Algunos estudios han demostrado como la IA puede disminuir la carga de trabajo en los programas de cribado hasta en un 70% sin reducir la sensibilidad, ayudando así a los radiólogos en la detección rápida y temprana.
El cáncer de mama supone un importante revés para sociedad española, especialmente teniendo en cuenta que es el segundo tumor más diagnosticado en territorio nacional solo por detrás del cáncer de colón. Así, según los últimos datos revelados por la Sociedad Española de Oncología Médica (SEOM), se estima que en 2022 alrededor de 35.000 mujeres serán diagnosticadas con la citada enfermedad. Unos números que se alinean con las cifras que baraja el Sistema Europeo de Información del Cáncer sobre la probabilidad de padecer este tipo de cáncer. En total, concluyen, una de cada ocho mujeres sufrirá la enfermedad, siendo las féminas con edades comprendidas entre los 45 y los 65 años quienes tienen mayores probabilidades de padecerlo. En este contexto, la prevención y el diagnóstico ocupan un papel protagonista.
Y es precisamente en la terea de detección donde los radiólogos han puesto en valor la ayuda que puede suponer la inteligencia artificial como apoyo en el cribado de este tipo de cáncer. La inteligencia artificial (IA) concede en este escenario una ayuda extra en la detección de un mayor número de tumores, un mejor pronóstico para el paciente y una apuesta en firme por el uso de tratamientos menos agresivos. Así, gracias al desarrollo de nuevos sistemas de IA con tecnología deep learning basados en el funcionamiento neurológico, la tecnología vuelve a ponerse al servicio de la salud brindándonos nuevas oportunidades.
Estos nuevos sistemas de inteligencia artificial han mejorado los algoritmos de los diagnósticos asistidos por ordenador que ayudan a los médicos en la interpretación de los contenidos multimedia que se obtienen en pruebas a las que se ha sometido el paciente. Así, a diferencia de los CAD tradicionales, los nuevos sistemas son capaces de detectar lesiones sospechosas de cáncer de mama asignándoles a las pruebas una puntuación en función de la probabilidad de malignidad. Además, pueden ser usados como apoyo a las lecturas del radiólogo haciendo más sencilla la tarea, consiguiendo una disminución de la demora, aumentando la detección de cáncer y disminuyendo los falsos positivos y negativos.
En esta misma línea cabe destacar que la inteligencia artificial también es capaz de clasificar las mamografías en función de la probabilidad de malignidad. Un avance que podría, incluso, disminuir la carga de trabajo en los programas de cribado hasta en un 70% sin reducir la sensibilidad. El sistema determina las lesiones sospechosas de malignidad, les asigna una puntuación del 1 al 100 en función de la probabilidad de malignidad y, luego, en función de la lesión, con la puntuación más alta clasifica el estudio completo en tres categorías: riesgo bajo, medio o elevado. Una forma avanzada de ayudar a los radiólogos en su tarea de ofrecer el mejor diagnóstico y tratamiento a sus pacientes.
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