Virtual histopathology with ultraviolet scattering and photoacoustic remote sensing microscopy

Thermal-tagging photoacoustic remote sensing flowmetry

Ultrasound coupling is one of the critical challenges for traditional photoacoustic (or optoacoustic) microscopy (PAM) techniques transferred to the clinical examination of chronic wounds and open tissues. A promising alternative potential solution for breaking the limitation of ultrasound coupling in PAM is photoacoustic remote sensing (PARS), which implements all-optical non-interferometric photoacoustic measurements. Functional imaging of PARS microscopy was demonstrated from the aspects of histopathology and oxygen metabolism, while its performance in hemodynamic quantification remains unexplored. In this Letter, we present an all-optical thermal-tagging flowmetry approach for PARS microscopy and demonstrate it with comprehensive mathematical modeling and ex vivo and in vivo experimental validations. Experimental results demonstrated that the detectable range of the blood flow rate was from 0 to 12 mm/s with a high accuracy (measurement error:±1.2%) at 10-kHz laser pulse repetition rate. The proposed all-optical thermal-tagging flowmetry offers an effective alternative approach for PARS microscopy realizing non-contact dye-free hemodynamic imaging.

Deep learning-enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy

The goal of oncologic surgeries is complete tumor resection, yet positive margins are frequently found postoperatively using gold standard H&E-stained histology methods. Frozen section analysis is sometimes performed for rapid intraoperative margin evaluation, albeit with known inaccuracies. Here, we introduce a label-free histological imaging method based on an ultraviolet photoacoustic remote sensing and scattering microscope, combined with unsupervised deep learning using a cycle-consistent generative adversarial network for realistic virtual staining. Unstained tissues are scanned at rates of up to 7 mins/cm2, at resolution equivalent to 400x digital histopathology. Quantitative validation suggests strong concordance with conventional histology in benign and malignant prostate and breast tissues. In diagnostic utility studies we demonstrate a mean sensitivity and specificity of 0.96 and 0.91 in breast specimens, and respectively 0.87 and 0.94 in prostate specimens. We also find virtual stain quality is preferred (P = 0.03) compared to frozen section analysis in a blinded survey of pathologists.

Rapid ultraviolet photoacoustic remote sensing microscopy using voice-coil stage scanning

There is an unmet need for fast virtual histology technologies that exhibit histological realism and can scan large sections of fresh tissue within intraoperative time-frames. Ultraviolet photoacoustic remote sensing microscopy (UV-PARS) is an emerging imaging modality capable of producing virtual histology images that show good concordance to conventional histology stains. However, a UV-PARS scanning system that can perform rapid intraoperative imaging over mm-scale fields-of-view at fine resolution (<500 nm) has yet to be demonstrated. In this work, we present a UV-PARS system which utilizes voice-coil stage scanning to demonstrate finely resolved images for 2×2 mm² areas at 500 nm sampling resolution in 1.33 minutes and coarsely resolved images for 4×4 mm² areas at 900 nm sampling resolution in 2.5 minutes. The results of this work demonstrate the speed and resolution capabilities of the UV-PARS voice-coil system and further develop the potential for UV-PARS microscopy to be employed in a clinical setting.

Investigating mechanisms of laser pulse-induced reflectivity modulations in photoacoustic remote sensing with a 10 million frames-per-second camera

Photoacoustic remote sensing has been recently developed as an all-optical imaging modality capable of imaging a variety of endogenous contrast agents label-free. Initially predicted laser pulse-induced refractive index perturbation-based interrogation beam reflectivity modulations have been found to be orders of magnitude smaller than those typically observed experimentally. In this report we utilize a 10 million frames-per-second camera to further investigate these predicted reflectivity modulations, while also exploring other potential mechanisms of laser pulse-induced reflectivity modulations. Laser-induced motion is demonstrated both laterally for gold wires suspended and submerged in air and water, respectively, and carbon fibers submerged in water, and axial motion is observed in gold wires submerged in a depth gradient of intralipid solution. This laser-induced sample motion is anticipated to cause reflectivity modulations local to the interrogation beam profile in microscopy set-ups. Non-motion-based maximum intensity modulations of 3% are also observed in gold wires submerged in water, indicating the presence of the originally predicted reflectivity modulations. Overall, these observations are important as they provide a widefield view of laser-pulse interactions unavailable in previous point scanning-based photoacoustic remote sensing microscopy configurations, where observed mechanisms occur on time-scales orders of magnitude faster than equivalent field of view point scanning capabilities.

Fast hybrid optomechanical scanning photoacoustic remote sensing microscopy for virtual histology

A rapid scanning microscopy method for hematoxylin and eosin (H&E) like images is sought after for interoperative diagnosis of solid tumor margins. The rapid observation and diagnosis of histological samples can greatly lower surgical risk and improve patient outcomes from solid tumor resection surgeries. Photoacoustic remote sensing (PARS) has recently been demonstrated to provide images of virtual H&E stains with excellent concordance with true H&E staining of formalin-fixed, paraffin embedded tissues. By using PARS with constant velocity and 1D galvanometer mirror scanning we acquire large virtual H&E images (10mm x 5mm) of prostate tissue in less than 3.5 minutes without staining, and over two orders of magnitude faster data acquisition than the current PARS imaging speed.