Current trends and emerging diagnostic techniques for lung cancer

Area of Science:

• Oncology
• Medical Diagnostics

Background:

• Lung cancer is a leading cause of mortality, often diagnosed late due to non-specific symptoms and misdiagnosis, particularly in regions like India where tuberculosis is prevalent.
• Risk factors include smoking, passive smoke inhalation, and environmental changes, contributing to high mortality rates.
• Late-stage diagnosis is a significant challenge, necessitating advanced detection and staging methods.

Purpose of the Study:

• To review current and emerging diagnostic techniques for lung cancer.
• To provide insights into novel tools such as biomarkers, biosensors, radiogenomics, and artificial intelligence.
• To discuss modifications in conventional methods and regulatory aspects of diagnostics.

Main Methods:

• Review of existing literature on lung cancer diagnostics.
• Focus on novel techniques including biomarkers, biosensors, radiogenomics, and artificial intelligence.
• Examination of enhanced conventional methods like CT-imaging, sputum cytology, biopsy, and bronchoscopy.

Main Results:

• Emerging diagnostic tools like biomarkers, biosensors, radiogenomics, and AI show promise for early and accurate lung cancer detection.
• Conventional methods (CT-imaging, cytology, biopsy, bronchoscopy) have been refined for improved sensitivity and accuracy.
• Regulatory frameworks (IDE, CLIA-certification) for diagnostic manufacturing and sales in key global markets are considered.

Conclusions:

• Advanced and modified conventional diagnostic techniques are crucial for improving lung cancer detection rates and patient outcomes.
• The integration of novel technologies like AI and biomarkers offers new avenues for combating lung cancer.
• Understanding regulatory provisions is essential for the global accessibility of lung cancer diagnostics.