Comparison of ultrasound biomicroscopy and ultrasonographic parameters in eyes with phacomorphic glaucoma and eyes with mature cataract.

Purpose: To compare data on anatomical and biometric parameters, and their combination, obtained by using ultrasound biomicroscopy (UBM) and A-scan in eyes with phacomorphic glaucoma (PG) and eyes with mature cataract and to determine differences that may predispose to development of PG.

Methods: Eighty patients (80 eyes) were enrolled in this cross-sectional study. Anterior chamber parameters, namely anterior chamber depth (ACD), angle-opening distance (AOD), iris-lens contact distance (ILCD), and trabecular-ciliary process distance (TCPD), among other parameters, were assessed by UBM (35 MHz), while axial length (AL) and lenticular thickness (LT) were determined by A-scan biometry. Absolute lenticular position (ALP) and relative lenticular position (RLP) were also compared.

Results: The mean AL of eyes with PG was less (P = 0.64) than the mean AL of eyes with mature cataract. The mean ILCD value in eyes with PG (1.30 ± 0.78 mm) was significantly higher (P = 0.0015) than that in eyes with mature cataract (0.86 ± 0.32 mm). The mean AOD value in eyes with PG (0.15 ± 0.10 mm) was significantly lower (P < 0.0001) than that in eyes with mature cataract (0.23 ± 0.06 mm); similarly, the mean RLP value in eyes with PG (0.20 ± 0.02) was significantly lower (P < 0.0001) than that in eyes with mature cataract (0.17 ± 0.02). TCPD showed negative correlation with LT r = -0.514; P = 0.017, r  = 0.264, in eyes with phacomorphic glaucoma and mature cataracts showed significant negative correlation of ILCD with AL (r = -0.575; P = 0.025, r  = 0.330).

Conclusion: The results of UBM examination suggest that there are multiple mechanisms underlying the pathophysiology of PG, namely crowding of the anterior segment, increased iris-lens contact distance, and a more pronounced anterior shift of the lens. Simultaneous evaluation of anatomic and biometric parameters can improve diagnostic accuracy in predicting cases at risk for PG.