Coherent anti-Stokes Raman scattering (CARS) microscopy offers label-free chemical contrasts based on molecular vibrations. Hyperspectral CARS (HS-CARS) microscopy enables comprehensive microscale chemical characterization of biological samples. Various HS-CARS methods have been developed with individual advantages and disadvantages. We present what we believe to be a new temporally optimized and spectrally shaped (TOSS) HS-CARS method to overcome the limitations of existing techniques by providing precise control of the spatial and temporal profiles of the excitation beams for efficient and accurate measurements. This method uniquely uses Fourier transform pulse shaping based on a two-dimensional spatial light modulator to control the phase and amplitude of the excitation beams. TOSS-HS-CARS achieves fast, stable, and flexible acquisition, minimizes photodamage, and is highly adaptable to a multimodal multiphoton imaging system. © 2024 Optica Publishing Group (formerly OSA). All rights reserved.

Extracellular vesicles (EVs) have been implicated in metastasis and proposed as cancer biomarkers. However, heterogeneity and small size makes assessments of EVs challenging. Often, EVs are isolated from biofluids, losing spatial and temporal context and thus lacking the ability to access EVs in situ in their native microenvironment. This work examines the capabilities of label-free nonlinear optical microscopy to extract biochemical optical metrics of EVs in ex vivo tissue and EVs isolated from biofluids in cases of human breast cancer, comparing these metrics within and between EV sources. Before surgery, fresh urine and blood serum samples were obtained from human participants scheduled for breast tumor surgery (24 malignant, 6 benign) or healthy participants scheduled for breast reduction surgery (4 control). EVs were directly imaged both in intact ex vivo tissue that was removed during surgery and in samples isolated from biofluids by differential ultracentrifugation. Isolated EVs and freshly excised ex vivo breast tissue samples were imaged with custom nonlinear optical microscopes to extract single-EV optical metabolic signatures of NAD(P)H and FAD autofluorescence. Optical metrics were significantly altered in cases of malignant breast cancer in biofluid-derived EVs and intact tissue EVs compared to control samples. Specifically, urinary isolated EVs showed elevated NAD(P)H fluorescence lifetime in cases of malignant cancer, serum-derived isolated EVs showed decreased optical redox ratio in stage II cancer, but not earlier stages, and exvivo breast tissue showed an elevated number of EVs in cases of malignant cancer. Results further indicated significant differences in the measured optical metabolic signature based on EV source (urine, serum and tissue) within individuals. © 2024. The Author(s).

With the latest advancements in optical bioimaging, rich structural and functional information has been generated from biological samples, which calls for capable computational tools to identify patterns and uncover relationships between optical characteristics and various biomedical conditions. Constrained by the existing knowledge of the novel signals obtained by those bioimaging techniques, precise and accurate ground truth annotations can be difficult to obtain. Here we present a weakly supervised deep learning framework for optical signature discovery based on inexact and incomplete supervision. The framework consists of a multiple instance learning-based classifier for the identification of regions of interest in coarsely labeled images and model interpretation techniques for optical signature discovery. We applied this framework to investigate human breast cancer-related optical signatures based on virtual histopathology enabled by simultaneous label-free autofluorescence multiharmonic microscopy (SLAM), with the goal of exploring unconventional cancer-related optical signatures from normal-appearing breast tissues. The framework has achieved an average area under the curve (AUC) of 0.975 on the cancer diagnosis task. In addition to well-known cancer biomarkers, non-obvious cancer-related patterns were revealed by the framework, including NAD(P)H-rich extracellular vesicles observed in normal-appearing breast cancer tissue, which facilitate new insights into the tumor microenvironment and field cancerization. This framework can be further extended to diverse imaging modalities and optical signature discovery tasks. © 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

Nonlinear optical imaging is a versatile tool that has been proven to be exceptionally useful in various research fields. However, due to the use of photomultiplier tubes (PMTs), the wide application of nonlinear optical imaging is limited by the incapability of imaging under ambient light. In this paper, we propose and demonstrate a new optical imaging detection method based on optical parametric amplification (OPA). As a nonlinear optical process, OPA intrinsically rejects ambient light photons by coherence gating. Periodical poled lithium niobate (PPLN) crystals are used in this study as the media for OPA. Compared to bulk nonlinear optical crystals, PPLN crystals support the generation of OPA signal with lower pump power. Therefore, this characteristic of PPLN crystals is particularly beneficial when using high-repetition-rate lasers, which facilitate high-speed optical signal detection, such as in spectroscopy and imaging. A PPLN-based OPA system was built to amplify the emitted imaging signal from second harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) microscopy imaging, and the amplified optical signal was strong enough to be detected by a biased photodiode under ordinary room light conditions. With OPA detection, ambient-light-on SHG and CARS imaging becomes possible, and achieves a similar result as PMT detection under strictly dark environments. These results demonstrate that OPA can be used as a substitute for PMTs in nonlinear optical imaging to adapt it to various applications with complex lighting conditions.

High-content screening (HCS) and high-throughput screening (HTS) are common processes used in biological research and drug discovery. They allow rapid examination of thousands of compounds tested at the same time for their activity in designed biological assays. After evolving in the 1990s, they quickly became pillars in the pharmaceutical industry, relying on the advances of process automation and adaptation of biochemical assays for small quantities, such as with multiple -well plates. The basic components of HTS and HCS are a miniaturized biological assay, automated transfers and liquid handling steps, and automated quantitative readouts of the assays. However, there has been an increased need for probing complex cellular and subcellular phenotypes as out-puts, such as changes in morphology and metabolic activity. The more common approach of labeling is expensive, time-consuming, and prohibits any usage of labeled cells or their products. Novel label-free noninvasive optical imaging could provide tools for multiparametric evaluation at the scale of biopharmaceutical production as well as for personalized medicine.

The electrical activity of neurons has a spatiotemporal footprint that spans three orders of magnitude. Traditional electrophysiology lacks the spatial throughput to image the activity of an entire neural network; besides, labeled optical imaging using voltage-sensitive dyes and tracking Ca2+ ion dynamics lack the versatility and speed to capture fast-spiking activity, respectively. We present a label-free optical imaging technique to image the changes to the optical path length and the local birefringence caused by neural activity, at 4,000 Hz, across a 200 x 200 mm(2) region, and with micron-scale spatial resolution and 300-pm displacement sensitivity using Superfast Polarization-sensitive Off-axis Full-field Optical Coherence Microscopy (SPoOF OCM). The undulations in the optical responses from mammalian neuronal activity were matched with field-potential electrophysiology measurements and validated with channel blockers. By directly tracking the widefield neural activity at millisecond timescales and micrometer resolution, SPoOF OCM provides a framework to progress from low-throughput electrophysiology to high-throughput ultra-parallel label-free optophysiology.

Label-free optical microscopy has matured as a noninvasive tool for biological imaging; yet, it is criticized for its lack of specificity, slow acquisition and processing times, and weak and noisy optical signals that lead to inaccuracies in quantification. We introduce FOCALS (Fast Optical Coherence, Autofluorescence Lifetime imaging, and Second harmonic generation) microscopy capable of generating NAD(P)H fluorescence lifetime, second harmonic generation (SHG), and polarization-sensitive optical coherence microscopy (OCM) images simultaneously. Multimodal imaging generates quantitative metabolic and morphological profiles of biological samples in vitro, ex vivo, and in vivo. Fast analog detection of fluorescence lifetime and real-time processing on a graphical processing unit enables longitudinal imaging of biological dynamics. We detail the effect of optical aberrations on the accuracy of FLIM beyond the context of undistorting image features. To compensate for the sample-induced aberrations, we implemented a closed-loop single-shot sensorless adaptive optics solution, which uses computational adaptive optics of OCM for wavefront estimation within 2 s and improves the quality of quantitative fluorescence imaging in thick tissues. Multimodal imaging with complementary contrasts improves the specificity and enables multidimensional quantification of the optical signatures in vitro, ex vivo, and in vivo, fast acquisition and real-time processing improve imaging speed by 4-40 x while maintaining enough signal for quantitative nonlinear microscopy, and adaptive optics improves the overall versatility, which enable FOCALS microscopy to overcome the limits of traditional label-free imaging techniques.