'Lab-on-a-Scalpel' Provides Real-Time Surgical Insights for POC Diagnostics in OR

During surgery, waiting for laboratory test results can slow critical decision-making, especially in emergency or oncological procedures. Now, researchers have introduced a new diagnostic concept: a surgical tool that can detect key biochemical signals in real time. This early-stage “Lab-on-a-Scalpel” platform integrates an electrochemical sensor directly into a surgical instrument, offering the potential for in-operation metabolic monitoring.

The technology was developed by researchers at the University of Chemistry and Technology, Prague (Prague, Czech Republic) using standard 3D printing hardware and materials, incorporating carbon nanomaterials into the printed plastic to create a functional sensing interface. The system works by embedding the electrochemical sensor within the scalpel handle itself.

During the printing process, conductive carbon nanomaterials are fused into the polymer structure, allowing the sensor to detect very low concentrations of specific analytes. The sensor can be tuned for different targets depending on pH and environmental conditions, such as buffer solutions. Under laboratory testing, it successfully detected selected metabolites linked to stress responses.

Although still in the conceptual and laboratory-validation stage, the tool suggests a range of future possibilities. If further developed, it could detect metabolites during surgery or biopsy, monitor ions and pH directly in tissue, and provide rapid biochemical feedback during time-critical procedures. This approach demonstrates that functional diagnostic sensors can be integrated into surgical instruments using commonly available 3D-printing platforms.

Practical applications could eventually include faster intraoperative decision-making, enhanced precision in cancer surgeries, and reduced reliance on external laboratory processing. The work, presented in ACS Analytical Chemistry, illustrates how nanomaterials and accessible printing technologies may drive the next generation of point-of-care diagnostic tools.

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