Cristina Tobías¹, Eneko Uruñuela¹, Vicente Ferrer-Gallardo¹, Hannah Goldberg², Christine Engelman², Mark Lowe², Stephen E. Jones², and César Caballero-Gaudes^1
1Signal Processing in Neuroimaging, Basque Center on Cognition Brain and Language, San Sebastián, Spain, ²Imaging Institute, Cleveland Clinic, OH, USA., Cleveland, OH, United States

We propose a novel methodology to identify spatio-temporal patterns of interictal epileptic activity in refractory epileptic patients using only BOLD functional MRI. It is based on clustering the activity-inducing signal deconvolved from the fMRI data with the Infomap algorithm. The proposed approach was validated on data acquired during a finger tapping task, and evaluated in four epileptic patients scanned at 7T. This method obtained activation maps that were concordant with the results obtained with EEG-informed GLM and MEG-based dipole source localization in 3 out of 4 patients, demonstrating its potential for mapping epileptic activity based only on fMRI data.

Remika Mito¹, Mangor Pedersen², Robert Smith^1,3, Donna Parker¹, Leonid Churilov⁴, David Vaughan^1,3,5, and Graeme Jackson^1,3,5
1Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia, ²Department of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand, ³Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia, ⁴Melbourne Medical School, University of Melbourne, Melbourne, VIC, Australia, ⁵Department of Neurology, Austin Health, Melbourne, VIC, Australia

Fibre tract-specific abnormalities have been identified in various neurological disorders and conditions using fixel-based analysis. However, for this technique to be useful in clinical practice, such abnormalities should be detectable in individual patients. In this work, we apply the fixel-based analysis framework to detect fibre density and cross-sectional changes in individual patients with varying epilepsy diagnoses. Abnormalities could be detected in individual epilepsy patients, both at the tract level, and at the fixel-level, with different patterns of tract-based abnormality observed across the different epilepsy syndromes. This information could be clinically valuable when examining individual patients.

Konrad Wagstyl¹, Mathilde Ripart², MELD Consortium³, Hannah Spitzer⁴, Torsten Baldeweg², and Sophie Adler^2
1Wellcome Centre for Human Neuroimaging, UCL, London, United Kingdom, ²Great Ormond Street Institute for Child Health, UCL, London, United Kingdom, ³UCL, London, United Kingdom, ⁴Institute of Computational Biology, Helmholtz Zentrum München, Munich, Germany

Identification of subtle epilepsy-causing focal cortical dysplasias (FCD) on MRI remains an outstanding challenge during presurgical assessment of patients. The Multi-centre Epilepsy Lesion Detection (MELD) project created an MRI lesion detection algorithm using a large, heterogenous cohort. The algorithm had a sensitivity of 67%, performing well on unseen test sites. Analysis of MRI lesions revealed distinct subgroups, with differing histopathological subtypes, imaging features and detection rates. Individual patient reports highlight a predicted lesion’s location, imaging features and their relative saliency to the classifier. This tool has the potential to improve presurgical lesion identification on MRI from patients with epileptogenic FCD.

Chiara Casella^1,2, Katy Vecchiato^1,2,3, Ayse Sila Dokumaci^2,4, Philippa Bridgen^2,4, Shaihan Malik^2,4, Joseph V Hajnal^2,4, Sharon Giles^2,4, Jan Sedlacik^1,2,4,5, Karin Shmueli^2,6, Tom Wilkinson^2,4, Raphael Tomi-Tricot^2,4,7, David W Carmichael^2,4, and Jonathan O'Muircheartaigh^1,2,3,8
1Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²London Collaborative Ultra high field System (LoCUS), London, United Kingdom, ³Department for Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, ⁴School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ⁵Radiology Department, Great Ormond Street Hospital for Children, London, United Kingdom, ⁶Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ⁷MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, ⁸MRC Centre for Neurodevelopmental Disorders, London, United Kingdom

We developed an analysis pipeline to explore normative QSM values in children and adolescents at 7T, and assessed the feasibility of this approach for detecting tissue-alterations in paediatric drug-resistant epilepsy. Normative values consistent with previous QSM studies were reported for deep brain regions, and normative cortical susceptibility values were described for the first time in children and adolescents at 7T. Finally, sensitivity to susceptibility changes in epileptogenic lesions was demonstrated using the analysis pipeline.

Rachael Garner¹, Alexis Bennett¹, Akul Sharma¹, Michael Douglas Morris², Marianna La Rocca^1,3, Giuseppe Barisano¹, Ruskin Cua⁴, Paul Vespa², Arthur W Toga¹, and Dominique Duncan^1
1USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ²David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States, ³Dipartimento Interateneo di Fisica, Università di Bari, Bari, Italy, ⁴USC Department of Radiology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States

Posttraumatic epilepsy (PTE), or recurrent seizures after traumatic brain injury (TBI), is a debilitating complication of TBI. We present a multimodal approach to classify seizure outcomes using computed tomography (CT) and magnetic resonance imaging (MRI) features that characterize lesion phenotypes. Five logistic regression models to predict seizure outcome are presented, using patient demographics and clinical information in conjunction with CT and MRI variables that describe lesion characteristics including contusion type and location as well as whole-brain lesion volumetrics. The optimal model utilized all four categories of features, yielding 91.4% sensitivity, 75% specificity, and 0.886 area under the curve performance.

Marina Radoul^1,2, Kai Qiao^1,2, Donghyun Hong², Mansi B. Parekh³, Philip Hampel³, Eric Steven Sevilla³, David Traver³, Hannah Kim³, Marina Bershteyn³, Yves Maury³, Catherine Priest³, Cory R. Nicholas³, and Myriam M. Chaumeil^1,2
1Department of Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, CA, United States, ²Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, ³Neurona Therapeutics, San Francisco, CA, United States

Interneuron transplantation targeting GABAergic network dysfunction is a novel alternative therapeutic approach for chronic focal epilepsy. However, in vivo monitoring of response to such cellular therapeutics remains challenging. Here, we combined high resolution in vivo and ex vivo ¹H MRS to investigate the metabolic alterations in epileptic hippocampus in a preclinical model of chronic mesial temporal lobe epilepsy, and the effect of human inhibitory interneuron transplantation on metabolism. We discovered that hippocampal levels of GABA, NAA/Cr, GLX/Cr, GABA/GLX and GABA/NAA were reversed to healthy control levels in epileptic mice transplanted with inhibitory interneurons, providing unique biomarkers of therapeutic response.