Prediction of anterior chamber volume after implantation of posterior chamber phakic intraocular lens

Abstract

Purpose To predict the anterior chamber volume (ACV) after implantable collamer lens (ICL) implantation based on ICL size and parameters of anterior segment optical coherence tomography (AS-OCT). Design Retrospective study. Methods This study included 222 eyes of 222 patients who underwent ICL implantation at Nagoya Eye Clinic. The patients were divided into two groups: prediction group, for creating the prediction equation (148 eyes, mean age: 32.11 ± 8.04 years), and verification group, for verifying the equation (74 eyes, mean age: 33.03 ± 6.74 years). The angle opening distance (AOD), anterior chamber width (ACW), ACV, anterior chamber depth, lens vault, angle-to-angle distance, angle recess area, and trabecular iris space area were calculated using AS-OCT. A stepwise multiple regression analysis was performed. After the creation of the prediction equation, its accuracy was verified in the verification group. Results The ACV, AOD750, ACW, and ICL size were selected as explanatory variables to predict postoperative ACV. Mean predicted (114.2 ± 21.83 mm3) and actual postoperative ACVs (116.1 ± 25.41 mm3) were not significantly different (P = 0.269); absolute error was 10.59 ± 9.13 mm3. In addition, there was high correlation between actual and predictive ACV (adjusted R2 = 0.6996, p < 0.0001). Bland-Altman plot revealed that there was no addition or proportional error between predicted and actual postoperative ACV. Conclusion Postoperative ACV was accurately predicted using AS-OCT parameters and ICL size. This prediction equation may be useful for making decisions regarding ICL size.

Safety of intraocular pressure measurement using air-puff tonometer after implantable collamer lens implantation

“…8,15 Notably, the E-ICL Dist was affected by SSI (a marker for corneal stiffness), but the E-Iris Dist was not, perhaps because Corvis ST assesses SSI by deforming the central area of the cornea. 15 The E-ICL Dist was measured from the central area of the corneal endothelial layer to the upper surface of the ICL when the cornea was deformed to the highest concavity, while the E-Iris Dist was measured vertically from the margo pupillaris to the paracentral area of the corneal endothelial layer, which deformed only slightly when the cornea was deformed to the highest concavity (Figure 1). These findings imply that soft corneas confer a higher risk for endothelium-ICL contact during IOP measurement using noncontact air-puff tonometers.…”

“…In addition, as the values of ACV, ACA, and ACD decreased remarkably after ICL implantation, adequate preoperative ACV, ACA, and ACD are essential to minimize the risk. 8,15 Notably, the E-ICL Dist was affected by SSI (a marker for corneal stiffness), but the E-Iris Dist was not, perhaps because Corvis ST assesses SSI by deforming the central area of the cornea. 15 The E-ICL Dist was measured from the central area of the corneal endothelial layer to the upper surface of the ICL when the cornea was deformed to the highest concavity, while the E-Iris Dist was measured vertically from the margo pupillaris to the paracentral area of the corneal endothelial layer, which deformed only slightly when the cornea was deformed to the highest concavity (Figure 1).…”

Automated Expert-level Scleral Spur Detection and Quantitative Biometric Analysis on the ANTERION Anterior Segment OCT System

“…8,15,16 In addition, automated measurements of ACW and LV could be beneficial for IOL selection: ACW is helpful in sizing anterior chamber and phakic IOLs, and there is evidence that LV could play an important role in determining effective lens position and calculating IOL power. [18][19][20][21][22][23] Our results demonstrate that rates of scleral spur detection are highly variable under realworld conditions without eyelid retraction during imaging, even among experienced graders. This point, which has not been previously studied, suggests there is differing confidence among graders when deciding whether to mark a scleral spur.…”

“…[18][19][20][21] Biometric parameters based on scleral spur location, such as lens vault (LV) and anterior chamber width (ACW), are potentially useful in IOL selection, but are difficult to measure and therefore rarely used in routine clinical practice. 22,23 Full biometric analysis of AS-OCT images on commercial devices currently requires specialized software and manual marking of scleral spurs, which is expertise-dependent and timeconsuming, thereby presenting a barrier to widespread implementation. 24,25 Prior studies have established the accuracy of scleral spur detection automated using deep learning (DL), a form of artificial intelligence.…”

“…18–21 Biometric parameters based on scleral spur location, such as lens vault (LV) and anterior chamber width (ACW), are potentially useful in IOL selection, but are difficult to measure and therefore rarely used in routine clinical practice. 22,23…”