Microstructural MRI characterisation of focal cortical dysplasia in paediatric epilepsy patients
Poster No:
1909
Submission Type:
Abstract Submission
Authors:
Sila Genc1, Emma Macdonald-Laurs1, Michael Kean1, Joseph Yang1
Institutions:
1The Royal Children's Hospital, Melbourne, Victoria
First Author:
Co-Author(s):
Introduction:
Focal cortical dysplasia type II (FCDII) is a common malformation of cortical development consisting of disrupted cortical lamination with abnormally shaped and enlarged (dysmorphic) neurons[1]. Children with FCDII often present with a drug-resistant focal epilepsy consisting of multiple daily seizures[2] with surgical removal of the epileptogenic lesion resulting in high seizure-freedom rates of 80-85%[3]. Magnetic resonance imaging (MRI) plays a key role in diagnosing FCDII, however, at least a third of patients with drug-resistant epilepsy are deemed "MR-negative"[4], meaning a lesion cannot be identified on MRI. This emphasizes the need for better non-invasive imaging methods to improve subtle lesion detection. Diffusion-weighted MRI (dMRI) is an ideal candidate to study the microscale brain structures in vivo, with recent advances in hardware[5] and biophysical modelling techniques[6] showing promise for studying cellular compartments in the cortex[7]. We implemented a dMRI protocol recently adapted for clinical use[8] to acquire advanced cell-body imaging data in paediatric epilepsy patients with suspected or confirmed FCDII.
Methods:
We included 14 patients aged 4-18 years (mean=13, SD=3.7 years) with focal epilepsy and suspected FCDII. Patients underwent two neuroimaging sessions at The Royal Children's Hospital, Parkville, Australia: 1) 18F-FDG-PET (voxel-size=2mm) and structural T1-weighted (voxel-size=0.8mm) data were acquired concurrently on a 3T Siemens mMR Biograph system. 2) Multi-shell dMRI data were acquired on a 3T Siemens Prisma system[8] across six diffusion-weightings [b=500,1000,2000,3000,4000,6000 s/mm2] over 6,32,40,40,40,40 directions, respectively (15 interleaved b0s; TE/TR=88/3000 ms). dMRI data were pre-processed and fit to the soma and neurite density imaging (SANDI[6]) biophysical model, to obtain whole-brain maps of neurite (fneurite), soma (fsoma) and extracellular (fextracellular) signal fractions, and apparent soma radius (Rsoma, µm)(Fig 1). 18F-FDG-PET and T1-weighted data were co-registered to dMRI data and whole-brain parcellations were obtained in Freesurfer(v7.4.1) refined using the HCP-MMP1 atlas[9]. For each imaging measure, an asymmetry index (AI) was computed, firstly in control regions (S1: primary sensory cortex, and V1: primary visual cortex), and secondly in suspected FCDII lesions and their equivalent HCP-MMP1 parcel in the contralateral hemisphere. For right-sided lesions, the AI was flipped in control regions to ensure a positive AI consistently indicates the lesional side has a higher value relative to the non-lesional side. Linear mixed effects modelling was performed in R to compare the lesional vs control AI.
·Figure 1
Results:
The asymmetry analysis revealed that 18F-FDG-PET uptake was significantly lower in the lesion compared with S1 (B=-14.54, p<6e-6) and V1 (B=-15.44, p<2.2e-6), in line with known patterns of focal hypometabolism in FCD[10]. Rsoma was significantly higher in the lesion compared with S1 (B=.86, p<.005) and V1 (B=.90, p=.003). There were no significant differences in asymmetry between lesions and control regions for any of the other MRI measures investigated (Fig 2a). Z-scores of asymmetry indices (using V1 as a control region) revealed 18F-FDG-PET was up to 5 times lower in the lesion (Fig 2b) and Rsoma was up to 5 times higher in the lesion compared with V1. All other microstructural and structural measures centred around zero indicating low asymmetry.
·Figure 2
Conclusions:
Since FCDII is characterised by enlarged dysmorphic neurons, our findings of increased soma radius in the lesion agrees with the hypothesis that an FCDII lesion will have, on average, larger neuronal cell bodies. Further work will integrate histopathology for patients that undergo resective surgery to provide tissue validation of our imaging findings. Overall our findings highlight the utility of biophysical modelling of dMRI data in characterising focal cortical dysplasia in a group of paediatric drug-resistant epilepsy patients.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Lifespan Development:
Early life, Adolescence, Aging
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Cyto- and Myeloarchitecture
Novel Imaging Acquisition Methods:
Diffusion MRI 1
Keywords:
Cortex
Data analysis
Development
Epilepsy
MRI
Neurological
PEDIATRIC
Pediatric Disorders
Positron Emission Tomography (PET)
Other - Microstructure
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
Genc, S. (2024). MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression. bioRxiv, 2024.2007.2030.605934. https://doi.org/10.1101/2024.07.30.605934
Glasser, M.F. (2016). A multi-modal parcellation of human cerebral cortex. Nature, 536(7615), 171-178. https://doi.org/10.1038/nature18933
Jones, D.K. (2018). Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI. NeuroImage, 182, 8-38. https://doi.org/10.1016/j.neuroimage.2018.05.047
Macdonald-Laurs, E. (2021). One-Stage, Limited-Resection Epilepsy Surgery for Bottom-of-Sulcus Dysplasia. Neurology, 97(2), e178. https://doi.org/10.1212/WNL.0000000000012147
Macdonald-Laurs, E. (2024). The clinical, imaging, pathological and genetic landscape of bottom-of-sulcus dysplasia. Brain, 147(4), 1264-1277. https://doi.org/10.1093/brain/awad379
Najm, I. (2022). The ILAE consensus classification of focal cortical dysplasia: An update proposed by an ad hoc task force of the ILAE diagnostic methods commission.
Palombo, M. (2020). Sandi: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion mri. NeuroImage, 215, 116835. doi:10.1016/j.neuroimage.2020.116835
Schiavi, S. (2023). Mapping tissue microstructure across the human brain on a clinical scanner with soma and neurite density image metrics. Human Brain Mapping, 44(13), 4792-4811. doi:https://doi.org/10.1002/hbm.26416
Sperling, M.R. (2004). The consequences of uncontrolled epilepsy. CNS Spectrums, 9(2), 98-109. doi:10.1017/S1092852900008464