Moxifloxacin based axially swept wide-field fluorescence microscopy for high-speed imaging of conjunctival goblet cells

Abstract

Goblet cells (GCs) in the conjunctiva are specialized epithelial cells producing mucins on the ocular surface. GCs play important roles in maintaining homeostasis of the ocular surface, and GC dysfunction is associated with various complications including dry eye diseases. Current GC examination methods, which are conjunctival impression cytology and confocal reflection microscopy, have limitations for routine examination. Fluorescence microscopy using moxifloxacin was recently introduced as a non-invasive and high-contrast imaging method, but further development is needed to be used for GC examination. Here we developed a non-invasive high-speed high-contrast GC imaging method, called moxifloxacin based axially swept wide-field fluorescence microscopy (MBAS-WFFM). This method acquired multiple fluorescence images with the axial sweeping of the focal plane to capture moxifloxacin labeled GCs on the tilted conjunctival surface in focus and generated all-in-focus images by combining the acquired images. The imaging field of view and imaging speed were increased to 1.6 mm × 1.6 mm and 30 fps. An image processing method was developed for the analysis of GC density. MBAS-WFFM was applied to alkali burn mouse models and detected GC damage and recovery via longitudinal imaging. MBAS-WFFM could assess the status of GCs rapidly and non-invasively. We anticipate MBAS-WFFM to be a starting point for non-invasive GC examination and the diagnosis of GC associated diseases. For example, MBAS-WFFM could be used to classify dry eye diseases into detail categories for effective treatment.

Fig. 1.

A schematic of MBAS-WFFM system and a stack of axially swept WFFM images. L1: achromatic lens (f = 150 mm), L2: achromatic lens (f = 150 mm), L3: achromatic lens (f = 50 mm), L4: objective lens, EF: excitation filter, BS: dichroic mirror, BF: emission filter. Red arrows indicate in-focus areas in the WFFM images.

Fig. 2.

Image processing flowchart. (a) a stack of axially swept WFFM images, (b) an all-in-focus image reconstructed by using an image stacking algorithm (FSTACK), (c) a magnified image from the selected region of interest (ROI) in the all-in-focus image, (d) a contrast enhanced image by using bilateral filter and contrast-limited adaptive histogram equalization, (e) a binary image, (f) a formula for GC density calculation.

Fig. 3.

MBAS-WFFM images and a bright-field image of the normal mouse conjunctiva, in vivo. (a) A single-plane WFFM image, (b) an all-in-focus MBAS-WFFM image, (c) a bright-field image, (b1) a magnified MBAS-WFFM image in a selected ROI area. Yellow arrows in (c) and (b) mark the identical blood vessel. The green boxes represent the same ROI in the WFFM image and the bright-field image.

Fig. 4.

WFFM and PAS histology images of the conjunctiva in alkali burn mouse models. (a-c): WFFM images before burn (a), immediately after burn (b), and 30 days after burn induction (c). (a1-c1): magnified WFFM images showing the change of individual GC clusters. (d-f): PAS histology images before burn (d), immediately after burn (e), and 30 days after burn induction (f). The area between red dashed lines are selected for GC density calculation. M, Meibomian gland; p, palpebral conjunctiva; f, fornix.