Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome

Author:

Kuroda Naoto12,Sonoda Masaki13ORCID,Miyakoshi Makoto4,Nariai Hiroki5,Jeong Jeong-Won16,Motoi Hirotaka17,Luat Aimee F16,Sood Sandeep8,Asano Eishi16

Affiliation:

1. Department of Paediatrics, Children’s Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA

2. Department of Epileptology, Tohoku University Graduate School of Medicine, Sendai 9808575, Japan

3. Department of Neurosurgery, Yokohama City University, Yokohama 2360004, Japan

4. Swartz Centre for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA 92093, USA

5. Division of Paediatric Neurology, Department of Paediatrics, UCLA Mattel Children’s Hospital, David Geffen School of Medicine, Los Angeles, CA 90095, USA

6. Department of Neurology, Children’s Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA

7. Department of Paediatrics, Yokohama City University Medical Centre, Yokohama 2320024, Japan

8. Department of Neurosurgery, Children’s Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA

Abstract

Abstract Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3–4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

General Earth and Planetary Sciences,General Environmental Science

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