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Handheld macroscopic Raman spectroscopy imaging instrument for machine-learning-based molecular tissue margins
François Daoust1,2, Tien Nguyen1,2, Patrick Orsini3
1Polytechnique Montreal, Department of Engineering Physics, Montreal, Quebec, Canada.
Journal of Biomedical Optics
|February 13, 2021
Summary
A new handheld Raman imaging system offers rapid, large field-of-view (FOV) tissue margin detection for cancer surgery. This technology achieved 99% accuracy in distinguishing tissue types, aiding tumor resection.
Area of Science:
- Biomedical Optics
- Surgical Technology
- Molecular Spectroscopy
Background:
- Raman spectroscopy aids surgical guidance by detecting molecular changes in tissue during tumor resection.
- Current systems offer limited fields of view (FOVs), hindering rapid intraoperative cancer margin assessment.
Purpose of the Study:
- To design and evaluate a handheld macroscopic Raman imaging system for in vivo tissue margin characterization.
Main Methods:
- A sterilizable line scanner with fiber optics relayed excitation light (785-nm laser) and hyperspectral Raman signal detection.
- Machine learning classifiers were trained and validated on porcine adipose and muscle tissue.
Main Results:
- The system achieved 99% accuracy in distinguishing porcine adipose from muscle tissue ex vivo.
- Detection was performed over a 95 mm² FOV within approximately 3 minutes.
Conclusions:
- This is the first large FOV Raman imaging system designed for surgical cancer resection workflows.
- Future development aims to discriminate brain tumors during glioma surgery within clinical timeframes.
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