(1) Purpose: To measure the change in vessel density (VD) and the flow area (FA) on the retina of eyes with primary angle-closure diseases (PACD), including primary angle-closure suspect (PACS), primary angle-closure (PAC), acute primary angle-closure (APAC) and primary angle-closure glaucoma (PACG). (2) Methods: Patients with PACD were prospectively enrolled in this study. All participants underwent thorough ophthalmic examinations. The mean defect (MD), retinal nerve fiber layer (RNFL), ganglion cell complex (GCC) thickness, VD measurement, and blood FA were measured. (3) Results: A total of 147 eyes from 121 subjects were included in this study. The VD of the nerve head layer was significantly lower in PACG and APAC (all p < 0.001). APAC and PACG had lower FA of all layers, except for the choroid layer (p < 0.05). The macular VD of the whole image and blood FA in the superficial layer was significantly lower in PACG (all p < 0.001). The MD, RNFL, and GCC thickness demonstrated a strong correlation with whole image VD in the superficial layer (p < 0.001), while the inside disc VD did not show a significant correlation with MD, RNFL, and GCC thickness (p > 0.05). (4) Conclusions: There was a significant decrease in the VD and FA on the optic disc as well as the VD and FA of the superficial layer in the macular area in APAC and PACG. The changes in VD and FA are correlated with the severity of the glaucomatous structural damage and functional impairment.

Background: The imaging and analysis of the ciliary body (CB) are valuable in many potential clinical applications. This study aims to demonstrate the anatomy characteristics of CB using radial and transverse imaging of ultrasound biometric microscopy (UBM) in healthy Chinese subjects, and to explore the determining factors. Methods: Fifty-four eyes of 30 healthy Chinese subjects were evaluated. Clinical data, including age, body mass index (BMI), intraocular pressure (IOP), axial length (AL), and lens thickness (LT), were collected. Radial and transverse UBM measurements of the ciliary body were performed. Anterior chamber depth (ACD), ciliary sulcus diameter (CSD), ciliary process length (CPL), ciliary process density (CPD), ciliary process area (CPA), ciliary muscle area (CMA), ciliary body area (CBA), ciliary body thickness (CBT₀, CBT₁, and CBT_max), anterior placement of ciliary body (APCB), and trabecular-ciliary angle (TCA) of four (superior, nasal, inferior, and temporal) quadrants were measured. Results: The average CPL was 0.513 ± 0.074 mm, and the average CPA was 0.890 ± 0.141 mm². CPL and CPA tended to be longer and larger in the superior quadrant (p < 0.001) than in the other three quadrants. Average CPL was significantly correlated with AL (r = 0.535, p < 0.001), ACD (r = 0.511, p < 0.001), and LT (r = −0.512, p < 0.001). Intraclass correlation coefficient (ICC) scores were high for CPL (0.979), CPD (0.992), CPA (0.966), CMA (0.963), and CBA (0.951). Conclusions: In healthy Chinese subjects, CPL was greatest in the superior quadrant, followed by the inferior, temporal, and nasal quadrants, and CPA was largest in the superior quadrant, followed by the tempdoral, inferior, and nasal quadrants. Transverse UBM images can be used to measure the anatomy of the ciliary process with relatively good repeatability and reliability.

Primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG) are prevailing eye diseases that can lead to blindness. In order to provide a non-invasive diagnostic method for glaucoma, we investigated the feasibility of using drop-coating deposition Raman spectroscopy (DCDRS) to discriminate glaucoma patients from healthy individuals based on tear samples. Tears from 27, 19 and 27 POAG patients, PACG patients and normal individuals, respectively, were collected for Raman measurement. For high-dimension data analysis, principal component analysis–linear discriminant analysis (PCA-LDA) was used to discriminate the features of the Raman spectra, followed by a support vector machine (SVM) used to classify samples into three categories, which is called a PCA-LDA-based SVM. The differences in the characteristic peaks of Raman spectra between glaucoma patients and normal people were related to the different contents of various proteins and lipids. For the PCA-LDA-based SVM, the total accuracy reached 93.2%. With the evaluation of 30% test dataset validation, the classification accuracy of the model was 90.9%. The results of this work reveal that tears can be used for Raman detection and discrimination by combining the process with the PCA-LDA-based SVM, supporting DCDRS being a potential method for the diagnosis of glaucoma in the future.