Learning Objectives
Lung cancer remains the world’s most common cause of cancer death with 1.8 million deaths in the year 2020 worldwide. As lung cancer is mainly detected in a late-stage setting, there is an urgent need for early detection and hence, improved survival rates. Through a clear risk profile, a population subgroup prone to frequent occurrences of lung cancer can be identified, benefitting from a screening program. However, the necessary low-dose CT examinations for this demand additional resources in an increasingly strained healthcare system. Therefore, it is imperative to employ AI methods to simplify the detection of pulmonary nodules and enable direct volumetric evaluation. Yet, we must not lose sight of other medical conditions associated with the same risk factors. It is crucial to exclude or confirm coronary artery disease (CAD) in the acquired CT scans. Additionally, an assessment of osteoporosis risk should be undertaken, recognizing the holistic potential of AI in healthcare diagnostics.