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Artificial Intelligence-Driven Platform: Unveiling Critical Hepatic Molecular Alterations in Hepatocellular Carcinoma
Miao Jiang1, Pengyun Wu2, Yuwei Zhang3
1School of Medical Imaging, Tianjin Medical University, Tianjin, 300203, China.
Advanced Healthcare Materials
|April 24, 2024
Summary
Researchers developed an AI-powered system for Hepatocellular Carcinoma (HCC) diagnosis. This novel approach uses computed tomography and Surface-enhanced Raman scattering to identify molecular changes, achieving 91.38% accuracy in detecting liver cancer.
Area of Science:
- Biomedical Engineering
- Oncology
- Artificial Intelligence
Background:
- Hepatocellular Carcinoma (HCC) development is linked to long-term liver damage and specific hepatic molecular characteristics.
- Accurate HCC diagnosis requires understanding tumor location, morphology, and molecular alterations.
- Current diagnostic technologies often lack the capability for concurrent HCC diagnosis and molecular profiling.
Purpose of the Study:
- To develop an integrated information system for pathological-level diagnosis of HCC.
- To reveal critical molecular alterations in the liver associated with HCC.
- To establish connections between HCC occurrence and hepatic biomolecule alterations using AI.
Main Methods:
- Integration of computed tomography (CT) and Surface-enhanced Raman scattering (SERS).
- Application of an artificial intelligence (AI) strategy for data analysis.
- Classification of SERS spectra from healthy and HCC patient groups.
Main Results:
- The AI system successfully classified healthy and HCC groups with 91.38% accuracy.
- Molecular profiling identified the nucleotide-to-lipid signal ratio as a potential indicator for HCC.
- Demonstrated the system's capability for pathological-level diagnosis and molecular alteration revelation.
Conclusions:
- The developed integrated system offers precise HCC diagnosis and identifies key molecular changes.
- The nucleotide-to-lipid signal ratio shows promise as a biomarker for HCC surveillance.
- This AI-driven approach provides a valuable tool for HCC prevention and therapeutic monitoring.
