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The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.

التفاصيل البيبلوغرافية
العنوان: The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.
المؤلفون: Mercier M; Neurology, Epilepsy and Movement Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, Piazza S. Onofrio 4, 00165, Rome, Italy.; Department of Physiology, Behavioural Neuroscience PhD Program, Sapienza University, Rome, Italy., Pepi C; Neurology, Epilepsy and Movement Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, Piazza S. Onofrio 4, 00165, Rome, Italy., Carfi-Pavia G; Neurology, Epilepsy and Movement Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, Piazza S. Onofrio 4, 00165, Rome, Italy., De Benedictis A; Neurosurgery Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, 00165, Rome, Italy., Espagnet MCR; Neuroradiology Unit, Imaging Department, Bambino Gesù Children's Hospital, 00165, Rome, Italy., Pirani G; Department of Mechanical and Aerospace Engineering - DIMA, Sapienza University of Rome, Rome, Italy., Vigevano F; Neurology, Epilepsy and Movement Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, Piazza S. Onofrio 4, 00165, Rome, Italy., Marras CE; Neurosurgery Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, 00165, Rome, Italy., Specchio N; Neurology, Epilepsy and Movement Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, Piazza S. Onofrio 4, 00165, Rome, Italy. nicola.specchio@opbg.net., De Palma L; Neurology, Epilepsy and Movement Disorders Unit, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, Piazza S. Onofrio 4, 00165, Rome, Italy.
المصدر: Scientific reports [Sci Rep] 2024 May 13; Vol. 14 (1), pp. 10887. Date of Electronic Publication: 2024 May 13.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : Nature Publishing Group, copyright 2011-
مواضيع طبية MeSH: Electroencephalography*/methods , Machine Learning*, Humans ; Child ; Female ; Male ; Child, Preschool ; Adolescent ; Epilepsy/surgery ; Epilepsy/physiopathology ; Epilepsy/diagnosis ; Neural Networks, Computer ; Treatment Outcome ; Infant ; Sleep/physiology
مستخلص: Epilepsy surgery is effective for patients with medication-resistant seizures, however 20-40% of them are not seizure free after surgery. Aim of this study is to evaluate the role of linear and non-linear EEG features to predict post-surgical outcome. We included 123 paediatric patients who underwent epilepsy surgery at Bambino Gesù Children Hospital (January 2009-April 2020). All patients had long term video-EEG monitoring. We analysed 1-min scalp interictal EEG (wakefulness and sleep) and extracted 13 linear and non-linear EEG features (power spectral density (PSD), Hjorth, approximate entropy, permutation entropy, Lyapunov and Hurst value). We used a logistic regression (LR) as feature selection process. To quantify the correlation between EEG features and surgical outcome we used an artificial neural network (ANN) model with 18 architectures. LR revealed a significant correlation between PSD of alpha band (sleep), Mobility index (sleep) and the Hurst value (sleep and awake) with outcome. The fifty-four ANN models gave a range of accuracy (46-65%) in predicting outcome. Within the fifty-four ANN models, we found a higher accuracy (64.8% ± 7.6%) in seizure outcome prediction, using features selected by LR. The combination of PSD of alpha band, mobility and the Hurst value positively correlate with good surgical outcome.
(© 2024. The Author(s).)
References: Clin Neurophysiol. 2005 Oct;116(10):2266-301. (PMID: 16115797)
J Neural Eng. 2019 Aug 21;16(5):056019. (PMID: 31100736)
Epilepsy Res. 2006 Apr;69(1):30-44. (PMID: 16503398)
Comput Biol Med. 2015 Nov 1;66:352-6. (PMID: 25982199)
Biomedicines. 2023 Mar 07;11(3):. (PMID: 36979795)
Lancet Neurol. 2020 Sep;19(9):748-757. (PMID: 32822635)
Epilepsia. 2015 Mar;56(3):359-65. (PMID: 25530458)
Int J Neural Syst. 2020 Nov;30(11):2050036. (PMID: 32812470)
Comput Biol Med. 2015 Sep;64:67-78. (PMID: 26149291)
J Neurol Neurosurg Psychiatry. 2022 May;93(5):499-508. (PMID: 35246493)
N Engl J Med. 2019 Apr 4;380(14):1347-1358. (PMID: 30943338)
Sci Rep. 2023 Aug 4;13(1):12650. (PMID: 37542101)
Sci Rep. 2020 May 21;10(1):8419. (PMID: 32439999)
Lancet Neurol. 2015 Mar;14(3):283-90. (PMID: 25638640)
Clin Neurophysiol Pract. 2022 Dec 14;8:32-41. (PMID: 36632368)
Epilepsia. 2023 Apr;64(4):962-972. (PMID: 36764672)
J Neurosurg. 1999 Jun;90(6):998-1004. (PMID: 10350243)
Health Inf Sci Syst. 2020 Oct 12;8(1):33. (PMID: 33088489)
Neuroimage. 2020 Oct 15;220:117111. (PMID: 32615255)
Epilepsia. 2013 May;54(5):772-82. (PMID: 23586531)
Epilepsia. 2022 Jul;63(7):1630-1642. (PMID: 35416285)
Epilepsia. 2023 Aug;64(8):2014-2026. (PMID: 37129087)
Dev Cogn Neurosci. 2022 Apr;54:101067. (PMID: 35065418)
Hum Brain Mapp. 2020 Feb 1;41(2):467-483. (PMID: 31625670)
Entropy (Basel). 2020 Dec 25;23(1):. (PMID: 33375658)
Brain Dev. 2018 Jan;40(1):26-35. (PMID: 28757110)
Lancet Child Adolesc Health. 2022 Jul;6(7):484-494. (PMID: 35568054)
Epilepsy Behav. 2021 Oct;123:108273. (PMID: 34507093)
Front Neurosci. 2020 Sep 30;14:808. (PMID: 33177970)
Epilepsia. 2022 Aug;63(8):1956-1969. (PMID: 35661152)
J Med Syst. 2010 Apr;34(2):195-212. (PMID: 20433058)
Clin Neurophysiol. 2005 Nov;116(11):2701-6. (PMID: 16221562)
Epilepsy Curr. 2023 Jan 18;23(2):78-83. (PMID: 37122399)
Front Hum Neurosci. 2022 Jun 27;16:913777. (PMID: 35832872)
Epilepsy Behav. 2019 Jun;95:124-130. (PMID: 31035104)
Epilepsia. 2019 Oct;60(10):2037-2047. (PMID: 31478577)
Int J Neural Syst. 2014 Nov;24(7):1450023. (PMID: 25164248)
Epilepsia. 1998 Jan;39(1):61-6. (PMID: 9578014)
Front Hum Neurosci. 2017 Jan 20;10:687. (PMID: 28163676)
IEEE Trans Biomed Circuits Syst. 2020 Apr;14(2):209-220. (PMID: 31796417)
Clin Neurophysiol. 2010 Mar;121(3):290-300. (PMID: 20005158)
Multimed Tools Appl. 2023 Apr 4;:1-31. (PMID: 37362745)
PLoS One. 2013 Apr 30;8(4):e62819. (PMID: 23646148)
Phys Eng Sci Med. 2021 Mar;44(1):157-171. (PMID: 33417158)
Sensors (Basel). 2020 Apr 21;20(8):. (PMID: 32326195)
Brain Sci. 2022 Dec 30;13(1):. (PMID: 36672052)
Epilepsia. 2021 Oct;62(10):2439-2450. (PMID: 34338324)
Epilepsia. 2022 May;63(5):1081-1092. (PMID: 35266138)
J Biol Phys. 2008 Aug;34(3-4):253-66. (PMID: 19669475)
معلومات مُعتمدة: PE0000006 This study was supported by #NEXTGENERATIONEU (NGEU) and funded by the Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006) - A Multiscale integrated approach to the study of the nervous system in health and disease; 202205 Precision medicine in epilepsy: definition of a predictive model of epilepsy outcome and creation of an automated tool based on machine learning." Ricerca 5x1000 Bambino Gesu' Children' Hospital. Project code: 202205
فهرسة مساهمة: Keywords: Artificial neural network; Brain machine learning; Diagnostic evaluation; Entropy; Epilepsy; Feature selection; Hjorth parameters; Hurst index; Lyapunov exponents; Non-linear EEG biomarkers; Predictive factors; Resective surgery; Scalp EEG; Seizure outcome
تواريخ الأحداث: Date Created: 20240513 Date Completed: 20240513 Latest Revision: 20240516
رمز التحديث: 20240516
مُعرف محوري في PubMed: PMC11091060
DOI: 10.1038/s41598-024-60622-5
PMID: 38740844
قاعدة البيانات: MEDLINE
الوصف
تدمد:2045-2322
DOI:10.1038/s41598-024-60622-5