Caracterización beta, gamma y de oscilaciones de alta frecuencia para localización de diana en procedimientos de Estimulación Cerebral Profunda

Palabras clave: Estimulación Cerebral Profunda, registro con micro-electrodos, procesamiento de señales biomédicas, enfermedad de Párkinson, núcleo subtalámico

Resumen

La estimulación cerebral profunda (DBS por sus siglas en inglés) ha sido usada exitosamente en el tratamiento de pacientes con enfermedad de Párkinson. La DBS tiene un electrodo que regula la actividad oscilatoria de los ganglios basales involucrados, como el núcleo subtalámico (STN). Un aspecto crítico en el implante de dicho electrodo es la localización precisa de la diana quirúrgica. Esta se realiza mediante imágenes pre-quirúrgicas, marcos estereotácticos y registros de micro-electrodos (MER). Este último permite visualizar la actividad eléctrica de diferentes estructuras a través del recorrido quirúrgico, cada una de ellas con un patrón de variaciones bien definidas en frecuencia; sin embargo, esto dista de ser un método automático o semi-automático que ayude al neurofisiólogo a tomar decisiones en cuanto a la diana quirúrgica. Con el ánimo de contribuir a la automatización, analizamos tres bandas de frecuencias de señales MER adquiridas en 11 pacientes sometidos a DBS: beta (13-40 Hz), gamma (40-200 Hz) y oscilaciones de alta frecuencia (HFO – 201-400 Hz). Se propusieron y evaluaron 5 índices para detectar el STN: variaciones de parámetros auto-regresivos y su derivada a lo largo del recorrido quirúrgico, la energía de cada banda a partir de la densidad espectral de potencia mediante el método de Yule-Walker, la relación de frecuencias altas a bajas y su derivada. Encontramos que la derivada de un parámetro de la banda beta y la relación alta-bajas de las bandas HFO/gamma alcanzaron errores en la localización del STN, similares a los reportados en la literatura (<2mm). Aunque los índices propuestos son sencillos de calcular y de fácil implementación en tiempo real, se deben seguir explorando para incrementar la capacidad de generalización de los resultados obtenidos.

Biografía del autor/a

Sarah Valderrama-Hincapié, Universidad de Antioquia, Colombia

Bioeng., Research Group Bioinstrumentation and Clinical Engineering (GIBIC), Universidad de Antioquia, Medellín-Colombia, saraheh1022@gmail.com

Sebastián Roldán-Vasco*, Instituto Tecnológico Metropolitano, Colombia

MSc. Engineer, Research Groups in Advanced Materials and Energy (MATyER), Instituto Tecnológico Metropolitano, Medellín-Colombia, sebastianroldan@itm.edu.co

Sebastián Restrepo-Agudelo, Instituto Tecnológico Metropolitano, Colombia

MSc. Automation and Industrial Control, Research Groups in Advanced Materials and Energy (MATyER), Instituto Tecnológico Metropolitano, Medellín-Colombia, sebastianrestrepo@itm.edu.co

Frank Sánchez-Restrepo, Universidad de Antioquia, Colombia

Bioeng., Research Group Bioinstrumentation and Clinical Engineering (GIBIC), Universidad de Antioquia, Medellín-Colombia, frank.sanchezr@udea.edu.co

William D. Hutchison, University of Toronto, Canadá

PhD. in Neuroscience, Division of Neurosurgery, Department of Surgery and Physiology, University of Toronto, Toronto- Canadá, whutch@uhnres.utoronto.ca

Adriana L. López-Ríos, Hospital Universitario San Vicente Fundación , Colombia

Neurosurgeon, Functional and Stereotactic Neurosurgeon, Neurosurgeon Oncologist and Skull Base, Hospital Universitario San Vicente Fundación (Medellín and Rionegro), Medellín – Colombia, adrilori@yahoo.com

Alher Mauricio Hernández, Universidad de Antioquia, Colombia

PhD. in Biomedical Engineer, Research Group Bioinstrumentation and Clinical Engineering (GIBIC), Universidad de Antioquia, Medellín- Colombia, alher.hernandez@udea.edu.co

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[1]
S. . Valderrama-Hincapié, «Caracterización beta, gamma y de oscilaciones de alta frecuencia para localización de diana en procedimientos de Estimulación Cerebral Profunda», TecnoL., vol. 23, n.º 49, pp. 11–32, sep. 2020.

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2020-09-15
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