A label-free optical imaging technique using autofluorescence lifetime and AI can distinguish colorectal cancer with 85% accuracy.
Key Details
- 1Champalimaud Foundation researchers developed a fiber-optic, label-free optical imaging method for colorectal tissue analysis.
- 2Technique involves autofluorescence lifetime measurements at two wavelengths to capture biochemical differences.
- 3Machine learning (AdaBoost) trained on 117 patients' surgical specimens, validated with matched pathology results.
- 4On test data, the AI achieved 85% accuracy, 85% sensitivity, and 85% specificity.
- 5Potential applications include real-time cancer detection during colonoscopy or surgery, reducing the need for biopsies.
- 6Simplified versions of the imaging system delivered strong results, supporting future clinical use.
Why It Matters
Real-time, label-free optical imaging enhanced with AI could support faster, more accurate detection of cancer during endoscopic procedures, leading to earlier intervention and fewer unnecessary biopsies. This advances integration of functional imaging and AI in clinical workflows.
Source
EurekAlert
Related News
•EurekAlert
AI Accelerates Solid Tumor Drug Development and Personalized Oncology
AI is expediting the timeline and personalization of solid tumor drug development using multi-omics, imaging, and advanced computational models.
•EurekAlert
MAGIC AI System Enables High-Throughput Cancer Cell Imaging and Analysis
Researchers developed MAGIC, an AI-based system integrating automated microscopy and genomics to study chromosomal abnormalities linked to cancer.
•EurekAlert
Biodegradable Wearable Sensor with AI Enables Interference-Free Respiration Monitoring
Researchers developed a biodegradable, interference-resistant smart mask sensor with AI-driven respiratory classification capability.