High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

Abstract

Surgical margin analysis (SMA), an essential procedure to confirm the complete excision of cancerous tissue in tumor resection surgery, requires intraoperative diagnostic tools to avoid repeated surgeries due to a positive surgical margin. Recently, by taking the advantage of the high intrinsic optical absorption of DNA/RNA at 266 nm wavelength, ultraviolet photoacoustic microscopy (UV-PAM) has been developed to provide high-resolution histological images without labeling, showing great promise as an intraoperative tool for SMA. To enable the development of UV-PAM for SMA, here, a high-speed and open-top UV-PAM system is presented, which can be operated similarly to conventional optical microscopies. The UV-PAM system provides a high lateral resolution of 1.2 µm, and a high imaging speed of 55 kHz A-line rate with one-axis galvanometer mirror scanning. Moreover, to ensure UV-PAM images can be easily interpreted by pathologists without additional training, the original grayscale UV-PAM images are virtually stained by a deep-learning algorithm to mimic the standard hematoxylin- and eosin-stained images, enabling training-free histological analysis. Mouse brain slice imaging is performed to demonstrate the high performance of the open-top UV-PAM system, illustrating its great potential for SMA applications.