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Modelos completamente individualizados para la propagación de tau basada en redes transversal y longitudinal

Christopher A Brown1, Sandhitsu R Das1, John A Detre1,2

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Imaging neuroscience (Cambridge, Mass.)
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Los modelos individualizados de conectividad cerebral predicen con precisión la propagación regional de tau en la enfermedad de Alzheimer. Este enfoque basado en redes ofrece una herramienta poderosa para comprender la heterogeneidad de la patología tau y la progresión de la enfermedad.

Palabras clave:
Enfermedad de AlzheimerRM de difusiónheterogeneidadconectividad estructuralPET tau

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Área de la Ciencia:

  • Neuroimagen
  • Neurología
  • Biofísica

Sus antecedentes:

  • La carga regional de tau exhibe heterogeneidad, lo que complica la evaluación de la progresión de la enfermedad.
  • Los estudios existentes de tomografía por emisión de positrones (PET) de tau vinculan la conectividad con los epicentros de la patología tau, pero carecen de individualización.
  • Los conectomas y epicentros basados en la población son insuficientes para una predicción precisa de la carga de tau.

Objetivo del estudio:

  • Desarrollar y validar modelos completamente individualizados para predecir la carga regional de tau utilizando conectomas estructurales y epicentros individualizados.
  • Evaluar el poder predictivo transversal y longitudinal de estos modelos individualizados.

Principales métodos:

  • Se utilizaron conectomas estructurales derivados de RM de difusión y epicentros de patología tau individualizados.
  • Se modeló la predicción de la carga de tau en función de la distancia a lo largo de los conectomas estructurales individuales desde epicentros individualizados.
  • Se evaluaron los modelos de forma transversal y longitudinal, incluidos los conjuntos de datos de validación.

Principales resultados:

  • Los modelos completamente individualizados superaron significativamente a los modelos basados en la población para explicar la carga regional de tau.
  • Los modelos individualizados demostraron una precisión de predicción mejorada en los conjuntos de datos de validación.
  • Se logró una predicción más sólida a nivel de sujeto único de la carga de tau.

Conclusiones:

  • Un enfoque completamente individualizado explica eficazmente la heterogeneidad regional de tau.
  • Los hallazgos proporcionan una sólida evidencia in vivo de la propagación de la patología tau basada en redes.
  • Este método mejora la comprensión de la progresión de la enfermedad de Alzheimer y la dinámica de redes.