Intraoperative use of high-speed Raman spectroscopy during soft tissue sarcoma resection

Area of Science:

• Oncology
• Medical Spectroscopy
• Surgical Technology

Background:

• Retroperitoneal soft tissue sarcoma (RSTS) is a rare malignancy with limited therapeutic strategies.
• Complete surgical resection with negative margins is crucial for RSTS patient survival.
• Existing imaging techniques for intraoperative margin assessment can be time-consuming.

Purpose of the Study:

• To evaluate the performance of the handheld UltraProbe Raman spectroscopy system for in vivo detection of soft tissue sarcoma (STS) during surgical resection.
• To assess the accuracy of the UltraProbe in differentiating STS from healthy tissues in real-time.
• To determine the potential of UltraProbe-assisted surgery in improving RSTS resection outcomes.

Main Methods:

• Thirty patients undergoing STS resection were enrolled.
• Raman spectra were collected intraoperatively using the UltraProbe system.
• A machine learning random forest algorithm classified spectra as STS or healthy tissue.

Main Results:

• The UltraProbe achieved high accuracy in classifying well-differentiated liposarcomas versus normal adipose tissue (94% accuracy).
• Classification of well-differentiated and dedifferentiated liposarcomas against normal adipose tissue yielded 90% accuracy.
• Detection of non-liposarcoma STS versus protein-rich non-adipose tissue showed 87% accuracy.

Conclusions:

• The UltraProbe demonstrates significant potential as an effective tool for real-time intraoperative margin assessment in STS surgery.
• This Raman spectroscopy system can aid surgeons in achieving complete tumor resection, potentially improving patient outcomes.
• The UltraProbe offers a faster alternative to current probe systems, reducing surgical time.