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Más allá de la norma: explorando las diversas facetas de las lesiones suprarrenales
Sadaf Afif1, Zoya Mahmood2, Atif Zaheer3
1Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Touro College of Osteopathic Medicine, New York City New York, USA.
Current problems in diagnostic radiology
|August 28, 2025
Resumen
El diagnóstico de las lesiones suprarrenales es difícil debido a las características superpuestas. La inteligencia artificial en CT y MRI muestra promesa para la caracterización precisa, reduciendo potencialmente el diagnóstico erróneo y las intervenciones innecesarias.
Área de la Ciencia:
- Radiología
- Imágenes médicas
- La inteligencia artificial en la medicina
Sus antecedentes:
- El diagnóstico de la lesión suprarrenal es un desafío debido a la superposición de características de imagen benignas y malignas.
- La caracterización precisa es crucial para evitar procedimientos de diagnóstico e intervenciones innecesarias.
- El subdiagnóstico y el diagnóstico erróneo de las lesiones suprarrenales presentan riesgos clínicos significativos.
Objetivo del estudio:
- Proporcionar una visión global de las características de las imágenes para lesiones suprarrenales comunes y raras.
- Explorar el papel emergente de la inteligencia artificial (IA) en el análisis de la TC y la RM para las lesiones suprarrenales.
- Evaluar el potencial de la IA para diferenciar las lesiones benignas de las malignas y las funcionales de las no funcionales.
Principales métodos:
- Revisión de las características típicas, atípicas y superpuestas de las lesiones suprarrenales.
- Exploración de las técnicas actuales y emergentes de análisis de imágenes basadas en IA para TC y RM.
- Síntesis de la evidencia con respecto a la precisión diagnóstica de la IA en la caracterización de las lesiones suprarrenales.
Principales resultados:
- Las lesiones suprarrenales presentan diversas características de imagen, a menudo con superposición de características.
- El análisis de la inteligencia artificial de la TC y la RM demuestra el potencial de una alta precisión diagnóstica.
- La IA puede mejorar significativamente la distinción entre lesiones suprarrenales benignas/malignas y funcionales/no funcionales.
Conclusiones:
- El diagnóstico radiológico preciso de las lesiones suprarrenales sigue siendo un desafío.
- El análisis de TC y RM impulsado por IA ofrece un enfoque prometedor para mejorar la confianza en el diagnóstico.
- La IA tiene el potencial de reducir las intervenciones innecesarias al mejorar la caracterización de las lesiones suprarrenales.
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