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Morita-Sherman M, Li M, Joseph B, Yasuda C, Vegh D, De Campos BM, Alvim MKM, Louis S, Bingaman W, Najm I, Jones S, Wang X, Blümcke I, Brinkmann BH, Worrell G, Cendes F, Jehi L. Incorporation of quantitative MRI in a model to predict temporal lobe epilepsy surgery outcome. Brain Commun 2021; 3:fcab164. [PMID: 34396113 PMCID: PMC8361423 DOI: 10.1093/braincomms/fcab164] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2021] [Indexed: 11/23/2022] Open
Abstract
Quantitative volumetric brain MRI measurement is important in research applications, but translating it into patient care is challenging. We explore the incorporation of clinical automated quantitative MRI measurements in statistical models predicting outcomes of surgery for temporal lobe epilepsy. Four hundred and thirty-five patients with drug-resistant epilepsy who underwent temporal lobe surgery at Cleveland Clinic, Mayo Clinic and University of Campinas were studied. We obtained volumetric measurements from the pre-operative T1-weighted MRI using NeuroQuant, a Food and Drug Administration approved software package. We created sets of statistical models to predict the probability of complete seizure-freedom or an Engel score of I at the last follow-up. The cohort was randomly split into training and testing sets, with a ratio of 7:3. Model discrimination was assessed using the concordance statistic (C-statistic). We compared four sets of models and selected the one with the highest concordance index. Volumetric differences in pre-surgical MRI located predominantly in the frontocentral and temporal regions were associated with poorer outcomes. The addition of volumetric measurements to the model with clinical variables alone increased the model’s C-statistic from 0.58 to 0.70 (right-sided surgery) and from 0.61 to 0.66 (left-sided surgery) for complete seizure freedom and from 0.62 to 0.67 (right-sided surgery) and from 0.68 to 0.73 (left-sided surgery) for an Engel I outcome score. 57% of patients with extra-temporal abnormalities were seizure-free at last follow-up, compared to 68% of those with no such abnormalities (P-value = 0.02). Adding quantitative MRI data increases the performance of a model developed to predict post-operative seizure outcomes. The distribution of the regions of interest included in the final model supports the notion that focal epilepsies are network disorders and that subtle cortical volume loss outside the surgical site influences seizure outcome.
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Affiliation(s)
| | - Manshi Li
- Department of Quantitative Health Sciences, Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - Boney Joseph
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas, Campinas, Brazil
| | - Deborah Vegh
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA
| | | | - Marina K M Alvim
- Department of Neurology, University of Campinas, Campinas, Brazil
| | - Shreya Louis
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA
| | - William Bingaman
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA
| | - Imad Najm
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA
| | - Stephen Jones
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA
| | - Xiaofeng Wang
- Department of Quantitative Health Sciences, Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - Ingmar Blümcke
- Department of Neuropathology, University Hospitals, Erlangen, Germany
| | | | | | - Fernando Cendes
- Department of Neurology, University of Campinas, Campinas, Brazil
| | - Lara Jehi
- Department of Neurology, Epilepsy Center, Cleveland Clinic, Cleveland, OH, USA
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Bharath RD, Sinha S, Panda R, Raghavendra K, George L, Chaitanya G, Gupta A, Satishchandra P. Seizure Frequency Can Alter Brain Connectivity: Evidence from Resting-State fMRI. AJNR Am J Neuroradiol 2015; 36:1890-8. [PMID: 26294642 DOI: 10.3174/ajnr.a4373] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 02/25/2015] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The frequency of seizures is an important factor that can alter functional brain connectivity. Analysis of this factor in patients with epilepsy is complex because of disease- and medication-induced confounders. Because patients with hot-water epilepsy generally are not on long-term drug therapy, we used seed-based connectivity analysis in these patients to assess connectivity changes associated with seizure frequency without confounding from antiepileptic drugs. MATERIALS AND METHODS Resting-state fMRI data from 36 patients with hot-water epilepsy (18 with frequent seizures [>2 per month] and 18 with infrequent seizures [≤2 per month]) and 18 healthy age- and sex-matched controls were analyzed for seed-to-voxel connectivity by using 106 seeds. Voxel wise paired t-test analysis (P < .005, corrected for false-discovery rate) was used to identify significant intergroup differences between these groups. RESULTS Connectivity analysis revealed significant differences between the 2 groups (P < .001). Patients in the frequent-seizure group had increased connectivity within the medial temporal structures and widespread areas of poor connectivity, even involving the default mode network, in comparison with those in the infrequent-seizure group. Patients in the infrequent-seizure group had focal abnormalities with increased default mode network connectivity and decreased left entorhinal cortex connectivity. CONCLUSIONS The results of this study suggest that seizure frequency can alter functional brain connectivity, which can be visualized by using resting-state fMRI. Imaging features such as diffuse network abnormalities, involvement of the default mode network, and recruitment of medial temporal lobe structures were seen only in patients with frequent seizures. Future studies in more common epilepsy groups, however, will be required to further establish this finding.
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Affiliation(s)
- R D Bharath
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.) Advanced Brain Imaging Facility (R.D.B., R.P.), Cognitive Neuroscience Center, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India
| | - S Sinha
- Neurology (S.S., K.R., G.C., P.S.)
| | - R Panda
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.) Advanced Brain Imaging Facility (R.D.B., R.P.), Cognitive Neuroscience Center, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India
| | | | - L George
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.)
| | | | - A Gupta
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.)
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Antony AR, Alexopoulos AV, González-Martínez JA, Mosher JC, Jehi L, Burgess RC, So NK, Galán RF. Functional connectivity estimated from intracranial EEG predicts surgical outcome in intractable temporal lobe epilepsy. PLoS One 2013; 8:e77916. [PMID: 24205027 PMCID: PMC3813548 DOI: 10.1371/journal.pone.0077916] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Accepted: 09/15/2013] [Indexed: 11/18/2022] Open
Abstract
This project aimed to determine if a correlation-based measure of functional connectivity can identify epileptogenic zones from intracranial EEG signals, as well as to investigate the prognostic significance of such a measure on seizure outcome following temporal lobe lobectomy. To this end, we retrospectively analyzed 23 adult patients with intractable temporal lobe epilepsy (TLE) who underwent an invasive stereo-EEG (SEEG) evaluation between January 2009 year and January 2012. A follow-up of at least one year was required. The primary outcome measure was complete seizure-freedom at last follow-up. Functional connectivity between two areas in the temporal lobe that were sampled by two SEEG electrode contacts was defined as Pearson's correlation coefficient of interictal activity between those areas. SEEG signals were filtered between 5 and 50 Hz prior to computing this correlation. The mean and standard deviation of the off diagonal elements in the connectivity matrix were also calculated. Analysis of the mean and standard deviation of the functional connections for each patient reveals that 90% of the patients who had weak and homogenous connections were seizure free one year after temporal lobectomy, whereas 85% of the patients who had stronger and more heterogeneous connections within the temporal lobe had recurrence of seizures. This suggests that temporal lobectomy is ineffective in preventing seizure recurrence for patients in whom the temporal lobe is characterized by weakly connected, homogenous networks. This pilot study shows promising potential of a simple measure of functional brain connectivity to identify epileptogenicity and predict the outcome of epilepsy surgery.
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Affiliation(s)
- Arun R. Antony
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, United States of America
| | | | | | - John C. Mosher
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Lara Jehi
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Richard C. Burgess
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Norman K. So
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, United States of America
| | - Roberto F. Galán
- Department of Neurosciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
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