of a relation between IHI and the pathophysiology of seizures in epileptic patients. Furthermore, IHI is a potential prognostic marker for therapeutic response in epilepsy.

A Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis Derived From Deep Learning-Based Segmentation of T1w-MRI

Purpose

Hippocampal volumetry is an important biomarker to quantify atrophy in patients with mesial temporal lobe epilepsy. We investigate the sensitivity of automated segmentation methods to support radiological assessments of hippocampal sclerosis (HS). Results from FreeSurfer and FSL-FIRST are contrasted to a deep learning (DL)-based segmentation method.

Materials and Methods

We used T1-weighted MRI scans from 105 patients with epilepsy and 354 healthy controls. FreeSurfer, FSL, and a DL-based method were applied for brain anatomy segmentation. We calculated effect sizes (Cohen's d) between left/right HS and healthy controls based on the asymmetry of hippocampal volumes. Additionally, we derived 14 shape features from the segmentations and determined the most discriminating feature to identify patients with hippocampal sclerosis by a support vector machine (SVM).

Results

Deep learning-based segmentation of the hippocampus was the most sensitive to detecting HS. The effect sizes of the volume asymmetries were larger with the DL-based segmentations (HS left d= −4.2, right = 4.2) than with FreeSurfer (left= −3.1, right = 3.7) and FSL (left= −2.3, right = 2.5). For the classification based on the shape features, the surface-to-volume ratio was identified as the most important feature. Its absolute asymmetry yielded a higher area under the curve (AUC) for the deep learning-based segmentation (AUC = 0.87) than for FreeSurfer (0.85) and FSL (0.78) to dichotomize HS from other epilepsy cases. The robustness estimated from repeated scans was statistically significantly higher with DL than all other methods.

Conclusion

Our findings suggest that deep learning-based segmentation methods yield a higher sensitivity to quantify hippocampal sclerosis than atlas-based methods and derived shape features are more robust. We propose an increased asymmetry in the surface-to-volume ratio of the hippocampus as an easy-to-interpret quantitative imaging biomarker for HS.

Hippocampal Malrotation Could Be Less Significant in Epilepsy Caused by Focal Cortical Dysplasia Type I and Type II

Objectives

Debates over the relationship between hippocampal malrotation (HIMAL) and epilepsy continue without consensus. This study explores the role of HIMAL in a cohort of epilepsy caused by focal cortical dysplasia (FCD).

Methods

In this study, 90 patients with epilepsy caused by FCD type I and type II and 48 healthy adults underwent a 3 Tesla MRI following a dedicated epilepsy protocol for the analysis of the prevalence and morphologic features of HIMAL. In addition, numerous clinical characteristics and hippocampal volumes were evaluated.

Results

The cohort included a total of 90 patients (32 were HIMAL, 58 were non-HIMAL). Among these patients, 32 (35.6%) had HIMAL (22 left, four right, and six bilateral), which did not differ from the 48 controls, where 16 (33.3%) had HIMAL (12 left, two right, and two bilateral). Neither the quantitative features of HIMAL (diameter ratio, dominant inferior temporal sulcus height ratio, medial distance ratio, dominant inferior temporal sulcus angle, and parahippocampal angle), nor the accompanying characteristics of HIMAL (vertical dominant inferior temporal sulcus, enlarged temporal horn, and a low position of ipsilateral fornix) showed differences between patients with FCD and controls. No statistical difference in the clinical characteristics between FCD patients with HIMAL and those without was found. Neither the side nor the existence of HIMAL was correlated with the lateralization and location of FCD. As to the hippocampal volume, there was no difference between FCD patients with HIMAL and those without.

Conclusion

Hippocampal malrotation is a common morphologic variant in healthy controls as well as in patients with epilepsy caused by FCD type I and type II. Hippocampal malrotation could be less significant in epilepsy caused by FCD type I and type II.

Temporal and extratemporal atrophic manifestation of temporal lobe epilepsy using voxel-based morphometry and corticometry: clinical application in lateralization of epileptogenic zone

BACKGROUND

Advances in MRI acquisition and data processing have become important for revealing brain structural changes. Previous studies have reported widespread structural brain abnormalities and cortical thinning in patients with temporal lobe epilepsy (TLE), as the most common form of focal epilepsy.

METHODS

In this research, healthy control cases (n = 20) and patients with left TLE (n = 19) and right TLE (n = 14) were recruited, all underwent 3.0 T MRI with magnetization-prepared rapid gradient echo sequence to acquire T1-weighted images. Morphometric alterations in gray matter were identified using voxel-based morphometry (VBM). Volumetric alterations in subcortical structures and cortical thinning were also determined.

RESULTS

Patients with left TLE demonstrated more prevailing and widespread changes in subcortical volumes and cortical thickness than right TLE, mainly in the left hemisphere, compared to the healthy group. Both VBM analysis and subcortical volumetry detected significant hippocampal atrophy in ipsilateral compared to contralateral side in TLE group. In addition to hippocampus, subcortical volumetry found the thalamus and pallidum bilaterally vulnerable to the TLE. Furthermore, the TLE patients underwent cortical thinning beyond the temporal lobe, affecting gray matter cortices in frontal, parietal, and occipital lobes in the majority of patients, more prevalently for left TLE cases. Exploiting volume changes in individual patients in the hippocampus alone led to 63.6% sensitivity and 100% specificity for lateralization of TLE.

CONCLUSION

Alteration of gray matter volumes in subcortical regions and neocortical temporal structures and also cortical gray matter thickness were evidenced as common effects of epileptogenicity, as manifested by the majority of cases in this study.

Incomplete hippocampal inversion in schizophrenia: prevalence, severity, and impact on hippocampal structure

Incomplete hippocampal inversion (IHI) is an anatomical variant of the human brain resulting from an arrest in brain development, especially prevalent in the left hemisphere. We hypothesized that IHI is more common in schizophrenia and contributes to the well-known hippocampal structural differences. We studied 199 schizophrenia patients and 161 healthy control participants with 3 T MRI to establish IHI prevalence and the relationship of IHI with hippocampal volume and asymmetry. IHI was more prevalent (left hemisphere: 15% of healthy control participants, 27% of schizophrenia patients; right hemisphere: 4% of healthy control participants, 10% of schizophrenia patients) and more severe in schizophrenia patients compared to healthy control participants. Severe IHI cases were associated with a higher rate of automated segmentation failure. IHI contributed to smaller hippocampal volume and increased R > L volume asymmetry in schizophrenia. The increased prevalence and severity of IHI supports the neurodevelopmental model of schizophrenia. The impact of this developmental variant deserves further exploration in studies of the hippocampus in schizophrenia.

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.

The impact of hippocampal segmentation methods on correlations with clinical data

BACKGROUND

In vivo measurement of hippocampal volume with magnetic resonance imaging (MRI) has become an important element in neuroimaging research. However, hippocampal volumetric findings and their relationship with cardiovascular risk factors and memory performance are still controversial and inconsistent for non-demented adults.

PURPOSE

To compare total and regional hippocampal volumes from manual tracing and automated Freesurfer segmentation methods and their relationship with mid-life clinical data and late-life verbal episodic memory performance in older women.

MATERIAL AND METHODS

This study used structural MRI datasets from 161 women who were scanned in 2012 and underwent neuropsychological assessments. Of these participants, 135 women had completed baseline measures of cardiovascular risk factors in 1992.

RESULTS

Our results showed a significant correlation between manual tracing and automated Freesurfer output segmentations of total (r = 0.71), anterior (r = 0.65), and posterior (r = 0.38) hippocampal volumes. Mid-life Framingham Cardiovascular Risk Profile score is not associated with late-life hippocampal volumes, adjusted for intracranial volume, age, education, and apolipoprotein E gene ε4 status. Anterior hippocampal volume segmented either with manual tracing or automated Freesurfer software is sensitive to changes in mid-life high-density lipoprotein (HDL) cholesterol level, while posterior hippocampal volume is linked with verbal episodic memory performance in elderly women.

CONCLUSION

These findings support the use of Freesurfer automated segmentation measures for large datasets as being highly correlated with the manual tracing method. In addition, our results suggest intervention strategies that target mid-life HDL cholesterol level in women.

Shared hippocampal abnormalities in sporadic temporal lobe epilepsy patients and their siblings

OBJECTIVE

To examine the shared familial contribution to hippocampal and extrahippocampal morphological abnormalities in patients with sporadic temporal lobe epilepsy (TLE) and their unaffected siblings.

METHODS

We collected clinical, electrophysiological, and T1-weighted magnetic resonance imaging (MRI) data of 18 sporadic patients with TLE without lesions other than hippocampal sclerosis (12 right, 6 left), their 18 unaffected full siblings, and 18 matched healthy volunteers. We compared between-group differences in cortical thickness and volumes of five subcortical areas (hippocampus, amygdala, thalamus, putamen, and pallidum). We determined the subregional extent of hippocampal abnormalities using surface shape analysis. All our imaging results were corrected for multiple comparisons using random field theory.

RESULTS

We detected smaller hippocampal volumes in patients (right TLE: median right hippocampus 1.92 mL, interquartile range [IQR] 1.39-2.62, P < .001; left TLE: left hippocampus 2.05 mL, IQR 1.99-2.33, P = .01) and their unaffected siblings (right hippocampus 2.65 mL, IQR 2.32-2.80, P < .001; left hippocampus 2.39 mL, IQR 2.18-2.53, P < .001) compared to healthy controls (right hippocampus 2.94 mL, IQR 2.77-3.24; left hippocampus 2.71 mL, IQR 2.37-2.89). Surface shape analysis showed that patients with TLE had bilateral subregional atrophy in both hippocampi (right > left). Similar but less-pronounced subregional atrophy was detected in the right hippocampus of unaffected siblings. Patients with TLE had reduced cortical thickness in bilateral premotor/prefrontal cortices and the right precentral gyrus. Siblings did not show abnormalities in cortical or subcortical areas other than the hippocampus.

SIGNIFICANCE

Our results demonstrate a shared vulnerability of the hippocampus in both patients with TLE and their unaffected siblings, pointing to a contribution of familial factors to hippocampal atrophy. This neuroimaging trait could represent an endophenotype of TLE, which might precede the onset of epilepsy in some individuals.

Genome wide association study of incomplete hippocampal inversion in adolescents

Incomplete hippocampal inversion (IHI), also called hippocampal malrotation, is an atypical presentation of the hippocampus present in about 20% of healthy individuals. Here we conducted the first genome-wide association study (GWAS) in IHI to elucidate the genetic underpinnings that may contribute to the incomplete inversion during brain development. A total of 1381 subjects contributed to the discovery cohort obtained from the IMAGEN database. The incidence rate of IHI was 26.1%. Loci with P<1e-5 were followed up in a validation cohort comprising 161 subjects from the PING study. Summary statistics from the discovery cohort were used to compute IHI heritability as well as genetic correlations with other traits. A locus on 18q11.2 (rs9952569; OR = 1.999; Z = 5.502; P = 3.755e-8) showed a significant association with the presence of IHI. A functional annotation of the locus implicated genes AQP4 and KCTD1. However, neither this locus nor the other 16 suggestive loci reached a significant p-value in the validation cohort. The h² estimate was 0.54 (sd: 0.30) and was significant (Z = 1.8; P = 0.036). The top three genetic correlations of IHI were with traits representing either intelligence or education attainment and reached nominal P< = 0.013.

Abnormal hippocampal structure and function in juvenile myoclonic epilepsy and unaffected siblings

Juvenile myoclonic epilepsy is the most common genetic generalized epilepsy syndrome, characterized by a complex polygenetic aetiology. Structural and functional MRI studies demonstrated mesial or lateral frontal cortical derangements and impaired fronto-cortico-subcortical connectivity in patients and their unaffected siblings. The presence of hippocampal abnormalities and associated memory deficits is controversial, and functional MRI studies in juvenile myoclonic epilepsy have not tested hippocampal activation. In this observational study, we implemented multi-modal MRI and neuropsychological data to investigate hippocampal structure and function in 37 patients with juvenile myoclonic epilepsy, 16 unaffected siblings and 20 healthy controls, comparable for age, gender, handedness and hemispheric dominance as assessed with language laterality indices. Automated hippocampal volumetry was complemented by validated qualitative and quantitative morphological criteria to detect hippocampal malrotation, assumed to represent a neurodevelopmental marker. Neuropsychological measures of verbal and visuo-spatial learning and an event-related verbal and visual memory functional MRI paradigm addressed mesiotemporal function. We detected a reduction of mean left hippocampal volume in patients and their siblings compared with controls (P < 0.01). Unilateral or bilateral hippocampal malrotation was identified in 51% of patients and 50% of siblings, against 15% of controls (P < 0.05). For bilateral hippocampi, quantitative markers of verticalization had significantly larger values in patients and siblings compared with controls (P < 0.05). In the patient subgroup, there was no relationship between structural measures and age at disease onset or degree of seizure control. No overt impairment of verbal and visual memory was identified with neuropsychological tests. Functional mapping highlighted atypical patterns of hippocampal activation, pointing to abnormal recruitment during verbal encoding in patients and their siblings [P < 0.05, familywise error (FWE)-corrected]. Subgroup analyses indicated distinct profiles of hypoactivation along the hippocampal long axis in juvenile myoclonic epilepsy patients with and without malrotation; patients with malrotation also exhibited reduced frontal recruitment for verbal memory, and more pronounced left posterior hippocampal involvement for visual memory. Linear models across the entire study cohort indicated significant associations between morphological markers of hippocampal positioning and hippocampal activation for verbal items (all P < 0.05, FWE-corrected). We demonstrate abnormalities of hippocampal volume, shape and positioning in patients with juvenile myoclonic epilepsy and their siblings, which are associated with reorganization of function and imply an underlying neurodevelopmental mechanism with expression during the prenatal stage. Co-segregation of abnormal hippocampal morphology in patients and their siblings is suggestive of a genetic imaging phenotype, independent of disease activity, and can be construed as a novel endophenotype of juvenile myoclonic epilepsy.

FAst Segmentation Through SURface Fairing (FASTSURF): A novel semi-automatic hippocampus segmentation method

Objective

The objective is to present a proof-of-concept of a semi-automatic method to reduce hippocampus segmentation time on magnetic resonance images (MRI).

Materials and methods

FAst Segmentation Through SURface Fairing (FASTSURF) is based on a surface fairing technique which reconstructs the hippocampus from sparse delineations. To validate FASTSURF, simulations were performed in which sparse delineations extracted from full manual segmentations served as input. On three different datasets with different diagnostic groups, FASTSURF hippocampi were compared to the original segmentations using Jaccard overlap indices and percentage volume differences (PVD). In one data set for which back-to-back scans were available, unbiased estimates of overlap and PVD were obtained. Using longitudinal scans, we compared hippocampal atrophy rates measured by manual, FASTSURF and two automatic segmentations (FreeSurfer and FSL-FIRST).

Results

With only seven input contours, FASTSURF yielded mean Jaccard indices ranging from 72(±4.3)% to 83(±2.6)% and PVDs ranging from 0.02(±2.40)% to 3.2(±3.40)% across the three datasets. Slightly poorer results were obtained for the unbiased analysis, but the performance was still considerably better than both tested automatic methods with only five contours.

Conclusions

FASTSURF segmentations have high accuracy and require only a fraction of the delineation effort of fully manual segmentation. Atrophy rate quantification based on completely manual segmentation is well reproduced by FASTSURF. Therefore, FASTSURF is a promising tool to be implemented in clinical workflow, provided a future prospective validation confirms our findings.

A comparison of automated segmentation and manual tracing in estimating hippocampal volume in ischemic stroke and healthy control participants

Manual quantification of the hippocampal atrophy state and rate is time consuming and prone to poor reproducibility, even when performed by neuroanatomical experts. The automation of hippocampal segmentation has been investigated in normal aging, epilepsy, and in Alzheimer's disease. Our first goal was to compare manual and automated hippocampal segmentation in ischemic stroke and to, secondly, study the impact of stroke lesion presence on hippocampal volume estimation. We used eight automated methods to segment T1-weighted MR images from 105 ischemic stroke patients and 39 age-matched controls sampled from the Cognition And Neocortical Volume After Stroke (CANVAS) study. The methods were: AdaBoost, Atlas-based Hippocampal Segmentation (ABHS) from the IDeALab, Computational Anatomy Toolbox (CAT) using 3 atlas variants (Hammers, LPBA40 and Neuromorphometics), FIRST, FreeSurfer v5.3, and FreeSurfer v6.0-Subfields. A number of these methods were employed to re-segment the T1 images for the stroke group after the stroke lesions were masked (i.e., removed). The automated methods were assessed on eight measures: process yield (i.e. segmentation success rate), correlation (Pearson's R and Shrout's ICC), concordance (Lin's RC and Kandall's W), slope 'a' of best-fit line from correlation plots, percentage of outliers from Bland-Altman plots, and significance of control-stroke difference. We eliminated the redundant measures after analysing between-measure correlations using Spearman's rank correlation. We ranked the automated methods based on the sum of the remaining non-redundant measures where each measure ranged between 0 and 1. Subfields attained an overall score of 96.3%, followed by AdaBoost (95.0%) and FIRST (94.7%). CAT using the LPBA40 atlas inflated hippocampal volumes the most, while the Hammers atlas returned the smallest volumes overall. FIRST (p = 0.014), FreeSurfer v5.3 (p = 0.007), manual tracing (p = 0.049), and CAT using the Neuromorphometics atlas (p = 0.017) all showed a significantly reduced hippocampal volume mean for the stroke group compared to control at three months. Moreover, masking of the stroke lesions prior to segmentation resulted in hippocampal volumes which agreed less with manual tracing. These findings recommend an automated segmentation without lesion masking as a more reliable procedure for the estimation of hippocampal volume in ischemic stroke.

Multi-Template Mesiotemporal Lobe Segmentation: Effects of Surface and Volume Feature Modeling

Numerous neurological disorders are associated with atrophy of mesiotemporal lobe structures, including the hippocampus (HP), amygdala (AM), and entorhinal cortex (EC). Accurate segmentation of these structures is, therefore, necessary for understanding the disease process and patient management. Recent multiple-template segmentation algorithms have shown excellent performance in HP segmentation. Purely surface-based methods precisely describe structural boundary but their performance likely depends on a large template library, as segmentation suffers when the boundaries of template and individual MRI are not well aligned while volume-based methods are less dependent. So far only few algorithms attempted segmentation of entire mesiotemporal structures including the parahippocampus. We compared performance of surface- and volume-based approaches in segmenting the three mesiotemporal structures and assess the effects of different environments (i.e., size of templates, under pathology). We also proposed an algorithm that combined surface- with volume-derived similarity measures for optimal template selection. To further improve the method, we introduced two new modules: (1) a non-linear registration that is driven by volume-based intensities and features sampled on deformable template surfaces; (2) a shape averaging based on regional weighting using multi-scale global-to-local icosahedron sampling. Compared to manual segmentations, our approach, namely HybridMulti showed high accuracy in 40 healthy controls (mean Dice index for HP/AM/EC = 89.7/89.3/82.9%) and 135 patients with temporal lobe epilepsy (88.7/89.0/82.6%). This accuracy was comparable across two different datasets of 1.5T and 3T MRI. It resulted in the best performance among tested multi-template methods that were either based on volume or surface data alone in terms of accuracy and sensitivity to detect atrophy related to epilepsy. Moreover, unlike purely surface-based multi-template segmentation, HybridMulti could maintain accurate performance even with a 50% template library size.

Evaluation of hippocampal infolding angle and incomplete hippocampal inversion in pediatric patients with epilepsy and febrile seizures

PURPOSE

We aimed to investigate the frequency of incomplete hippocampal inversion (IHI) and the hippocampal infolding angle (HIA) in pediatric patients with no additional abnormal findings in the brain.

METHODS

Pediatric brain magnetic resonance imaging (MRI) examinations conducted between September 2012 and February 2015 were screened and 83 patients with epilepsy, 49 patients with febrile convulsion, and 74 control patients were included in this retrospective study. Presence of IHI was evaluated and HIA was measured on MRI.

RESULTS

IHI was found in 23 patients in the epilepsy group (27.7%), 15 patients in the febrile convulsion group (30.6%), and 14 patients in the control group (19.0%), with no significant difference between the groups (P = 0.27). Compared with the epilepsy and febrile convulsion groups, HIA was significantly larger in the control group in sections of the right cerebral pedincule, the left cerebral pedincule, and the right superior cerebellar pedincule. No correlation was found between the laterality of the epileptogenic focus in the epilepsy group and existence of IHI, nor between age and HIA values among the groups.

CONCLUSION

Although IHI is not an uncommon abnormality in the normal pediatric population, decreased HIA is more frequently found in patients with epilepsy or febrile convulsions.

Personalized structural image analysis in patients with temporal lobe epilepsy

Volumetric and morphometric studies have demonstrated structural abnormalities related to chronic epilepsies on a cohort- and population-based level. On a single-patient level, specific patterns of atrophy or cortical reorganization may be widespread and heterogeneous but represent potential targets for further personalized image analysis and surgical therapy. The goal of this study was to compare morphometric data analysis in 37 patients with temporal lobe epilepsies with expert-based image analysis, pre-informed by seizure semiology and ictal scalp EEG. Automated image analysis identified abnormalities exceeding expert-determined structural epileptogenic lesions in 86% of datasets. If EEG lateralization and expert MRI readings were congruent, automated analysis detected abnormalities consistent on a lobar and hemispheric level in 82% of datasets. However, in 25% of patients EEG lateralization and expert readings were inconsistent. Automated analysis localized to the site of resection in 60% of datasets in patients who underwent successful epilepsy surgery. Morphometric abnormalities beyond the mesiotemporal structures contributed to subtype characterisation. We conclude that subject-specific morphometric information is in agreement with expert image analysis and scalp EEG in the majority of cases. However, automated image analysis may provide non-invasive additional information in cases with equivocal radiological and neurophysiological findings.

Regional analysis of volumes and reproducibilities of automatic and manual hippocampal segmentations

PURPOSE

Precise and reproducible hippocampus outlining is important to quantify hippocampal atrophy caused by neurodegenerative diseases and to spare the hippocampus in whole brain radiation therapy when performing prophylactic cranial irradiation or treating brain metastases. This study aimed to quantify systematic differences between methods by comparing regional volume and outline reproducibility of manual, FSL-FIRST and FreeSurfer hippocampus segmentations.

MATERIALS AND METHODS

This study used a dataset from ADNI (Alzheimer's Disease Neuroimaging Initiative), including 20 healthy controls, 40 patients with mild cognitive impairment (MCI), and 20 patients with Alzheimer's disease (AD). For each subject back-to-back (BTB) T1-weighted 3D MPRAGE images were acquired at time-point baseline (BL) and 12 months later (M12). Hippocampi segmentations of all methods were converted into triangulated meshes, regional volumes were extracted and regional Jaccard indices were computed between the hippocampi meshes of paired BTB scans to evaluate reproducibility. Regional volumes and Jaccard indices were modelled as a function of group (G), method (M), hemisphere (H), time-point (T), region (R) and interactions.

RESULTS

For the volume data the model selection procedure yielded the following significant main effects G, M, H, T and R and interaction effects G-R and M-R. The same model was found for the BTB scans. For all methods volumes reduces with the severity of disease. Significant fixed effects for the regional Jaccard index data were M, R and the interaction M-R. For all methods the middle region was most reproducible, independent of diagnostic group. FSL-FIRST was most and FreeSurfer least reproducible.

DISCUSSION/CONCLUSION

A novel method to perform detailed analysis of subtle differences in hippocampus segmentation is proposed. The method showed that hippocampal segmentation reproducibility was best for FSL-FIRST and worst for Freesurfer. We also found systematic regional differences in hippocampal segmentation between different methods reinforcing the need of adopting harmonized protocols.

Whole-Brain High-Resolution Structural Connectome: Inter-Subject Validation and Application to the Anatomical Segmentation of the Striatum

The present study describes extraction of high-resolution structural connectome (HRSC) in 99 healthy subjects, acquired and made available by the Human Connectome Project. Single subject connectomes were then registered to the common surface space to allow assessment of inter-individual reproducibility of this novel technique using a leave-one-out approach. The anatomic relevance of the surface-based connectome was examined via a clustering algorithm, which identified anatomic subdivisions within the striatum. The connectivity of these striatal subdivisions were then mapped on the cortical and other subcortical surfaces. Findings demonstrate that HRSC analysis is robust across individuals and accurately models the actual underlying brain networks related to the striatum. This suggests that this method has the potential to model and characterize the healthy whole-brain structural network at high anatomic resolution.

A longitudinal study of associations between psychiatric symptoms and disorders and cerebral gray matter volumes in adolescents born very preterm

Background

Being born preterm with very low birthweight (VLBW ≤ 1500 g) poses a risk for cortical and subcortical gray matter (GM) abnormalities, as well as for having more psychiatric problems during childhood and adolescence than term-born individuals. The aim of this study was to investigate the relationship between cortical and subcortical GM volumes and the course of psychiatric disorders during adolescence in VLBW individuals.

Methods

We followed VLBW individuals and term-born controls (birth weight ≥10th percentile) from 15 (VLBW;controls n = 40;56) to 19 (n = 44;60) years of age. Of these, 30;37 individuals were examined longitudinally. Cortical and subcortical GM volumes were extracted from MRPRAGE images obtained with the same 1.5 T MRI scanner at both time points and analyzed at each time point with the longitudinal stream of the FreeSurfer software package 5.3.0. All participants underwent clinical interviews and were assessed for psychiatric symptoms and diagnosis (Schedule for Affective Disorders and Schizophrenia for School-age Children, Children’s Global Assessment Scale, Attention-Deficit/Hyperactivity Disorder Rating Scale-IV). VLBW adolescents were divided into two groups according to diagnostic status from 15 to 19 years of age: persisting/developing psychiatric diagnosis or healthy/becoming healthy.

Results

Reduction in subcortical GM volume at 15 and 19 years, not including the thalamus, was limited to VLBW adolescents with persisting/developing diagnosis during adolescence, whereas VLBW adolescents in the healthy/becoming healthy group had similar subcortical GM volumes to controls. Moreover, across the entire VLBW group, poorer psychosocial functioning was predicted by smaller subcortical GM volumes at both time points and with reduced GM volume in the thalamus and the parietal and occipital cortex at 15 years. Inattention problems were predicted by smaller GM volumes in the parietal and occipital cortex.

Conclusions

GM volume reductions in the parietal and occipital cortex as well as smaller thalamic and subcortical GM volumes were associated with the higher rates of psychiatric symptoms found across the entire VLBW group. Significantly smaller subcortical GM volumes in VLBW individuals compared with term-born peers might pose a risk for developing and maintaining psychiatric diagnoses during adolescence. Future research should explore the possible role of reduced cortical and subcortical GM volumes in the pathogenesis of psychiatric illness in VLBW adolescents.

Electronic supplementary material

The online version of this article (doi:10.1186/s12887-017-0793-0) contains supplementary material, which is available to authorized users.

Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease

The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed - 562 subjects at 1.5T, a 75 subject group that also had manual segmentation and 111 subjects at 3T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were -1.1%/year for healthy controls, -3.0%/year for mildly cognitively impaired and -5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5T and 3T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered.

The superficial white matter in temporal lobe epilepsy: a key link between structural and functional network disruptions

Drug-resistant temporal lobe epilepsy is increasingly recognized as a system-level disorder affecting the structure and function of large-scale grey matter networks. While diffusion magnetic resonance imaging studies have demonstrated deep fibre tract alterations, the superficial white matter immediately below the cortex has so far been neglected despite its proximity to neocortical regions and key role in maintaining cortico-cortical connectivity. Using multi-modal 3 T magnetic resonance imaging, we mapped the topography of superficial white matter diffusion alterations in 61 consecutive temporal lobe epilepsy patients relative to 38 healthy controls and studied the relationship to large-scale structural as well as functional networks. Our approach continuously sampled mean diffusivity and fractional anisotropy along surfaces running 2 mm below the cortex. Multivariate statistics mapped superficial white matter diffusion anomalies in patients relative to controls, while correlation and mediation analyses evaluated their relationship to structural (cortical thickness, mesiotemporal volumetry) and functional parameters (resting state functional magnetic resonance imaging amplitude) and clinical variables. Patients presented with overlapping anomalies in mean diffusivity and anisotropy, particularly in ipsilateral temporo-limbic regions. Diffusion anomalies did not relate to cortical thinning; conversely, they mediated large-scale functional amplitude decreases in patients relative to controls in default mode hub regions (i.e. anterior and posterior midline regions, lateral temporo-parietal cortices), and were themselves mediated by hippocampal atrophy. With respect to clinical variables, we observed more marked diffusion anomalies in patients with a history of febrile convulsions and those with longer disease duration. Similarly, more marked diffusion alterations were associated with seizure-free outcome. Bootstrap analyses indicated high reproducibility of our findings, suggesting generalizability. The temporo-limbic distribution of superficial white matter anomalies, together with the mediation-level findings, suggests that this so far neglected region serves a key link between the hippocampal atrophy and large-scale default mode network alterations in temporal lobe epilepsy.

Mesial temporal lobe morphology in intractable pediatric epilepsy: so-called hippocampal malrotation, associated findings, and relevance to presurgical assessment

OBJECTIVE Diagnostic criteria for hippocampal malrotation (HIMAL) on brain MRI typically include a rounded hippocampus, vertical collateral sulcus, and architectural blurring. Relationship to epileptogenesis remains speculative, and usefulness for surgical guidance is unknown. The study was performed to determine the prevalence of hippocampal rotational anomalies in a cohort of pediatric patients with intractable epilepsy undergoing evaluation for surgery and to determine the significance of this finding in the context of surgical planning. METHODS Forty-eight surgically treated children with intractable epilepsy were compared with matched healthy subjects; reviewers were blinded to surgical side. Each temporal lobe was evaluated for rounded hippocampus, blurring, vertical collateral sulcus, wide choroidal fissure, enlarged temporal horn, low fornix, hippocampal signal, and findings of hippocampal sclerosis. A mesial temporal lobe (MTL) score was calculated by summing the number of features, and the collateral sulcus angle (CSA) was measured in each temporal lobe. Surgical side, pathological diagnosis, and imaging findings elsewhere in the brain were tabulated. Presence of HIMAL, associated imaging features, and MTL score were compared between sides, between epilepsy and control groups, in relationship to side of surgery, and in relationship to postoperative outcome. RESULTS Only 3 epilepsy patients (6.2%) and no controls exhibited all 3 features of HIMAL (p = 0.12). Eight of 48 (16.7%) epilepsy versus 2 of 48 (4.6%) control subjects had both a rounded hippocampus and vertical collateral sulcus (suggesting HIMAL) (p = 0.045). In control and epilepsy subjects, most findings were more prevalent on the left, and the left CSA was more vertical (p < 0.0001). Epilepsy subjects had higher MTL scores (z = -2.95, p = 0.002) and more acute CSAs (p = 0.04) than controls. Only lateralizing raw MTL score had a significant association with surgical side (p = 0.03, OR 7.33); however, this was not significant when hippocampal sclerosis cases were excluded. HIMAL findings were more prevalent and MTL scores were higher in patients with resections involving the temporal lobes. On group analysis, HIMAL findings did not predict eventual surgical side and did not predict outcome, although the numbers are small. In 4 patients the abnormally rotated hippocampus was resected and showed hippocampal sclerosis and/or dysplastic changes on histopathology. All of these patients had a good outcome after surgery. CONCLUSIONS While increased in prevalence in children with intractable epilepsy, imaging findings of HIMAL did not have preoperative lateralizing utility in this group. Findings of HIMAL (including round hippocampus, architectural blurring, and vertical collateral sulcus) did not predict outcome after surgery, although the small number of patients with these findings limits evaluation. In the small number of patients in which the malrotated hippocampus was removed, outcome was good. Further research is needed to continue to define this association in children with intractable epilepsy, focusing on a temporal lobe cohort.

Hippocampal volume predicts antidepressant efficacy in depressed patients without incomplete hippocampal inversion

Background

Incomplete hippocampal inversion (IHI), also called malrotation, is a frequent atypical anatomical pattern of the hippocampus. Because of the crucial implication of the hippocampus in Major Depressive Disorder (MDD) and the neurodevelopmental hypothesis of MDD, we aimed to assess the prevalence of IHI in patients with MDD, the link of IHI with hippocampal volume (HV) and the impact of IHI on the predictive value of HV for response and remission after antidepressant treatment.

Methods

IHI (right and left, partial and total and IHI scores) and HV were assessed in 60 patients with a current Major Depressive Episode (MDE) in a context of MDD and 60 matched controls. Patients were prospectively assessed at baseline and after one, three and six months of antidepressant treatment for response and remission.

Results

The prevalence of IHI did not significantly differ between MDD patients (right = 23.3%; left = 38.3%) and controls (right = 16.7%; left = 33.3%). IHI was not significantly associated with MDD clinical characteristics. IHI alone did not predict response and remission after antidepressant treatment. However, an interaction between left HV and left IHI predicted six-month response (p = 0.04), HDRS score decrease (p = 0.02) and both three-month (p = 0.04) and six-month (p = 0.03) remission. A case-control design in 30 matched patients with or without left IHI confirmed that interaction. In patients without left IHI, left HV at baseline were smaller in six-month non-remitters as compared to remitters (2.2(± 0.43) cm³ vs 2.97(± 0.5) cm³ p = 0.02), and in six-month non-responders as compared to responders (2.18(± 0.42) cm³ vs 2.86(± 0.54) cm³, p = 0.03). In patients with left IHI, no association was found between left HV at baseline and antidepressant response and remission.

Conclusion

IHI is not more frequent in MDD patients than in controls, is not associated with HV, but is a confounder that decreases the predictive value of hippocampal volume to predict response or remission after antidepressant treatment. IHI should be systematically assessed in future research studies assessing hippocampal volume in MDD.

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Incomplete hippocampal inversion (IHI) is not significantly more frequent in MDD than in controls.

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IHI is not significantly associated with MDD clinical characteristics.

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Hippocampal volume predicts antidepressant efficacy in MDD patients without IHI.

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Hippocampal volume does not predict antidepressant efficacy in patients with IHI.

Brain structure-function associations identified in large-scale neuroimaging data

The relationships between structural and functional measures of the human brain remain largely unknown. A majority of our limited knowledge regarding structure–function associations has been obtained through comparisons between specific groups of patients and healthy controls. Unfortunately, a direct and complete view of the associations across multiple structural and functional metrics in normal population is missing. We filled this gap by learning cross-individual co-variance among structural and functional measures using large-scale neuroimaging datasets. A discover-confirm scheme was applied to two independent samples (N = 184 and N = 340) of multi-modal neuroimaging datasets. A data mining tool, gRAICAR, was employed in the discover stage to generate quantitative and unbiased hypotheses of the co-variance among six functional and six structural imaging metrics. These hypotheses were validated using an independent dataset in the confirm stage. Fifteen multi-metric co-variance units, representing different co-variance relationships among the 12 metrics, were reliable across the two sets of neuroimaging datasets. The reliable co-variance units were summarized into a database, where users can select any location on the cortical map of any metric to examine the co-varying maps with the other 11 metrics. This database characterized the six functional metrics based on their co-variance with structural metrics, and provided a detailed reference to connect previous findings using different metrics and to predict maps of unexamined metrics. Gender, age, and handedness were associated to the co-variance units, and a sub-study of schizophrenia demonstrated the usefulness of the co-variance database.

Incomplete Hippocampal Inversion: A Comprehensive MRI Study of Over 2000 Subjects

The incomplete-hippocampal-inversion (IHI), also known as malrotation, is an atypical anatomical pattern of the hippocampus, which has been reported in healthy subjects in different studies. However, extensive characterization of IHI in a large sample has not yet been performed. Furthermore, it is unclear whether IHI are restricted to the medial-temporal lobe or are associated with more extensive anatomical changes. Here, we studied the characteristics of IHI in a community-based sample of 2008 subjects of the IMAGEN database and their association with extra-hippocampal anatomical variations. The presence of IHI was assessed on T1-weighted anatomical magnetic resonance imaging (MRI) using visual criteria. We assessed the association of IHI with other anatomical changes throughout the brain using automatic morphometry of cortical sulci. We found that IHI were much more frequent in the left hippocampus (left: 17%, right: 6%, χ(2)-test, p < 10(-28)). Compared to subjects without IHI, subjects with IHI displayed morphological changes in several sulci located mainly in the limbic lobe. Our results demonstrate that IHI are a common left-sided phenomenon in normal subjects and that they are associated with morphological changes outside the medial temporal lobe.

Gray matter structural compromise is equally distributed in left and right temporal lobe epilepsy

In drug-resistant temporal lobe epilepsy (TLE), MRI studies have shown consistent mesiotemporal and neocortical structural alterations when comparing patients to healthy controls. It remains, however, relatively unclear whether the side of seizure focus differentially impacts the degree of structural damage. This work performed a comprehensive surface-based analysis of mesiotemporal and neocortical morphology on preoperative 1.5 T MRI in 25/35 LTLE/RTLE patients that achieved seizure freedom after surgery (i.e., Engel-I outcome; 7 ± 2 years follow-up), an imaging-independent confirmation of focus lateralization. Compared to 46 age- and sex-matched controls, both TLE groups displayed marked ipsilateral atrophy in mesiotemporal regions, while cortical thinning was bilateral. Direct contrasts between LTLE and RTLE did not reveal significant differences. Bootstrap simulations indicated low reproducibility of observing a between-cohort difference; power analysis revealed that more than 110 patients would be necessary to detect subtle differences. No difference between LTLE and RTLE was confirmed when using voxel-based morphometry, an independent proxy of gray matter volume. Similar results were obtained analyzing a separate 3 T dataset (15/15 LTLE/RTLE patients; Engel-I after 4 ± 2 years follow-up; 42 controls). Our results strongly support equivalent gray matter compromise in left and right TLE. The morphological profile of seizure-free patients, presenting with ipsilateral mesiotemporal and bilateral cortical atrophy, motivates the development of neuromarkers of outcome that consider both mesiotemporal and neocortical structures. Hum Brain Mapp 37:515-524, 2016. © 2015 Wiley Periodicals, Inc.

Multi-atlas segmentation of biomedical images: A survey

Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, et al. (2004), Klein, et al. (2005), and Heckemann, et al. (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of "atlases" (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003-2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation.

Accurate cortical tissue classification on MRI by modeling cortical folding patterns

Accurate tissue classification is a crucial prerequisite to MRI morphometry. Automated methods based on intensity histograms constructed from the entire volume are challenged by regional intensity variations due to local radiofrequency artifacts as well as disparities in tissue composition, laminar architecture and folding patterns. Current work proposes a novel anatomy-driven method in which parcels conforming cortical folding were regionally extracted from the brain. Each parcel is subsequently classified using nonparametric mean shift clustering. Evaluation was carried out on manually labeled images from two datasets acquired at 3.0 Tesla (n = 15) and 1.5 Tesla (n = 20). In both datasets, we observed high tissue classification accuracy of the proposed method (Dice index >97.6% at 3.0 Tesla, and >89.2% at 1.5 Tesla). Moreover, our method consistently outperformed state-of-the-art classification routines available in SPM8 and FSL-FAST, as well as a recently proposed local classifier that partitions the brain into cubes. Contour-based analyses localized more accurate white matter-gray matter (GM) interface classification of the proposed framework compared to the other algorithms, particularly in central and occipital cortices that generally display bright GM due to their highly degree of myelination. Excellent accuracy was maintained, even in the absence of correction for intensity inhomogeneity. The presented anatomy-driven local classification algorithm may significantly improve cortical boundary definition, with possible benefits for morphometric inference and biomarker discovery.

Beyond the CA1 subfield: Local hippocampal shape changes in MRI-negative temporal lobe epilepsy

OBJECTIVE

Hippocampal atrophy in temporal lobe epilepsy (TLE) can indicate mesial temporal sclerosis and predict surgical success. Yet many patients with TLE do not have significant atrophy (magnetic resonance imaging (MRI) negative), which presents a diagnostic challenge. We used a new variant of high-dimensional large-deformation mapping to assess whether patients with apparently normal hippocampi have local shape changes that mirror those of patients with significant hippocampal atrophy.

METHODS

Forty-seven patients with unilateral TLE and 32 controls underwent structural brain MRI. High-dimensional large-deformation mapping provided hippocampal surface and volume estimates for each participant, dividing patients into low versus high hippocampal atrophy groups. A vertex-level generalized linear model compared local shape changes between groups.

RESULTS

Patients with low-atrophy TLE (MRI negative) had significant local hippocampal shape changes compared to controls, similar to those in the contralateral hippocampus of high-atrophy patients. These changes primarily involved the subicular and hilar/dentate regions, instead of the classically affected CA1 region. Disease duration instead co-varied with lateral hippocampal atrophy, co-localizing with the CA1 subfield.

SIGNIFICANCE

These findings show that patients with "MRI-negative" TLE have regions of hippocampal atrophy that cluster medially, sparing the lateral regions (CA1) involved in high-atrophy patients. This suggests an overall effect of temporal lobe seizures manifesting as bilateral medial hippocampal atrophy, and a more selective effect of hippocampal seizures leading to disease-proportional CA1 atrophy, potentially reflecting epileptogenesis.

Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults

BACKGROUND

Preterm born very-low-birth-weight (VLBW: birth weight ≤1500 g) survivors have increased risk of perinatal brain injury that may cause deviant brain development and later neuroimpairments, including reduced cognitive functioning.

AIMS

In this long-term follow up study of three year-cohorts (birth years 1986-88) of VLBW subjects and term born controls with normal birth weight, the aim was to examine differences in brain volumes at age 20 years. In addition, the relationships between brain volumes and cognitive abilities and perinatal variables were explored.

METHODS

Forty-four VLBW subjects and 60 controls were assessed with cognitive testing (Wechsler Adult Intelligence Scale - WAIS-III) and structural MRI at 1.5 T, using the FreeSurfer 5.1 software for volumetric analysis. A subpopulation had MRI performed also at age 15, and for this group changes in brain volumes with age were examined.

RESULTS

The VLBW subjects had smaller brain volumes, especially of thalamus, globus pallidus and parts of the corpus callosum, and larger lateral ventricles than controls at age 20. However, no significant group differences in longitudinal change from age 15 to 20 were observed. The most immature and smallest VLBW subjects at birth, and those with the highest perinatal morbidity, showed most pronounced volume deviations. Positive associations between several brain volumes and full IQ, as well as three of four IQ indices in the VLBW group, were observed.

CONCLUSION

Reduced volumes of grey and white matter and ventricular dilatation in VLBW young adults may indicate permanent effects on brain development from perinatal brain injury with influence on later cognitive function.

Automated versus manual hippocampal segmentation in preoperative and postoperative patients with epilepsy

OBJECTIVE

To compare manual and automated preoperative and postoperative hippocampal volume measurements in patients with intractable epilepsy.

METHODS

We studied 34 patients referred to the Clinical Epilepsy Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH) for evaluation of intractable epilepsy and 21 normal volunteers who received 1.5 or 3 T GE Signa magnetic resonance imaging (MRI) scans. Hippocampal volumes were traced manually on each slice and assembled into three-dimensional volumes by investigators who were blinded to other data. Automated volumetric measurements were obtained using FreeSurfer. Statistical analysis was performed with GraphPad Prism.

RESULTS

Automated hippocampal volumes were larger than manual volumes in both patients and normal volunteers (p < 0.05). Right to left hemisphere hippocampal ratio and percent of hippocampus resected did not differ significantly by segmentation method. It was not possible to obtain accurate total resection volumes with the automated method.

SIGNIFICANCE

Values such as side-to-side ratio and percent resected may be more directly translatable between manual and automated methods than absolute measures of volume. Accurate determination of resection volumes is important for studies of the effects of surgery on both seizure control and postoperative neuropsychological deficits. Our preliminary data suggest that FreeSurfer may provide an accurate and simple method for quantitating hippocampal resections. However, it may be less valuable for large or extratemporal resections, or when distortions of normal anatomy are present. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Hippocampal surface deformation accuracy in T1-weighted volumetric MRI sequences in subjects with epilepsy

BACKGROUND AND PURPOSE

To demonstrate the accuracy across different acquisition and analysis methods, we evaluated the variability in hippocampal volumetric and surface displacement measurements resulting from two different MRI (magnetic resonance imaging) acquisition protocols.

METHODS

Nine epilepsy patients underwent two independent T1-weighted magnetization prepared spoiled gradient sequences during a single 3T MRI session. Using high-dimension mapping-large deformation (HDM-LD) segmentation, we calculated volumetric estimates and generated a vector-based 3-dimensional surface model of each subject's hippocampi, and evaluated volume and surface changes, the latter using a cluster-based noise estimation model.

RESULTS

Mean hippocampal volumes and standard deviations for the left hippocampi were 2,750 (826) mm3 and 2,782 (859) mm3 (P = .13), and for the right hippocampi were 2,558 (750) mm3 and 2,547 (692) mm3 (P = .76), respectively for the MPR1 and MPR2 sequences. Average Dice coefficient comparing overlap for segmentations was 86%. There was no significant effect of MRI sequence on volume estimates and no significant hippocampal surface change between sequences.

CONCLUSION

Statistical comparison of hippocampal volumes and statistically thresholded HDM-LD surfaces in TLE patients showed no differences between the segmentations obtained in the two MRI acquisition sequences. This validates the robustness across MRI sequences of the HDM-LD technique for estimating volume and surface changes in subjects with epilepsy.

Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST

BACKGROUND

To measure hippocampal volume change in Alzheimer's disease (AD) or mild cognitive impairment (MCI), expert manual delineation is often used because of its supposed accuracy. It has been suggested that expert outlining yields poorer reproducibility as compared to automated methods, but this has not been investigated.

AIM

To determine the reproducibilities of expert manual outlining and two common automated methods for measuring hippocampal atrophy rates in healthy aging, MCI and AD.

METHODS

From the Alzheimer's Disease Neuroimaging Initiative (ADNI), 80 subjects were selected: 20 patients with AD, 40 patients with mild cognitive impairment (MCI) and 20 healthy controls (HCs). Left and right hippocampal volume change between baseline and month-12 visit was assessed by using expert manual delineation, and by the automated software packages FreeSurfer (longitudinal processing stream) and FIRST. To assess reproducibility of the measured hippocampal volume change, both back-to-back (BTB) MPRAGE scans available for each visit were analyzed. Hippocampal volume change was expressed in μL, and as a percentage of baseline volume. Reproducibility of the 1-year hippocampal volume change was estimated from the BTB measurements by using linear mixed model to calculate the limits of agreement (LoA) of each method, reflecting its measurement uncertainty. Using the delta method, approximate p-values were calculated for the pairwise comparisons between methods. Statistical analyses were performed both with inclusion and exclusion of visibly incorrect segmentations.

RESULTS

Visibly incorrect automated segmentation in either one or both scans of a longitudinal scan pair occurred in 7.5% of the hippocampi for FreeSurfer and in 6.9% of the hippocampi for FIRST. After excluding these failed cases, reproducibility analysis for 1-year percentage volume change yielded LoA of ±7.2% for FreeSurfer, ±9.7% for expert manual delineation, and ±10.0% for FIRST. Methods ranked the same for reproducibility of 1-year μL volume change, with LoA of ±218 μL for FreeSurfer, ±319 μL for expert manual delineation, and ±333 μL for FIRST. Approximate p-values indicated that reproducibility was better for FreeSurfer than for manual or FIRST, and that manual and FIRST did not differ. Inclusion of failed automated segmentations led to worsening of reproducibility of both automated methods for 1-year raw and percentage volume change.

CONCLUSION

Quantitative reproducibility values of 1-year microliter and percentage hippocampal volume change were roughly similar between expert manual outlining, FIRST and FreeSurfer, but FreeSurfer reproducibility was statistically significantly superior to both manual outlining and FIRST after exclusion of failed segmentations.

Automated hippocampal segmentation in patients with epilepsy: available free online

PURPOSE

Hippocampal sclerosis, a common cause of refractory focal epilepsy, requires hippocampal volumetry for accurate diagnosis and surgical planning. Manual segmentation is time-consuming and subject to interrater/intrarater variability. Automated algorithms perform poorly in patients with temporal lobe epilepsy. We validate and make freely available online a novel automated method.

METHODS

Manual hippocampal segmentation was performed on 876, 3T MRI scans and 202, 1.5T scans. A template database of 400 high-quality manual segmentations was used to perform automated segmentation of all scans with a multi-atlas-based segmentation propagation method adapted to perform label fusion based on local similarity to ensure accurate segmentation regardless of pathology. Agreement between manual and automated segmentations was assessed by degree of overlap (Dice coefficient) and comparison of hippocampal volumes.

KEY FINDINGS

The automated segmentation algorithm provided robust delineation of the hippocampi on 3T scans with no more variability than that seen between different human raters (Dice coefficients: interrater 0.832, manual vs. automated 0.847). In addition, the algorithm provided excellent results with the 1.5T scans (Dice coefficient 0.827), and automated segmentation remained accurate even in small sclerotic hippocampi. There was a strong correlation between manual and automated hippocampal volumes (Pearson correlation coefficient 0.929 on the left and 0.941 on the right in 3T scans).

SIGNIFICANCE

We demonstrate reliable identification of hippocampal atrophy in patients with hippocampal sclerosis, which is crucial for clinical management of epilepsy, particularly if surgical treatment is being contemplated. We provide a free online Web-based service to enable hippocampal volumetry to be available globally, with consequent greatly improved evaluation of those with epilepsy.

Disentangling hippocampal shape anomalies in epilepsy

Drug-resistant temporal lobe epilepsy (TLE) and epileptic syndromes related to malformations of cortical development (MCD) are associated with complex hippocampal morphology. The contribution of volume and position to the overall hippocampal shape in these conditions has not been studied. We propose a surface-based framework to localize volume changes through measurement of Jacobian determinants, and quantify fine-scale position and curvature through a medial axis model. We applied our methodology to T1-weighted 3D volumetric MRI of 88 patients with TLE and 78 patients with MCD, including focal cortical dysplasia (FCD, n = 29), heterotopia (HET, n = 40), and polymicrogyria (PMG, n = 19). Patients were compared to 46 age- and sex-matched healthy controls. Surface-based analysis of volume in TLE revealed severe ipsilateral atrophy mainly along the rostro-caudal extent of the hippocampal CA1 subfield. In MCD, patterns of volume changes included bilateral CA1 atrophy in HET and FCD, and left dentate hypertrophy in all three groups. The analysis of curvature revealed medial bending of the posterior hippocampus in TLE, whereas in MCD there was a supero-medial shift of the hippocampal body. Albeit hippocampal shape anomalies in TLE and MCD result from a combination of volume and positional changes, their nature and distribution suggest different pathogenic mechanisms.

Quantitative analysis of structural neuroimaging of mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is the most common of the surgically remediable drug-resistant epilepsies. MRI is the primary diagnostic tool to detect anatomical abnormalities and, when combined with EEG, can more accurately identify an epileptogenic lesion, which is often hippocampal sclerosis in cases of MTLE. As structural imaging technology has advanced the surgical treatment of MTLE and other lesional epilepsies, so too have the analysis techniques that are used to measure different structural attributes of the brain. These techniques, which are reviewed here and have been used chiefly in basic research of epilepsy and in studies of MTLE, have identified different types and the extent of anatomical abnormalities that can extend beyond the affected hippocampus. These results suggest that structural imaging and sophisticated imaging analysis could provide important information to identify networks capable of generating spontaneous seizures and ultimately help guide surgical therapy that improves postsurgical seizure-freedom outcomes.

A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease

Hippocampal volumetry derived from structural MRI is increasingly used to delineate regions of interest for functional measurements, assess efficacy in therapeutic trials of Alzheimer's disease (AD) and has been endorsed by the new AD diagnostic guidelines as a radiological marker of disease progression. Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus. Recent developments in automated volumetry commonly use multi-template fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects. However, there are several protocols to define the hippocampus anatomically in vivo, and the method used to generate atlases may impact automatic accuracy and sensitivity - particularly in pathologically heterogeneous samples. Here we report a fully automated segmentation technique that provides a robust platform to directly evaluate both technical and biomarker performance in AD among anatomically unique labeling protocols. For the first time we test head-to-head the performance of five common hippocampal labeling protocols for multi-atlas based segmentation, using both the Sunnybrook Longitudinal Dementia Study and the entire Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) baseline and 24-month dataset. We based these atlas libraries on the protocols of (Haller et al., 1997; Killiany et al., 1993; Malykhin et al., 2007; Pantel et al., 2000; Pruessner et al., 2000), and a single operator performed all manual tracings to generate de facto "ground truth" labels. All methods distinguished between normal elders, mild cognitive impairment (MCI), and AD in the expected directions, and showed comparable correlations with measures of episodic memory performance. Only more inclusive protocols distinguished between stable MCI and MCI-to-AD converters, and had slightly better associations with episodic memory. Moreover, we demonstrate that protocols including more posterior anatomy and dorsal white matter compartments furnish the best voxel-overlap accuracies (Dice Similarity Coefficient=0.87-0.89), compared to expert manual tracings, and achieve the smallest sample sizes required to power clinical trials in MCI and AD. The greatest distribution of errors was localized to the caudal hippocampus and the alveus-fimbria compartment when these regions were excluded. The definition of the medial body did not significantly alter accuracy among more comprehensive protocols. Voxel-overlap accuracies between automatic and manual labels were lower for the more pathologically heterogeneous Sunnybrook study in comparison to the ADNI-1 sample. Finally, accuracy among protocols appears to significantly differ the most in AD subjects compared to MCI and normal elders. Together, these results suggest that selection of a candidate protocol for fully automatic multi-template based segmentation in AD can influence both segmentation accuracy when compared to expert manual labels and performance as a biomarker in MCI and AD.