high-speed-ultraviolet-photoacoustic-microscopy-for-histological

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

Surgical margin analysis (SMA), an essential procedure to confirm the complete excision of cancerous tissue in tumor resection surgery, requires ...

Hong Kong University of Science and Technology

Optical-resolution photoacoustic microscopy (OR-PAM) is an emerging imaging modality for studying biological tissues. However, in conventional single-view OR-PAM, the lateral and axial resolutions-determined optically and acoustically, respectively-are highly anisotropic. In this Letter, we introduce dual-view OR-PAM to improve axial resolution, achieving three-dimensional (3D) resolution isotropy. We first use 0.5 μm polystyrene beads and carbon fibers to validate the resolution isotropy improvement. Imaging of mouse brain slices further demonstrates the improved resolution isotropy, revealing the 3D structure of cell nuclei in detail, which facilitates quantitative cell nuclear analysis.

Dual-view photoacoustic microscopy for quantitative cell nuclear imaging.

Acquiring ultrafast and high spectral resolution optical images is key to measure transient physical or chemical processes, such as photon propagation, plasma dynamics, and femtosecond chemical reactions. At a trillion Hz frame rate, most ultrafast imaging modalities can acquire only a limited number of frames. Here, we present a compressed ultrafast spectral-temporal (CUST) photographic technique, enabling both an ultrahigh frame rate of 3.85 trillion Hz and a large frame number. We demonstrate that CUST photography records 60 frames, enabling precisely recording light propagation, reflection, and self-focusing in nonlinear media over 30 ps. CUST photography has the potential to further increase the frame number beyond hundreds of frames. Using spectral-temporal coupling, CUST photography can record multiple frames with a subnanometer spectral resolution with a single laser exposure, enabling ultrafast spectral imaging. CUST photography with high frame rate, high spectral resolution, and high frame number in a single modality offer a new tool for observing many transient phenomena with high temporal complexity and high spectral precision.

Compressed Ultrafast Spectral-Temporal Photography.

Mid-infrared (MIR) microscopy provides rich chemical and structural information about biological samples, without staining. Conventionally, the long MIR wavelength severely limits the lateral resolution owing to optical diffraction; moreover, the strong MIR absorption of water ubiquitous in fresh biological samples results in high background and low contrast. To overcome these limitations, we propose a method that employs photoacoustic detection highly localized with a pulsed ultraviolet (UV) laser on the basis of the Grüneisen relaxation effect. For cultured cells, our method achieves water-background suppressed MIR imaging of lipids and proteins at UV resolution, at least an order of magnitude finer than the MIR diffraction limits. Label-free histology using this method is also demonstrated in thick brain slices. Our approach provides convenient high-resolution and high-contrast MIR imaging, which can benefit diagnosis of fresh biological samples.

High-resolution, high-contrast mid-infrared imaging of fresh biological samples with ultraviolet-localized photoacoustic microscopy.

Optical-resolution photoacoustic microscopy (OR-PAM) has demonstrated high-spatial-resolution imaging of optical absorption in biological tissue. To date, most OR-PAM systems rely on mechanical scanning with confocally aligned optical excitation and ultrasonic detection, limiting the wide-field imaging speed of these systems. Although several multifocal OR-PA (MFOR-PA) systems have attempted to address this limitation, they are hindered by the complex design in a constrained physical space. Here, we present a two-dimensional (2D) MFOR-PAM system that utilizes a 2D microlens array and an acoustic ergodic relay. Using a single-element ultrasonic transducer, this system can detect PA signals generated from 400 optical foci in parallel and then raster scan the optical foci patterns to form an MFOR-PAM image. This system improves the imaging resolution of an acoustic ergodic relay system from 220 to 13 μm and enables 400-folds shorter scanning time than that of a conventional OR-PAM system at the same resolution and laser repetition rate. We demonstrated the imaging ability of the system with both in vitro and in vivo experiments.

Multifocal photoacoustic microscopy using a single-element ultrasonic transducer through an ergodic relay.

Optical-based sensing approaches have long been an indispensable way to detect molecules in biological tissues for various biomedical research and applications. The advancement in optical microscopy is one of the main drivers for discoveries and innovations in both life science and biomedical imaging. However, the shallow imaging depth due to the use of ballistic photons fundamentally limits optical imaging approaches' translational potential to a clinical setting. Photoacoustic (PA) tomography (PAT) is a rapidly growing hybrid imaging modality that is capable of acoustically detecting optical contrast. PAT uniquely enjoys high-resolution deep-tissue imaging owing to the utilization of diffused photons. The exploration of endogenous contrast agents and the development of exogenous contrast agents further improve the molecular specificity for PAT. PAT's versatile design and non-invasive nature have proven its great potential as a biomedical imaging tool for a multitude of biomedical applications. In this review, representative endogenous and exogenous PA contrast agents will be introduced alongside common PAT system configurations, including the latest advances of all-optical acoustic sensing techniques.

A Review of Endogenous and Exogenous Contrast Agents Used in Photoacoustic Tomography with Different Sensing Configurations.

Laser diodes (LDs) have been considered as cost-effective and compact excitation sources to overcome the requirement of costly and bulky pulsed laser sources that are commonly used in photoacoustic microscopy (PAM). However, the spatial resolution and/or imaging speed of previously reported LD-based PAM systems have not been optimized simultaneously. In this paper, we developed a high-speed and high-resolution LD-based PAM system using a continuous wave LD, operating at a pulsed mode, with a repetition rate of 30 kHz, as an excitation source. A hybrid scanning mechanism that synchronizes a one-dimensional galvanometer mirror and a two-dimensional motorized stage is applied to achieve a fast imaging capability without signal averaging due to the high signal-to-noise ratio. By optimizing the optical system, a high lateral resolution of 4.8 μm has been achieved. In vivo microvasculature imaging of a mouse ear has been demonstrated to show the high performance of our LD-based PAM system.

High-speed high-resolution laser diode-based photoacoustic microscopy for in vivo microvasculature imaging.

Histopathological examination of tissue sections is the gold standard for disease diagnosis. However, the conventional histopathology workflow requires lengthy and laborious sample preparation to obtain thin tissue slices, causing about a one-week delay to generate an accurate diagnostic report. Recently, microscopy with ultraviolet surface excitation (MUSE), a rapid and slide-free imaging technique, has been developed to image fresh and thick tissues with specific molecular contrast. Here, we propose to apply an unsupervised generative adversarial network framework to translate colorful MUSE images into Deep-MUSE images that highly resemble hematoxylin and eosin staining, allowing easy adaptation by pathologists. By eliminating the needs of all sample processing steps (except staining), a MUSE image with subcellular resolution for a typical brain biopsy (5 mm × 5 mm) can be acquired in 5 minutes, which is further translated into a Deep-MUSE image in 40 seconds, simplifying the standard histopathology workflow dramatically and providing histological images intraoperatively.

Deep-learning-assisted microscopy with ultraviolet surface excitation for rapid slide-free histological imaging.

Histological images can reveal rich cellular information of tissue sections, which are widely used by pathologists in disease diagnosis. However, the gold standard for histopathological examination is based on thin sections on slides, which involves inevitable time-consuming and labor-intensive tissue processing steps, hindering the possibility of intraoperative pathological assessment of the precious patient specimens. Here, by incorporating ultraviolet photoacoustic microscopy (UV-PAM) with deep learning, we show a rapid and label-free histological imaging method that can generate virtually stained histological images (termed Deep-PAM) for both thin sections and thick fresh tissue specimens. With the tissue non-destructive nature of UV-PAM, the imaged intact specimens can be reused for other ancillary tests. We demonstrated Deep-PAM on various tissue preparation protocols, including formalin-fixation and paraffin-embedding sections (7-µm thick) and frozen sections (7-µm thick) in traditional histology, and rapid assessment of intact fresh tissue (~ 2-mm thick, within 15 min for a tissue with a surface area of 5 mm × 5 mm). Deep-PAM potentially serves as a comprehensive histological imaging method that can be simultaneously applied in preoperative, intraoperative, and postoperative disease diagnosis.

Deep learning enables ultraviolet photoacoustic microscopy based histological imaging with near real-time virtual staining.

Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP). With the assistance of computational microscopy, CHAMP enables high-throughput and label-free imaging of thick and unprocessed tissues with large surface irregularity at an acquisition speed of 10 mm /10 s with 1.1-µm lateral resolution. Moreover, the CHAMP image can be transformed into a virtually stained histological image (Deep-CHAMP) through unsupervised learning within 15 s, where significant cellular features are quantitatively extracted with high accuracy. The versatility of CHAMP is experimentally demonstrated using mouse brain/kidney and human lung tissues prepared with various clinical protocols, which enables a rapid and accurate intraoperative/postoperative pathological examination without tissue processing or staining, demonstrating its great potential as an assistive imaging platform for surgeons and pathologists to provide optimal adjuvant treatment.

High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning.

Ultraviolet photoacoustic microscopy (UV-PAM) has been investigated to provide label-free and registration-free volumetric histological images for whole organs, offering new insights into complex biological organs. However, because of the high UV absorption of lipids and pigments in tissue, UV-PAM suffers from low image contrast and shallow image depth, hindering its capability for revealing various microstructures in organs. To improve the UV-PAM imaging contrast and imaging depth, here we propose to implement a state-of-the-art optical clearing technique, CUBIC (clear, unobstructed brain/body imaging cocktails and computational analysis), to wash out the lipids and pigments from tissues. Our results show that the UV-PAM imaging contrast and quality can be significantly improved after tissue clearing. With the cleared tissue, multilayers of cell nuclei can also be extracted from time-resolved PA signals. Tissue clearing-enhanced UV-PAM can provide fine details for organ imaging.

Ultraviolet photoacoustic microscopy with tissue clearing for high-contrast histological imaging.

Three-dimensional (3D) histology is vitally important to characterize disease-induced tissue heterogeneity at the individual cell level. However, it remains challenging for both high-throughput 3D imaging and volumetric reconstruction. Here we propose a label-free, cost-effective, and ready-to-use 3D histological imaging technique, termed microtomy-assisted autofluorescence tomography with ultraviolet excitation (MATE). With the combination of block-face imaging and serial microtome sectioning, MATE can achieve rapid and label-free imaging of paraffin-embedded whole organs at an acquisition speed of 1 cm per 4 h with a voxel resolution of 1.2 × 1.2 × 10 μm. We demonstrate that MATE enables simultaneous visualization of cell nuclei, fiber tracts, and blood vessels in mouse/human brains without tissue staining or clearing. Moreover, diagnostic features, including nuclear size and packing density, can be quantitatively extracted with high accuracy. MATE is augmented to the current slide-based 2D histology, holding great promise to facilitate histopathological interpretation at the organelle level.

Terence T. W. Wong

Translational and Advanced Bioimaging Laboratory,
Department of Chemical and Biological Engineering,
Translational and Advanced Bioimaging Laboratory, Department of Chemical and Biological Engineering

Hong Kong University of Science and Technology

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

Terence T. W. Wong

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Translational and Advanced Bioimaging Laboratory,Department of Chemical and Biological Engineering,Translational and Advanced Bioimaging Laboratory, Department of Chemical and Biological Engineering

Hong Kong University of Science and Technology

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

Translational and Advanced Bioimaging Laboratory,
Department of Chemical and Biological Engineering,
Translational and Advanced Bioimaging Laboratory, Department of Chemical and Biological Engineering