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Updated: Jun 17, 2025
Intraoperative Assessment of Resection Margins in Oral Cavity Cancer: This is the Way
Published on: May 10, 2021
Intraoperative margin assessment with near real time pathology during partial gland ablation of prostate cancer: A
Miles P Mannas1, Fang-Ming Deng2, Adrian Ion-Margineanu3
1Dept. of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada; Vancouver Prostate Centre, University of British Columbia, Vancouver, British Columbia, Canada; Dept. of Urology, NYU Langone Health, New York, NY.
Background:
In-field or in-margin recurrence after partial gland cryosurgical ablation (PGCA) of prostate cancer (PCa) remains a limitation of the paradigm. Stimulated Raman histology (SRH) is a novel microscopic technique allowing real time, label-free, high-resolution microscopic images of unprocessed, un-sectioned tissue which can be interpreted by humans or artificial intelligence (AI). We evaluated surgical team and AI interpretation of SRH for real-time pathologic feedback in the planning and treatment of PCa with PGCA.
Methods:
About 12 participants underwent prostate mapping biopsies during PGCA of their PCa between January and June 2022. Prostate biopsies were immediately scanned in a SRH microscope at 20 microns depth using 2 Raman shifts to create SRH images which were interpreted by the surgical team intraoperatively to guide PGCA, and retrospectively assessed by AI. The cores were then processed, hematoxylin and eosin stained as per normal pathologic protocols and used for ground truth pathologic assessment.
Results:
Surgical team interpretation of SRH intraoperatively revealed 98.1% accuracy, 100% sensitivity, 97.3% specificity for identification of PCa, while AI showed a 97.9% accuracy, 100% sensitivity and 97.5% specificity for identification of clinically significant PCa. 3 participants' PGCA treatments were modified after SRH visualized PCa adjacent to an expected MRI predicted tumor margin or at an untreated cryosurgical margin.
Conclusion:
SRH allows for accurate rapid identification of PCa in PB by a surgical team interpretation or AI. PCa tumor mapping and margin assessment during PGCA appears to be feasible and accurate. Further studies evaluating impact on clinical outcomes are warranted.
