Advancing Colorectal Cancer Diagnostics from Barium Enema to AI-Assisted Colonoscopy

Area of Science:

• Oncology
• Medical Imaging
• Artificial Intelligence

Background:

• Colorectal cancer (CRC) poses a significant global health challenge.
• Traditional CRC screening methods are being superseded by advanced diagnostics.
• Continuous innovation in diagnostic tools is crucial for effective CRC management.

Purpose of the Study:

• To review the evolution of colorectal cancer diagnostic tools.
• To compare conventional, endoscopic, liquid biopsy, and AI-assisted imaging techniques.
• To assess the clinical utility, cost-effectiveness, and integration of these methods.

Main Methods:

• Comprehensive literature search of PubMed, Medline, and Scopus databases.
• Inclusion of studies evaluating diagnostic accuracy, sensitivity, specificity, and clinical outcomes.
• Focus on endoscopic advancements, liquid biopsy, and AI-assisted imaging for CRC detection.

Main Results:

• AI-assisted colonoscopy shows higher adenoma detection rates (ADR) and reduced variability.
• AI colonoscopy offers a cost-effective alternative to liquid biopsy in high-volume settings.
• Liquid biopsy is valuable for surveillance but remains costly for initial screening.

Conclusions:

• The future of CRC diagnostics involves a hybrid model integrating AI endoscopy and liquid biopsy.
• This integrated approach promises to revolutionize early detection, risk stratification, and personalized treatment.
• Enhanced diagnostic precision and efficiency are expected to improve patient outcomes.