학술논문

Intraoperative Margin Assessment in Oral and Oropharyngeal Cancer Using Label-Free Fluorescence Lifetime Imaging and Machine Learning
Document Type
Periodical
Source
IEEE Transactions on Biomedical Engineering IEEE Trans. Biomed. Eng. Biomedical Engineering, IEEE Transactions on. 68(3):857-868 Mar, 2021
Subject
Bioengineering
Computing and Processing
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Cancer
Surgery
Imaging
Robots
Probes
Machine learning
Feature extraction
medical robotics
surgical guidance/navigation
Language
ISSN
0018-9294
1558-2531
Abstract
Objective: To demonstrate the diagnostic ability of label-free, point-scanning, fiber-based Fluorescence Lifetime Imaging (FLIm) as a means of intraoperative guidance during oral and oropharyngeal cancer removal surgery. Methods: FLIm point-measurements acquired from 53 patients (n = 67893 pre-resection in vivo , n = 89695 post-resection ex vivo ) undergoing oral or oropharyngeal cancer removal surgery were used for analysis. Discrimination of healthy tissue and cancer was investigated using various FLIm-derived parameter sets and classifiers (Support Vector Machine, Random Forests, CNN). Classifier output for the acquired set of point-measurements was visualized through an interpolation-based approach to generate a probabilistic heatmap of cancer within the surgical field. Classifier output for dysplasia at the resection margins was also investigated. Results: Statistically significant change (P $< $ 0.01) between healthy and cancer was observed in vivo for the acquired FLIm signal parameters (e.g., average lifetime) linked with metabolic activity. Superior classification was achieved at the tissue region level using the Random Forests method (ROC-AUC: 0.88). Classifier output for dysplasia (% probability of cancer) was observed to lie between that of cancer and healthy tissue, highlighting FLIm's ability to distinguish various conditions. Conclusion: The developed approach demonstrates the potential of FLIm for fast, reliable intraoperative margin assessment without the need for contrast agents. Significance: Fiber-based FLIm has the potential to be used as a diagnostic tool during cancer resection surgery, including Transoral Robotic Surgery (TORS), helping ensure complete resections and improve the survival rate of oral and oropharyngeal cancer patients.