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13 March 2024 In vivo colorectal polyp evaluation using an optical coherence tomography catheter and deep learning: results of a feasibility study
Haolin Nie, Hongbo Luo, Vladimir Lamm, Shuying Li, Sanskar Thakur, Quing Zhu
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Proceedings Volume PC12830, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII; PC128302S (2024) https://doi.org/10.1117/12.3004215
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
We present the development of an optical coherence tomography (OCT) catheter designed for in vivo subsurface imaging during colonoscopy, along with the results of a clinical pilot study involving 36 subjects to assess its ability to characterize colorectal polyps real-time. High-resolution cross-sectional OCT imaging of polyp microsctructure revealed distinct morphological structures that correlated with histological findings, including tubular adenoma, tubulovillous adenoma, sessile serrated polyps, and cancer. To enhance the in vivo diagnostic capabilities, we integrated a Vision Transformer (ViT) based deep learning classifier to differentiate between cancerous and complex benign polyps, and achieved a 100% accuracy for 5 test cases. Our findings suggest that the OCT catheter combined with deep learning complements standard-of-care imaging and has the potential to enhance real-time polyp characterization and improve clinical decision-making.
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Haolin Nie, Hongbo Luo, Vladimir Lamm, Shuying Li, Sanskar Thakur, and Quing Zhu "In vivo colorectal polyp evaluation using an optical coherence tomography catheter and deep learning: results of a feasibility study", Proc. SPIE PC12830, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXVIII, PC128302S (13 March 2024); https://doi.org/10.1117/12.3004215
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KEYWORDS
Polyps
Optical coherence tomography
Deep learning
In vivo imaging
Error control coding
Tumor growth modeling
Visual process modeling
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