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Photoacoustic microscopy is a hybrid imaging technology based on the conversion of absorbed light into ultrasound emission. A single-wavelength pulse-width-based method allows fast functional imaging of the brain. We present fast functional photoacoustic microscopy (PAM) for three-dimensional high-resolution, high-speed imaging of the mouse brain, complementary to other imaging modalities. We implemented a single-wavelength pulse-width-based method with a one-dimensional imaging rate of 100 kHz to image blood oxygenation with capillary-level resolution. We applied PAM to image the vascular morphology, blood oxygenation, blood flow and oxygen metabolism in both resting and stimulated states in the mouse brain.

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 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 ultraviolet 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 the diagnosis of fresh biological samples.Photoacoustic detection highly localized with a pulsed ultraviolet laser based on the Grüneisen relaxation effect allows water-background suppressed mid-infrared (MIR) imaging of lipids and proteins at ultraviolet resolution, at least an order of magnitude finer than the MIR diffraction limits.

Photoacoustic (PA) imaging (PAI) holds great promise for non-invasive biomedical diagnostics. However, the efficacy of current contrast agents is often limited by photobleaching, toxicity, and complex synthesis processes. In this study, we introduce a novel, biocompatible PAI contrast agent: a recombinant water-soluble chlorophyll-binding protein (WSCP) from Lepidium virginicum (LvP) reconstituted with chlorophyll a (LvP-chla). LvP-chla exhibits a strong and narrow absorption peak at 665 nm, with a molar extinction coefficient substantially higher than oxyhemoglobin and deoxyhemoglobin, enabling robust signal generation orthogonal to endogenous chromophores. Phantom studies confirmed a linear relationship between PA signal amplitude and LvP-chla concentration, demonstrating its stability and reliability. In vitro cytotoxicity testing using 4T1 cells showed high cell viability at 5 mg/mL, justifying its use for in vivo studies. In vivo experiments with a 4T1 tumor-bearing mouse model demonstrated successful tumor localization following intratumoral injection of LvP-chla, with clear visualization via spectroscopic differentiation from endogenous absorbers at 665 nm and 685 nm. Toxicity assessments, both in vitro and in vivo, revealed no adverse effects, and clearance studies confirmed minimal retention after 96 h. These findings show that LvP-chla is a promising contrast agent that enhances PAI capabilities through its straightforward synthesis, stability, and biocompatibility.

Photoacoustic microscopy (PAM) is a promising imaging technique to provide structural, functional, and molecular information for preclinical and clinical studies. However, expensive and bulky lasers and motorized stages have limited the broad applications of conventional PAM systems. A recent trend is to use low-cost light sources and miniaturized designs to develop a compact PAM system and expand its applications from benchtop to bedside. We provide (1) an overview of PAM systems and their limitations, (2) a comprehensive review of PAM systems with low-cost light sources and their applications, (3) a comprehensive review of PAM systems with miniaturized and handheld scanning designs, and (4) perspective applications and a summary of the cost-effective and miniaturized PAM systems. Papers published before July 2023 in the area of using low-cost light sources and miniaturized designs in PAM were reviewed. They were categorized into two main parts: (1) low-cost light sources and (2) miniaturized or handheld designs. The first part was classified into two subtypes: pulsed laser diode and continuous-wave laser diode. The second part was also classified into two subtypes: galvanometer scanner and micro-electro-mechanical system scanner. Significant progress has been made in the development of PAM systems based on low-cost and compact light sources as well as miniaturized and handheld designs. The review highlights the potential of these advancements to revolutionize PAM technology, making it more accessible and practical for various applications in preclinical studies, clinical practice, and long-term monitoring.

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.

Three-dimensional (3D) optical imaging of whole biological organs with microscopic resolution has remained a challenge. Most versions of such imaging techniques require special preparation of the tissue specimen. Here we demonstrate microtomy-assisted photoacoustic microscopy (mPAM) of mouse brains and other organs, which automatically acquires serial distortion-free and registration-free images with endogenous absorption contrasts. Without tissue staining or clearing, mPAM generates micrometer-resolution 3D images of paraffin- or agarose-embedded whole organs with high fidelity, achieved by label-free simultaneous sensing of DNA/RNA, hemoglobins, and lipids. mPAM provides histology-like imaging of cell nuclei, blood vessels, axons, and other anatomical structures, enabling the application of histopathological interpretation at the organelle level to analyze a whole organ. Its deep tissue imaging capability leads to less sectioning, resulting in negligible sectioning artifact. mPAM offers a new way to better understand complex biological organs. The state-of-the-art three-dimensional biomedical imaging often requires specific tissue preparation that may alter the physical properties of the specimen causing loss of information. Here Wong et al. develop a microtomy-assisted photoacoustic microscopy that allows imaging of biological samples without labelling agents and with reduced sectioning.

Rapid multicolor three-dimensional (3D) imaging for centimeter-scale specimens with subcellular resolution remains a challenging but captivating scientific pursuit. Here, we present a fast, cost-effective, and robust multicolor whole-organ 3D imaging method assisted with ultraviolet (UV) surface excitation and vibratomy-assisted sectioning, termed translational rapid ultraviolet-excited sectioning tomography (TRUST). With an inexpensive UV light-emitting diode (UV-LED) and a color camera, TRUST achieves widefield exogenous molecular-specific fluorescence and endogenous content-rich autofluorescence imaging simultaneously while preserving low system complexity and system cost. Formalin-fixed specimens are stained layer by layer along with serial mechanical sectioning to achieve automated 3D imaging with high staining uniformity and time efficiency. 3D models of all vital organs in wild-type C57BL/6 mice with the 3D structure of their internal components (e.g., vessel network, glomeruli, and nerve tracts) can be reconstructed after imaging with TRUST to demonstrate its fast, robust, and high-content multicolor 3D imaging capability. Moreover, its potential for developmental biology has also been validated by imaging entire mouse embryos (~2 days for the embryo at the embryonic day of 15). TRUST offers a fast and cost-effective approach for high-resolution whole-organ multicolor 3D imaging while relieving researchers from the heavy sample preparation workload.

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.

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 mm2/10 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. A rapid, label‐free, and slide‐free histological imaging method, termed computational high‐throughput autofluorescence microscopy by pattern illumination (CHAMP) is proposed. With the assistance of computational imaging and unsupervised learning, CHAMP enables rapid and accurate pathological examination without tissue processing or staining, demonstrating great potential as an assistive imaging platform for surgeons and pathologists to provide optimal adjuvant treatment intraoperatively.

Abstract Deep learning algorithms have been widely used in microscopic image translation. The corresponding data-driven models can be trained by supervised or unsupervised learning depending on the availability of paired data. However, general cases are where the data are only roughly paired such that supervised learning could be invalid due to data unalignment, and unsupervised learning would be less ideal as the roughly paired information is not utilized. In this work, we propose a unified framework (U-Frame) that unifies supervised and unsupervised learning by introducing a tolerance size that can be adjusted automatically according to the degree of data misalignment. Together with the implementation of a global sampling rule, we demonstrate that U-Frame consistently outperforms both supervised and unsupervised learning in all levels of data misalignments (even for perfectly aligned image pairs) in a myriad of image translation applications, including pseudo-optical sectioning, virtual histological staining (with clinical evaluations for cancer diagnosis), improvement of signal-to-noise ratio or resolution, and prediction of fluorescent labels, potentially serving as new standard for image translation.