Journal of biomedical optics
Intraoperative margin assessment in colorectal cancer via AI-enhanced multiphoton microscopy
By Lai Q, Lin Z, Xi G and 5 others.
Abstract
Significance
Identifying residual tumors at the resection margins is crucial for individuals undergoing colorectal cancer (CRC) surgery. Accurate margin assessment can help minimize residual tumor while avoiding unnecessary removal of healthy tissue.
Aim
This study uses label-free multiphoton microscopy to visualize collagen architecture and develops a feature-enhanced deep-learning model to distinguish CRC from margin-adjacent normal tissue. Approach: Margin-adjacent normal and carcinoma tissues were imaged using multiphoton microscopy, and 142 quantitative collagen features were extracted from SHG images. We propose PVT-Enhanced, a feature-fusion model that integrates handcrafted collagen features with deep image features derived from PVTv2-b5 through an attention-based fusion strategy. Its performance was compared with LASSO-LR, three convolutional neural networks, and image-only PVTv2-b5.