Determining the clinical utility of BioEP: a multisite, prospective, study

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Our proposal is focussed on Epilepsy: a serious neurological condition. Epilepsy is characterised by the tendency to have repeated, spontaneous, seizures. Since seizures occur seemingly at random, epilepsy diagnosis is very challenging. The electroencephalogram (EEG) is an important clinical tool for revealing abnormalities that indicate epilepsy. However, around 70% of recorded EEGs provide no clinical indication of epilepsy. Consequently, diagnostic delays regularly exceed a year and the rate of misdiagnosis is estimated at 30%. The cost of this misdiagnosis has been estimated at over £300M annually to the NHS.To address this challenge, Neuronostics have developed a computer Biomarker ofEpilepsy: BioEP. BioEP works by integrating routinely acquired EEG into a computer model of the brain. Simulations of this model, interrogated using advanced machine learning algorithms, provide a risk score showing how easy it is for seizures to occur. For EEGs currently considered clinically non-contributory, the BioEP risk score provides valuable additional diagnostic information. Research underpinning BioEP has been recognised by the Lancet Neurology (as a breakthrough study in epilepsy in 2015), the Epilepsy Foundation (through a commercialisation prize in 2017) and Nature (Neuronostics was one of the final four in the SpinOff Prize 2021).Through Innovate UK and NIHR funding, Neuronostics have developed a prototype of a diagnostic decision support tool powered by BioEP, that enables semi-automated feature extraction and report writing. Neuronostics have recently completed a retrospective study (using data from people with a known and accurate diagnosis) to validate the performance of the BioEP. The largest study of its kind, we demonstrated that BioEP can reveal susceptibility to epilepsy in apparently normal EEGs at a level that out performs current clinical practice.In the current project, we will undertake a prospective study to demonstrate the clinical utility of the BioEP risk score. We will conduct a multi-site study where people with suspected epilepsy will go through the normal care pathway, but in half the cases we will additionally provide the BioEP risk score. We will compare the time to working diagnosis, the types of diagnosis made, and the confidence of the clinician in the decision made in each arm. This will enable us to understand the impact BioEP has on the key clinical outcomes of time to diagnosis, accuracy and objectivity of decision making, as well as confidence in the decision reached.