Inteligencia Artificial aplicada a la Planificación Preoperatoria de la Reconstrucción Mamaria Autóloga: Revisión Sistemática
Resumen
Se realizó una revisión sistemática para sintetizar la evidencia clínica sobre las aplicaciones de inteligencia artificial (IA) en reconstrucción mamaria, con énfasis en la planificación preoperatoria de colgajos autólogos. Se siguieron las recomendaciones PRISMA 2020 y se realizaron búsquedas en PubMed/MEDLINE, Scopus y Cochrane Library entre 2015 y 2026. Se incluyeron estudios originales con resultados cuantitativos y, debido a la heterogeneidad metodológica, se efectuó una síntesis narrativa. Se analizaron 16 estudios. En reconstrucción autóloga, los algoritmos de visión computacional y aprendizaje profundo permitieron automatizar el mapeo vascular, reducir el tiempo de análisis y obtener mediciones anatómicas reproducibles, aunque persistieron limitaciones en vasos de pequeño calibre. Los modelos pronósticos mostraron un rendimiento variable para falla de colgajo, complicaciones y resultados reportados por las pacientes. Las redes neuronales aplicadas a evaluación estética alcanzaron alta precisión, mientras que los modelos de lenguaje mostraron utilidad en educación y apoyo a decisiones estructuradas. No se identificó evidencia prospectiva multicéntrica que demostrara reducción de necrosis, pérdida del colgajo o reintervenciones. La IA muestra utilidad como herramienta complementaria, pero aún requiere validación externa y estudios clínicos prospectivos antes de su incorporación rutinaria.
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Derechos de autor 2026 Mateo José González Dávila , Santiago David Dutan Amay, Diego Xavier Gutiérrez Ramón, María José Arévalo Abad, Diego Alejandro Espinoza Marin
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
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