Low-dose computed tomography (LDCT) is used in individuals at high risk of developing lung cancer (smokers over 50 years of age), as it allows for the identification of pulmonary nodules, which, in a small percentage of cases, may represent early-stage lung cancer. However, according to LUNG-RADS guidelines, individuals undergoing screening must repeat multiple LDCT scans, as the comparison between successive LDCT scans enables the assessment of existing nodules' progression and the identification of newly developed pulmonary nodules. This results in cumulative exposure to ionizing radiation, increasing the risk of radiation-induced cancers.
This study addresses, through the implementation of new imaging techniques utilizing the latest and most advanced technological innovation (high-field 3T Magnetic Resonance Imaging (MRI) with artificial intelligence), the critical challenge of reducing radiation exposure in current LDCT-based screening programs, proposing the use of MRI as an alternative screening method to LDCT.