Neda Bernasconi

YNICL Journal 2024 Journal Article

Region-specific MRI predictors of surgical outcome in temporal lobe epilepsy

• Fatemeh Fadaie
• Benoit Caldairou
• Ravnoor S. Gill
• Niels A. Foit
• Jeffery A. Hall
• Boris C. Bernhardt
• Neda Bernasconi
• Andrea Bernasconi

OBJECTIVE: In drug-resistant temporal lobe epilepsy (TLE), it is not well-established in how far surgery should target morphological anomalies to achieve seizure freedom. Here, we assessed interactions between structural brain compromise and surgery to identify region-specific predictors of seizure outcome. METHODS: We obtained pre- and post-operative 3D T1-weighted MRI in 55 TLE patients who underwent selective amygdalo-hippocampectomy (SAH) or anterior temporal lobectomy (ATL) and 40 age and sex-matched healthy subjects. We measured surface-based morphological alterations of the mesiotemporal lobe structures (hippocampus, amygdala, entorhinal and piriform cortices), the neocortex and the thalamus on both pre- and post-operative MRI. Using precise co-registration, in each patient we mapped the surgical cavity onto the MRI acquired before surgery, thereby quantifying the amount of pathological tissue resected; these features, together with the preoperative morphometric data, served as input to a supervised classification algorithm for postsurgical outcome prediction. RESULTS: On pre-operative MRI, patients who became seizure-free (TLE-SF) presented with severe ipsilateral amygdalar and hippocampal atrophy, while not seizure-free patients (TLE-NSF) displayed amygdalar hypertrophy. Stratifying patients based on the surgical approach, post-operative MRI showed similar patterns of mesiotemporal and thalamic changes, but divergent neocortical thinning affecting the parieto-temporo-occipital regions following ATL and the frontal lobes after SAH. Irrespective of the surgical approach, hippocampal atrophy on pre-operative MRI and its extent of resection were the most predictive features of seizure-freedom in 89% of patients (selected 100% across validations). SIGNIFICANCE: Our study indicates a critical role of the extent of resection of MRI-derived hippocampal morphological anomalies on seizure outcome. Precise pre-operative quantification of the mesiotemporal lobe provides non-invasive prognostics for individualized surgery.

YNIMG Journal 2022 Journal Article

A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface

• Niels A. Foit
• Seles Yung
• Hyo Min Lee
• Andrea Bernasconi
• Neda Bernasconi
• Seok-Jun Hong

Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrated a close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease.

YNIMG Journal 2022 Journal Article

Heritability of hippocampal functional and microstructural organisation

• Şeyma Bayrak
• Reinder Vos de Wael
• H. Lina Schaare
• Meike D. Hettwer
• Benoit Caldairou
• Andrea Bernasconi
• Neda Bernasconi
• Boris C. Bernhardt

The hippocampus is a uniquely infolded allocortical structure in the medial temporal lobe that consists of the microstructurally and functionally distinct subregions: subiculum, cornu ammonis, and dentate gyrus. The hippocampus is a remarkably plastic region that is implicated in learning and memory. At the same time it has been shown that hippocampal subregion volumes are heritable, and that genetic expression varies along a posterior to anterior axis. Here, we studied how a heritable, stable, hippocampal organisation may support its flexible function in healthy adults. Leveraging the twin set-up of the Human Connectome Project with multimodal neuroimaging, we observed that the functional connectivity between hippocampus and cortex was heritable and that microstructure of the hippocampus genetically correlated with cortical microstructure. Moreover, both functional and microstructural organisation could be consistently captured by anterior-to-posterior and medial-to-lateral axes across individuals. However, heritability of functional, relative to microstructural, organisation was found reduced, suggesting individual variation in functional organisation may be explained by experience-driven factors. Last, we demonstrate that structure and function couple along an inherited macroscale organisation, suggesting an interplay of stability and plasticity within the hippocampus. Our study provides new insights on the heritability of the hippocampal of the structure and function within the hippocampal organisation.

YNICL Journal 2021 Journal Article

Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

• Ezequiel Gleichgerrcht
• Brent C. Munsell
• Saud Alhusaini
• Marina K.M. Alvim
• Núria Bargalló
• Benjamin Bender
• Andrea Bernasconi
• Neda Bernasconi

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

YNICL Journal 2020 Journal Article

Microstructural imaging in temporal lobe epilepsy: Diffusion imaging changes relate to reduced neurite density

• Gavin P Winston
• Sjoerd B Vos
• Benoit Caldairou
• Seok-Jun Hong
• Monika Czech
• Tobias C Wood
• Stephen J Wastling
• Gareth J Barker

PURPOSE: Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics. METHODS: 20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured. RESULTS: In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF. CONCLUSIONS: Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study.

YNICL Journal 2020 Journal Article

Unsupervised machine learning reveals lesional variability in focal cortical dysplasia at mesoscopic scale

• Hyo M. Lee
• Ravnoor S. Gill
• Fatemeh Fadaie
• Kyoo H. Cho
• Marie C. Guiot
• Seok-Jun Hong
• Neda Bernasconi
• Andrea Bernasconi

OBJECTIVE: Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation and a prevalent cause of surgically amenable epilepsy. While cellular and molecular biology data suggest that FCD lesional characteristics lie along a spectrum, this notion remains to be verified in vivo. We tested the hypothesis that machine learning applied to MRI captures FCD lesional variability at a mesoscopic scale. METHODS: We studied 46 patients with histologically verified FCD Type II and 35 age- and sex-matched healthy controls. We applied consensus clustering, an unsupervised learning technique that identifies stable clusters based on bootstrap-aggregation, to 3 T multicontrast MRI (T1-weighted MRI and FLAIR) features of FCD normalized with respect to distributions in controls. RESULTS: Lesions were parcellated into four classes with distinct structural profiles variably expressed within and across patients: Class-1 with isolated white matter (WM) damage; Class-2 combining grey matter (GM) and WM alterations; Class-3 with isolated GM damage; Class-4 with GM-WM interface anomalies. Class membership was replicated in two independent datasets. Classes with GM anomalies impacted local function (resting-state fMRI derived ALFF), while those with abnormal WM affected large-scale connectivity (assessed by degree centrality). Overall, MRI classes reflected typical histopathological FCD characteristics: Class-1 was associated with severe WM gliosis and interface blurring, Class-2 with severe GM dyslamination and moderate WM gliosis, Class-3 with moderate GM gliosis, Class-4 with mild interface blurring. A detection algorithm trained on class-informed data outperformed a class-naïve paradigm. SIGNIFICANCE: Machine learning applied to widely available MRI contrasts uncovers FCD Type II variability at a mesoscopic scale and identifies tissue classes with distinct structural dimensions, functional and histopathological profiles. Integrating in vivo staging of FCD traits with automated lesion detection is likely to inform the development of novel personalized treatments.

YNIMG Journal 2018 Journal Article

Preferential susceptibility of limbic cortices to microstructural damage in temporal lobe epilepsy: A quantitative T1 mapping study

• Boris C. Bernhardt
• Fatemeh Fadaie
• Reinder Vos de Wael
• Seok-Jun Hong
• Min Liu
• Marie C. Guiot
• David A. Rudko
• Andrea Bernasconi

The majority of MRI studies in temporal lobe epilepsy (TLE) have utilized morphometry to map widespread cortical alterations. Morphological markers, such as cortical thickness or grey matter density, reflect combinations of biological events largely driven by overall cortical geometry rather than intracortical tissue properties. Because of its sensitivity to intracortical myelin, quantitative measurement of longitudinal relaxation time (qT1) provides and an in vivo proxy for cortical microstructure. Here, we mapped the regional distribution of qT1 in a consecutive cohort of 24 TLE patients and 20 healthy controls. Compared to controls, patients presented with a strictly ipsilateral distribution of qT1 increases in temporopolar, parahippocampal and orbitofrontal cortices. Supervised statistical learning applied to qT1 maps could lateralize the seizure focus in 92% of patients. Intracortical profiling of qT1 along streamlines perpendicular to the cortical mantle revealed marked effects in upper levels that tapered off at the white matter interface. Findings remained robust after correction for cortical thickness and interface blurring, suggesting independence from previously reported morphological anomalies in this disorder. Mapping of qT1 along hippocampal subfield surfaces revealed marked increases in anterior portions of the ipsilateral CA1-3 and DG that were also robust against correction for atrophy. Notably, in operated patients, qualitative histopathological analysis of myelin stains in resected hippocampal specimens confirmed disrupted internal architecture and fiber organization. Both hippocampal and neocortical qT1 anomalies were more severe in patients with early disease onset. Finally, analysis of resting-state connectivity from regions of qT1 increases revealed altered intrinsic functional network embedding in patients, particularly to prefrontal networks. Analysis of qT1 suggests a preferential susceptibility of ipsilateral limbic cortices to microstructural damage, possibly related to disrupted myeloarchitecture. These alterations may reflect atypical neurodevelopment and affect the integrity of fronto-limbic functional networks.

YNIMG Journal 2017 Journal Article

Knowing what from where: Hippocampal connectivity with temporoparietal cortex at rest is linked to individual differences in semantic and topographic memory

• Mladen Sormaz
• Elizabeth Jefferies
• Boris C. Bernhardt
• Theodoros Karapanagiotidis
• Giovanna Mollo
• Neda Bernasconi
• Andrea Bernasconi
• Tom Hartley

The hippocampus contributes to episodic, spatial and semantic aspects of memory, yet individual differences within and between these functions are not well-understood. In 136 healthy individuals, we investigated whether these differences reflect variation in the strength of connections between functionally-specialised segments of the hippocampus and diverse cortical regions that participate in different aspects of memory. Better topographical memory was associated with stronger connectivity between lingual gyrus and left anterior, rather than posterior, hippocampus. Better semantic memory was associated with increased connectivity between the intracalcarine/cuneus and left, rather than right, posterior hippocampus. Notably, we observed a double dissociation between semantic and topographical memory: better semantic memory was associated with stronger connectivity between left temporoparietal cortex and left anterior hippocampus, while better topographic memory was linked to stronger connectivity with right anterior hippocampus. Together these data support a division-of-labour account of hippocampal functioning: at the population level, differences in connectivity across the hippocampus reflect functional specialisation for different facets of memory, while variation in these connectivity patterns across individuals is associated with differences in the capacity to retrieve different types of information. In particular, within-hemisphere connectivity between hippocampus and left temporoparietal cortex supports conceptual processing at the expense of spatial ability.

YNIMG Journal 2012 Journal Article

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

• Hosung Kim
• Marie Chupin
• Olivier Colliot
• Boris C. Bernhardt
• Neda Bernasconi
• Andrea Bernasconi

In drug-resistant temporal lobe epilepsy (TLE), detecting hippocampal atrophy on MRI is important as it allows defining the surgical target. The performance of automatic segmentation in TLE has so far been considered unsatisfactory. In addition to atrophy, about 40% of patients present with developmental abnormalities (referred to as malrotation) characterized by atypical morphologies of the hippocampus and collateral sulcus. Our purpose was to evaluate the impact of malrotation and atrophy on the performance of three state-of-the-art automated algorithms. We segmented the hippocampus in 66 patients and 35 sex- and age-matched healthy subjects using a region-growing algorithm constrained by anatomical priors (SACHA), a freely available atlas-based software (FreeSurfer) and a multi-atlas approach (ANIMAL-multi). To quantify malrotation, we generated 3D models from manual hippocampal labels and automatically extracted collateral sulci. The accuracy of automated techniques was evaluated relative to manual labeling using the Dice similarity index and surface-based shape mapping, for which we computed vertex-wise displacement vectors between automated and manual segmentations. We then correlated segmentation accuracy with malrotation features and atrophy. ANIMAL-multi demonstrated similar accuracy in patients and healthy controls (p>0. 1), whereas SACHA and FreeSurfer were less accurate in patients (p<0. 05). Surface-based analysis of contour accuracy revealed that SACHA over-estimated the lateral border of malrotated hippocampi (r=0. 61; p<0. 0001), but performed well in the presence of atrophy (|r|<0. 34; p>0. 2). Conversely, FreeSurfer and ANIMAL-multi were affected by both malrotation (FreeSurfer: r=0. 57; p=0. 02, ANIMAL-multi: r=0. 50; p=0. 05) and atrophy (FreeSurfer: r=0. 78, p<0. 0001, ANIMAL-multi: r=0. 61; p<0. 0001). Compared to manual volumetry, automated procedures underestimated the magnitude of atrophy (Cohen's d: manual: 1. 68; ANIMAL-multi: 1. 11; SACHA: 1. 10; FreeSurfer: 0. 90, p<0. 0001). In addition, they tended to lateralize the seizure focus less accurately in the presence of malrotation (manual: 64%; ANIMAL-multi: 55%, p=0. 4; SACHA: 50%, p=0. 1; FreeSurfer: 41%, p=0. 05). Hippocampal developmental anomalies and atrophy had a negative impact on the segmentation performance of three state-of-the-art automated methods. These shape variants should be taken into account when designing segmentation algorithms.

YNIMG Journal 2009 Journal Article

Thalamo–cortical network pathology in idiopathic generalized epilepsy: Insights from MRI-based morphometric correlation analysis

• Boris C. Bernhardt
• Daniel A. Rozen
• Keith J. Worsley
• Alan C. Evans
• Neda Bernasconi
• Andrea Bernasconi

Epileptic activity underlying idiopathic generalized epilepsy (IGE) is related to abnormal thalamo–cortical interactions. Our purpose was to map in vivo the organization of the thalamo–cortical network in IGE. We measured cortical thickness and thalamic volumes on MRI in 23 IGE patients with generalized tonic–clonic seizures only and 46 healthy controls. Significant correlations between thalamic volumes and cortical thickness were interpreted as thalamo–cortical network connections. In controls, thickness of frontal, limbic, and occipital regions was positively correlated with the thalamic volumes, corresponding to known anatomical connections from sacrificial tracer studies in primates and human in vivo DTI data. In patients, thalamo–cortical network correlations increased in fronto-central and parietal regions, but decreased in limbic areas. Group analysis revealed that, compared to controls, IGE patients had bilateral thalamic atrophy and widespread cortical thinning that was most prominent in fronto-central areas, with a prevalence of up to 40%. Duration of epilepsy affected negatively thalamic volumes and thickness of fronto-central and limbic cortices. These effects were significantly different from aging in controls. Patients with poorly controlled seizures showed an even faster progression in these neocortical regions. Fronto-centro-parietal atrophy in IGE is likely the effect of generalized seizure activity inducing thalamo–cortical network remodeling. On the other hand, limbic abnormalities may take place secondary to thalamic disconnection.

YNIMG Journal 2008 Journal Article

Mapping limbic network organization in temporal lobe epilepsy using morphometric correlations: Insights on the relation between mesiotemporal connectivity and cortical atrophy

• Boris C. Bernhardt
• Keith J. Worsley
• Pierre Besson
• Luis Concha
• Jason P. Lerch
• Alan C. Evans
• Neda Bernasconi

Temporal lobe epilepsy (TLE) is considered primarily a limbic disorder. Our purpose was to map limbic network organization in TLE and to statistically relate it to neocortical atrophy. We performed MRI-based cortical thickness analysis in 110 TLE patients (including 68 patients with hippocampal atrophy and 42 patients with normal hippocampal volume) and 46 healthy controls. Limbic connectivity was statistically inferred by correlating mean thickness of the entorhinal cortex (EC) with thickness at each vertex across the entire neocortex. The EC was chosen as seed region since it is the link between the neocortex and the hippocampal formation. Patients showed cortical thinning mainly in temporal and fronto-central neocortices, with a prevalence of atrophy in up to 35%. In controls, EC networks corresponded closely to known anatomical connections. In TLE the pattern of correlations was similar to controls, suggesting that pathological processes in the EC affect the same networks that co-vary with the EC in the healthy brain. Nevertheless, we found decreases in correlations mainly in the temporal lobe and increases mainly in orbitofrontal cortices. Although our analysis indicated alterations in the temporo-limbic network in TLE, there was no association between mesiotemporal connectivity and atrophy across the entire cortical surface. This divergence underlines the complexity of the pathophysiological mechanisms leading to neocortical atrophy in TLE.

YNIMG Journal 2004 Journal Article

Quantitative analysis of temporal lobe white matter T2 relaxation time in temporal lobe epilepsy

• Tiffany N. Townsend
• Neda Bernasconi
• G.Bruce Pike
• Andrea Bernasconi

The objective of this study was to assess temporal lobe white matter (WM) quantitatively using T2 relaxometry in patients with pharmacologically intractable temporal lobe epilepsy (TLE). T2 relaxometry was performed using a dual-echo sequence with 23 contiguous oblique coronal slices in 56 consecutive TLE patients and in 30 healthy subjects. Averages of six slices were chosen to calculate T2 relaxation time in the temporal lobe WM (WM-T2) and the hippocampus (Hippo-T2). Twenty-seven patients had unilateral hippocampal atrophy (HA), and twenty-nine patients had normal hippocampal volumes (NV) on volumetric MRI. Mean WM-T2 was increased ipsilateral to the seizure focus in TLE patients with HA and those with NV (P < 0. 001). Contralateral mean WM-T2 was increased in left and right TLE with HA (P < 0. 001) and in right TLE with NV (P = 0. 001). There was a positive correlation between WM-T2 and Hippo-T2. Individual analysis showed a prolongation of WM-T2 in about 70% of TLE patients with HA and NV. In half of the patients, WM-T2 increase was bilateral and symmetric. However, in 33% of patients with NV and bilateral symmetric increase in Hippo-T2, WM-T2 provided a correct lateralization of the seizure focus. Regardless of the pattern of T2 abnormalities, that is, bilateral symmetric or ipsilateral, the majority of patients with HA became seizure-free after surgery, while those with NV did not have a favorable outcome. In patients with NV, WM-T2 measurement may provide additional lateralizing information compared to Hippo-T2.

YNIMG Journal 2003 Journal Article

Automated detection of focal cortical dysplasia lesions using computational models of their MRI characteristics and texture analysis

• Samson B Antel
• D.Louis Collins
• Neda Bernasconi
• Frederick Andermann
• Rajjan Shinghal
• Robert E Kearney
• Douglas L Arnold
• Andrea Bernasconi

Focal cortical dysplasia (FCD), a malformation of cortical development, is a frequent cause of pharmacologically intractable epilepsy. FCD is characterized on Tl-weighted MRI by cortical thickening, blurring of the gray-matter/white-matter interface, and gray-level hyperintensity. We have previously used computational models of these characteristics to enhance visual lesion detection. In the present study we seek to improve our methods by combining these models with features derived from texture analysis of MRI, which allows measurement of image properties not readily accessible by visual analysis. These computational models and texture features were used to develop a two-stage Bayesian classifier to perform automated FCD lesion detection. Eighteen patients with histologically confirmed FCD and 14 normal controls were studied. On the MRI volumes of the 18 patients, 20 FCD lesions were manually labeled by an expert observer. Three-dimensional maps of the computational models and texture features were constructed for all subjects. A Bayesian classifier was trained on the computational models to classify voxels as cerebrospinal fluid, gray-matter, white-matter, transitional, or lesional. Voxels classified as lesional were subsequently reclassified based on the texture features. This process produced a 3D lesion map, which was compared to the manual lesion labels. The automated classifier identified 17/20 manually labeled lesions. No lesions were identified in controls. Thus, combining models of the T1-weighted MRI characteristics of FCD with texture analysis enabled successful construction of a classifier. This computer-based, automated method may be useful in the presurgical evaluation of patients with severe epilepsy related to FCD.

YNIMG Journal 2001 Journal Article

T2 Relaxometry Can Lateralize Mesial Temporal Lobe Epilepsy in Patients with Normal MRI

• Andrea Bernasconi
• Neda Bernasconi
• Zografos Caramanos
• David C. Reutens
• Frederick Andermann
• Fraçois Dubeau
• Donatella Tampieri
• Bruce G. Pike

YNIMG Journal 2000 Journal Article

T2 Relaxometry Can Lateralize Mesial Temporal Lobe Epilepsy in Patients with Normal MRI

• Andrea Bernasconi
• Neda Bernasconi
• Zografos Caramanos
• David C. Reutens
• Frederick Andermann
• François Dubeau
• Donatella Tampieri
• Bruce G. Pike

In unselected patients with intractable temporal lobe epilepsy (TLE), approximately 15% do not have detectable hippocampal atrophy on MRI. The purpose of this study was to evaluate whether T2 relaxometry can identify hippocampal pathology and lateralize the epileptic focus in patients with intractable TLE, who do not demonstrate hippocampal atrophy on volumetric MRI (MRIV). We selected 14 patients with unilateral TLE who had unilateral atrophy and 11 patients with unilateral TLE who had no evidence of atrophy on MRIV. Images were acquired on a 1. 5 T MR scan using a dual echo sequence with 23 contiguous oblique coronal slices in all patients and in 14 healthy subjects. Fitting a single exponential decay equation to the imaging data generated T2 maps. Averages of six slices containing the head, body, and tail of the hippocampus were used to calculate hippocampal T2 relaxation times (HT2). The epileptic focus was defined by history, video-EEG, and surgical response. All TLE patients with hippocampal atrophy and 9/11 (82%) patients with normal MRI had abnormally high HT2 ipsilateral to the epileptic focus. Bilateral abnormal HT2 were found in 6/14 (43%) of patients with unilateral hippocampal atrophy and 2/11 (18%) of patients with normal MRI. However, this increase was always greater ipsilateral to the epileptic focus. Qualitative hippocampal pathology showed gliosis and neuronal loss in 10/14 operated patients with hippocampal atrophy on MRIV and in 5/7 operated patients with normal MRI. In conclusion, hippocampal T2 mapping provides evidence of hippocampal damage in the majority of patients with intractable TLE who have no evidence of atrophy on MRI and can correctly lateralize the epileptic focus in most patients.