Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy
Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analys...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2015-01-01
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| Series: | NeuroImage: Clinical |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158214001119 |
| _version_ | 1811245397731966976 |
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| author | Daniel S. Barron Peter T. Fox Heath Pardoe Jack Lancaster Larry R. Price Karen Blackmon Kristen Berry Jose E. Cavazos Ruben Kuzniecky Orrin Devinsky Thomas Thesen |
| author_facet | Daniel S. Barron Peter T. Fox Heath Pardoe Jack Lancaster Larry R. Price Karen Blackmon Kristen Berry Jose E. Cavazos Ruben Kuzniecky Orrin Devinsky Thomas Thesen |
| author_sort | Daniel S. Barron |
| collection | DOAJ |
| description | Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied.
No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses. |
| first_indexed | 2024-04-12T14:38:30Z |
| format | Article |
| id | doaj.art-fa863943099c42e5997b1585845bf109 |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-04-12T14:38:30Z |
| publishDate | 2015-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-fa863943099c42e5997b1585845bf1092022-12-22T03:28:58ZengElsevierNeuroImage: Clinical2213-15822015-01-017C27328010.1016/j.nicl.2014.08.002Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategyDaniel S. Barron0Peter T. Fox1Heath Pardoe2Jack Lancaster3Larry R. Price4Karen Blackmon5Kristen Berry6Jose E. Cavazos7Ruben Kuzniecky8Orrin Devinsky9Thomas Thesen10Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USAResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USADepartment of Neurology, New York University, New York, NY, USAResearch Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USACollege of Education, Texas State University, San Marcos, TX, USADepartment of Neurology, New York University, New York, NY, USADepartment of Neurology, New York University, New York, NY, USADepartment of Neurology, University of TX Health Science Center, San Antonio, TX, USADepartment of Neurology, New York University, New York, NY, USADepartment of Neurology, New York University, New York, NY, USADepartment of Neurology, New York University, New York, NY, USANoninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.http://www.sciencedirect.com/science/article/pii/S2213158214001119EpilepsyTemporal Lobe EpilepsyThalamusResting-state fMRIfMRIBiomarkerLateralization |
| spellingShingle | Daniel S. Barron Peter T. Fox Heath Pardoe Jack Lancaster Larry R. Price Karen Blackmon Kristen Berry Jose E. Cavazos Ruben Kuzniecky Orrin Devinsky Thomas Thesen Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy NeuroImage: Clinical Epilepsy Temporal Lobe Epilepsy Thalamus Resting-state fMRI fMRI Biomarker Lateralization |
| title | Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy |
| title_full | Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy |
| title_fullStr | Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy |
| title_full_unstemmed | Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy |
| title_short | Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy |
| title_sort | thalamic functional connectivity predicts seizure laterality in individual tle patients application of a biomarker development strategy |
| topic | Epilepsy Temporal Lobe Epilepsy Thalamus Resting-state fMRI fMRI Biomarker Lateralization |
| url | http://www.sciencedirect.com/science/article/pii/S2213158214001119 |
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