OBJECTIVE The use of the optical contrast agent sodium fluorescein (NaFl) to guide resection of gliomas has been under investigation for decades. Although this imaging strategy assumes the agent remains confined to the vasculature except in regions of blood-brain barrier (BBB) disruption, clinical studies have reported significant NaFl signal in normal brain tissue, limiting tumor-to-normal contrast. A possible explanation arises from earlier studies, which reported that NaFl exists in both pure and protein-bound forms in the blood, the former being small enough to cross the BBB. This study aims to elucidate the kinetic binding behavior of NaFl in circulating blood and its effect on NaFl accumulation in brain tissue and tumor contrast. Additionally, the authors examined the blood and tissue kinetics, as well as tumor uptake, of a pegylated form of fluorescein selected as a potential optical analog of gadolinium-based MRI contrast agents. METHODS Cohorts of mice were administered one of the following doses/forms of NaFl: 1) high human equivalent dose (HED) of NaFl, 2) low HED of NaFl, or 3) pegylated form of fluorescein. In each cohort, groups of animals were euthanized 15, 30, 60, and 120 minutes after administration for ex vivo analysis of fluorescein fluorescence. Using gel electrophoresis and fluorescence imaging of blood and brain specimens, the authors quantified the temporal kinetics of bound NaFl, unbound NaFl, and pegylated fluorescein in the blood and normal brain tissue. Finally, they compared tumor-to-normal contrast for NaFl and pegylated-fluorescein in U251 glioma xenografts. RESULTS Administration of NaFl resulted in the presence of unbound and protein-bound NaFl in the circulation, with unbound NaFl constituting up to 70% of the signal. While protein-bound NaFl was undetectable in brain tissue, unbound NaFl was observed throughout the brain. The observed behavior was time and dose dependent. The pegylated form of fluorescein showed minimal uptake in brain tissue and improved tumor-to-normal contrast by 38%. CONCLUSIONS Unbound NaFl in the blood crosses the BBB, limiting the achievable tumor-to-normal contrast and undermining the inherent advantage of tumor imaging in the brain. Dosing and incubation time should be considered carefully for NaFl-based fluorescence-guided surgery (FGS) of glioma. A pegylated form of fluorescein showed more favorable normal tissue kinetics that translated to higher tumor-to-normal contrast. These results warrant further development of pegylated-fluorescein for FGS of glioma.

Significance: Quantitative oblique back-illumination microscopy (qOBM) is a recently developed label-free imaging technique that enables 3D quantitative phase imaging of thick scattering samples with epi-illumination. Here, we propose dynamic qOBM to achieve functional imaging based on subcellular dynamics, potentially indicative of metabolic activity. We show the potential utility of this novel technique by imaging adherent mesenchymal stromal cells (MSCs) grown in bioreactors, which can help address important unmet needs in cell manufacturing for therapeutics.Aim: We aim to develop dynamic qOBM and demonstrate its potential for functional imaging based on cellular and subcellular dynamics.Approach: To obtain functional images with dynamic qOBM, a sample is imaged over a period of time and its temporal signals are analyzed. The dynamic signals display an exponential frequency response that can be analyzed with phasor analysis. Functional images of the dynamic signatures are obtained by mapping the frequency dynamic response to phasor space and colorcoding clustered signals.Results: Functional imaging with dynamic qOBM provides unique information related to subcellular activity. The functional qOBM images of MSCs not only improve conspicuity of cells in complex environments (e.g., porous micro-carriers) but also reveal two distinct cell populations with different dynamic behavior. Conclusions:In this work we present a label-free, fast, and scalable functional imaging approach to study and intuitively display cellular and subcellular dynamics. We further show the potential utility of this novel technique to help monitor adherent MSCs grown in bioreactors, which can help achieve quality-by-design of cell products, a significant unmet need in the field of cell therapeutics. This approach also has great potential for dynamic studies of other thick samples, such as organoids.

Quantitative oblique back-illumination microscopy (qOBM) is an emerging label-free optical imaging technology that enables 3D, tomographic quantitative phase imaging (QPI) with epi-illumination in thick scattering samples. In this work, we present a robust optimization of a flexible, fiber-optic-based qOBM system. Our approach enables in silico optimization of the phase signal-to-noise-ratio over a wide parameter space and obviates the need for tedious experimental optimization which could easily miss optimal conditions. Experimental validations of the simulations are also presented and sensitivity limits for the probe are assessed. The optimized probe is light-weight (∼40g) and compact (8mm in diameter) and achieves a 2µm lateral resolution, 6µm axial resolution, and a 300µm field of view, with near video-rate operation (10Hz, limited by the camera). The phase sensitivity is <20nm for a single qOBM acquisition (at 10Hz) and a lower limit of ∼3 nm via multi-frame averaging. Finally, to demonstrate the utility of the optimized probe, we image (1) thick, fixed rat brain samples from a 9L gliosarcoma tumor model and (2) freshly excised human brain tissues from neurosurgery. Acquired qOBM images using the flexible fiber-optic probe are in excellent agreement with those from a free-space qOBM system (both in-situ), as well as with gold-standard histopathology slices (after tissue processing).

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Slide-free microscopy techniques have been proposed for accelerating standard histopathology and intraoperative guidance. One such technology is quantitative oblique back-illumination microscopy (qOBM), which enables real-time, label-free quantitative phase imaging of thick, unsectioned in-vivo and ex-vivo tissues. However, the grayscale phase contrast provided by qOBM differs from the colored histology images familiar to pathologists and clinicians, limiting its current potential for adoption. Here we demonstrate the application of unsupervised deep learning using a Cycleconsistent Generative Adversarial Network (CycleGAN) model to transform qOBM images into virtual hematoxylin and eosin (H&E)-stained images. The models were trained on a dataset of qOBM and H&E images of similar regions in excised brain tissue from a 9L gliosarcoma rat tumor model. We observed successful qOBM-to-H&E conversion of both uninvolved and tumor-containing specimens, as demonstrated by a classifier test. We describe several crucial preprocessing steps that improve the quality of conversion, such as intensity inversion, pixel harmonization, and color normalization. This unsupervised deep learning framework does exhibit occasional subpar performance; for example, as with GANs in general, it can create so-called "hallucinations", displaying features not actually present in the original qOBM images. We anticipate that this behavior can be minimized with more extensive training and deployment of advanced ML techniques, and that virtual-H&E-converted qOBM imaging will prove safe and appropriate for rapid tissue imaging applications.