Radiomics in Pulmonary Lesion Imaging

Area of Science:

• Medical Imaging
• Oncology
• Radiology

Background:

• Traditional lung cancer diagnosis relies on limited qualitative imaging characteristics.
• Radiomics extracts quantitative imaging features imperceptible to the human eye.
• These features hold potential for noninvasive cancer diagnosis, mutation identification, and prognosis prediction.

Purpose of the Study:

• To provide insights into current trends in lung cancer radiomics.
• To identify challenges hindering the widespread adoption of radiomics in clinical practice.

Main Methods:

• Extraction and analysis of quantitative radiomic features from diagnostic imaging.
• Review of current trends and challenges in lung cancer radiomics.

Main Results:

• Radiomics can identify additional imaging characteristics beyond visual assessment.
• Potential for accurate and noninvasive diagnosis, mutation identification, and prognosis prediction.
• Current studies are limited in scope and standardization across centers.

Conclusions:

• Radiomics shows promise for advancing lung cancer management.
• Standardization of application across centers and development of accessible tools are crucial.
• Increased multicenter studies and inclusion in resident training are recommended for broader adoption.