Aim
We describe the application of fiber-based attenuated total reflection infrared (ATR IR) spectroscopy for label-free discrimination of normal pancreatic, tumorous, and pancreatitis tissue. A pilot study for the intraoperative application was performed. Approach: The method was applied for unprocessed freshly resected tissue samples of 58 patients, and a classification model for differentiating between the distinct tissue classes was established.
Conclusion
Our study shows the possibility of applying fiber-based ATR IR spectroscopy in combination with a supervised classification model for rapid pancreatic tissue identification with a high potential for transfer into intraoperative surgical diagnostics.
Results
The developed three-class classification model for tissue spectra allows for the delineation of tumors from normal and pancreatitis tissues using a probability score for class assignment. Subsequently, the method was translated into intraoperative application. Fiber optic ATR IR spectra were obtained from freshly resected pancreatic tissue directly in the operating room.
Significance
Pancreatic surgery is a highly demanding and routinely applied procedure for the treatment of several pancreatic lesions. The outcome of patients with malignant entities crucially depends on the margin resection status of the tumor. Frozen section analysis for intraoperative evaluation of tissue is still time consuming and laborious. Aim: We describe the application of fiber-based attenuated total reflection infrared (ATR IR) spectroscopy for label-free discrimination of normal pancreatic, tumorous, and pancreatitis tissue. A pilot study for the intraoperative application was performed. Approach: The method was applied for unprocessed freshly resected tissue samples of 58 patients, and a classification model for differentiating between the distinct tissue classes was established. Results: The developed three-class classification model for tissue spectra allows for the delineation of tumors from normal and pancreatitis tissues using a probability score for class assignment. Subsequently, the method was translated into intraoperative application. Fiber optic ATR IR spectra were obtained from freshly resected pancreatic tissue directly in the operating room. Conclusion: Our study shows the possibility of applying fiber-based ATR IR spectroscopy in combination with a supervised classification model for rapid pancreatic tissue identification with a high potential for transfer into intraoperative surgical diagnostics.