Porównanie możliwości detekcji i stymulacji w implantowanych systemach neurostymulacji z zamkniętą pętlą zwrotną stosowanych w leczeniu epilepsji
Device-level comparisons of sensing and stimulation in implantable closed-loop neurostimulation for epilepsy
W skrócie
Badanie porównuje siedem systemów medycznych (cztery już zatwierdzone i trzy eksperymentalne), które mogą być wszczepianie pacjentom z oporną na leki epilepsją. Systemy te działają na zasadzie wykrywania nieprawidłowych wyładowań mózgu i automatycznego podawania elektrostymulacji tylko wtedy, gdy jest potrzebna. Główne różnice między systemami dotyczą sposobu rejestrowania sygnałów z mózgu, możliwości jednoczesnego nagrywania i stymulowania, oraz sposobu usuwania zakłóceń, a potrzebne są jeszcze dodatkowe badania potwierdzające skuteczność tych urządzeń specjalnie w epilepsji.
Oryginalny abstract (angielski)
Drug-resistant epilepsy affects roughly one-third of people with epilepsy, and options remain limited for patients whose seizures arise from eloquent cortex, involve multiple foci, or persist after prior surgery. For these patients, closed-loop neurostimulation offers a nondestructive and adjustable alternative that detects pathological activity and delivers stimulation only when and where it is needed. The NeuroPace responsive neurostimulation (RNS) System, approved in 2013, remains the most established clinical example: it senses at the therapeutic target, drives stimulation from biomarkers recorded there, and stores raw neural signals for iterative programming. These same principles increasingly define a newer generation of adaptive deep brain stimulation (DBS) platforms developed largely for movement disorders, motivating a direct, device-level comparison of contemporary implantable closed-loop systems for epilepsy. We compare four clinically approved systems in depth (the NeuroPace RNS, Medtronic Percept PC, Newronika AlphaDBS, and PINS G106RS) together with three investigational platforms (the Picostim-DyNeuMo, CorTec Brain Interchange, and Cadence Neuroscience system), examining sensing architecture, artifact management, bandwidth, onboard data handling, stimulation-source design, and degree of autonomous control, and summarizing their relative capabilities across a common set of scored dimensions. Across platforms, the most consequential differences arise less from stimulation parameter ranges than from sensing design: which contacts can record, whether sensing can continue during stimulation, what frequency range is accessible, how stimulation artifact is suppressed, and whether raw waveforms or only derived features are retained. Because much of the sensing and adaptive-control evidence for the DBS platforms derives from movement-disorder rather than epilepsy applications, we interpret their epilepsy relevance conservatively and highlight where epilepsy-specific validation is still needed.