[Lung cancer screening: new frontiers].

Area of Science:

• Oncology
• Radiology
• Public Health

Background:

• Lung cancer is a leading cause of cancer death globally.
• Early detection is crucial for curative treatment, but often missed.
• Low-dose computed tomography (LDCT) aids early lung cancer detection and reduces mortality.

Purpose of the Study:

• To evaluate the effectiveness of lung cancer screening (LCS) using LDCT.
• To assess the role of artificial intelligence (AI) in analyzing LDCT scans.
• To support the recommendation for a structured LCS program in Germany.

Main Methods:

• Meta-analysis of eight LCS studies.
• Application of AI algorithms for precise LDCT scan analysis.
• Review of evidence for structured LCS program implementation.

Main Results:

• A statistically significant 12% relative reduction in lung cancer mortality was observed.
• AI enables more precise analysis of LDCT scans.
• Strong scientific evidence supports LCS recommendations for high-risk populations.

Conclusions:

• A holistic LCS program requires clear high-risk population definition and individual risk assessment.
• Qualified personnel, verification of diagnostic/therapeutic steps, and central quality assurance are essential.
• Integration of tobacco cessation programs is a key component of the LCS program.