Advancement Of Detecting Epilepsy Concerning Biomarkers

Abstract

Recent advances in the detection of epilepsy using biomarkers have made significant improvements in diagnosis, treatment, and care. Key developments comprise genetic biomarkers, which demonstrate that improvements in genetic testing have found mutations associated to epilepsy, facilitating early diagnosis and tailored therapies, particularly in hereditary types such as Dravet syndrome. Neuroimaging methods such as high-resolution MRI, functional MRI, and magnetoencephalography provide more specific insights into brain disorders, assisting in seizure diagnosis and surgery planning. EEG represents the benchmark, but new machine learning algorithms use EEG data to detect minor biomarkers and anticipate seizures, allowing for prompt treatment. Metabolic and inflammation Seizure frequency and neuronal damage may be tracked using biomarkers present in cerebrospinal fluid and blood, such as neurofilament light chain and BDNF. Wearable technology and AI-powered algorithms are currently being researched to track biomarkers in real time, with the potential to identify seizures prior to they arise. Genetic information and biomarkers are directing the development of more tailored treatment approaches, maximizing anti-epileptic medication options depending on an individual's genetic profile. While many biomarkers currently remain in the research stage, their ability to enhance early diagnosis, tailor medications, and anticipate seizures bodes well for the coming years of epilepsy management.