Three-Dimensional Virtual Histology in Unprocessed Resected Tissues with Photoacoustic Remote Sensing (PARS) Microscopy and Optical Coherence Tomography

TL;DR

This paper introduces a novel multimodal imaging system combining PARS and SS-OCT to enable label-free, 3D virtual histology of unprocessed tissues, potentially revolutionizing real-time diagnostics in pathology.

Contribution

The study presents the first integration of PARS and OCT for 3D virtual histology in unprocessed tissues, demonstrating non-contact nuclear imaging and co-registered multimodal visualization.

Findings

First nuclear contrast images in resected human tissues

First 3D visualization of nuclear morphology in resected rat tissues

Co-registered OCT and PARS images for direct histological assessment

Abstract

Histological images are critical in the diagnosis and treatment of cancers. Unfortunately, the current method for capturing these microscopy images require resource intensive tissue preparation that delays diagnosis for many days to a few weeks. To streamline this process, clinicians are limited to assessing small macroscopically representative subsets of tissues. Here, we present a combined photoacoustic remote sensing (PARS) microscope and swept source optical coherence tomography (SS-OCT) system designed to circumvent these diagnostic limitations. The proposed multimodal microscope provides label-free three-dimensional depth resolved virtual histology visualizations, capturing nuclear and extranuclear tissue morphology directly on thick unprocessed specimens. The capabilities of the proposed method are demonstrated directly in unprocessed formalin fixed resected tissues. Here, we present the first images of nuclear contrast in resected human tissues, and the first 3-dimensional visualization of subsurface nuclear morphology in resected Rattus tissues, captured with a non-contact photoacoustic system. Moreover, we present the first co-registered OCT and PARS images enabling direct histological assessment of unprocessed tissues. This work represents a vital step towards the development of a real-time histological imaging modality to circumvent the limitations of current histopathology techniques.