A new label-free optical imaging method for the lymphatic system enhanced by deep learning.

Researchers

Journal

Modalities

Models

Abstract

Our understanding of the lymphatic vascular system lags far behind that of the blood vascular system, limited by available imaging technologies. We present a label-free optical imaging method that visualizes the lymphatic system with high contrast. We developed an orthogonal polarization imaging (OPI) in the shortwave infrared range (SWIR) and imaged both lymph nodes and lymphatic vessels of mice and rats in vivo through intact skin, as well as human mesenteric lymph nodes in colectomy specimens. By integrating SWIR-OPI with U-Net, a deep learning image segmentation algorithm, we automated the lymph node size measurement process. Changes in lymph nodes in response to cancer progression were monitored in two separate mouse cancer models, through which we obtained insights into pre-metastatic niches and correlation between lymph node masses and many important biomarkers. In a human pilot study, we demonstrated the effectiveness of SWIR-OPI to detect human lymph nodes in real time with clinical colectomy specimens.We develop a real-time high contrast optical technique for imaging the lymphatic system, and apply it to anatomical pathology gross examination in a clinical setting, as well as real-time monitoring of tumor microenvironment in animal studies.