Dados do Trabalho

Título

WHAT’S THE ROLE OF QEEG IN PATIENTS WITH AUTISM SPECTRUM DISORDERS? STATE-OF-THE-ART

Introdução

Autism Spectrum Disorders (ASD) comprise highly prevalent neurodevelopmental conditions that affect behavior, cognition, and socialization deeply. Their pathophysiology, although unclear, includes genetic predisposition and environmental factors. The diagnosis is made clinically, based on a set of criteria established in DSM-5. However, complementary tests are emerging as alternatives to improve diagnostic accuracy, favoring a broader and more in-depth understanding of individual cases, especially when it comes to pediatric patients. Recently, artificial intelligence has provided a way of improving neurophysiological methods. In this sense, quantitative electroencephalography (qEEG) has emerged as a powerful tool for understanding brain circuitry, making it possible to plan personalized interventions based on their main features.

Objetivo

To evaluate the potential role of qEEG in the diagnostic workup and clinical characterization of pediatric patients with ASD.

Método

A search for articles within a 10-year time window was performed in the Medline, Cochrane Library, Embase, Lilacs and Web of Science databases using the terms "ASD" and "qEEG", with the Boolean operator AND, as well as the search key "ASD", "qEEG" and "Child" with the same operator.

Resultados

28 papers were identified. In these studies, there is a recurrent finding of reduced absolute power of alpha waves in the left frontotemporal topography, as well as a reduction in the absolute power of delta and theta waves under electrode Cz and beta waves in the right occipital region. However, other studies have shown an increase in slow waves in frontal topography associated with a worse cognitive performance. Connectometry analysis indicates hypercoherence in gamma waves and hypocoherence in alpha and beta waves, with impaired intra- and inter-hemispheric information flow.

Conclusão

qEEG may become a valuable tool in the investigation of patients with ASD in terms of the individuality of their manifestations and improved correlation of clinical aspects with electroneurophysiological features. It should be noted, however, that the great variability of the findings is due to heterogeneity of samples. Therefore, additional studies of larger and more homogeneous clinical samples are likely to expand our knowledge of patients with ASD.

Referências

Hirota, T., & King, B. H. (2023). Autism Spectrum Disorder: A Review. JAMA, 329(2), 157–168. https://doi.org/10.1001/jama.2022.23661

Machado, C., Estévez, M., Leisman, G. et al. QEEG Spectral and Coherence Assessment of Autistic Children in Three Different Experimental Conditions. J Autism Dev Disord 45, 406–424 (2015). https://doi.org/10.1007/s10803-013-1909-5

McVoy, M., Lytle, S., Fulchiero, E., Aebi, M. E., Adeleye, O., & Sajatovic, M. (2019). A systematic review of quantitative EEG as a possible biomarker in child psychiatric disorders. Psychiatry research, 279, 331–344. https://doi.org/10.1016/j.psychres.2019.07.004

Pop-Jordanova, N., Zorcec, T., Demerdzieva, A. et al. QEEG characteristics and spectrum weighted frequency for children diagnosed as autistic spectrum disorder. Nonlinear Biomed Phys 4, 4 (2010). https://doi.org/10.1186/1753-4631-4-4

Sharma, S. R., Gonda, X., & Tarazi, F. I. (2018). Autism Spectrum Disorder: Classification, diagnosis and therapy. Pharmacology & therapeutics, 190, 91–104. https://doi.org/10.1016/j.pharmthera.2018.05.007

Sheikhani, A., Behnam, H., Mohammadi, M.R. et al. Detection of Abnormalities for Diagnosing of Children with Autism Disorders Using of Quantitative Electroencephalography Analysis. J Med Syst 36, 957–963 (2012). https://doi.org/10.1007/s10916-010-9560-6

Wang, L., Wang, B., Wu, C., Wang, J., & Sun, M. (2023). Autism Spectrum Disorder: Neurodevelopmental Risk Factors, Biological Mechanism, and Precision Therapy. International journal of molecular sciences, 24(3), 1819. https://doi.org/10.3390/ijms24031819

Palavras Chave

Autism Spectrum Disorders; Quantitative; Electroencephalography