Using machine learning to predict post-operative depth of focus after cataract surgery with implantation of Tecnis Symfony

Abstract

Objective: To predict post-operative depth of focus (DoF) using machine learning techniques after cataract surgery with Tecnis Symfony implantation and determine associated impact factors. Methods: This was a retrospective cohort study among patients receiving Tecnis Symfony implantation, an extended-range-of-vision intraocular lens, during October 2016–January 2020 at Daqing Oilfield General Hospital, China. Four different predictive models were used to predict good post-operative DoF (⩾2.5 D): Extreme Gradient Boost (XGBoost), random forest (RF), LASSO penalized regression, and multivariable logistic regression (MLR). Apriori algorithm was employed to further explore the association between patient attributes and DoF. Results: A total of 182 unique cases (143 patients) were included. The XGBoost model produced the best predictive accuracy compared to RF, LASSO, and MLR models. Overall performance of the best fitting XGBoost model was as follows: accuracy = 70.3%, AUC = 80.2%, sensitivity = 65.5%, and specificity = 87.5%. The Apriori algorithm identified six preoparative attributes with substantial effects on good post-operative DoF: low anterior chamber depth (ACD) (1.9 to <2.5 mm), smaller pupil size (1.7 to <2.5 mm), low-to-mid axial length (21 to <23 mm), minimum astigmatism degree (−0.2 to 0 diopter), low IOP (9 to <12 mmHg), and medium lens target refractive error (−0.5 to <−0.25 diopter). Conclusions: Machine Learning models were able to predict good post-operative DoF among cataract patients receiving a Tecnis Symfony ocular lens implantation. The accuracy of the model was above 70%. The Apriori algorithm identified six preoperative attributes with a strong association with post-operative DoF.

Retrospective Case Series on The Enduring Rotational Stability of The AcrySof IQ Toric Intraocular Lens in Cataract Patients Suffering from Myopia

“…Visual acuity was measured following surgery. The measurement of diopter and IOL rotation is a standard practice for assessing the effectiveness of Toric IOL surgery [16][17] . Within the scope of the research, the effectiveness of IOL in correcting corneal astigmatism in patients with high myopia and cataracts was demonstrated over a 24-48-month follow-up period.…”

The Zhu-Lu formula: a machine learning-based intraocular lens power calculation formula for highly myopic eyes

“…For a machine learning based formula, plenty and credible training data are crucial to its accuracy and stability. Furthermore, the XGBoost and SVR algorithms are both highly accurate in data prediction and have helped with numerous situations in ophthalmology, such as diabetic retinopathy diagnosis, implantable collamer lens size selection, and post-cataract-surgery focus depth prediction [ 23 – 25 ]. Using the XGBoost, our group has previously developed an enhanced calculator for the BUII formula, which demonstrated improved prediction accuracy in highly myopic eyes [ 26 , 27 ].…”

Artificial intelligence in cataract: What’s new?

“…However, the study concluded that the utility of supervised ML was very limited in everyday scenario as compared to the standard regression formulas. Liu et al [20] employed ML algorithms for predicting the depth of focus post-cataract surgery in patients receiving Tecnis Symfony IOL. The authors enrolled 182 eyes and employed four AI prediction methodologies, namely multivariable logistic regression, Extreme Gradient Boost, LASSO penalised regression, and RF.…”

“…[5] In addition, a prevalence of 0.32-22.9/10,000 children has been noted for paediatric cataracts. [6] In recent times, the use of AI has been described in cataract detection, [7][8][9][10][11][12][13][14][15] cataract grading, [5] intraocular lens (IOL)-related calculations [16][17][18][19][20][21][22][23], and even as an aid in cataract surgery. [24][25][26][27] The developing countries, where healthcare distribution is not equitable, can greatly benefit from such wide-ranging applications of AI.…”