In Vivo Quantification of Anterior and Posterior Chamber Volumes in Mice: Implications for Aqueous Humor Dynamics

Abstract

Purpose: Aqueous humor inflow rate, a key parameter influencing aqueous humor dynamics, is typically measured by fluorophotometry. Analyzing fluorophotometric data depends, inter alia, on the volume of aqueous humor in the anterior chamber but not the posterior chamber. Previous fluorophotometric studies of the aqueous inflow rate in mice have assumed the ratio of anterior:posterior volumes in mice to be similar to those in humans. Our goal was to measure anterior and posterior chamber volumes in mice to facilitate better estimates of aqueous inflow rates.

Methods: We used standard near-infrared (NIR) optical coherence tomography (OCT) and robotic visible-light OCT (vis-OCT) to visualize, reconstruct, and quantify the volumes of the anterior and posterior chambers of the mouse eye in vivo. We used histology and micro-computed tomography (CT) scans to validate relevant landmarks from ex vivo tissues and facilitate in vivo measurement.

Results: Posterior chamber volume is 1.1 times the anterior chamber volume in BALB/cAnNCrl mice, that is, the anterior chamber constitutes about 47% of the total aqueous humor volume, which is very dissimilar to the situation in humans. Anterior chamber volumes in 2-month-old BALB/cAnNCrl and C57BL6/J mice were 1.55 ± 0.36 µL (n = 10) and 2.05 ± 0.25 µL (n = 10), respectively. This implies that previous studies likely overestimated the aqueous inflow rate by approximately twofold.

Conclusions: It is necessary to reassess previously reported estimates of aqueous inflow rates and, thus, aqueous humor dynamics in the mouse. For example, we now estimate that only 0% to 15% of aqueous humor drains via the pressure-independent (unconventional) route, similar to that seen in humans and monkeys.

Figure 1.

Experimental setup of vis-OCT imaging. (a) Schematic of robotic vis-OCT. Light from an NKT Photonics laser is filtered by a dichroic mirror (DM), spectral shaping filter (SSF), and bandpass filter (BPF). The output light is coupled into a collimator (CL) and split by a 90:10 fiber coupler (FC). The reference arm includes a polarization controller (PC) and dispersion compensation (DC). Light in the sample arm is scanned by a galvanometer scanning mirror (SM) before being focused by a 25-mm scan lens (SL). The interference signal is split by a 50:50 FC into 2 spectrometers. (b) Schematic cross-section of the mouse eye with the anterior chamber shaded in green and the posterior chamber in blue. (c) Eight vis-OCT volumes, with scan planes perpendicular to the incident vis-OCT beam shaded in blue, are acquired around the eye.

Figure 2.

Overview of anterior segment reconstruction. (a) The outer surface of the globe for each sub-volume is extracted and (b) landmark points are identified along the top surface of each sub-volume. The locations of several landmark points are shown by the red dots, whose spatial locations correspond to the red dots in a. (c) The landmark points are registered between adjacent volumes and used to align them. (d) After alignment, all sub-volumes are mapped into a common spatial reference frame.

Figure 3.

Posterior chamber and anterior chamber reconstruction processes. (a) B-scans were segmented using SAM, with the posterior chamber shaded in blue. (b) After segmenting all B-scans, we generated a volumetric representation of the posterior chamber for each volume. A transformation matrix mapped each volume into a common coordinate system and the union of (c) segmented volumes was taken to be the posterior chamber. (d) The transformation matrices were also used to map the OCT structural data into a common reference frame, where (e) the anterior segment of each cross-section was segmented using SAM. (f) The union of the segmented B-scans was used to generate a volumetric representation of the anterior chamber.

Figure 4.

Workflow for identifying the posterior boundary of posterior chamber. (a) Chamber segmentations were used to obtain the posterior boundary of the anterior chamber (green) and the interior boundary of the posterior chamber (blue). (b) These boundaries were taken to coincide with the anterior surface of the lens. (c) An ellipsoid (red) was fit to the lens’ upper boundaries. The center of the ellipsoid and the optical axis of the eye were used to (d) generate a plane at the equator of the eye, approximating the location of the anterior hyaloid membrane. (e) The posterior border of the reconstructed posterior chamber in the montaged B-scans is (f) updated with the estimated position of the anterior hyaloid membrane.

Figure 5.

Validation of reconstruction volume accuracy. (a) Design of the cavity within our phantom. (b) Reconstructed cavity volume using vis-OCT after montaging. (c) SEM image of the 3D-printed phantom. (d) The cavity volumes obtained by water weighing and from the OCT reconstruction agreed to within one percent, with error bars representing the 95% confidence intervals (*P < 0.05; **P < 0.01, ***P < 0.001, ****P < 0.0001).

Figure 6.

Reconstruction of the anterior and posterior chambers. (a) Isometric view of the reconstructed anterior segment with anterior chamber (AC) in green and posterior chamber (PC) in blue. (b) Posterior view of reconstruction with the AC and PC shaded in green and blue respectively. (c) Montaged B-scan of the anterior segment with the anterior chamber overlayed in green and the posterior chamber in blue. (d) Comparison of the anterior chamber volume and posterior chamber volume in BALB/cAnNCrl mice reveals that the volumes of aqueous humor in the anterior and posterior chambers are comparable. (e) Comparison of anterior chamber volumes in 2-month-old BALB/cAnNCrl albino mice and 2-month-old C57BL/6J mice reveals that the anterior chamber is larger in the C57BL/6J mice (*P < 0.05; **P < 0.01, ***P < 0.001, ****P < 0.0001).