Title: In Vivo Fluorescence Imaging and Tracking of Circulating Cells and Therapeutic Nanoparticles
Noninvasive enumeration of rare circulating cell populations in small animals is of great importance in many areas of biomedical research, but existing enumeration techniques involve drawing and enriching blood which is known to be problematic. Recently, small animal “in vivo flow cytometry” (IVFC) techniques have been developed, where cells flowing through small arterioles are detected and counted in vivo without the need for drawing blood samples. As such, these techniques allow continuous and non-invasive study of circulating cell populations. However, there is a persistent need for new, higher sensitivity IVFC techniques for studying low-abundance cell types at concentrations i.e. below 100 cells/mL.
To this end, we developed a macroscopic fluorescence imaging system and automated computer vision algorithm that allows in vivo detection, enumeration and tracking of circulating fluorescently labeled cells from multiple large blood vessels in the ear of a mouse. This technique – termed “computer vision IVFC” (CV-IVFC) allows single-cell detection at concentrations of 20 cells/mL of peripheral blood. In addition to in vivo proof of concept validation with multiple myeloma (MM) cells, the performance of CV-IVFC was characterized for low-contrast imaging scenarios, representing conditions of weak cell fluorescent labeling or high background tissue autofluorescence. Our analysis showed that CV-IVFC was capable of efficiently tracking and enumerating circulating cells with at least 50% sensitivity in conditions with 2 orders of magnitude degraded contrast than our in vivo testing. These results support the significant potential utility of CV-IVFC in a wide range of in vivo biological models, for example, cells labeled with constitutively expressed fluorescent proteins.
We also continued refinement of a separate technology platform for rare-cell detection and enumeration termed ‘diffuse fluorescence flow cytometry” (DFFC). This builds on prior DFFC work in our lab. Briefly, two red lasers sequentially illuminate the hind-leg of a mouse, and as fluorescently-labeled cells passed through the DFFC field of view, weak fluorescent “spikes” are detected, allowing us to count them. In this current work, we implemented a “frequency encoding” scheme, where two excitation lasers are modulated at set frequencies. Fluorescent light from each laser can be detected simultaneously and split by frequency, allowing better discrimination of noise, better sensitivity and better cell localization. The details of this design and preliminary work is shown.
Last, in a separate project, we developed and tested a broad-field transmission fluorescence imaging system to observe nanoparticle (NP) diffusion in bulk biological tissue in mice. New implantable smart NP coated brachytherapy spacers have recently been developed by Sridhar et. al. which allow controlled, long-term release of chemotherapeutic drugs into tumors. However, kinetics of NP (drug) diffusion over time is still poorly understood, and new methods for controlling and optimizing this release are needed. Our imaging system allowed us to quantify diffusion both in phantoms in vitro and in mice in vivo. We performed in vitro studies with free dye and NPs of different sizes (30 nm and 200 nm) in agar gel phantoms and analyzed the diffusion over time. It was found that the free dye diffusion coefficient was orders of magnitude larger than both NP types verifying that diffusion could be controlled based on particle size. We also performed preliminary studies in mice, where functionalized brachytherapy spacers were implanted into the hind flank of nude mice. Continuous diffusion of free dye and NPs was observed, with maximal diffusion areas observed on day 4 and 6 for 30 and 200 nm NPs, respectively. Our fluorescence imaging system was capable of robustly quantifying this size-dependent diffusion. In the future, we will use it to optimize and control drug delivery from smart nanoparticles over time.
Professor Mark Niedre (advisor)
Professor Charles DiMarzio
Professor Srinivas Sridhar