¿Puede la IA identificar el cáncer de pulmón en etapa temprana a partir de biomarcadores en el aliento usando narices electrónicas portátiles ?

Ciertos compuestos orgánicos volátiles en el aliento exhalado cambian en presencia de cáncer de pulmón en etapa temprana, incluso antes de que las imágenes detecten tumores. Las narices electrónicas con IA podrían analizar muestras de aliento en clínicas o farmacias. Esto podría reducir la dependencia de biopsias invasivas y tomografías computarizadas. Sin embargo, factores ambientales como el tabaquismo o la contaminación del aire pueden confundir los resultados.

Background

Researchers have demonstrated that portable electronic noses (e-noses) can detect volatile organic compounds (VOCs) in exhaled breath with promising sensitivity and specificity for early-stage lung cancer screening. A 2022 meta-analysis reported pooled sensitivity of about 85% and specificity of 87% across multiple studies using machine-learning models trained on breath-chemistry data. Certain volatile organic compounds in exhaled breath change in presence of early lung cancer, even before imaging detects tumors, and AI-powered e-noses could analyze breath samples in clinics or pharmacies, reducing reliance on invasive diagnostics. However, environmental factors like smoking or air pollution may confound results. Furthermore, real-world deployment faces challenges such as sensor drift, environmental confounders like smoking or diet, and the need for larger, multi-center validation cohorts. Regulatory approval remains limited to a few devices with narrow indications, underscoring the gap between promising research and routine clinical use.