We developed a 3D ultrasound biomicroscopy (3D-UBM) imaging system and used it to assess ciliary tissues in the eye. As ultrasound can penetrate opaque ocular tissues, 3D-UBM has a unique ability to creating informative 3D visualization of anterior ocular structures not visible with other, optical imaging modalities. Ciliary body, located behind the iris, is responsible for fluid production making it an important ocular structure for glaucoma. Only 3DUBM allows visualization and measurements of ciliary body. Several steps were required for visualization and quantitative assessment. To reduce eye motion in 3D-UBM volumes, we performed slice alignment using Transformation Diffusion approach to avoid geometric artifacts. We applied noise reduction and aligned the volumes to the optic axis to create 3D renderings of ciliary body in its entirety. We extracted two different sets of images from these volumes, namely en face and radial images. We created a dataset of eye volumes with slices containing ciliary body, segmented by two analyst trainees and approved by two experts. Deep learning segmentation models (UNet and Inception-v3+) were trained on both sets of images using appropriate loss functions. Using en face images and Inception-v3+, and weighted cross entropy loss, we obtained Dice = 0.81±0.04. Using radial images, Inception-v3+, and with Dice loss, results were improved to Dice = 0.89±0.03, probably because radial images enable full usage of the symmetry of the eye. Cyclophotocoagulation (CPC) is a glaucoma treatment that is used to destroy the ciliary body partially or completely and reduce fluid production. 3D-UBM allows one to visualize and quantitatively analyze CPC treatments.
We developed a methodology for 3D assessment of ciliary body of the eye, an important, but understudied tissue, using our new 3D ultrasound biomicroscopy (3D-UBM) imaging system. The ciliary body produces aqueous humor, which if not drained properly, can lead to increased intraocular pressure and glaucoma, a leading cause of blindness. Most medications and some surgical procedures for glaucoma target the ciliary body. Ciliary body is also responsible for focusing-accommodation by muscle contraction and relaxation. UBM is the only imaging modality which can be used to visualize structures behind the opaque iris, such as ciliary body. Our 3D-UBM acquires several hundred high resolutions (50 MHz) 2D-UBM images and creates a 3D volume, enabling heretofore unavailable en face visualizations and quantifications. In this study, we calculated unique 3D biometrics from automated segmentation using deep learning (UNet). Our results show accuracy of 0.93 ± 0.01, sensitivity of 0.79 ± 0.07 and dice score of 0.72 ± 0.07 on deep learning segmentation of ciliary muscle. For an eye, volume of ciliary body was 67.87 mm3, single ciliary process volumes were 0.234 ± 0.093 mm3 with surface areas adjacent to aqueous humor of 3.02 ± 1.07 mm2. Automated and manual measurements of ciliary muscle volume and cross-sectional area are compared which show overestimation in volume measurement but higher agreeability in cross-sectional area measurements.
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