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Un método optimizado de planificación basado en el conocimiento para la irradiación craneoespinal integrado con

Yihua Zhong1, Mingyuan Pan2, Jiyou Peng3

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Un flujo de trabajo automatizado para la irradiación craneoespinal (ICC) reduce significativamente el tiempo de planificación y mantiene la calidad clínica. Este enfoque impulsado por IA mejora la eficiencia para tratamientos complejos de cáncer.

Palabras clave:
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Área de la Ciencia:

  • Oncología de Radiación; Física Médica; Inteligencia Artificial en Medicina

Sus antecedentes:

  • La irradiación craneoespinal (ICC) es una técnica compleja de radioterapia que requiere una delineación precisa del objetivo y de los órganos.; La planificación tradicional de la ICC consume mucho tiempo y requiere mucha experiencia, lo que limita la eficiencia.; Las aplicaciones de IA en la planificación de la ICC se ven obstaculizadas por los desafíos de generalización y sensibilidad a los valores atípicos.

Objetivo del estudio:

  • Desarrollar y evaluar un flujo de trabajo automatizado para la planificación de la irradiación craneoespinal (ICC).; Integrar el autocontorneado de aprendizaje profundo y la planificación rápida mejorada por aprendizaje automático.; Evaluar las mejoras en eficiencia y calidad del plan del flujo de trabajo automatizado.

Principales métodos:

  • Se desarrolló un modelo de autocontorneado basado en DPNUNet entrenado con 91 pacientes de ICC.; Se integró el aprendizaje automático para el refinamiento iterativo de un modelo de planificación basado en el conocimiento (KBP).; Se compararon 20 planes rápidos automatizados (RP) con 20 planes manuales (MP) utilizando índices dosimétricos.

Principales resultados:

  • El modelo de autocontorneado logró coeficientes de Dice de 0,93 para PTV y >0,85 para OAR, reduciendo el tiempo de contorneado en un 75 % (de 1-2 horas a 10 minutos).; RapidPlan (RP) cumplió los objetivos clínicos y mejoró la protección de OAR pero tuvo puntos calientes de PTV y unidades de monitor más altos.; El flujo de trabajo automatizado redujo el tiempo total de contorneado y planificación en un 75 % (de 6-8 horas a 1 hora).

Conclusiones:

  • El marco propuesto impulsado por IA mejora significativamente la eficiencia en la planificación de la ICC.; Se mantiene la calidad del plan clínico y se logran importantes ahorros de tiempo.; El flujo de trabajo automatizado demuestra factibilidad para la planificación estandarizada de la irradiación craneoespinal.