MRI-Based Artificial Intelligence in Rectal Cancer

Area of Science:

• Medical Imaging
• Artificial Intelligence
• Oncology

Background:

• Rectal cancer (RC) is a significant part of colorectal cancer (CRC), with rising mortality in younger populations.
• Current MRI semantic features are insufficient for guiding treatment decisions.
• Functional MRI has limitations in repeatability and reproducibility.

Purpose of the Study:

• To review the advancements of Artificial Intelligence (AI) in evaluating rectal cancer (RC) using Magnetic Resonance Imaging (MRI).
• To highlight AI's role in improving diagnosis, treatment strategies, and patient outcomes for RC.
• To identify future research directions for AI in RC clinical applications.

Main Methods:

• Review of current research on AI applications in RC based on MRI data.
• Analysis of AI's role in staging, risk prediction, genotyping, therapy response, recurrence, metastasis, and segmentation.
• Discussion of challenges and future directions for clinical AI implementation.

Main Results:

• AI demonstrates significant potential in various aspects of RC evaluation, including staging and predicting treatment response.
• AI-powered MRI analysis can provide novel noninvasive imaging markers for personalized RC management.
• AI facilitates a more comprehensive understanding of tumor characteristics for individualized diagnosis and treatment.

Conclusions:

• AI integrated with MRI offers promising tools for enhancing rectal cancer evaluation and management.
• Further research is needed to address challenges in imaging, model performance, and biological interpretation for widespread clinical adoption.
• AI is poised to revolutionize personalized diagnosis and treatment strategies for rectal cancer patients.