Evaluation of resonant scanning as a high-speed imaging technique for two-photon imaging of cortical vasculature

Suppression of Subpixel Jitter in Resonant Scanning Systems With Phase-locked Sampling

Resonant scanning is critical to high speed and in vivo imaging in many applications of laser scanning microscopy. However, resonant scanning suffers from well-known image artifacts due to scanner jitter, limiting adoption of high-speed imaging technologies. Here, we introduce a real-time, inexpensive and all electrical method to suppress jitter more than an order of magnitude below the diffraction limit that can be applied to most existing microscope systems with no software changes. By phase-locking imaging to the resonant scanner period, we demonstrate an 86% reduction in pixel jitter, a 15% improvement in point spread function with resonant scanning and show that this approach enables two widely used models of resonant scanners to achieve comparable accuracy to galvanometer scanners running two orders of magnitude slower. Finally, we demonstrate the versatility of this method by retrofitting a commercial two photon microscope and show that this approach enables significant quantitative and qualitative improvements in biological imaging.

A Deep Learning Approach for Improving Two-Photon Vascular Imaging Speeds

A potential method for tracking neurovascular disease progression over time in preclinical models is multiphoton fluorescence microscopy (MPM), which can image cerebral vasculature with capillary-level resolution. However, obtaining high-quality, three-dimensional images with traditional point scanning MPM is time-consuming and limits sample sizes for chronic studies. Here, we present a convolutional neural network-based (PSSR Res-U-Net architecture) algorithm for fast upscaling of low-resolution or sparsely sampled images and combine it with a segmentation-less vectorization process for 3D reconstruction and statistical analysis of vascular network structure. In doing so, we also demonstrate that the use of semi-synthetic training data can replace the expensive and arduous process of acquiring low- and high-resolution training pairs without compromising vectorization outcomes, and thus open the possibility of utilizing such approaches for other MPM tasks where collecting training data is challenging. We applied our approach to images with large fields of view from a mouse model and show that our method generalizes across imaging depths, disease states and other differences in neurovasculature. Our pretrained models and lightweight architecture can be used to reduce MPM imaging time by up to fourfold without any changes in underlying hardware, thereby enabling deployability across a range of settings.

Non-Degenerate Two-Photon Imaging of Deep Rodent Cortex using Indocyanine Green in the water absorption window

We present a novel approach for deep vascular imaging in rodent cortex at excitation wavelengths susceptible to water absorption using two-photon microscopy with photons of dissimilar wavelengths. We demonstrate that non-degenerate two-photon excitation (ND-2PE) enables imaging in the water absorption window from 1400-1550 nm using two synchronized excitation sources at 1300 nm and 1600 nm that straddle the absorption window. We explore the brightness spectra of indocyanine green (ICG) and assess its suitability for imaging in the water absorption window. Further, we demonstrate in vivo imaging of the rodent cortex vascular structure up to 1.2 mm using ND-2PE. Lastly, a comparative analysis of ND-2PE at 1435 nm and single-wavelength, two-photon imaging at 1300 nm and 1435 nm is presented. Our work extends the excitation range for fluorescent dyes to include water absorption regimes and underscores the feasibility of deep two-photon imaging at these wavelengths.

Pulse train gating to improve signal generation for in vivo two-photon fluorescence microscopy

Significance

Two-photon microscopy is used routinely for in vivo imaging of neural and vascular structures and functions in rodents with a high resolution. Image quality, however, often degrades in deeper portions of the cerebral cortex. Strategies to improve deep imaging are therefore needed. We introduce such a strategy using the gating of high repetition rate ultrafast pulse trains to increase the signal level.

Aim

We investigate how the signal generation, signal-to-noise ratio (SNR), and signal-to-background ratio (SBR) improve with pulse gating while imaging in vivo mouse cerebral vasculature.

Approach

An electro-optic modulator with a high-power (6 W) 80 MHz repetition rate ytterbium fiber amplifier is used to create gates of pulses at a 1 MHz repetition rate. We first measure signal generation from a Texas Red solution in a cuvette to characterize the system with no gating and at a 50%, 25%, and 12.5% duty cycle. We then compare the signal generation, SNR, and SBR when imaging Texas Red-labeled vasculature using these conditions.

Results

We find up to a 6.73-fold increase in fluorescent signal from a cuvette when using a 12.5% duty cycle pulse gating excitation pattern as opposed to a constant 80 MHz pulse train at the same average power. We verify similar increases for in vivo imaging to that observed in cuvette testing. For deep imaging, we find that pulse gating results in a 2.95-fold increase in the SNR and a 1.37-fold increase in the SBR on average when imaging mouse cortical vasculature at depths ranging from 950 to 1050    μ m .

Conclusions

We demonstrate that a pulse gating strategy can either be used to limit heating when imaging superficial brain regions or used to increase signal generation in deep regions. These findings should encourage others to adopt similar pulse gating excitation schemes for imaging neural structures through two-photon microscopy.

Signal Improved ultra-Fast Light-sheet Microscope (SIFT) for large tissue imaging

Light-sheet fluorescence microscopy (LSFM) in conjunction with tissue clearing techniques enables morphological investigation of large tissues faster and with excellent optical sectioning. Recently, cleared tissue axially swept light-sheet microscope (ctASLM) demonstrated three-dimensional isotropic resolution in millimeter-scaled tissues. But ASLM based microscopes suffer from low detection signal and slow imaging speed. Here we report a simple and efficient imaging platform that employs precise control of two fixed distant light-sheet foci to carry out ASLM. This allowed us to carry out full field of view (FOV) imaging at 40 frames per second (fps) which is a four-fold improvement compared to the current state-of-the-art. In addition, in a particular frame rate, our method doubles the signal compared to the current ASLM technique. To augment the overall imaging performance, we also developed a deep learning based tissue information classifier that enables faster determination of tissue boundary. We demonstrated the performance of our imaging platform on various cleared tissue samples and demonstrated its robustness over a wide range of clearing protocols.

Design and test of a rigid endomicroscopic system for multimodal imaging and femtosecond laser ablation

Significance

Conventional diagnosis of laryngeal cancer is normally made by a combination of endoscopic examination, a subsequent biopsy, and histopathology, but this requires several days and unnecessary biopsies can increase pathologist workload. Nonlinear imaging implemented through endoscopy can shorten this diagnosis time, and localize the margin of the cancerous area with high resolution.

Aim

Develop a rigid endomicroscope for the head and neck region, aiming for in-vivo multimodal imaging with a large field of view (FOV) and tissue ablation.

Approach

Three nonlinear imaging modalities, which are coherent anti-Stokes Raman scattering, two-photon excitation fluorescence, and second harmonic generation, as well as the single photon fluorescence of indocyanine green, are applied for multimodal endomicroscopic imaging. High-energy femtosecond laser pulses are transmitted for tissue ablation.

Results

This endomicroscopic system consists of two major parts, one is the rigid endomicroscopic tube 250 mm in length and 6 mm in diameter, and the other is the scan-head (10 × 12 × 6    cm 3 in size) for quasi-static scanning imaging. The final multimodal image accomplishes a maximum FOV up to 650    μ m , and a resolution of 1    μ m is achieved over 560    μ m FOV. The optics can easily guide sub-picosecond pulses for ablation.

Conclusions

The system exhibits large potential for helping real-time tissue diagnosis in surgery, by providing histological tissue information with a large FOV and high resolution, label-free. By guiding high-energy fs laser pulses, the system is even able to remove suspicious tissue areas, as has been shown for thin tissue sections in this study.

Pulse train gating to improve signal generation for in vivo two-photon fluorescence microscopy

Significance

Two-photon microscopy is used routinely for in vivo imaging of neural and vascular structure and function in rodents with a high resolution. Image quality, however, often degrades in deeper portions of the cerebral cortex. Strategies to improve deep imaging are therefore needed. We introduce such a strategy using gates of high repetition rate ultrafast pulse trains to increase signal level.

Aim

We investigate how signal generation, signal-to-noise ratio (SNR), and signal-to-background ratio (SBR) improve with pulse gating while imaging in vivo mouse cerebral vasculature.

Approach

An electro-optic modulator is used with a high-power (6 W) 80 MHz repetition rate ytterbium fiber amplifier to create gates of pulses at a 1 MHz repetition rate. We first measure signal generation from a Texas Red solution in a cuvette to characterize the system with no gating and at a 50%, 25%, and 12.5% duty cycle. We then compare signal generation, SNR, and SBR when imaging Texas Red-labeled vasculature using these conditions.

Results

We find up to a 6.73-fold increase in fluorescent signal from a cuvette when using a 12.5% duty cycle pulse gating excitation pattern as opposed to a constant 80 MHz pulse train. We verify similar increases for in vivo imaging to that observed in cuvette testing. For deep imaging we find pulse gating to result in a 2.95-fold increase in SNR and a 1.37-fold increase in SBR on average when imaging mouse cortical vasculature at depths ranging from 950 μm to 1050 μm.

Conclusions

We demonstrate that a pulse gating strategy can either be used to limit heating when imaging superficial brain regions or used to increase signal generation in deep regions. These findings should encourage others to adopt similar pulse gating excitation schemes for imaging neural structure through two-photon microscopy.

Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging

Multiphoton microscopy is a formidable tool for the pathological analysis of tumors. The physical limitations of imaging systems and the low efficiencies inherent in nonlinear processes have prevented the simultaneous achievement of high imaging speed and high resolution. We demonstrate a self-alignment dual-attention-guided residual-in-residual generative adversarial network trained with various multiphoton images. The network enhances image contrast and spatial resolution, suppresses noise, and scanning fringe artifacts, and eliminates the mutual exclusion between field of view, image quality, and imaging speed. The network may be integrated into commercial microscopes for large-scale, high-resolution, and low photobleaching studies of tumor environments.

Diamond Raman laser and Yb fiber amplifier for in vivo multiphoton fluorescence microscopy

Here we introduce a fiber amplifier and a diamond Raman laser that output high powers (6.5 W, 1.3 W) at valuable wavelengths (1060 nm, 1250 nm) for two-photon excitation of red-shifted fluorophores. These custom excitation sources are both simple to construct and cost-efficient in comparison to similar custom and commercial alternatives. Furthermore, they operate at a repetition rate (80 MHz) that allows fast image acquisition using resonant scanners. With our system we demonstrate compatibility with fast resonant scanning, the ability to acquire neuronal images, and the capability to image vasculature at deep locations (>1 mm) within the mouse cerebral cortex.