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  • 1
    Online Resource
    Online Resource
    Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression
    Springer Science and Business Media LLC ; 2022
    In:  Nature Communications Vol. 13, No. 1 ( 2022-07-27)
    Details
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2022-07-27)
    Abstract: Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    URL: Article
    DOI: 10.1038/s41467-022-31730-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2553671-0
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  • 2
    Online Resource
    Online Resource
    Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study
    Wiley ; 2022
    In:  Epilepsia Vol. 63, No. 1 ( 2022-01), p. 61-74
    Details
    In: Epilepsia, Wiley, Vol. 63, No. 1 ( 2022-01), p. 61-74
    Abstract: Drug‐resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. Methods The MELD (Multi‐centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging‐based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. Results FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. Significance FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data‐driven atlases and predictive models are essential for evidence‐based, precision medicine and risk counseling in epilepsy.
    Type of Medium: Online Resource
    ISSN: 0013-9580 , 1528-1167
    URL: Issue
    URL: Article
    DOI: 10.1111/epi.v63.1
    DOI: 10.1111/epi.17130
    RVK:
    XA 10000
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2002194-X
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  • 3
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    Online Resource
    Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study
    American Association for the Advancement of Science (AAAS) ; 2020
    In:  Science Advances Vol. 6, No. 47 ( 2020-11-20)
    Details
    In: Science Advances, American Association for the Advancement of Science (AAAS), Vol. 6, No. 47 ( 2020-11-20)
    Abstract: Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.
    Type of Medium: Online Resource
    ISSN: 2375-2548
    URL: Article
    DOI: 10.1126/sciadv.abc6457
    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2020
    detail.hit.zdb_id: 2810933-8
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  • 4
    Online Resource
    Online Resource
    Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study
    Oxford University Press (OUP) ; 2022
    In:  Brain Vol. 145, No. 11 ( 2022-11-21), p. 3859-3871
    Details
    In: Brain, Oxford University Press (OUP), Vol. 145, No. 11 ( 2022-11-21), p. 3859-3871
    Abstract: One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted ‘gold-standard’ subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    URL: Article
    DOI: 10.1093/brain/awac224
    RVK:
    XA 10000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy
    Oxford University Press (OUP) ; 2022
    In:  Brain Vol. 145, No. 4 ( 2022-05-24), p. 1285-1298
    Details
    In: Brain, Oxford University Press (OUP), Vol. 145, No. 4 ( 2022-05-24), p. 1285-1298
    Abstract: Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    URL: Article
    DOI: 10.1093/brain/awab417
    RVK:
    XA 10000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1474117-9
    SSG: 12
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