Consumer-grade electroencephalography devices as potential tools for early detection of brain tumors

Emily So,Nardin Samuel,Ugljesa Djuric,Phedias Diamandis

doi:10.1186/s12916-020-01889-z

Abstract

Consumer-grade electroencephalography devices as potential tools for early detection of brain tumors

Highlights

Diffuse gliomas, such as glioblastoma (GBM), represent the most common and aggressive form of brain cancer with an unfortunate dearth of treatment advances despite decades of ongoing research [1]
The aggressive biology and low incidence of gliomas make them poor candidates for conventional screening strategies
While the role of early detection in the management of brain tumors is still unclear, recent innovations in personal brain wearables, artificial intelligence, and evidence for the benefits of aggressive surgery offer new opportunities to refine our clinical approach to these challenging clinical entities

Summary

Background

Diffuse gliomas, such as glioblastoma (GBM), represent the most common and aggressive form of brain cancer with an unfortunate dearth of treatment advances despite decades of ongoing research [1]. If gliomas could be detected earlier in their evolution, while remaining potentially more localized, it could offer the possibility to better maximize the extent of safe surgical resection and favorable outcomes Despite this prospect, the aggressive biology and low incidence of gliomas make them poor candidates for conventional screening strategies. The amount and timing of daily wear needed to detect subtle baseline changes would need optimization and balance with enthusiasm to wear such devices Despite these current unknowns, rapid and widespread acceptance of other smart wearables offers encouraging insights. Like any screening tool, a beneficial balance between sensitivity and specificity, along with proven beneficial outcomes following early detection and treatment, will still need to be formally demonstrated [7] The ability of these devices to provide continuous longitudinal and personalized data, along with the advent of modern deep learning computational tools, could provide new solutions for the early detection and differentiation of various nervous system pathologies. Deployment of these devices to existing brain tumor patients could help monitor disease recurrence and understand treatmentrelated neurocognitive sequalae

Conclusions

Not applicable

Consent for publication Not applicable