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<p>To reduce the burden of screening of colorectal polyps, *leave-in-situ* management of diminutive (≤ 5&#xa0;mm) polyps is being considered. However, such an approach requires increased diagnostic efficacy (PIVI-1 criterion). The aim of this study was to use Optical Coherence Tomography (OCT) for the classification of pre-malignant polyps as benign (i.e., normal or hyperplastic) vs. those with a malignant potential (i.e., adenomas and sessile serrated adenomas) at an accuracy that would enable clinical screening of colorectal cancer. The OCT raw data, from volume imaging of resected polyps, were used to extract features that can serve as biomarkers of disease. In addition to intensity and textural measures, novel biomarkers, such as scatterer size, group velocity dispersion, and spectral information, were also estimated. Their statistical properties were combined to produce scores which, in turn, were used to classify the images or polyps. This approach yielded 79.6% accuracy (72.3% NPV) for the classification of individual images and 97.3% accuracy (95.5% NPV) when combining the feature values to classify whole polyp sections. The results of this study confirm the potential of OCT imaging of colorectal polyps as a viable adjunct to colonoscopy that could enable leave-in-situ management strategies.</p>

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Classification of colon polyps with malignant potential using statistical analysis of features extracted from ex vivo optical coherence tomography images

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月26日

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  • Christos Photiou,
  • Andrew D. Thrapp,
  • Guillermo J. Tearney,
  • Costas Pitris

摘要

To reduce the burden of screening of colorectal polyps, *leave-in-situ* management of diminutive (≤ 5 mm) polyps is being considered. However, such an approach requires increased diagnostic efficacy (PIVI-1 criterion). The aim of this study was to use Optical Coherence Tomography (OCT) for the classification of pre-malignant polyps as benign (i.e., normal or hyperplastic) vs. those with a malignant potential (i.e., adenomas and sessile serrated adenomas) at an accuracy that would enable clinical screening of colorectal cancer. The OCT raw data, from volume imaging of resected polyps, were used to extract features that can serve as biomarkers of disease. In addition to intensity and textural measures, novel biomarkers, such as scatterer size, group velocity dispersion, and spectral information, were also estimated. Their statistical properties were combined to produce scores which, in turn, were used to classify the images or polyps. This approach yielded 79.6% accuracy (72.3% NPV) for the classification of individual images and 97.3% accuracy (95.5% NPV) when combining the feature values to classify whole polyp sections. The results of this study confirm the potential of OCT imaging of colorectal polyps as a viable adjunct to colonoscopy that could enable leave-in-situ management strategies.