Preview

Neurology, Neuropsychiatry, Psychosomatics

Advanced search

Neurophysiological parameters and neuroimaging data in predicting the course of structural focal epilepsy

https://doi.org/10.14412/2074-2711-2019-4-82-87

Full Text:

Abstract

The complex interactions of the epileptic focus and the brain systemic response require an integrated approach to predicting the course of focal epilepsy.
Objective: to investigate the role of interictal neurophysiological parameters and neuroimaging data in predicting the course of epilepsy.
Patients and methods. Eighty-two patients with focal structural epilepsy and 82 healthy participants (a control group) were examined. Clinical, psychological, and social characteristics and the data of neuroimaging and comprehensive neurophysiological studies (electroencephalography (EEG), recording exogenous and cognitive evoked potentials, motor testing, and heart rate variability) were assessed.
Results and discussion. The investigators identified the prognostic factors of the unfavorable course of epilepsy: temporal lobe epilepsy, left temporal lobe lesion, nontraumatic intracerebral hemorrhages. They proposed algorithms for predicting the course of epilepsy based on neurophysiological and neuroimaging data. An analysis of physiological parameters in patients with the unfavorable course of epilepsy demonstrated the slowing of the background rhythm on the EEG, a decrease in the power of specific afferentation, and an increase in the decision-making time for the stimulus, as evidenced by the P300 potential, and insufficiency of the central mechanisms in providing a motor reaction. These patients also showed the enhanced activity of stress-implementing systems. Taking into account not only neurophysiological parameters, but also neuroimaging data could improve the prognostic capabilities of an artificial neural network that determines the type of a disease course.
Conclusion. The unfavorable course of focal epilepsy is associated with a number of clinical and physiological parameters; in this case, it is possible to identify the specific physiological pattern of this course of the disease. The integrated clinical and physiological approach and neuroimaging data make it possible to successfully predict the course of the disease through machine learning technology.

About the Authors

Yu. I. Medvedeva
Acad. I.P. Pavlov Ryazan State Medical State University, Ministry of Health of Russia
Russian Federation
9, Vysokovoltnaya St., Ryazan 390026


R. A. Zorin
Acad. I.P. Pavlov Ryazan State Medical State University, Ministry of Health of Russia
Russian Federation
9, Vysokovoltnaya St., Ryazan 390026


V. A. Zhadnov
Acad. I.P. Pavlov Ryazan State Medical State University, Ministry of Health of Russia
Russian Federation
9, Vysokovoltnaya St., Ryazan 390026


M. M. Lapkin
Acad. I.P. Pavlov Ryazan State Medical State University, Ministry of Health of Russia
Russian Federation
9, Vysokovoltnaya St., Ryazan 390026


References

1. Sheffer IE, Berkovic S, Capovilla G, et al. ILAE classification of the epilepsies: Position paper of the ILAE Comission for Classification and Terminology. Epilepsia. 2017 Apr;58(4): 512-521. doi: 10.1111/epi.13709. Epub 2017 Mar 8.

2. Luders H, Noachtar S. Epileptic seizures. Pathophysiology and Clinical Semiology. Churchill Livingstone; 2000.

3. Bersnev VP, Stepanova TS, Zotov YuV, et al. Clinical and neurophysiological aspects of surgical treatment of pharmacoresistant epilepsy. Zhurnal nevrologii i psikhiatrii im. S.S. Korsakova. 2004;104(4):11-8. (In Russ.)

4. Avanzini G, Manganottie P, Meletti S, et al. The system epilepsies: a pathophysiological hypothesis. Epilepsia. 2012 May;53(5):771-8. doi: 10.1111/j.1528-1167.2012.03462.x.

5. Rogacheva TA, Mel'nikova TS, Tushmalova NA, et al. Cognitive functioning in epilepsy patients in remission of seizures. Sotsial'naya i klinicheskaya psikhiatriya. 2011;21(3):49–53. (In Russ.)

6. Zorin RA, Zhadnov VA, Lapkin MM. The heterogeneity of patients with epilepsy in terms of psychological characteristics, quality of life, and a response to anticonvulsant therapy. Nevrologiya, neiropsikhiatriya, psikhosomatika = Neurology, Neuropsychiatry, Psychosomatics. 2017;9(1S):58-63. (In Russ.) doi: 10.14412/2074-2711-2017-1S-58-63

7. Boev VM, Borshchuk EL, Ekimov AK, et al. Rukovodstvo po obespecheniyu resheniya mediko-biologicheskikh zadach s primeneniem programmy Statistica 10.0 [Guidelines for ensuring the solution of biomedical problems using the program Statistica 10.0]. Orenburg: Yuzhnyi Ural; 2014.

8. Janszky J, Pannek HW, Janszky I, et al. Failed surgery for temporal lobe epilepsy: predictors of long-term seizure-free course. Epilepsy Res. 2005 Mar-Apr;64(1-2):35-44.

9. Choi H, Hayat MJ, Zhang R, et al. Drugresistant epilepsy in adults: Outcome trajectories after failure of two medications. Epilepsia. 2016 Jul;57(7):1152-60. doi: 10.1111/epi.13406. Epub 2016 Jun 6.

10. Vanli-Yavuz EN, Baykan B, Sencer S, et al.How different are the patients with bilateral hippocampal sclerosis from the unilateral ones clinically? Clin EEG Neurosci. 2017 May;48(3): 209-216. doi: 10.1177/1550059416653900. Epub 2016 Jun 10.

11. Hesdorffer DC, Benn EK, Cascino GD, et al. Is a first acute symptomatic seizure epilepsy? Mortality and risk for recurrent seizure. Epilepsia. 2009 May;50(5):1102-8. doi: 10.1111/j.1528-1167.2008.01945.x. Epub 2009 Jan 26.

12. Danilova NN, Krylova AL. Fiziologiya vysshei nervnoi deyatel'nosti [Physiology of higher nervous activity]. Rostov-na-Donu: Feniks; 2005.

13. Sivakova NA, Korsakova EA, Lipatova LV. Pathomorphosis of focal epilepsy and its neurophysiological correlates. Epilepsiya i paroksizmal'nye sostoyaniya. 2018;10(1):6-13. (In Russ.)

14. Cash SS. Status epilepticus as a system disturbance: is status epilepticus due to synchronization or desynchronization? Epilepsia. 2013 Sep;54 Suppl 6:37-9. doi: 10.1111/epi.12273.

15. Den Heijer JM, Otte WM, Van Diessen E, et al. The relation between cortisol and functional connectivity in people with and without stress sensitive epilepsy. Epilepsia. 2018 Jan;59(1): 179-189. doi: 10.1111/epi.13947. Epub 2017 Nov 10.

16. Gu L, Chen J, Gao L, et al. Cognitive reserve modulates attention processes in healthy elderly and amnestic mild cognitive impairment: An event-related potential study. Clin Neurophysiol. 2018 Jan;129(1):198-207. doi: 10.1016/j.clinph.2017.10.030. Epub 2017 Nov 10.

17. Pulliainen V, Kuikka P, Jokelainen M. Motor and cognitive functions in newly diagnosed adult seizure patients before antiepileptic medication. Acta Neurol Scand. 2000 Feb;101(2): 73-8.

18. Tumay Y, Altun Y, Ekmekci K, et al. The effects of levetiracetam, carbamazepine, and sodium valproate on P100 and P300 in epileptic patients. Clin Neuropharmacol. 2013 Mar-Apr;36(2):55-8. doi: 10.1097/WNF.0b013e318285f3da.

19. Myers KA, Sivathamboo S, Perucca P. Heart rate variability measurement in epilepsy: how can we move from research t clinical practice? Epilepsia. 2018 Dec;59(12):2169-2178. doi: 10.1111/epi.14587. Epub 2018 Oct 21.

20. Miranda AA, Zorin RA, Zhadnov VA. Prediction of the development of epileptic syndrome in patients with brain tumors on the basis of a complex ofneurophysiological indicators and logit-regression analysis. Rossiiskii mediko-biologicheskii vestnik im. akademika I.P. Pavlova. 2017;52(2): 223-30. (In Russ.)

21. Ernst G. Heart rate variability. London: Springer-Verlag; 2014. 336 p.


For citation:


Medvedeva Y.I., Zorin R.A., Zhadnov V.A., Lapkin M.M. Neurophysiological parameters and neuroimaging data in predicting the course of structural focal epilepsy. Neurology, Neuropsychiatry, Psychosomatics. 2019;11(4):82-87. (In Russ.) https://doi.org/10.14412/2074-2711-2019-4-82-87

Views: 79


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2074-2711 (Print)
ISSN 2310-1342 (Online)