Clinical Scores, Biomarkers and IT Tools in Lung Cancer Screening-Can an Integrated Approach Overcome Current...

Area of Science:

• Pulmonology
• Radiology
• Oncology

Background:

• Lung cancer (LC) is often diagnosed at advanced, incurable stages.
• Early detection via low-dose computed tomography (LDCT) screening is crucial for improving patient outcomes.
• Current screening protocols have limitations in candidate selection and pulmonary nodule (PN) management.

Purpose of the Study:

• To review current advancements in lung cancer screening.
• To explore improvements in candidate selection, screening technology, and PN malignancy evaluation.
• To present an integrated approach for safer lung cancer screening decisions.

Main Methods:

• Scoping review of literature on lung cancer screening.
• Assessment of candidate selection criteria and potential refinements.
• Evaluation of IT tools for augmenting CT scan reading accuracy.
• Analysis of semi-automatic volume measurements for PN follow-up.
• Presentation of an integrative approach for PN malignancy probability assessment.

Main Results:

• Current eligibility criteria for LDCT screening have limitations.
• IT tools can enhance radiologist accuracy and manage workload during screening.
• Semi-automatic PN volume measurement improves follow-up scan precision.
• An integrated approach combining clinical risk, imaging, and biomarkers can improve PN malignancy evaluation.

Conclusions:

• Integration of clinical risk models, advanced imaging, and biomarker research can enhance lung cancer screening performance.
• Further validation studies are needed for innovative diagnostic approaches.
• Improved candidate selection and PN management are key to optimizing lung cancer screening.