Intraocular Pressure Measurement Using Ocular Response Analyzer, Dynamic Contour Tonometer, and Scheimpflug Analyzer Corvis ST

Agreement of intraocular pressure measurement with Corvis ST, non-contact tonometer, and Goldmann applanation tonometer in children with ocular hypertension and related factors

AIM

To access the agreement of intraocular pressure (IOP) values obtained from biomechanically corrected tonometer [Corvis ST (CST)], non-contact tonometer (NCT), and Goldmann applanation tonometer (GAT) in children with NCT measured-IOP (NCT-IOP) values of 22 mm Hg or more, and related factors.

METHODS

A total of 51 eyes with NCT-IOP≥22 mm Hg in children aged 7 to 14y were examined and IOP was measured by CST, NCT, and GAT. Based on GAT measured IOP (GAT-IOP), ocular hypertension (OHT) group (≥22 mm Hg, 24 eyes) and the non-OHT group (<22 mm Hg, 27 eyes) were defined. We compared the agreement of the three measurements, i.e., CST measured IOP (CST-IOP), GAT-IOP, and NCT-IOP, and further analyzed the correlation between the differences in tonometry readings, central corneal thickness (CCT), axial length (AL), optic disc rim volume, and age.

RESULTS

Compared with the OHT group, thicker CCT, larger rim volume, and higher differences between NCT-IOP and GAT-IOP, were found in the non-OHT group. The differences between CST-IOP and GAT-IOP were lower than the differences between NCT-IOP and GAT-IOP in both groups. The mean differences in CST-IOP and GAT-IOP were 1.26 mm Hg (95% limit of agreement ranged from 0.1 to 2.41 mm Hg, OHT group) and 1.20 mm Hg (95% limit of agreement ranged from -0.5 to 3.00 mm Hg, non-OHT group), and the mean differences in NCT and GAT were 3.90 mm Hg (95% limit of agreement ranged from -0.19 to 9.70 mm Hg, OHT group) and 6.00 mm Hg (95% limit of agreement ranged from 1.50 to 10.50 mm Hg, non-OHT group). The differences between CST-IOP and GAT-IOP were not related to CCT, age, and AL in both groups; while the differences between NCT-IOP and GAT-IOP were related to CCT in the OHT group (r=0.93, P<0.001) and to CCT and AL in the non-OHT group (r=0.66, P<0.001, r=-0.81, P<0.001).

CONCLUSION

The accuracy of NCT in the diagnosis of pediatric OHT is low. The agreement of CST-IOP and GAT-IOP was significantly higher in children with and without OHT than in those with NCT-IOP and GAT-IOP. Therefore, CST can be used as a good alternative for IOP measurement in children. The impacts of CCT and AL on NCT measurement need to be fully considered when managing childhood IOP.

A Mechanical Evaluation of a Robot-Assisted Cutting Cornea Based on Force Response

The aim of this paper is to propose laws of trephine operation based on a robot-assisted cutting cornea in order to obtain better microsurgical effects for keratoplasty. Using a trephine robot integrated with a microforce sensor and a handheld trephine manipulator, robotic and manual experiments were performed, with porcine corneas as the test subjects. The effect of trephine operational parameters on the results reflected by the biomechanical response is discussed, and the parameters include linear velocity, rotating angle, and angular velocity. Using probability density functions, the distributions of the manual operational parameters show some randomness, and there is a large fluctuation in the trephine force during the experiments. The biomechanical response shows regular trends in the robotic experiments even under different parameters, and compared to manual trephination, the robot may perform the operation of trephine cornea cutting more stably. Under different operational parameters, the cutting force shows different trends, and the optimal initial parameters that result in better trephine effects can be obtained based on the trends. Based on this derived law, the operational parameters can be set in robotic trephination, and surgeons can also be specially trained to achieve a better microsurgical result.

Introduction and Clinical Validation of an Updated Biomechanically Corrected Intraocular Pressure bIOP (v2)

PURPOSE

To improve the stability of the Corvis ST biomechanically-corrected intraocular pressure measurements (bIOP) after refractive surgery and its independence of corneal biomechanics.

METHODS

A parametric study was carried out using numerical models simulating the behavior of the eye globe under the effects of IOP and Corvis ST external air pressure and used to develop a new algorithm for bIOP; bIOP(v2). It was tested on 528 healthy participants to evaluate correlations with CCT and age. Its ability to compensate for the geometrical changes was tested in 60 LASIK and 80 SMILE patients with six months follow up. The uncorrected Corvis ST IOP (CVS-IOP) and the two versions of biomechanically corrected IOP; bIOP(v1) and bIOP(v2), were compared.

RESULTS

In the healthy dataset, bIOP(v2) had weak and non-significant correlation with both CCT (R = -0.048, p = .266) and age (R = 0.085, p = .052). For bIOP(v1), the correlation was non-significant with CCT (R = -0.064, p = .139) but significant with age (R = -0.124, p < .05). In both LASIK and SMILE groups, the median change in bIOP(v2) following surgery was below 1 mmHg at follow-up stages and the interquartile range was smaller than both bIOP(v1) and CVS-IOP.

CONCLUSION

The bIOP(v2) algorithm performs better than bIOP(v1) and CVS-IOP in terms of correlation with CCT and age. The bIOP(v2) also demonstrated the smallest variation after LASIK and SMILE refractive surgeries indicating improved ability to compensate for geometrical changes.

Intraocular pressure after myopic laser refractive surgery measured with a new Goldmann convex prism: correlations with GAT and ORA

Background

The purpose of this study is to describe measurements using a newly developed modified Goldmann convex tonometer (CT) 1 year after myopic laser refractive surgery. Intraocular pressure (IOP) measurements were compared with IOP values obtained by Goldmann applanation tonometer (GAT), and Ocular Response Analyzer (ORA).

Methods

Prospective double-masked study performed on thirty eyes of thirty patients that underwent laser in situ keratomileusis (LASIK; n = 19) or photorefractive keratectomy (PRK; n = 11). IOP was measured before and 3 and 12 months after surgery. Intraclass correlation coefficient (ICC) and Bland-Altman plot were calculated to assess the agreement between GAT, CT, IOPg (Goldmann-correlated IOP) and IOPcc (corneal-compensated IOP) from ORA.

Results

Twelve months after LASIK, IOP measured with CT showed the best correlation with IOP measured with GAT before surgery (GATpre) (ICC = 0.886, 95% CI: 0.703–0.956) (15.60 ± 3.27 vs 15.80 ± 3.22; p < 0.000). However, a moderate correlation was found for IOP measured with IOPcc and CT 12 months after LASIK (ICC = 0.568, 95% CI: − 0.185 – 0.843) (15.80 ± 3.22 vs 12.87 ± 2.77; p < 0.004). Twelve months after PRK, CT showed a weak correlation (ICC = − 0.266, 95% CI: − 3.896 – 0.663), compared to GATpre (17.30 ± 3.47 vs 16.01 ± 1.45; p < 0.642), as well as poor correlation (ICC = 0.256, 95% CI: − 0.332 – 0.719) with IOPcc (17.30 ± 3.47 vs 13.38 ± 1.65; p < 0.182).

Conclusions

Twelve months after LASIK, IOP measured with CT strongly correlated with GAT before surgery and could therefore provide an alternative method for measuring IOP after this surgery. More studies regarding this new convex prism are needed to assess its accuracy.

Association Between Diabetes, Diabetic Retinopathy, and Glaucoma

PURPOSE OF REVIEW

The strength of the relationship between diabetes, diabetic retinopathy (DR), and glaucoma remains controversial. We review evidence supporting and refuting this association and explore mechanistic pathological and treatment relationships linking these diseases.

RECENT FINDINGS

While studies have shown diabetes/DR may increase the risk for glaucoma, this remains inconsistently demonstrated. Diabetes/DR may contribute toward glaucomatous optic neuropathy indirectly (either by increasing intraocular pressure or vasculopathy) or through direct damage to the optic nerve. However, certain elements of diabetes may slow glaucoma progression, and diabetic treatment may concurrently be beneficial in glaucoma management. Diabetes plays a significant role in poor outcomes after glaucoma surgery. While the relationship between diabetes/DR and glaucoma remains controversial, multiple mechanistic links connecting pathophysiology and management of diabetes, DR, and glaucoma have been made. However, a deeper understanding of the causes of disease association is needed.