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McDonald CR, Busch RM, Reyes A, Arrotta K, Barr W, Block C, Hessen E, Loring DW, Drane DL, Hamberger MJ, Wilson SJ, Baxendale S, Hermann BP. Development and application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE): Initial results from a multi-center study of adults with temporal lobe epilepsy. Neuropsychology 2023; 37:301-314. [PMID: 35084879 PMCID: PMC9325925 DOI: 10.1037/neu0000792] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
[Correction Notice: An Erratum for this article was reported online in Neuropsychology on Sep 15 2022 (see record 2023-01997-001). In the original article, there was an error in Figure 2. In the box at the top left of the figure, the fourth explanation incorrectly stated, "Generalized impairment = At least one test < -1.0 or -1.5SD in three or more domains." The correct wording is "Generalized impairment = At least two tests < -1.0 or -1.5SD in each of three or more domains." All versions of this article have been corrected.] Objective: To describe the development and application of a consensus-based, empirically driven approach to cognitive diagnostics in epilepsy research-The International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) and to assess the ability of the IC-CoDE to produce definable and stable cognitive phenotypes in a large, multi-center temporal lobe epilepsy (TLE) patient sample. METHOD Neuropsychological data were available for a diverse cohort of 2,485 patients with TLE across seven epilepsy centers. Patterns of impairment were determined based on commonly used tests within five cognitive domains (language, memory, executive functioning, attention/processing speed, and visuospatial ability) using two impairment thresholds (≤1.0 and ≤1.5 standard deviations below the normative mean). Cognitive phenotypes were derived across samples using the IC-CoDE and compared to distributions of phenotypes reported in existing studies. RESULTS Impairment rates were highest on tests of language, followed by memory, executive functioning, attention/processing speed, and visuospatial ability. Application of the IC-CoDE using varying operational definitions of impairment (≤ 1.0 and ≤ 1.5 SD) produced cognitive phenotypes with the following distribution: cognitively intact (30%-50%), single-domain (26%-29%), bi-domain (14%-19%), and generalized (10%-22%) impairment. Application of the ≤ 1.5 cutoff produced a distribution of phenotypes that was consistent across cohorts and approximated the distribution produced using data-driven approaches in prior studies. CONCLUSIONS The IC-CoDE is the first iteration of a classification system for harmonizing cognitive diagnostics in epilepsy research that can be applied across neuropsychological tests and TLE cohorts. This proof-of-principle study in TLE offers a promising path for enhancing research collaborations globally and accelerating scientific discoveries in epilepsy. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Relationship between visuoperceptual functions and parietal structural abnormalities in temporal lobe epilepsy. Brain Imaging Behav 2023; 17:35-43. [PMID: 36357555 DOI: 10.1007/s11682-022-00738-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2022] [Indexed: 11/12/2022]
Abstract
Progressive gray matter volume reductions beyond the epileptogenic area has been described in temporal lobe epilepsy. There is less evidence regarding correlations between gray and white matter volume changepres and multi-domain cognitive performance in this setting. We aimed to investigate correlations between volume changes in parietal structures and visuospatial performance in temporal lobe epilepsy patients. we performed a cross-sectional study comparing global and regional brain volume data from 34 temporal lobe epilepsy patients and 30 healthy controls. 3D T1-weighted sequences were obtained on a 3.0 T magnet, and data were analyzed using age and sex-adjusted linear regression models. Global and regional brain volumes and cortical thickness in patients were correlated with standardized visual memory, visuoperceptual, visuospatial, and visuoconstructive parameters obtained in a per-protocol neuropsychological assessment. temporal lobe epilepsy patients had smaller volume fractions of the deep gray matter structures, putamen and nucleus accumbens, and larger cerebrospinal fluid volume fraction than controls. Correlations were found between: 1) visual memory and precuneus and inferior parietal cortical thickness; 2) visuoperceptual performance and precuneus and supramarginal white matter volumes; 3) visuospatial skills and precuneus, postcentral, and inferior and superior parietal white matter volumes; 4) visuoconstructive performance and inferior parietal white matter volume. Brain volume loss is widespread in temporal lobe epilepsy. Volumetric reductions in parietal lobe structures were associated with visuoperceptual cognitive performance.
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Reyes A, Hermann BP, Busch RM, Drane DL, Barr WB, Hamberger MJ, Roesch SC, McDonald CR. Moving towards a taxonomy of cognitive impairments in epilepsy: application of latent profile analysis to 1178 patients with temporal lobe epilepsy. Brain Commun 2022; 4:fcac289. [PMID: 36447559 PMCID: PMC9692194 DOI: 10.1093/braincomms/fcac289] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 07/07/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022] Open
Abstract
In efforts to understand the cognitive heterogeneity within and across epilepsy syndromes, cognitive phenotyping has been proposed as a new taxonomy aimed at developing a harmonized approach to cognitive classification in epilepsy. Data- and clinically driven approaches have been previously used with variability in the phenotypes derived across studies. In our study, we utilize latent profile analysis to test several models of phenotypes in a large multicentre sample of patients with temporal lobe epilepsy and evaluate their demographic and clinical profiles. For the first time, we examine the added value of replacing missing data and examine factors that may be contributing to missingness. A sample of 1178 participants met the inclusion criteria for the study, which included a diagnosis of temporal lobe epilepsy and the availability of comprehensive neuropsychological data. Models with two to five classes were examined using latent profile analysis and the optimal model was selected based on fit indices, posterior probabilities and proportion of sample sizes. The models were also examined with imputed data to investigate the impact of missing data on model selection. Based on the fit indices, posterior probability and distinctiveness of the latent classes, a three-class solution was the optimal solution. This three-class solution comprised a group of patients with multidomain impairments, a group with impairments predominantly in language and a group with no impairments. Overall, the multidomain group demonstrated a worse clinical profile and comprised a greater proportion of patients with mesial temporal sclerosis, a longer disease duration and a higher number of anti-seizure medications. The four-class and five-class solutions demonstrated the lowest probabilities of a group membership. Analyses with imputed data demonstrated that the four-class solution was the optimal solution; however, there was a weak agreement between the missing and imputed data sets for the four-Class solutions (κ = 0.288, P < 0.001). This study represents the first to use latent profile analysis to test and compare multiple models of cognitive phenotypes in temporal lobe epilepsy and to determine the impact of missing data on model fit. We found that the three-phenotype model was the most meaningful based on several fit indices and produced phenotypes with unique demographic and clinical profiles. Our findings demonstrate that latent profile analysis is a rigorous method to identify phenotypes in large, heterogeneous epilepsy samples. Furthermore, this study highlights the importance of examining the impact of missing data in phenotyping methods. Our latent profile analysis-derived phenotypes can inform future studies aimed at identifying cognitive phenotypes in other neurological disorders.
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Affiliation(s)
- Anny Reyes
- Center for Multimodal Imaging and Genetics, University of CaliforniaSan Diego, La Jolla, CA 92093, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA 92120, USA
| | - Bruce P Hermann
- Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53726, USA
| | - Robyn M Busch
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44106, USA
- Department of Neurology, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Daniel L Drane
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, University of Washington, Seattle, WA 98195, USA
| | - William B Barr
- Department of Neurology, NYU-Langone Medical Center and NYU School of Medicine, New York, NY 10016, USA
- Department of Psychiatry, NYU-Langone Medical Center and NYU School of Medicine, New York, NY 10016, USA
| | - Marla J Hamberger
- Department of Neurology, Columbia University, New York, NY 10027, USA
| | - Scott C Roesch
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Carrie R McDonald
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA 92093, USA
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Goldstein HE, Poliakov A, Shaw DW, Barry D, Tran K, Novotny EJ, Saneto RP, Marashly A, Warner MH, Wright JN, Hauptman JS, Ojemann JG, Shurtleff HA. Precision medicine in pediatric temporal epilepsy surgery: optimization of outcomes through functional MRI memory tasks and tailored surgeries. J Neurosurg Pediatr 2022; 30:272-283. [PMID: 35901731 DOI: 10.3171/2022.5.peds22148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 05/27/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The goal of epilepsy surgery is both seizure cessation and maximal preservation of function. In temporal lobe (TL) cases, the lack of functional MRI (fMRI) tasks that effectively activate mesial temporal structures hampers preoperative memory risk assessment, especially in children. This study evaluated pediatric TL surgery outcome optimization associated with tailored resection informed by an fMRI memory task. METHODS The authors identified focal onset TL epilepsy patients with 1) TL resections; 2) viable fMRI memory scans; and 3) pre- and postoperative neuropsychological (NP) evaluations. They retrospectively evaluated preoperative fMRI memory scans, available Wada tests, pre- and postoperative NP scores, postoperative MRI scans, and postoperative Engel class outcomes. To assess fMRI memory task outcome prediction, the authors 1) overlaid preoperative fMRI activation onto postoperative structural images; 2) classified patients as having "overlap" or "no overlap" of activation and resection cavities; and 3) compared these findings with memory improvement, stability, or decline, based on Reliable Change Index calculations. RESULTS Twenty patients met the inclusion criteria. At a median of 2.1 postoperative years, 16 patients had Engel class IA outcomes and 1 each had Engel class IB, ID, IIA, and IID outcomes. Functional MRI activation was linked to NP memory outcome in 19 of 20 cases (95%). Otherwise, heterogeneity characterized the cohort. CONCLUSIONS Functional MRI memory task activation effectively predicted individual NP outcomes in the context of tailored TL resections. Patients had excellent seizure and overall good NP outcomes. This small study adds to extant literature indicating that pediatric TL epilepsy does not represent a single clinical syndrome. Findings support individualized surgical intervention using fMRI memory activation to help guide this precision medicine approach.
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Affiliation(s)
- Hannah E Goldstein
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 2Department of Neurological Surgery, University of Washington School of Medicine, Seattle
- 3Division of Neurosurgery, Seattle Children's Hospital, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
| | - Andrew Poliakov
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 3Division of Neurosurgery, Seattle Children's Hospital, Seattle
- 4Department of Radiology, Seattle Children's Hospital, Seattle
| | - Dennis W Shaw
- 4Department of Radiology, Seattle Children's Hospital, Seattle
- 5Department of Radiology, University of Washington School of Medicine, Seattle
| | - Dwight Barry
- 6Clinical Analytics, Seattle Children's Hospital, Seattle
| | - Kieu Tran
- 2Department of Neurological Surgery, University of Washington School of Medicine, Seattle
- 3Division of Neurosurgery, Seattle Children's Hospital, Seattle
| | - Edward J Novotny
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 7Division of Pediatric Neurology, Seattle Children's Hospital, Seattle
- 8Department of Neurology, University of Washington School of Medicine, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
| | - Russell P Saneto
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 7Division of Pediatric Neurology, Seattle Children's Hospital, Seattle
- 8Department of Neurology, University of Washington School of Medicine, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
| | - Ahmad Marashly
- 10Epilepsy Center, Department of Neurology, The Johns Hopkins University Medical Center, Baltimore, Maryland
| | - Molly H Warner
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 7Division of Pediatric Neurology, Seattle Children's Hospital, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
| | - Jason N Wright
- 4Department of Radiology, Seattle Children's Hospital, Seattle
- 5Department of Radiology, University of Washington School of Medicine, Seattle
| | - Jason S Hauptman
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 2Department of Neurological Surgery, University of Washington School of Medicine, Seattle
- 3Division of Neurosurgery, Seattle Children's Hospital, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
| | - Jeffrey G Ojemann
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 2Department of Neurological Surgery, University of Washington School of Medicine, Seattle
- 3Division of Neurosurgery, Seattle Children's Hospital, Seattle
- 5Department of Radiology, University of Washington School of Medicine, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
| | - Hillary A Shurtleff
- 1Neurosciences Center, Seattle Children's Hospital, Seattle
- 7Division of Pediatric Neurology, Seattle Children's Hospital, Seattle
- 9Center for Integrated Brain Research, Seattle Children's Hospital, Seattle, Washington; and
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Zimmermann N, Pontes M, da Silva Fontana R, D'Andrea Meira I, Fonseca R, Delaere FJ. The modified Ruche visuospatial learning test (RUCHE-M) for the assessment of visuospatial episodic memory in patients with temporal lobe epilepsy: Preliminary evidence for the investigation of memory binding. APPLIED NEUROPSYCHOLOGY. ADULT 2022:1-16. [PMID: 35133219 DOI: 10.1080/23279095.2022.2031200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
INTRODUCTION The Ruche test is a visuospatial form of the Rey auditory verbal learning test (RAVLT), with initial evidence of utility in the diagnosis of temporal lobe epilepsy (TLE)-related memory disorders. AIMS To present the translation to Brazilian Portuguese and modification of the Ruche test (RUCHE-M) and compare the RUCHE-M and RAVLT performance between patients with right and left TLE. METHODS Twenty-five neuropsychologists participated in instrument adaptation. Thirty-seven patients with right (n = 19) and left (n = 18) TLE participated. Data were compared with the Mann-Whitney U test. RESULTS All specialists considered the final RUCHE-M to be adequate. The RUCHE-M forgetting speed index (FSI) score and several RAVLT scores differed significantly between patients with right and left TLE. CONCLUSION The RUCHE-M showed limited utility for the assessment of visuospatial episodic memory in patients with TLE. The manipulation of memory binding as demonstrated by FSI score seems to be a promising paradigm for the assessment of right hippocampal function.
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Affiliation(s)
- Nicolle Zimmermann
- Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
- Paulo Niemeyer State Brain Institute, Rio de Janeiro, Brazil
| | - Monique Pontes
- Paulo Niemeyer State Brain Institute, Rio de Janeiro, Brazil
| | | | | | - Rochele Fonseca
- Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
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Helmstaedter C, Sadat-Hossieny Z, Kanner AM, Meador KJ. Cognitive disorders in epilepsy II: Clinical targets, indications and selection of test instruments. Seizure 2020; 83:223-231. [PMID: 33172763 DOI: 10.1016/j.seizure.2020.09.031] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 09/18/2020] [Accepted: 09/21/2020] [Indexed: 12/26/2022] Open
Abstract
This is the second of two narrative reviews on cognitive disorders in epilepsy (companion manuscript: Cognitive disorders in epilepsy I: Clinical experience, real-world evidence and recommendations). Its focus is on the clinical targets, indications, and the selection of neuropsychological test instruments. Cognitive assessment has become an essential tool for the diagnosis and outcome control in the clinical management of epilepsy. The diagnostics of basic and higher brain functions can provide valuable information on lateralized and localized brain dysfunctions associated with epilepsy, its underlying pathologies and treatment. In addition to the detection or verification of deficits, neuropsychology reveals the patient's cognitive strengths and, thus, information about the patient reserve capacities for functional restitution and compensation. Neuropsychology is an integral part of diagnostic evaluations mainly in the context of epilepsy surgery to avoid new or additional damage to preexisting neurocognitive impairments. In addition and increasingly, neuropsychology is being used as a tool for monitoring of the disease and its underlying pathologies, and it is suited for the quality and outcome control of pharmacological or other non-invasive medical intervention. This narrative review summarizes the present state of neuropsychological assessments in epilepsy, reveals diagnostic gaps, and shows the great need for education, homogenization, translation and standardization of instruments.
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Affiliation(s)
- C Helmstaedter
- University Clinic Bonn, Department of Epileptology, Germany.
| | - Z Sadat-Hossieny
- Department of Neurology & Neurological Sciences, Stanford University School of Medicine, 213 Quarry Road, MC 5979, CA, 94304, USA
| | - A M Kanner
- University of Miami Health System, Uhealth Neurology, 1150 NW 14th St #609, Miami, FL 33136, USA
| | - K J Meador
- Department of Neurology & Neurological Sciences, Stanford University School of Medicine, 213 Quarry Road, MC 5979, CA, 94304, USA
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