Dados do Trabalho

Título

ADVANCED METHODS FOR EARLY DIAGNOSIS OF NEUROLOGICAL DISORDERS IN NEWBORNS

Introdução

The early diagnosis of neurological disorders in newborns is crucial for timely interventions that can significantly improve patient outcomes. Recent advancements in neuroimaging and automated movement analysis offer promising tools for detecting these conditions early.

Objetivo

This review evaluates advanced methods for the early diagnosis of neurological disorders in neonates, focusing on neuroimaging and video-based movement analysis.

Método

A systematic review was conducted using academic articles from scientific databases. Studies discussing advanced diagnostic techniques for neurological disorders in newborns, including magnetic resonance imaging (MRI), automated movement analysis, and deep learning applied to neuroimaging, were selected based on relevance, methodological quality, and timeliness.

Resultados

Neonatal MRI has proven essential for early diagnosis of brain anomalies. This technology identifies cerebellar malformations and other central nervous system anomalies, facilitating the diagnosis of specific neurological disorders. Additionally, deep learning applied to neonatal MRI enables the detection of subtle brain lesions not visible through traditional methods, enhancing diagnostic accuracy. Video-based automated movement analysis is another promising tool for diagnosing neurodevelopmental disorders early. Systems using computer vision and machine learning to monitor infant movements have shown effectiveness in identifying abnormal movement patterns associated with neurological disorders. These systems are non-invasive and efficient, suitable for clinical use, and allow for continuous and detailed monitoring of neonatal neurological development.

Conclusão

Advanced neuroimaging and automated movement analysis methods are revolutionizing the early diagnosis of neurological disorders in newborns. Neonatal MRI, combined with deep learning, provides early and precise detection of brain anomalies, while video-based movement analysis offers a non-invasive approach to monitor neurological development. These advancements are crucial for implementing early interventions that can significantly improve outcomes for newborns with neurological disorders. Future research should focus on validating and integrating these techniques into clinical practice.

Referências

1. Marco Leo, Giuseppe Massimo Bernava, Pierluigi Carcagnì, Cosimo Distante. Video-Based Automatic Baby Motion Analysis for Early Neurological Disorder Diagnosis: State of the Art and Future Directions. Sensors. 2022;22(3):866. doi:10.3390/s22030866.

2. Clinical and neuroimaging features as diagnostic guides in neonatal neurology diseases with cerebellar involvement. Cerebellum & Ataxias. Available from: https://cerebellumandataxias.biomedcentral.com/articles/10.1186/s40673-021-00145-0

3. Salih MA, Bosley TM, Alorainy IA, Sabry MA, Rashed MS, et al. Preimplantation genetic diagnosis in isolated sulfite oxidase deficiency. The Canadian Journal of Neurological Sciences. 2013;40(1):109-12. doi:10.1017/S031716710001330X.

4. Guan B, Dai C, Zhang Y, Zhu L, He X, Wang N, Liu H. Early diagnosis and outcome prediction of neonatal hypoxic-ischemic encephalopathy with color Doppler ultrasound. Diagn Interv Imaging. 2017;98(6):469-475. doi:10.1016/j.diii.2017.02.002.

Palavras Chave

Neuroimaging; Automated Movement Analysis; Early Diagnosis