Improved contrast in inverted selective plane illumination microscopy of thick tissues using confocal detection and structured illumination

Self-Supervised Joint Learning for pCLE Image Denoising

Probe-based confocal laser endoscopy (pCLE) has emerged as a powerful tool for disease diagnosis, yet it faces challenges such as the formation of hexagonal patterns in images due to the inherent characteristics of fiber bundles. Recent advancements in deep learning offer promise in image denoising, but the acquisition of clean-noisy image pairs for training networks across all potential scenarios can be prohibitively costly. Few studies have explored training denoising networks on such pairs. Here, we propose an innovative self-supervised denoising method. Our approach integrates noise prediction networks, image quality assessment networks, and denoising networks in a collaborative, jointly trained manner. Compared to prior self-supervised denoising methods, our approach yields superior results on pCLE images and fluorescence microscopy images. In summary, our novel self-supervised denoising technique enhances image quality in pCLE diagnosis by leveraging the synergy of noise prediction, image quality assessment, and denoising networks, surpassing previous methods on both pCLE and fluorescence microscopy images.

High contrast, isotropic, and uniform 3D-imaging of centimeter-scale scattering samples using structured illumination light-sheet microscopy with axial sweeping

Light-sheet fluorescent microscopy (LSFM) has, in recent years, allowed for rapid 3D-imaging of cleared biomedical samples at larger and larger scale. However, even in cleared samples, multiple light scattering often degrades the imaging contrast and widens the optical sectioning. Accumulation of scattering intensifies these negative effects as light propagates inside the tissue, which accentuates the issues when imaging large samples. With axially swept light-sheet microscopy (ASLM), centimeter-scale samples can be scanned with a uniform micrometric optical sectioning. But to fully utilize these benefits for 3D-imaging in biomedical tissue samples, suppression of scattered light is needed. Here, we address this by merging ASLM with light-sheet based structured illumination into Structured Illumination Light-sheet Microscopy with Axial Sweeping (SILMAS). The SILMAS method thus enables high-contrast imaging, isotropic micrometric resolution and uniform optical sectioning in centimeter-scale scattering samples, creating isotropic 3D-volumes of e.g., whole mouse brains without the need for any computation-heavy post-processing. We demonstrate the effectiveness of the approach in agarose gel phantoms with fluorescent beads, and in an PFF injected alpha-synuclein transgenic mouse model tagged with a green fluorescent protein (SynGFP). SILMAS imaging is compared to standard ASLM imaging on the same samples and using the same optical setup, and is shown to increase contrast by as much as 370% and reduce widening of optical sectioning by 74%. With these results, we show that SILMAS improves upon the performance of current state-of-the-art light-sheet microscopes for large and imperfectly cleared tissue samples and is a valuable addition to the LSFM family.

Lightsheet Microscopy

In this paper, we review lightsheet (selective plane illumination) microscopy for mouse developmental biologists. There are different means of forming the illumination sheet, and we discuss these. We explain how we introduced the lightsheet microscope economically into our core facility and present our results on fixed and living samples. We also describe methods of clearing fixed samples for three-dimensional imaging and discuss the various means of preparing samples with particular reference to mouse cilia, adipose spheroids, and cochleae. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Assessment of photoacoustic tomography contrast for breast tissue imaging using 3D correlative virtual histology

Current breast tumor margin detection methods are destructive, time-consuming, and result in significant reoperative rates. Dual-modality photoacoustic tomography (PAT) and ultrasound has the potential to enhance breast margin characterization by providing clinically relevant compositional information with high sensitivity and tissue penetration. However, quantitative methods that rigorously compare volumetric PAT and ultrasound images with gold-standard histology are lacking, thus limiting clinical validation and translation. Here, we present a quantitative multimodality workflow that uses inverted Selective Plane Illumination Microscopy (iSPIM) to facilitate image co-registration between volumetric PAT-ultrasound datasets with histology in human invasive ductal carcinoma breast tissue samples. Our ultrasound-PAT system consisted of a tunable Nd:YAG laser coupled with a 40 MHz central frequency ultrasound transducer. A linear stepper motor was used to acquire volumetric PAT and ultrasound breast biopsy datasets using 1100 nm light to identify hemoglobin-rich regions and 1210 nm light to identify lipid-rich regions. Our iSPIM system used 488 nm and 647 nm laser excitation combined with Eosin and DRAQ5, a cell-permeant nucleic acid binding dye, to produce high-resolution volumetric datasets comparable to histology. Image thresholding was applied to PAT and iSPIM images to extract, quantify, and topologically visualize breast biopsy lipid, stroma, hemoglobin, and nuclei distribution. Our lipid-weighted PAT and iSPIM images suggest that low lipid regions strongly correlate with malignant breast tissue. Hemoglobin-weighted PAT images, however, correlated poorly with cancerous regions determined by histology and interpreted by a board-certified pathologist. Nuclei-weighted iSPIM images revealed similar cellular content in cancerous and non-cancerous tissues, suggesting malignant cell migration from the breast ducts to the surrounding tissues. We demonstrate the utility of our nondestructive, volumetric, region-based quantitative method for comprehensive validation of 3D tomographic imaging methods suitable for bedside tumor margin detection.

Emerging and Established Histological Techniques for the Analysis of Thrombosis in COVID-19 Lungs

Coronavirus disease 2019 (COVID-19) is the potentially lethal disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Patients with COVID-19 have an increased risk of thrombosis, but the role of thrombosis in the pathogenesis and progression of severe COVID-19 remains unclear. A better understanding of the contribution of thrombosis to the development and progression of COVID-19 could lead to the development of novel COVID-19 treatments. For this reason, established and emerging histological techniques have recently been used to analyze COVID-19 lungs quantitatively and visually and in two and three dimensions. The gold standard and novel state-of the-art histological techniques that have been used to assess thrombosis in COVID-19 lungs are described in this Mini Review.

μSPIM Toolset: A software platform for selective plane illumination microscopy

BACKGROUND

Selective Plane Illumination Microscopy (SPIM) is a fluorescence imaging technique that allows volumetric imaging at high spatio-temporal resolution to monitor neural activity in live organisms such as larval zebrafish. A major challenge in the construction of a custom SPIM microscope using a scanned laser beam is the control and synchronization of the various hardware components.

NEW METHOD

We present an open-source software, μSPIM Toolset, built around the widely adopted MicroManager platform, that provides control and acquisition functionality for a SPIM. A key advantage of μSPIM Toolset is a series of calibration procedures that optimize acquisition for a given set-up, making it relatively independent of the optical design of the microscope or the hardware used to build it.

RESULTS

μSPIM Toolset allows imaging of calcium activity throughout the brain of larval zebrafish at rates of 100 planes per second with single cell resolution.

COMPARISON WITH EXISTING METHODS

Several designs of SPIM have been published but are focused on imaging of developmental processes using a slower setup with a moving stage and therefore have limited use for functional imaging. In comparison, μSPIM Toolset uses a scanned beam to allow imaging at higher acquisition frequencies while minimizing disturbance of the sample.

CONCLUSIONS

The μSPIM Toolset provides a flexible solution for the control of SPIM microscopes and demonstrated its utility for brain-wide imaging of neural activity in larval zebrafish.

Tissue dynamics spectroscopic imaging: functional imaging of heterogeneous cancer tissue

SIGNIFICANCE

Tumor heterogeneity poses a challenge for the chemotherapeutic treatment of cancer. Tissue dynamics spectroscopy captures dynamic contrast and can capture the response of living tissue to applied therapeutics, but the current analysis averages over the complicated spatial response of living biopsy samples.

AIM

To develop tissue dynamics spectroscopic imaging (TDSI) to map the heterogeneous spatial response of tumor tissue to anticancer drugs.

APPROACH

TDSI is applied to tumor spheroids grown from cell lines and to ex vivo living esophageal biopsy samples. Doppler fluctuation spectroscopy is performed on a voxel basis to extract spatial maps of biodynamic biomarkers. Functional images and bivariate spatial maps are produced using a bivariate color merge to represent the spatial distribution of pairs of signed drug-response biodynamic biomarkers.

RESULTS

We have mapped the spatial variability of drug responses within biopsies and have tracked sample-to-sample variability. Sample heterogeneity observed in the biodynamic maps is associated with histological heterogeneity observed using inverted selective-plane illumination microscopy.

CONCLUSION

We have demonstrated the utility of TDSI as a functional imaging method to measure tumor heterogeneity and its potential for use in drug-response profiling.

Line scanning, fiber bundle fluorescence HiLo endomicroscopy with confocal slit detection

Fiber bundle fluorescence endomicroscopy is an effective method for in vivo imaging of biological tissue samples. Line-scanning confocal laser endomicroscopy realizes confocal imaging at a much higher frame rate compared to the point scanning system, but with reduced optical sectioning. To address this problem, we describe a fiber bundle endomicroscopy system that utilizes the HiLo technique to enhance the optical sectioning while still maintaining high image acquisition rates. Confocal HiLo endomicroscopy is achieved by synchronizing the scanning hybrid-illumination laser line with the rolling shutter of a CMOS camera. An evident improvement of axial sectioning is achieved as compared to the line-scanning confocal endomicroscopy without the HiLo technique. Comparisons are also made with epifluorescence endomicroscopy with and without HiLo. The optical sectioning enhancement is demonstrated on lens tissue as well as porcine kidney tissue.

Spatially modulated illumination allows for light sheet fluorescence microscopy with an incoherent source and compressive sensing

Light sheet fluorescence microscopy has become one of the most widely used techniques for three-dimensional imaging due to its high speed and low phototoxicity. Further improvements in 3D microscopy require limiting the light exposure of the sample and increasing the volumetric acquisition rate. We hereby present an imaging technique that allows volumetric reconstruction of the fluorescent sample using spatial modulation on a selective illumination volume. We demonstrate that this can be implemented using an incoherent LED source, avoiding shadowing artifacts, typical of light sheet microscopy. Furthermore, we show that spatial modulation allows the use of Compressive Sensing, reducing the number of modulation patterns to be acquired. We present results on zebrafish embryos which prove that selective spatial modulation can be used to reconstruct relatively large volumes without any mechanical movement. The technique yields an accurate reconstruction of the sample anatomy even at significant compression ratios, achieving higher volumetric acquisition rate and reducing photodamage biological samples.

Enhanced resolution 3D digital cytology and pathology with dual-view inverted selective plane illumination microscopy

The current gold-standard histopathology for tissue analysis is destructive, time consuming, and limited to 2D slices. Light sheet microscopy has emerged as a powerful tool for 3D imaging of tissue biospecimens with its fast speed and low photo-damage, but usually with worse axial resolution and complicated configuration for sample imaging. Here, we utilized inverted selective plane illumination microscopy for easy sample mounting and imaging, and dual-view imaging and deconvolution to overcome the anisotropic resolution. We have rendered 3D images of fresh cytology cell blocks and millimeter- to centimeter-sized fixed tissue samples with high resolution in both lateral and axial directions. More accurate cellular quantification, higher image sharpness, and more image details have been achieved with the dual-view method compared with single-view imaging.

Imaging neural events in zebrafish larvae with linear structured illumination light sheet fluorescence microscopy

Light sheet fluorescence microscopy (LSFM) is a powerful tool for investigating model organisms including zebrafish. However, due to scattering and refractive index variations within the sample, the resulting image often suffers from low contrast. Structured illumination (SI) has been combined with scanned LSFM to remove out-of-focus and scattered light using square-law detection. Here, we demonstrate that the combination of LSFM with linear reconstruction SI can further increase resolution and contrast in the vertical and axial directions compared to the widely adopted root-mean square reconstruction method while using the same input images. We apply this approach to imaging neural activity in 7-day postfertilization zebrafish larvae. We imaged two-dimensional sections of the zebrafish central nervous system in two colors at an effective frame rate of 7 frames per second.