ArticleNeuroImage. Clinical2015
Predicting the laterality of temporal lobe epilepsy from PET, MRI, and DTI: A multimodal study.
Article in NeuroImage. Clinical, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Nuclear imaging for localization and surgical outcome prediction in epilepsy: A review of latest discoveries and future perspectives.Frontiers in neurology · 2022Pooled it
- Network dysfunction underlying verbal fluency deficits in newly diagnosed epilepsy: a resting-state fMRI functional connectivity study.BMC medicine · 2025Article
- Left parietal structural connectivity mediates typical and atypical language laterality in temporal lobe epilepsy.Epilepsia · 2025Article
- Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion.Neural networks : the official journal of the International Neural Network Society · 2025Article
- Superficial and deep white matter abnormalities in temporal lobe epilepsy.Brain communications · 2025Article
- Brain morphology normative modelling platform for abnormality and centile estimation: Brain MoNoCle.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Article
- Prediction of Post Traumatic Epilepsy Using MR-Based Imaging Markers.Human brain mapping · 2024Article
- Artificial intelligence in epilepsy - applications and pathways to the clinic.Nature reviews. Neurology · 2024Review
- Article
- In vivo characterization of magnetic resonance imaging-based T1w/T2w ratios reveals myelin-related changes in temporal lobe epilepsy.Human brain mapping · 2023Article
- Combined [European radiology · 2022Article
- Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy.Science advances · 2022Article
- Combined quantitative T2 mapping and [European radiology · 2022Article
- Comparison of multimodal findings on epileptogenic side in temporal lobe epilepsy using self-organizing maps.Magma (New York, N.Y.) · 2022Article
- Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning.AJNR. American journal of neuroradiology · 2022Article
- Brain laterality evaluated by F-18 fluorodeoxyglucose positron emission computed tomography in autism spectrum disorders.Frontiers in molecular neuroscience · 2022Article
- QuantitativeEpilepsy & behavior : E&B · 2021Article
- Lateralizing the affected side of hippocampal sclerosis with quantitative high angular resolution diffusion scalars: a preliminary approach validated by diffusion spectrum imaging.Annals of translational medicine · 2021Article
- Clinical Application of Machine Learning Models for Brain Imaging in Epilepsy: A Review.Frontiers in neuroscience · 2021Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Pre-surgical evaluation of patients with temporal lobe epilepsy (TLE) relies on information obtained from multiple neuroimaging modalities. The relationship between modalities and their combined power in predicting the seizure focus is currently unknown. We investigated asymmetries from three different modalities, PET (glucose metabolism), MRI (cortical thickness), and diffusion tensor imaging (DTI; white matter anisotropy) in 28 left and 30 right TLE patients (LTLE and RTLE). Stepwise logistic regression models were built from each modality separately and from all three combined, while bootstrapped methods and split-sample validation verified the robustness of predictions. Among all multimodal asymmetries, three PET asymmetries formed the best predictive model (100% success in full sample, >95% success in split-sample validation). The combinations of PET with other modalities did not perform better than PET alone. Probabilistic classifications were obtained for new clinical cases, which showed correct lateralization for 7/7 new TLE patients (100%) and for 4/5 operated patients with discordant or non-informative PET reports (80%). Metabolism showed closer relationship with white matter in LTLE and closer relationship with gray matter in RTLE. Our data suggest that metabolism is a powerful modality that can predict seizure laterality with high accuracy, and offers high value for automated predictive models. The side of epileptogenic focus can affect the relationship of metabolism with brain structure. The data and tools necessary to obtain classifications for new TLE patients are made publicly available.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.