John S. Duncan

YNICL Journal 2023 Journal Article

The impact of temporal lobe epilepsy surgery on picture naming and its relationship to network metric change

• Lawrence Peter Binding
• Peter Neal Taylor
• Aidan G. O'Keeffe
• Davide Giampiccolo
• Marine Fleury
• Fenglai Xiao
• Lorenzo Caciagli
• Jane de Tisi

BACKGROUND: Anterior temporal lobe resection (ATLR) is a successful treatment for medically-refractory temporal lobe epilepsy (TLE). In the language-dominant hemisphere, 30%- 50% of individuals experience a naming decline which can impact upon daily life. Measures of structural networks are associated with language performance pre-operatively. It is unclear if analysis of network measures may predict post-operative decline. METHODS: White matter fibre tractography was performed on preoperative diffusion MRI of 44 left lateralised and left resection individuals with TLE to reconstruct the preoperative structural network. Resection masks, drawn on co-registered pre- and post-operative T1-weighted MRI scans, were used as exclusion regions on pre-operative tractography to estimate the post-operative network. Changes in graph theory metrics, cortical strength, betweenness centrality, and clustering coefficient were generated by comparing the estimated pre- and post-operative networks. These were thresholded based on the presence of the connection in each patient, ranging from 75% to 100% in steps of 5%. The average graph theory metric across thresholds was taken. We incorporated leave-one-out cross-validation with smoothly clipped absolute deviation (SCAD) least absolute shrinkage and selection operator (LASSO) feature selection and a support vector classifier to assess graph theory metrics on picture naming decline. Picture naming was assessed via the Graded Naming Test preoperatively and at 3 and 12 months post-operatively and the outcome was classified using the reliable change index (RCI) to identify clinically significant decline. The best feature combination and model was selected using the area under the curve (AUC). The sensitivity, specificity and F1-score were also reported. Permutation testing was performed to assess the machine learning model and selected regions difference significance. RESULTS: A combination of clinical and graph theory metrics were able to classify outcome of picture naming at 3 months with an AUC of 0.84. At 12 months, change in strength to cortical regions was best able to correctly classify outcome with an AUC of 0.86. Longitudinal analysis revealed that betweenness centrality was the best metric to identify patients who declined at 3 months, who will then continue to experience decline from 3 to 12 months. Both models were significantly higher AUC values than a random classifier. CONCLUSION: Our results suggest that inferred changes of network integrity were able to correctly classify picture naming decline after ATLR. These measures may be used to prospectively to identify patients who are at risk of picture naming decline after surgery and could potentially be utilised to assist tailoring the resection in order to prevent this decline.

YNICL Journal 2022 Journal Article

Volumetric and structural connectivity abnormalities co-localise in TLE

• Jonathan J. Horsley
• Gabrielle M. Schroeder
• Rhys H. Thomas
• Jane de Tisi
• Sjoerd B. Vos
• Gavin P. Winston
• John S. Duncan
• Yujiang Wang

Patients with temporal lobe epilepsy (TLE) exhibit both volumetric and structural connectivity abnormalities relative to healthy controls. How these abnormalities inter-relate and their mechanisms are unclear. We computed grey matter volumetric changes and white matter structural connectivity abnormalities in 144 patients with unilateral TLE and 96 healthy controls. Regional volumes were calculated using T1-weighted MRI, while structural connectivity was derived using white matter fibre tractography from diffusion-weighted MRI. For each regional volume and each connection strength, we calculated the effect size between patient and control groups in a group-level analysis. We then applied hierarchical regression to investigate the relationship between volumetric and structural connectivity abnormalities in individuals. Additionally, we quantified whether abnormalities co-localised within individual patients by computing Dice similarity scores. In TLE, white matter connectivity abnormalities were greater when joining two grey matter regions with abnormal volumes. Similarly, grey matter volumetric abnormalities were greater when joined by abnormal white matter connections. The extent of volumetric and connectivity abnormalities related to epilepsy duration, but co-localisation did not. Co-localisation was primarily driven by neighbouring abnormalities in the ipsilateral hemisphere. Overall, volumetric and structural connectivity abnormalities were related in TLE. Our results suggest that shared mechanisms may underlie changes in both volume and connectivity alterations in patients with TLE.

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.

YNIMG Journal 2021 Journal Article

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

• Kurt G. Schilling
• François Rheault
• Laurent Petit
• Colin B. Hansen
• Vishwesh Nath
• Fang-Cheng Yeh
• Gabriel Girard
• Muhamed Barakovic

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

YNIMG Journal 2021 Journal Article

Validation of a combined image derived input function and venous sampling approach for the quantification of [18F]GE-179 PET binding in the brain

• Marian Galovic
• Kjell Erlandsson
• Tim D. Fryer
• Young T. Hong
• Roido Manavaki
• Hasan Sari
• Sarah Chetcuti
• Benjamin A. Thomas

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0. 99, p<0. 001), PWB ratio (r = 0. 93, p<0. 001), and the PIF (r = 0. 92, p<0. 001) as well as total distribution volume (VT ) in 11 regions across the brain (r = 0. 95, p<0. 001). IDIF+venous VT had a mean bias of −1. 7% and a comparable regional coefficient of variation (arterial: 21. 3 ± 2. 5%, IDIF+venous: 21. 5 ± 2. 0%). Simplification of the IDIF+venous method to use only one venous sample provided less accurate V T estimates (mean bias 9. 9%; r = 0. 71, p<0. 001). A version of the method that avoids the need for blood sampling by combining the IDIF with population-based PF and PWB ratio estimates systematically underestimated VT (mean bias −20. 9%), and produced VT estimates with a poor correlation to those obtained using arterial data (r = 0. 45, p<0. 001). Arterial and venous blood data from 7 TBI patients showed high correlations for PF (r = 0. 92, p = 0. 003) and PWB ratio (r = 0. 93, p = 0. 003). In conclusion, the IDIF+venous method with five venous samples provides a viable alternative to arterial sampling for quantification of [18F]GE-179 VT.

YNICL Journal 2020 Journal Article

Computer-assisted planning for minimally invasive anterior two-thirds laser corpus callosotomy: A feasibility study with probabilistic tractography validation

• Vejay N. Vakharia
• Rachel E. Sparks
• Sjoerd B. Vos
• Yarema Bezchlibnyk
• Ashesh D. Mehta
• Jon T. Willie
• Chengyuan Wu
• Ashwini Sharan

BACKGROUND: Anterior two-thirds corpus callosotomy is an effective palliative neurosurgical procedure for drug-refractory epilepsy that is most commonly used to treat drop-attacks. Laser interstitial thermal therapy is a novel stereotactic ablative technique that has been utilised as a minimally invasive alternative to resective and disconnective open neurosurgery. Case series have reported success in performing laser anterior two-thirds corpus callosotomy. Computer-assisted planning algorithms may help to automate and optimise multi-trajectory planning for this procedure. OBJECTIVE: To undertake a simulation-based feasibility study of computer-assisted corpus callostomy planning in comparison with expert manual plans in the same patients. METHODS: Ten patients were selected from a prospectively maintained database. Patients had previously undergone diffusion-weighted imaging and digital subtraction angiography as part of routine SEEG care. Computer-assisted planning was performed using the EpiNav™ platform and compared to manually planned trajectories from two independent blinded experts. Estimated ablation cavities were used in conjunction with probabilistic tractography to simulate the expected extent of interhemispheric disconnection. RESULTS: Computer-assisted planning resulted in significantly improved trajectory safety metrics (risk score and minimum distance to vasculature) compared to blinded external expert manual plans. Probabilistic tractography revealed residual interhemispheric connectivity in 1/10 cases following computer-assisted planning compared to 4/10 and 2/10 cases with manual planning. CONCLUSION: Computer-assisted planning successfully generates multi-trajectory plans capable of LITT anterior two-thirds corpus callosotomy. Computer-assisted planning may provide a means of standardising trajectory planning and serves as a potential new tool for optimising trajectories. A prospective validation study is now required to determine if this translates into improved patient outcomes.

YNICL Journal 2019 Journal Article

Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts

• Matteo Mancini
• Sjoerd B. Vos
• Vejay N. Vakharia
• Aidan G. O'Keeffe
• Karin Trimmel
• Frederik Barkhof
• Christian Dorfer
• Salil Soman

Diffusion MRI and tractography hold great potential for surgery planning, especially to preserve eloquent white matter during resections. However, fiber tract reconstruction requires an expert with detailed understanding of neuroanatomy. Several automated approaches have been proposed, using different strategies to reconstruct the white matter tracts in a supervised fashion. However, validation is often limited to comparison with manual delineation by overlap-based measures, which is limited in characterizing morphological and topological differences. In this work, we set up a fully automated pipeline based on anatomical criteria that does not require manual intervention, taking advantage of atlas-based criteria and advanced acquisition protocols available on clinical-grade MRI scanners. Then, we extensively validated it on epilepsy patients with specific focus on language-related bundles. The validation procedure encompasses different approaches, including simple overlap with manual segmentations from two experts, feasibility ratings from external multiple clinical raters and relation with task-based functional MRI. Overall, our results demonstrate good quantitative agreement between automated and manual segmentation, in most cases better performances of the proposed method in qualitative terms, and meaningful relationships with task-based fMRI. In addition, we observed significant differences between experts in terms of both manual segmentation and external ratings. These results offer important insights on how different levels of validation complement each other, supporting the idea that overlap-based measures, although quantitative, do not offer a full perspective on the similarities and differences between automated and manual methods.

YNICL Journal 2018 Journal Article

Structural and effective connectivity in focal epilepsy

• Christopher S. Parker
• Jonathan D. Clayden
• M. Jorge Cardoso
• Roman Rodionov
• John S. Duncan
• Catherine Scott
• Beate Diehl
• Sebastien Ourselin

Patients with medically-refractory focal epilepsy may be candidates for neurosurgery and some may require placement of intracranial EEG electrodes to localise seizure onset. Assessing cerebral responses to single pulse electrical stimulation (SPES) may give diagnostically useful data. SPES produces cortico-cortical evoked potentials (CCEPs), which infer effective brain connectivity. Diffusion-weighted images and tractography may be used to estimate structural brain connectivity. This combination provides the opportunity to observe seizure onset and its propagation throughout the brain, spreading contiguously along the cortex explored with electrodes, or non-contiguously. We analysed CCEPs and diffusion tractography in seven focal epilepsy patients and reconstructed the effective and structural brain networks. We aimed to assess the inter-modal similarity of the networks at a large scale across the cortex, the effective and structural connectivity of the ictal-onset zone, and investigate potential mechanisms of non-contiguous seizure spread. We found a significant overlap between structural and effective networks. Effective network CCEP amplitude, baseline variation, and outward connectivity was higher at ictal-onset zones, while structural connection strength within the ictal-onset zone tended to be higher. These findings support the concept of hyperexcitable cortex being associated with seizure generation. The high prevalence of structural and effective connections from the ictal-onset zone to sites of non-contiguous spread suggests that macroscopic structural and effective connections are plausible routes for non-contiguous seizure spread.

YNICL Journal 2018 Journal Article

The impact of epilepsy surgery on the structural connectome and its relation to outcome

• Peter N. Taylor
• Nishant Sinha
• Yujiang Wang
• Sjoerd B. Vos
• Jane de Tisi
• Anna Miserocchi
• Andrew W. McEvoy
• Gavin P. Winston

Background: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. Methods: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. Results: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. Conclusion: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only.

YNICL Journal 2016 Journal Article

Cerebral metabolism and perfusion in MR-negative individuals with refractory focal epilepsy assessed by simultaneous acquisition of 18F-FDG PET and arterial spin labeling

• Ilaria Boscolo Galazzo
• Maria Vittoria Mattoli
• Francesca Benedetta Pizzini
• Enrico De Vita
• Anna Barnes
• John S. Duncan
• Hans Rolf Jäger
• Xavier Golay

The major challenge in pre-surgical epileptic patient evaluation is the correct identification of the seizure onset area, especially in MR-negative patients. In this study, we aimed to: (1) assess the concordance between perfusion, from ASL, and metabolism, from (18)F-FDG, acquired simultaneously on PET/MR; (2) verify the utility of a statistical approach as supportive diagnostic tool for clinical readers. Secondarily, we compared (18)F-FDG PET data from the hybrid PET/MR system with those acquired with PET/CT, with the purpose of validate the reliability of (18)F-FDG PET/MR data. Twenty patients with refractory focal epilepsy, negative MR and a defined electro-clinical diagnosis underwent PET/MR, immediately followed by PET/CT. Standardized uptake value ratio (SUVr) and cerebral blood flow (CBF) maps were calculated for PET/CT-PET/MR and ASL, respectively. For all techniques, z-score of the asymmetry index (zAI) was applied for depicting significant Right/Left differences. SUVr and CBF images were firstly visually assessed by two neuroimaging readers, who then re-assessed them considering zAI for reaching a final diagnosis. High agreement between (18)F-FDG PET/MR and ASL was found, showing hypometabolism and hypoperfusion in the same hemisphere in 18/20 patients, while the remaining were normal. They were completely concordant in 14/18, concordant in at least one lobe in the remaining. zAI maps improved readers' confidence in 12/20 and 15/20 patients for (18)F-FDG PET/MR and ASL, respectively. (18)F-FDG PET/CT-PET/MR showed high agreement, especially when zAI was considered. The simultaneous metabolism-perfusion acquisition provides excellent concordance on focus lateralisation and good concordance on localisation, determining useful complementary information.

YNICL Journal 2016 Journal Article

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI

• Umair J. Chaudhary
• Maria Centeno
• Rachel C. Thornton
• Roman Rodionov
• Serge Vulliemoz
• Andrew W. McEvoy
• Beate Diehl
• Matthew C. Walker

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as 'ON' blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.

YNICL Journal 2014 Journal Article

Progressive white matter changes following anterior temporal lobe resection for epilepsy

• Gavin P. Winston
• Jason Stretton
• Meneka K. Sidhu
• Mark R. Symms
• John S. Duncan

Anterior temporal lobe resection (ATLR) is an effective treatment for refractory temporal lobe epilepsy (TLE). Widespread abnormalities in diffusion parameters involving the ipsilateral temporal lobe white matter and extending into extratemporal white matter have been shown in cross-sectional studies in TLE. However longitudinal changes following surgery have been less well addressed. We systematically assess diffusion changes in white matter in patients with TLE in comparison to controls before surgery and look at the longitudinal changes following ATLR at two timepoints (3-4 months, 12 months) using a whole brain approach. We find predominantly unilateral baseline changes in temporal and extratemporal structures compatible with altered myelination (reduced fractional anisotropy, increased mean and radial diffusivity). Following surgery, these changes progress in efferent tracts from the resected temporal lobe compatible with Wallerian degeneration. However more superiorly in the corona radiata, internal and external capsules and nearby tracts, changes compatible with plasticity are observed (increased fractional anisotropy and axial diffusivity, reduced radial diffusivity). There is little progression between 3-4 months and 12 months following surgery in patients with left TLE, but the changes become more widespread in patients with right TLE suggesting that plasticity occurs more slowly in this population. The neuropsychological correlates of such plasticity should be explored further.

YNIMG Journal 2014 Journal Article

Test–retest reproducibility of cannabinoid-receptor type 1 availability quantified with the PET ligand [11C]MePPEP

• Daniela A. Riaño Barros
• Colm J. McGinnity
• Lula Rosso
• Rolf A. Heckemann
• Oliver D. Howes
• David J. Brooks
• John S. Duncan
• Federico E. Turkheimer

Background Endocannabinoids are involved in normal cognition, and dysfunction in cannabinoid-receptor-mediated neurotransmission has been suggested in a variety of neurological and psychiatric pathologies. The type 1 cannabinoid receptor (CB1) is widely expressed in the human central nervous system. The objective of this study was to quantify the test–retest reproducibility of measures of the PET ligand [11C]MePPEP in order to assess the stability of CB1-receptor quantification in humans in vivo. Methods Fifteen healthy subjects (eight females; median age 32years, range 25 to 65years) had a 90-minute PET scan on two occasions after injection of a median dose of [11C]MePPEP of 364MBq. Metabolite-corrected arterial plasma input functions were obtained for all scans. Eight ROIs, reflecting different levels of receptor densities/concentrations, were defined automatically: hippocampus, anterior cingulate gyrus, inferior frontal gyrus, caudate nucleus, globus pallidus, nucleus accumbens, thalamus, and pons. We used seven quantification methods: reversible compartmental models with one and two tissue classes, two and four rate constants, and a variable blood volume term (2kbv; 4kbv); model-free (spectral) analyses with and without regularisation, including one with voxel-wise quantification; the simplified reference tissue model (SRTM) with pons as a pseudo-reference region; and modified standard uptake values (mSUVs) calculated for the period of ~30–60min after injection. Percentage test–retest change and between-subject variability were both assessed, and test–retest reliability was quantified by the intraclass correlation coefficient (ICC). The ratio of binding estimates pallidum: pons served as an indicator of a method's ability to reflect binding heterogeneity. Results Neither the SRTM nor the 4kbv model produced reliable measures, with ICCs around zero. Very good (>0. 75) or excellent (>0. 80) ICCs were obtained with the other methods. The most reliable were spectral analysis parametric maps (average across regions±standard deviation 0. 83±0. 03), rank shaping regularised spectral analysis (0. 82±0. 05), and the 2kbv model (0. 82±0. 09), but mSUVs were also reliable for most regions (0. 79±0. 13). Mean test–retest changes among the five well-performing methods ranged from 12±10% for mSUVs to 16% for 2kbv. Intersubject variability was high, with mean between-subject coefficients of variation ranging from 32±13% for mSUVs to 45% for 2kbv. The highest pallidum: pons ratios of binding estimates were achieved by mSUV (4. 2), spectral analysis-derived parametric maps (3. 6), and 2kbv (3. 6). Conclusion Quantification of CB1 receptor availability using [11C]MePPEP shows good to excellent reproducibility with several kinetic models and model-free analyses, whether applied on a region-of-interest or voxelwise basis. Simple mSUV measures were also reliable for most regions, but do not allow fully quantitative interpretation. [11C]MePPEP PET is well placed as a tool to investigate CB1-receptor mediated neurotransmission in health and disease.

YNIMG Journal 2013 Journal Article

Quantification of opioid receptor availability following spontaneous epileptic seizures: Correction of [11C]diprenorphine PET data for the partial-volume effect

• Colm J. McGinnity
• Miho Shidahara
• Maria Feldmann
• Shiva Keihaninejad
• Daniela A. Riaño Barros
• Ioannis S. Gousias
• John S. Duncan
• David J. Brooks

Previous positron emission tomography (PET) studies in refractory temporal lobe epilepsy (TLE) using the non-selective opioid receptor antagonist [11C]diprenorphine (DPN) did not detect any changes in mesial temporal structures, despite known involvement of the hippocampus in seizure generation. Normal binding in smaller hippocampi is suggestive of increased receptor concentration in the remaining grey matter. Correction for partial-volume effect (PVE) has not been used in previous DPN PET studies. Here, we present PVE-corrected DPN-PET data quantifying post-ictal and interictal opioid receptor availability in humans with mTLE. Eight paired datasets of post-ictal and interictal DPN PET scans and eleven test/retest control datasets were available from a previously published study on opioid receptor changes in TLE following seizures (Hammers et al. , 2007a). Five of the eight participants with TLE had documented hippocampal sclerosis. Data were re-analyzed using regions of interest and a novel PVE correction method (structural functional synergistic-resolution recovery (SFS-RR); (Shidahara et al. , 2012)). Data were denoised, followed by application of SFS-RR, with anatomical information derived via precise anatomical segmentation of the participants' MRI (MAPER; (Heckemann et al. , 2010)). [11C]diprenorphine volume-of-distribution (VT) was quantified in six regions of interest. Post-ictal increases were observed in the ipsilateral fusiform gyri and lateral temporal pole. A novel finding was a post-ictal increase in [11C]DPN VT relative to the interictal state in the ipsilateral parahippocampal gyrus, not observed in uncorrected datasets. As for voxel-based (SPM) analyses, correction for global VT values was essential in order to demonstrate focal post-ictal increases in [11C]DPN VT. This study provides further direct human in vivo evidence for changes in opioid receptor availability in TLE following seizures, including changes that were not evident without PVE correction. Denoising, resolution recovery and precise anatomical segmentation can extract valuable information from PET studies that would be missed with conventional post-processing procedures.

YNIMG Journal 2012 Journal Article

Automated MR image classification in temporal lobe epilepsy

• Niels K. Focke
• Mahinda Yogarajah
• Mark R. Symms
• Oliver Gruber
• Walter Paulus
• John S. Duncan

In those with drug refractory focal epilepsy, MR imaging is important for identifying structural causes of seizures that may be amenable to surgical treatment. In up to 25% of potential surgical candidates, however, MRI is reported as unremarkable even when employing epilepsy specific sequences. Automated MRI classification is a desirable tool to augment the interpretation of images, especially when changes are subtle or distributed and may be missed on visual inspection. Support vector machines (SVM) have recently been described to be useful for voxel-based MR image classification. In the present study we sought to evaluate whether this method is feasible in temporal lobe epilepsy, with adequate accuracy. We studied 38 patients with hippocampal sclerosis and unilateral (mesial) temporal lobe epilepsy (mTLE) (20 left) undergoing presurgical evaluation and 22 neurologically normal control subjects. 3D T1-weighted images were acquired at 3T (GE Excite), segmented into tissue classes, normalized and smoothed with SPM8. Diffusion tensor imaging (DTI) and double echo images for T2 relaxometry were also acquired and processed. The SVM analysis was done with the libsvm software package in a leave-one-out cross-validation design and predictive accuracy was measured. Local weighting was applied by SPM F-contrast maps. Best accuracies were achieved using the gray matter based segmentation (90–100%) and mean diffusivity (95–97%). For the three-way classification, accuracies were 88 and 93% respectively. Local weighting generally improved the accuracies except in the FA-based processing for which no effect was noted. Removing the hippocampus from the analysis, on the other hand, reduced the obtainable diagnostic indices but these were still >90% for DTI-based methods and lateralization based on gray matter maps. These findings show that automated SVM image classification can achieve high diagnostic accuracy in mTLE and that voxel-based MRI can be used at the individual subject level. This could be helpful for screening assessments of MRI scans in patients with epilepsy and when no lesion is detected on visual evaluation.

YNIMG Journal 2011 Journal Article

Clustering probabilistic tractograms using independent component analysis applied to the thalamus

• Jonathan O'Muircheartaigh
• Christian Vollmar
• Catherine Traynor
• Gareth J. Barker
• Veena Kumari
• Mark R. Symms
• Pam Thompson
• John S. Duncan

The connectivity information contained in diffusion tensor imaging (DTI) has previously been used to parcellate cortical and subcortical regions based on their connectivity profiles. The aim of the current study is to investigate the utility of a novel approach to connectivity based parcellation of the thalamus using probabilistic tractography and independent component analysis (ICA). We use ICA to identify spatially coherent tractograms as well as their underlying seed regions, in a single step. We compare this to seed-based tractography results and to an established and reliable approach to parcellating the thalamus based on the dominant cortical connection from each thalamic voxel (Behrens et al. , 2003a, b). The ICA approach identifies thalamo-cortical pathways that correspond to known anatomical connections, as well as parcellating the underlying thalamus in a spatially similar way to the connectivity based parcellation. We believe that the use of such a multivariate method to interpret the complex datasets created by probabilistic tractography may be better suited than other approaches to parcellating brain regions.

YNIMG Journal 2010 Journal Article

Identical, but not the same: Intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0T scanners

• Christian Vollmar
• Jonathan O'Muircheartaigh
• Gareth J. Barker
• Mark R. Symms
• Pamela Thompson
• Veena Kumari
• John S. Duncan
• Mark P. Richardson

Diffusion Tensor Imaging (DTI) is being increasingly used to assess white matter integrity and it is therefore paramount to address the test–retest reliability of DTI measures. In this study we assessed inter- and intra-site reproducibility of two nominally identical 3T scanners at different sites in nine healthy controls using a DTI protocol representative of typical current “best practice” including cardiac gating, a multichannel head coil, parallel imaging and optimized diffusion gradient parameters. We calculated coefficients of variation (CV) and intraclass correlation coefficients (ICC) of fractional anisotropy (FA) measures for the whole brain, for three regions of interest (ROI) and for three tracts derived from these ROI by probabilistic tracking. We assessed the impact of affine, nonlinear and template based methods for spatially aligning FA maps on the reproducibility. The intra-site CV for FA ranged from 0. 8% to 3. 0% with ICC from 0. 90 to 0. 99, while the inter-site CV ranged from 1. 0% to 4. 1% with ICC of 0. 82 to 0. 99. Nonlinear image coregistration improved reproducibility compared to affine coregistration. Normalization to template space reduced the between-subject variation, resulting in lower ICC values and indicating a possibly reduced sensitivity. CV from probabilistic tractography were about 50% higher than for the corresponding seed ROI. Reproducibility maps of the whole scan volume showed a low variation of less than 5% in the major white matter tracts but higher variations of 10–15% in gray matter regions. One of the two scanners showed better intra-site reproducibility, while the intra-site CV for both scanners was significantly better than inter-site CV. However, when using nonlinear coregistration of FA maps, the average inter-site CV was below 2%. There was a consistent inter-site bias, FA values on site 2 were 1. 0–1. 5% lower than on site 1. Correction for this bias with a global scaling factor reduced the inter-site CV to the range of intra-site CV. Our results are encouraging for multi-centre DTI studies in larger populations, but also illustrate the importance of the image processing pipeline for reproducibility.

YNIMG Journal 2008 Journal Article

BOLD and perfusion changes during epileptic generalised spike wave activity

• Khalid Hamandi
• Helmut Laufs
• Ulrike Nöth
• David W. Carmichael
• John S. Duncan
• Louis Lemieux

It is unclear whether neurovascular coupling is maintained during epileptic discharges. Knowing this is important to allow appropriate inferences from functional imaging studies of epileptic activity. Recent blood oxygen level-dependent (BOLD) functional MRI (fMRI) studies have demonstrated negative BOLD responses (NBR) in frontal, parietal and posterior cingulate cortices during generalised spike wave activity (GSW). We hypothesized that GSW-related NBR commonly reflect decreased cerebral blood flow (CBF). We measured BOLD and cerebral blood flow responses using simultaneous EEG with BOLD and arterial spin label (ASL) fMRI at 3 T. Four patients with epilepsy were studied; two with idiopathic generalized epilepsy (IGE) and two with secondary generalized epilepsy (SGE). We found GSW-related NBR in frontal, parietal and posterior cingulate cortices. We measured the coupling between BOLD and CBF changes during GSW and normal background EEG and found a positive correlation between the simultaneously measured BOLD and CBF throughout the imaged volume. Frontal and thalamic activation were seen in two patients with SGE, concordant with the electro-clinical features of their epilepsy. There was striking reproducibility of the GSW-associated BOLD response in subjects previously studied at 1. 5 T. Our results show a preserved relationship between BOLD and CBF changes during rest and GSW activity consistent with normal neurovascular coupling in patients with generalized epilepsy and in particular during GSW activity. Cortical activations appear to reflect areas of discharge generation whilst deactivations reflect changes in conscious resting state activity.

YNIMG Journal 2008 Journal Article

Voxel-based diffusion tensor imaging in patients with mesial temporal lobe epilepsy and hippocampal sclerosis

• Niels K. Focke
• Mahinda Yogarajah
• Silvia B. Bonelli
• Philippa A. Bartlett
• Mark R. Symms
• John S. Duncan

Background Mesial temporal lobe epilepsy (mTLE) with hippocampus sclerosis (HS) is an important cause for focal epilepsy. In this study, we explored the integrity of connecting networks using diffusion tensor imaging (DTI) and two whole-brain voxel-based methods: statistical parametric mapping (SPM) and tract-based spatial statistics (TBSS). Methods Thirty-three consecutive patients with mTLE and HS undergoing presurgical evaluation were scanned at 3 T, a DTI data set was acquired and parametric maps of fractional anisotropy (FA) and mean diffusivity (MD) were calculated. Twenty-one patients had left hippocampal sclerosis (LHS) and 12 patients had right HS (RHS). These groups were compared to 37 normal control subjects using both SPM5 and TBSS. Results The ipsilateral temporal lobe showed widespread FA reduction in both groups. The limbic system was clearly abnormal in the LHS group, also involving the arcuate fasciculus. In RHS, changes were more restricted but also showed involvement of the contralateral temporal and inferior frontal lobe. Increased MD was found in the ipsilateral hippocampus by SPM that was only marginally detected by TBSS. In white matter regions, however, TBSS was more sensitive to changes than SPM. Conclusion DTI detects extensive changes in mTLE with HS. The affected networks were principally in the ipsilateral temporal lobe and the limbic system but also the arcuate fasciculus. SPM and TBSS gave complementary information with higher sensitivity to FA changes using TBSS.

YNIMG Journal 2007 Journal Article

Abnormalities of language networks in temporal lobe epilepsy

• H.W. Robert Powell
• Geoff J.M. Parker
• Daniel C. Alexander
• Mark R. Symms
• Philip A. Boulby
• Claudia A.M. Wheeler-Kingshott
• Gareth J. Barker
• Matthias J. Koepp

Functional magnetic resonance imaging (fMRI) in patients with temporal lobe epilepsy (TLE) has demonstrated reorganisation of language functions with greater involvement of the non-dominant hemisphere. The structural brain connections supporting this atypical language dominance have not previously been identified. We performed fMRI of language functions and imaging of white matter connections using MR tractography in 14 patients with unilateral TLE and hippocampal sclerosis and 10 controls. Verb generation and reading comprehension paradigms were used to define functional regions which were used to generate starting regions for tractography. Controls and right TLE patients had a left-lateralised pattern of both language-related activations and the associated structural connections. Left TLE patients showed more symmetrical language activations, along with reduced left hemisphere and increased right hemisphere structural connections. Subjects with more lateralised functional activation had also more highly lateralised connecting pathways. We provide evidence for structural reorganisation of white matter tracts that reflects the altered functional language lateralisation in left TLE patients. The combination of fMRI and tractography offers a promising tool for studying the reorganisation of language functions in many neurological conditions and may prove useful in predicting language deficits following temporal lobe surgery.

YNIMG Journal 2007 Journal Article

Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study

• Alexander Hammers
• Rolf Heckemann
• Matthias J. Koepp
• John S. Duncan
• Jo V. Hajnal
• Daniel Rueckert
• Paul Aljabar

In temporal lobe epilepsy (TLE), hippocampal atrophy (HA) is a marker of poor prognosis regarding seizure remission, but predicts success of anterior temporal lobe resection. Manual quantification of HA on MRI is time-consuming and limited by investigator availability. Normal ranges of hippocampal volumes, both in absolute terms and relative to intracranial volume, and of hippocampal asymmetry were defined using an automatic label propagation and decision fusion technique based on thirty manually derived atlases of healthy controls. Manual test–retest reliability and overlaps of automatically and manually determined hippocampal volumes were quantified with similarity indices (SIs). Correct clinical identification of ipsilateral HA, and contralaterally normal hippocampal volumes, was determined in nine patients with histologically confirmed hippocampal sclerosis in terms of volumes and asymmetry indices (AIs) for standard statistical thresholds and with receiver operating characteristic (ROC) analysis. Manual test–retest reliability was very high, with SIs between 0. 87 and 0. 90. Manual and automatic hippocampus labels overlapped with a SI of 0. 83 on the unaffected but with 0. 76 on the atrophic side. Accuracy was higher for less atrophic hippocampi. The automatic method correctly identified 6/9 HAs in terms of absolute volume, 7/9 in terms of relative volume at a standard 2 SD threshold, and 9/9 for AIs. ROC-determined thresholds allowed clinically desirable correct identification of all HAs (100% sensitivity) with 85–100% specificity for volumes, and 100% specificity for AIs. The method has the potential to automatically detect unilateral HA, but further work is needed to determine its performance in detecting clinically important bilateral disease.

YNIMG Journal 2007 Journal Article

Balancing bias, reliability, noise properties and the need for parametric maps in quantitative ligand PET: [11C]diprenorphine test–retest data

• Alexander Hammers
• Marie-Claude Asselin
• Federico E. Turkheimer
• Rainer Hinz
• Safiye Osman
• Gary Hotton
• David J. Brooks
• John S. Duncan

[11C]diprenorphine (DPN) is a non-subtype selective opioid receptor PET ligand with slow kinetics and no region devoid of specific binding. Parametric maps are desirable but have to overcome high noise at the voxel level. We obtained parameter values, parametric map image quality, test–retest reproducibility and reliability (using intraclass correlation coefficients (ICCs)) for conventional spectral analysis and a derived method (rank shaping), compared them with values obtained through sampling of volumes of interest (VOIs) on the dynamic data sets and tested whether smaller amounts of radioactivity injected maintained reliability. Ten subjects were injected twice with either ∼185 MBq or ∼135 MBq of [11C]DPN, followed by dynamic PET for 90 min. Data were movement corrected with a frame-to-frame co-registration method. Arterial plasma input functions corrected for radiolabelled metabolites were created. There was no overall effect of movement correction except for one subject with substantial movement whose test–retest differences decreased by ∼50%. Actual parametric values depended heavily on the cutoff for slow frequencies (between 0. 0008 s−1 and 0. 00063 s−1). Image quality was satisfactory for restricted base ranges when using conventional spectral analysis. The rank shaping method allowed maximising of this range but had similar bias. VOI-based methods had the widest dynamic range between regions. Average percentage test–retest differences were smallest for the parametric maps with restricted base ranges; similarly ICCs were highest for these (up to 0. 86) but unacceptably low for VOI-derived VD estimates at the low doses of injected radioactivity (0. 24/0. 04). Our data can inform the choice of methodology for a given biological problem.

YNIMG Journal 2007 Journal Article

Independent component analysis of interictal fMRI in focal epilepsy: Comparison with general linear model-based EEG-correlated fMRI

• R. Rodionov
• F. De Martino
• H. Laufs
• D.W. Carmichael
• E. Formisano
• M. Walker
• John S. Duncan
• L. Lemieux

The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG–fMRI data in which abnormalities are not apparent on scalp EEG.

YNIMG Journal 2007 Journal Article

Volumes, spatial extents and a probabilistic atlas of the human basal ganglia and thalamus

• R. Laila Ahsan
• Richard Allom
• Ioannis S. Gousias
• Helai Habib
• Federico E. Turkheimer
• Samantha Free
• Louis Lemieux
• Ralph Myers

The basal ganglia and thalamus are involved in processing all physiological behaviors and affected by many diseases. Accurate localization is a crucial issue in neuroimaging, particularly when working with groups of normalized images in a standard stereotaxic space. Here, manual delineation of the central structures (thalamus; nucleus caudatus and accumbens; putamen, pallidum, substantia nigra) was performed on 30 high resolution MRIs of healthy young adults (15 female, median age 31 years) in native space. Protocol inter-rater reliabilities were quantified as structure overlap (similarity indices, SIs). Structural volumes were calculated in native space, and after spatial normalization to stereotaxic space (MNI/ICBM152) and in relation to hemispheric volumes. Spatial extents relative to the anterior commissure (AC) were extracted. The 30 resulting atlases were then used to create probabilistic maps in stereotaxic space. Inter-rater SIs were high at 0. 85–0. 92 except for the nucleus accumbens. In native space, caudate, nucleus accumbens and putamen were significantly larger on the left, and the globus pallidus larger in males. After normalizing for brain volume, the nucleus accumbens, putamen and thalamus were larger on the left, with the gender difference in the globus pallidus still detectable. Some of these volume differences translated into significantly different distances from the AC. The probabilistic maps showed that overall the central structures' boundaries are relatively unchanged after spatial normalization. We present a comprehensive assessment of thalamic and basal ganglia volumetric and geometric data in both native and stereotaxic spaces. Probabilistic maps in MNI/ICBM152 space will allow accurate localization in group analyses.

YNIMG Journal 2006 Journal Article

Analysis of EEG–fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection

• Adam D. Liston
• Jan C. de Munck
• Khalid Hamandi
• Helmut Laufs
• Pauly Ossenblok
• John S. Duncan
• Louis Lemieux

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG–fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

YNIMG Journal 2006 Journal Article

EEG–fMRI of idiopathic and secondarily generalized epilepsies

• Khalid Hamandi
• Afraim Salek-Haddadi
• Helmut Laufs
• Adam Liston
• Karl Friston
• David R. Fish
• John S. Duncan
• Louis Lemieux

We used simultaneous EEG and functional MRI (EEG–fMRI) to study generalized spike wave activity (GSW) in idiopathic and secondary generalized epilepsy (SGE). Recent studies have demonstrated thalamic and cortical fMRI signal changes in association with GSW in idiopathic generalized epilepsy (IGE). We report on a large cohort of patients that included both IGE and SGE, and give a functional interpretation of our findings. Forty-six patients with GSW were studied with EEG–fMRI; 30 with IGE and 16 with SGE. GSW-related BOLD signal changes were seen in 25 of 36 individual patients who had GSW during EEG–fMRI. This was seen in thalamus (60%) and symmetrically in frontal cortex (92%), parietal cortex (76%), and posterior cingulate cortex/precuneus (80%). Thalamic BOLD changes were predominantly positive and cortical changes predominantly negative. Group analysis showed a negative BOLD response in the cortex in the IGE group and to a lesser extent a positive response in thalamus. Thalamic activation was consistent with its known role in GSW, and its detection in individual cases with EEG–fMRI may in part be related to the number and duration of GSW epochs recorded. The spatial distribution of the cortical fMRI response to GSW in both IGE and SGE involved areas of association cortex that are most active during conscious rest. Reduction of activity in these regions during GSW is consistent with the clinical manifestation of absence seizures.

YNIMG Journal 2006 Journal Article

Hemispheric asymmetries in language-related pathways: A combined functional MRI and tractography study

• H.W. Robert Powell
• Geoff J.M. Parker
• Daniel C. Alexander
• Mark R. Symms
• Philip A. Boulby
• Claudia A.M. Wheeler-Kingshott
• Gareth J. Barker
• Uta Noppeney

Functional lateralization is a feature of human brain function, most apparent in the typical left-hemisphere specialization for language. A number of anatomical and imaging studies have examined whether structural asymmetries underlie this functional lateralization. We combined functional MRI (fMRI) and diffusion-weighted imaging (DWI) with tractography to study 10 healthy right-handed subjects. Three language fMRI paradigms were used to define language-related regions in inferior frontal and superior temporal regions. A probabilistic tractography technique was then employed to delineate the connections of these functionally defined regions. We demonstrated consistent connections between Broca's and Wernicke's areas along the superior longitudinal fasciculus bilaterally but more extensive fronto-temporal connectivity on the left than the right. Both tract volumes and mean fractional anisotropy (FA) were significantly greater on the left than the right. We also demonstrated a correlation between measures of structure and function, with subjects with more lateralized fMRI activation having a more highly lateralized mean FA of their connections. These structural asymmetries are in keeping with the lateralization of language function and indicate the major structural connections underlying this function.

YNIMG Journal 2006 Journal Article

Imaging the neocortex in epilepsy with double inversion recovery imaging

• Fergus J. Rugg-Gunn
• Philip A. Boulby
• Mark R. Symms
• Gareth J. Barker
• John S. Duncan

The neocortices of 10 patients with partial seizures and acquired lesions, 14 patients with malformations of cortical development (MCD) and 33 patients with partial seizures and normal conventional MRI were quantitatively evaluated using whole brain double inversion recovery imaging (DIR) and Statistical Parametric Mapping (SPM). Compared to a group of 30 control subjects, DIR and objective voxel-by-voxel statistical comparison identified regions of significantly abnormal DIR signal intensity (DSI) in 9 out of 10 patients with acquired nonprogressive cerebral lesions and partial seizures. In all 9 patients, the areas of abnormal DSI concurred with abnormalities identified on visual inspection of conventional MRI. In all 14 patients with MCD, SPM detected regions of significantly abnormal DSI; all of which corresponded to abnormalities identified on visual inspection of conventional MRI. In addition, in both groups, there were areas that were normal on conventional imaging, which demonstrated abnormal DSI. Voxel-by-voxel statistical analysis identified significantly abnormal DSI in 15 of the 33 patients with cryptogenic focal epilepsy. In 10 of these, the areas of abnormal DSI concurred with epileptic EEG abnormality and clinical seizure semiology. Group analysis of MRI-negative patients with electroclinical seizure onset localising to the left temporal and left and right frontal regions revealed significantly abnormal DSI within the white matter of each respective lobe. DIR analysed using SPM was sensitive in patients with MCDs and acquired cerebral damage. Significant abnormalities in DSI in individual and grouped MRI-negative patients suggest that occult epileptogenic cerebral lesions are associated with subtle structural abnormalities. DIR is, therefore, a useful quantitative MRI technique for characterising epileptic foci and may contribute to presurgical evaluation.

YNIMG Journal 2000 Journal Article

Functional MRI activation of individual interictal spikes

• Karsten Krakow
• Demetrio Messina
• David R. Fish
• John S. Duncan
• Louis Lemieux

YNIMG Journal 1999 Journal Article

Voxel-by-Voxel Comparison of Automatically Segmented Cerebral Gray Matter—A Rater-Independent Comparison of Structural MRI in Patients with Epilepsy

• Friedrich G. Woermann
• Samantha L. Free
• Matthias J. Koepp
• John Ashburner
• John S. Duncan

Quantitative evaluation of MRI in patients with epilepsy can give more information than qualitative assessment. Previously developed volume-of-interest-based methods identified subtle widespread structural changes in the neocortex beyond the visualized lesions in patients with malformations of cortical development (MCD) and hippocampal sclerosis (HS) and also in MRI-negative patients with juvenile myoclonic epilepsy (JME). This study evaluates a voxel-based automated analysis of structural MRI in epilepsy. After fully automated segmentation of cerebral gray matter from structural T1-weighted, high-resolution MRI scans, we applied the automated and objective technique of statistical parametric mapping (SPM) to the analysis of gray matter of 35 control subjects, 10 patients with partial seizures and MCD, 10 patients with left temporal lobe epilepsy (TLE) and HS, 10 patients with left TLE and normal MR quantitation of the hippocampus, and 20 patients with JME. At a corrected threshold of P < 0. 05, significant abnormalities were found in 3/35 controls; in all 10 patients with MCD, 6 of whom had additional lesions beyond the margins of the visualized abnormalities; in 2/10 TLE patients with HS; in 2/10 MRI-negative TLE; and in 4/20 JME patients. Group comparisons between control subjects and HS patients identified the affected left temporal lobe with an increase in gray matter in the posterior temporal lobe, but did not identify hippocampal atrophy. The group of MRI-negative TLE patients showed no abnormalities compared with control subjects. Group comparison between control subjects and JME patients identified a mesial frontal increase in gray matter. The SPM-based voxel-by-voxel comparison of gray matter distribution identified MCD and abnormalities beyond the visualized lesion in individual MCD patients. The method did not reliably identify HS in individual patients or identify abnormalities in individual MRI-negative patients with TLE or JME in a proportion larger than the chance findings in the control group. Using group comparisons, structural abnormalities in the neocortical gray matter of patients with TLE and HS were lateralized to the affected temporal lobe. In patients with JME as a group, an increase in gray matter was localized to the mesial frontal area, corroborating earlier quantitative MRI findings.