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Feasibility of Diffuse Reflection Spectroscopy for Intraoperative Margin Assessment During Prostatectomy.
Lotte M de Roode1,2, Lisanne L de Boer2, Marcos Da Silva Guimaraes3
1Department of Nanobiophysics, University of Twente, Enschede, The Netherlands.
European Urology Open Science
|September 4, 2024
Summary
Diffuse reflectance spectroscopy (DRS) shows promise for real-time detection of positive surgical margins during robot-assisted radical prostatectomy. This technique can differentiate prostate cancer from benign tissue, aiding surgeons in achieving clear margins.
Area of Science:
- Biomedical optics
- Surgical oncology
- Medical device technology
Background:
- Positive surgical margins (PSM) complicate robot-assisted radical prostatectomy (RARP), occurring in up to 32% of cases.
- Diffuse reflectance spectroscopy (DRS) offers potential for real-time PSM detection by analyzing tissue optical properties.
Purpose of the Study:
- To evaluate the feasibility of using DRS to distinguish prostate cancer from benign tissue in RARP specimens.
- To develop and assess a machine learning algorithm for real-time PSM identification during RARP.
Main Methods:
- A prospective, single-center study involving ex vivo DRS measurements on RARP specimens from 59 patients.
- Development of a machine learning classification algorithm using 20 discriminating features from DRS spectra.
- Patient-wise data splitting (70% training, 30% testing) with ten iterations for algorithm validation.
Main Results:
- Analysis of 542 DRS measurements (53% tumor, 47% healthy tissue).
- A support vector machine model achieved an average sensitivity of 89%, specificity of 82%, accuracy of 85%, and AUC of 0.91 on the test set.
- The algorithm demonstrated robust performance across ten validation iterations.
Conclusions:
- DRS shows significant potential for discriminating between cancerous and benign prostate tissue.
- Further research is required to validate DRS performance on heterogeneous tissue and ex vivo prostate surfaces before clinical implementation.
