Early Diagnosis of Lung Cancer: From Screening to Precision Biomarkers

This comprehensive book chapter explores the multifaceted landscape of early lung cancer detection, from traditional screening approaches to emerging precision technologies. It examines evidence-based screening programs and their real-world implementation challenges across diverse healthcare systems, including epidemiological perspectives and risk stratification models. It evaluates technological advances in imaging modalities, particularly focusing on low-dose CT optimization and artificial intelligence (AI)-augmented analysis. It presents the latest research on the potential of liquid biopsy and noninvasive biomarkers, including ctDNA and volatile organic compounds in exhaled breath, in early lung cancer diagnosis. AI applications in early lung cancer detection are thoroughly described, with a particular emphasis on the multifaceted integration of imaging, multiomics data, and clinical information to enhance detection accuracy. This chapter also includes a critical analysis of health economics, ethical considerations, and future directions toward personalized lung cancer screening paradigms that combine multiple diagnostic modalities. It provides a comprehensive framework for advancing early lung cancer detection strategies that balance clinical efficacy, cost-effectiveness, and patient-centered care.