L'IA può identificare il cancro del polmone in fase iniziale tramite biomarcatori del respiro utilizzando nasi elettronici portatili ?

Certi composti organici volatili nell'aria espirata cambiano in presenza di un tumore polmonare precoce, anche prima che le tecniche di imaging rilevino masse tumorali. Nasi elettronici basati su intelligenza artificiale potrebbero analizzare campioni di respiro in cliniche o farmacie. Questo potrebbe ridurre l'affidamento su biopsie invasive e TAC. Tuttavia, fattori ambientali come il fumo o l'inquinamento atmosferico potrebbero confondere i risultati.

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.