Toward knowledge-based liver surgery: holistic information processing for surgical decision support.

Area of Science:

• Oncology
• Medical Informatics
• Decision Support Systems

Background:

• Liver cancer is a frequent global malignancy with diverse treatment options.
• Treatment selection for liver cancer is complex, depending on patient-specific factors and clinical data.
• Existing approaches often lack a unified system for integrating comprehensive patient and knowledge data.

Purpose of the Study:

• To present the first approach for liver cancer treatment strategy planning using a holistic data processing method.
• To integrate patient-individual data, practical case knowledge, and factual knowledge (guidelines, studies) for treatment planning.
• To develop a system supporting clinical decision-making in liver cancer therapy.

Main Methods:

• Development of a formalized dynamic patient model to integrate heterogeneous patient data throughout treatment.
• Creation of a concept for formalizing factual medical knowledge.
• Establishment of a technical infrastructure for storing, accessing, and processing diverse data.

Main Results:

• The patient model was instantiated for 184 patients, incorporating 602 parameters.
• 72 rules were formalized from studies on colorectal liver metastases and hepatocellular carcinoma.
• The system successfully derived an average of [Formula: see text] assertions per patient for a subset of 70 patients.

Conclusions:

• The proposed concept enables holistic treatment strategy planning for liver cancer.
• Joint storage and processing of heterogeneous data from multiple sources are facilitated.
• This approach supports improved clinical decision-making in liver cancer management.