Abstract

We demonstrate a fast two-color widefield fluorescence microendoscopy system capable of simultaneously detecting several disease targets in intact human ex vivo lung tissue. We characterize the system for light throughput from the excitation light emitting diodes, fluorescence collection efficiency, and chromatic focal shifts. We demonstrate the effectiveness of the instrument by imaging bacteria (Pseudomonas aeruginosa) in ex vivo human lung tissue. We describe a mechanism of bacterial detection through the fiber bundle that uses blinking effects of bacteria as they move in front of the fiber core providing detection of objects smaller than the fiber core and cladding (∼3 μm ∼3 μm ). This effectively increases the measured spatial resolution of 4 μm 4 μm . We show simultaneous imaging of neutrophils, monocytes, and fungus (Aspergillus fumigatus) in ex vivo human lung tissue. The instrument has 10 nM and 50 nM sensitivity for fluorescein and Cy5 solutions, respectively. Lung tissue autofluorescence remains visible at up to 200 fps camera acquisition rate. The optical system lends itself to clinical translation due to high-fluorescence sensitivity, simplicity, and the ability to multiplex several pathological molecular imaging targets simultaneously.

Highlights

  • Clinical molecular imaging (MI) covers a broad range of techniques, including fluorescence, positron emission tomography, single photon emission computed tomography (CT), and magnetic resonance imaging.[1]

  • We focus on advancing fluorescence-based MI microendoscopy of the distal lung.[2]

  • We show that camera-based systems provide a robust and economical route to multicolor fluorescence detection

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Summary

Introduction

Clinical molecular imaging (MI) covers a broad range of techniques, including fluorescence, positron emission tomography, single photon emission computed tomography (CT), and magnetic resonance imaging.[1]. Our evolving strategy is to deploy custom smartprobes alongside pulmonary microendoscopy in vivo to image disease relevant targets

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