As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL pow...As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL power calculation methods have evolved and innovated throughout time, from early theoretical and regression formulas to nonlinear formulas for estimating effective lens position (ELP), multivariable formulas, and innovative formulas that use optical principles and AI-based online formulas. This paper thoroughly discusses the development and iteration of traditional IOL calculation formulas, the emergence of new IOL calculation formulas, and the selection of IOL calculation formulas for different patients in the era of refractive cataract surgery, serving as a reference for “personalized” IOL implantation in clinical practice.展开更多
AIM:To investigate the influence of postoperative intraocular lens(IOL)positions on the accuracy of cataract surgery and examine the predictive factors of postoperative biometry prediction errors using the Barrett Uni...AIM:To investigate the influence of postoperative intraocular lens(IOL)positions on the accuracy of cataract surgery and examine the predictive factors of postoperative biometry prediction errors using the Barrett Universal II(BUII)IOL formula for calculation.METHODS:The prospective study included patients who had undergone cataract surgery performed by a single surgeon from June 2020 to April 2022.The collected data included the best-corrected visual acuity(BCVA),corneal curvature,preoperative and postoperative central anterior chamber depths(ACD),axial length(AXL),IOL power,and refractive error.BUII formula was used to calculate the IOL power.The mean absolute error(MAE)was calculated,and all the participants were divided into two groups accordingly.Independent t-tests were applied to compare the variables between groups.Logistic regression analysis was used to analyze the influence of age,AXL,corneal curvature,and preoperative and postoperative ACD on MAE.RESULTS:A total of 261 patients were enrolled.The 243(93.1%)and 18(6.9%)had postoperative MAE<1 and>1 D,respectively.The number of females was higher in patients with MAE>1 D(χ^(2)=3.833,P=0.039).The postoperative BCVA(logMAR)of patients with MAE>1 D was significantly worse(t=-2.448;P=0.025).After adjusting for gender in the logistic model,the risk of postoperative refractive errors was higher in patients with a shallow postoperative anterior chamber[odds ratio=0.346;95% confidence interval(CI):0.164,0.730,P=0.005].CONCLUSION:Risk factors for biometry prediction error after cataract surgery include the patient’s sex and postoperative ACD.Patients with a shallow postoperative anterior chamber are prone to have refractive errors.展开更多
AIM:To evaluate the accuracy of intraocular lens(IOL)power calculation formulas with/without preoperative aphakic anterior chamber depth(aph-ACD)in pediatric aphakia.METHODS:A total of 102 pediatric patients(150 eyes)...AIM:To evaluate the accuracy of intraocular lens(IOL)power calculation formulas with/without preoperative aphakic anterior chamber depth(aph-ACD)in pediatric aphakia.METHODS:A total of 102 pediatric patients(150 eyes)undergoing secondary IOL implantation were divided into two groups(in-the-bag or ciliary sulcus).Prediction error was calculated for 9 IOL power calculation formulas,including:1)not requiring ACD:Hoffer Q,Holladay 1,SRK/T;2)usable without or with entering ACD:Barrett Universal II(BUII),Emmetropia Verifying Optical(EVO)2.0,and Ladas Artificial Intelligence Super(Ladas AI);3)requiring ACD:Haigis,Kane,and Pearl-DGS.Mean prediction error(ME),mean absolute error(MAE),median absolute error(MedAE)and the percentage of eyes within±0.25,±0.50,±0.75,and±1.00 D were calculated.RESULTS:For the BUII,EVO 2.0,and Ladas AI,with aph-ACD demonstrated a higher MedAE compared to without aph-ACD(BUII:1.27 vs 1.13 D,EVO 2.0:1.26 vs 1.06 D,Ladas AI:1.30 vs 1.10 D;all P<0.05).Formulas requiring ACD(Haigis,Kane,and Pearl-DGS)exhibited larger MedAE than those not requiring aph-ACD(Hoffer Q,Holladay 1,and SRK/T;P<0.05).In the capsular group,the percentage of eyes within±1.00 D ranged from 44.83%to 74.14%,and it was 19.57%to 32.61%in the sulcus group.CONCLUSION:The introduction of aph-ACD does not improve the accuracy of IOL calculation for pediatric aphakia,regardless of in-the-bag or sulcus IOL secondary implantation.The relationship between aph-ACD and effective lens position in pediatric aphakia warrants further study.展开更多
Objective:To compare the accuracy of six intraocular lens(IOL)power calculation methods in post-myopic-LASIK eyes.Methods:Post-myopic-LASIK patients scheduled for cataract surgery were enrolled.Mean error(ME),mean abs...Objective:To compare the accuracy of six intraocular lens(IOL)power calculation methods in post-myopic-LASIK eyes.Methods:Post-myopic-LASIK patients scheduled for cataract surgery were enrolled.Mean error(ME),mean absolute error(MAE),and median absolute error(MedAE)of ASCRS(ASCRS-Max,ASCRS-Average,ASCRS-Min),EVO 2.0,Pearl-DGS,Barrett True-K no-history,Shammas-PL,and Haigis-L were compared.The ASCRS method employed four formulas,including Shammas-PL,Haigis-L,Potvin-Hill Pentacam,and Barrett True-K no-history.Trueness,precision,and accuracy indices were evaluated by comparing trimmed-mean values with heteroscedasticity adjustment.Subgroup analyses were performed based on K value,axial length(AL),and corneal decentered ablation,respectively.Factors influencing prediction errors were analyzed.Results:Totally,87 eyes were analyzed.ASCRS-Min had the lowest MAE(0.79 D)and MedAE(0.62 D),followed by EVO 2.0,Pearl-DGS,and Barrett True-K no-history.It also had the highest percentage of absolute errors within 1.00 D.All methods outperformed ASCRS-Max in accuracy indices,and ASCRS-Min and EVO 2.0 showed superior accuracy indices compared to Shammas-PL and Haigis-L.In the subgroups of lower K value,longer AL,and larger decentration of ablation zone,ASCRS-Min,EVO 2.0,Pearl-DGS,and Barrett True-K no-history generated statistically lower MedAEs than ASCRS-Max.The accuracy of Shammas-PL was associated with AL;the accuracy of Haigis-L was associated with K value and AL;no other significant associations were found.Conclusions:Generally,ASCRS-Min,EVO 2.0,Pearl-DGS,and Barrett True-K no-history achieve relatively better accuracy than the other methods,which might be considered as first choices for IOL power calculation in postmyopic-LASIK eyes.展开更多
Refractive outcomes following cataract surgery in patients that have previously undergone laser refractive surgery have traditionally been underwhelming.This is related to several key issues including the preoperative...Refractive outcomes following cataract surgery in patients that have previously undergone laser refractive surgery have traditionally been underwhelming.This is related to several key issues including the preoperative assessment(keratometry)and intraocular lens power calculations.Peer-reviewed literature is overwhelmed by the influx of methodology to manipulate the corneal or intraocular lens(IOL)powers following refractive surgery.This would suggest that the optimal derivative formula has yet been introduced.This review discusses the problems facing surgeons approaching IOL calculations in these post-refractive laser patients,the existing formulae and programs to address these concerns.Prior published outcomes will be reviewed.展开更多
Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes ...Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL(SN60WF,Alcon)at Miyata Eye Hospital were reviewed and analyzed.Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients,constants of the SRK/T and Haigis formulas were optimized.The SRK/T formula was adapted using a support vector regressor.Prediction errors in the use of adapted formulas as well as the SRK/T,Haigis,Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients.Mean prediction errors,median absolute errors,and percentages of eyes within±0.25 D,±0.50 D,and±1.00 D,and over+0.50 D of errors were compared among formulas.Results:The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas(P<0.001).In the absolute errors,the Hill-RBF and adapted methods were better than others.The performance of the Barrett Universal II was not better than the others for the patient group.There were the least eyes with hyperopic refractive errors(16.5%)in the use of the adapted formula.Conclusions:Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.展开更多
Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes ...Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL(SN60WF,Alcon)at Miyata Eye Hospital were reviewed and analyzed.Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients,constants of the SRK/T and Haigis formulas were optimized.The SRK/T formula was adapted using a support vector regressor.Prediction errors in the use of adapted formulas as well as the SRK/T,Haigis,Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients.Mean prediction errors,median absolute errors,and percentages of eyes within±0.25 D,±0.50 D,and±1.00 D,and over+0.50 D of errors were compared among formulas.Results:The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas(P<0.001).In the absolute errors,the Hill-RBF and adapted methods were better than others.The performance of the Barrett Universal II was not better than the others for the patient group.There were the least eyes with hyperopic refractive errors(16.5%)in the use of the adapted formula.Conclusions:Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.展开更多
Background:Cataract surgery is the most common surgical procedure in ophthalmology.Biometry data and accurate intraocular lens(IOL)calculations are very important in achieving the desired refractive outcomes.The aim o...Background:Cataract surgery is the most common surgical procedure in ophthalmology.Biometry data and accurate intraocular lens(IOL)calculations are very important in achieving the desired refractive outcomes.The aim of this study was to compare measurements using a new optical low coherence reflectometry(OLCR)biometer(OA-2000)and the gold standard partial coherence interferometry(PCI)optical biometer(IOLMaster 500).Methods:Ocular biometry of cataract patients were measured by the OA-2000 and IOLMaster 500 to compare keratometry(K),axial length(AL),anterior chamber depth(ACD),white-to-white(WTW)diameter,and IOL power using the SRK/T formula.Results:One hundred and two eyes of 68 cataract patients were evaluated with the two optical biometers.The mean values of the AL,K,ACD,and WTW differed very little(OCLR biometer,23.12 mm,44.50 diopters(D),3.06,and 11.64 mm,respectively;PCI biometer,23.18 mm,44.6 D,3.15,and 11.86 mm,respectively),but the differences were significant(all,p≤0.05).The AL,K,and ACD showed excellent correlations(r=0.999,0.980,and 0.824,respectively;all p<0.001);however,there was a weak correlation of the WTW diameter between the two devices(r=0.256).The IOL powers using the SRK-T formula derived from both instruments were very similar,with an excellent correlation(r=0.989).The mean difference between the two instruments was 0.32 D.Conclusions:The OLCR biometer showed very a strong agreement with the standard PCI optical biometer for almost all ocular biometry measurements,except for the WTW diameter.Trial registration:TCTR20160614003;date 06/09/2016;‘retrospectively registered’.展开更多
文摘As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL power calculation methods have evolved and innovated throughout time, from early theoretical and regression formulas to nonlinear formulas for estimating effective lens position (ELP), multivariable formulas, and innovative formulas that use optical principles and AI-based online formulas. This paper thoroughly discusses the development and iteration of traditional IOL calculation formulas, the emergence of new IOL calculation formulas, and the selection of IOL calculation formulas for different patients in the era of refractive cataract surgery, serving as a reference for “personalized” IOL implantation in clinical practice.
基金Supported by the Innovation&Transfer Fund of Peking University Third Hospital(No.BYSYZHKC2021108).
文摘AIM:To investigate the influence of postoperative intraocular lens(IOL)positions on the accuracy of cataract surgery and examine the predictive factors of postoperative biometry prediction errors using the Barrett Universal II(BUII)IOL formula for calculation.METHODS:The prospective study included patients who had undergone cataract surgery performed by a single surgeon from June 2020 to April 2022.The collected data included the best-corrected visual acuity(BCVA),corneal curvature,preoperative and postoperative central anterior chamber depths(ACD),axial length(AXL),IOL power,and refractive error.BUII formula was used to calculate the IOL power.The mean absolute error(MAE)was calculated,and all the participants were divided into two groups accordingly.Independent t-tests were applied to compare the variables between groups.Logistic regression analysis was used to analyze the influence of age,AXL,corneal curvature,and preoperative and postoperative ACD on MAE.RESULTS:A total of 261 patients were enrolled.The 243(93.1%)and 18(6.9%)had postoperative MAE<1 and>1 D,respectively.The number of females was higher in patients with MAE>1 D(χ^(2)=3.833,P=0.039).The postoperative BCVA(logMAR)of patients with MAE>1 D was significantly worse(t=-2.448;P=0.025).After adjusting for gender in the logistic model,the risk of postoperative refractive errors was higher in patients with a shallow postoperative anterior chamber[odds ratio=0.346;95% confidence interval(CI):0.164,0.730,P=0.005].CONCLUSION:Risk factors for biometry prediction error after cataract surgery include the patient’s sex and postoperative ACD.Patients with a shallow postoperative anterior chamber are prone to have refractive errors.
基金Supported by the Joint Funding Project of Municipal Schools(Colleges)of Science and Technology Program of Guangzhou,China(No.2023A03J0188)the Construction Project of High-Level Hospitals in Guangdong Province(No.303020102)the Natural Science Fund of Guangdong Province(No.2023A1515011102).
文摘AIM:To evaluate the accuracy of intraocular lens(IOL)power calculation formulas with/without preoperative aphakic anterior chamber depth(aph-ACD)in pediatric aphakia.METHODS:A total of 102 pediatric patients(150 eyes)undergoing secondary IOL implantation were divided into two groups(in-the-bag or ciliary sulcus).Prediction error was calculated for 9 IOL power calculation formulas,including:1)not requiring ACD:Hoffer Q,Holladay 1,SRK/T;2)usable without or with entering ACD:Barrett Universal II(BUII),Emmetropia Verifying Optical(EVO)2.0,and Ladas Artificial Intelligence Super(Ladas AI);3)requiring ACD:Haigis,Kane,and Pearl-DGS.Mean prediction error(ME),mean absolute error(MAE),median absolute error(MedAE)and the percentage of eyes within±0.25,±0.50,±0.75,and±1.00 D were calculated.RESULTS:For the BUII,EVO 2.0,and Ladas AI,with aph-ACD demonstrated a higher MedAE compared to without aph-ACD(BUII:1.27 vs 1.13 D,EVO 2.0:1.26 vs 1.06 D,Ladas AI:1.30 vs 1.10 D;all P<0.05).Formulas requiring ACD(Haigis,Kane,and Pearl-DGS)exhibited larger MedAE than those not requiring aph-ACD(Hoffer Q,Holladay 1,and SRK/T;P<0.05).In the capsular group,the percentage of eyes within±1.00 D ranged from 44.83%to 74.14%,and it was 19.57%to 32.61%in the sulcus group.CONCLUSION:The introduction of aph-ACD does not improve the accuracy of IOL calculation for pediatric aphakia,regardless of in-the-bag or sulcus IOL secondary implantation.The relationship between aph-ACD and effective lens position in pediatric aphakia warrants further study.
基金supported by research grants from the National Natural Science Foundation of China(82271069,82371040,82122017,81870642,81970780,81470613 and 81670835)Science and Technology Innovation Action Plan of Shanghai Science and Technology Commission(23Y11909800)Outstanding Youth Medical Talents of Shanghai“Rising Stars of Medical Talents”Youth Development Program,Shanghai Municipal Health Commission Project(2024ZZ1025 and 20244Z0015).
文摘Objective:To compare the accuracy of six intraocular lens(IOL)power calculation methods in post-myopic-LASIK eyes.Methods:Post-myopic-LASIK patients scheduled for cataract surgery were enrolled.Mean error(ME),mean absolute error(MAE),and median absolute error(MedAE)of ASCRS(ASCRS-Max,ASCRS-Average,ASCRS-Min),EVO 2.0,Pearl-DGS,Barrett True-K no-history,Shammas-PL,and Haigis-L were compared.The ASCRS method employed four formulas,including Shammas-PL,Haigis-L,Potvin-Hill Pentacam,and Barrett True-K no-history.Trueness,precision,and accuracy indices were evaluated by comparing trimmed-mean values with heteroscedasticity adjustment.Subgroup analyses were performed based on K value,axial length(AL),and corneal decentered ablation,respectively.Factors influencing prediction errors were analyzed.Results:Totally,87 eyes were analyzed.ASCRS-Min had the lowest MAE(0.79 D)and MedAE(0.62 D),followed by EVO 2.0,Pearl-DGS,and Barrett True-K no-history.It also had the highest percentage of absolute errors within 1.00 D.All methods outperformed ASCRS-Max in accuracy indices,and ASCRS-Min and EVO 2.0 showed superior accuracy indices compared to Shammas-PL and Haigis-L.In the subgroups of lower K value,longer AL,and larger decentration of ablation zone,ASCRS-Min,EVO 2.0,Pearl-DGS,and Barrett True-K no-history generated statistically lower MedAEs than ASCRS-Max.The accuracy of Shammas-PL was associated with AL;the accuracy of Haigis-L was associated with K value and AL;no other significant associations were found.Conclusions:Generally,ASCRS-Min,EVO 2.0,Pearl-DGS,and Barrett True-K no-history achieve relatively better accuracy than the other methods,which might be considered as first choices for IOL power calculation in postmyopic-LASIK eyes.
文摘Refractive outcomes following cataract surgery in patients that have previously undergone laser refractive surgery have traditionally been underwhelming.This is related to several key issues including the preoperative assessment(keratometry)and intraocular lens power calculations.Peer-reviewed literature is overwhelmed by the influx of methodology to manipulate the corneal or intraocular lens(IOL)powers following refractive surgery.This would suggest that the optimal derivative formula has yet been introduced.This review discusses the problems facing surgeons approaching IOL calculations in these post-refractive laser patients,the existing formulae and programs to address these concerns.Prior published outcomes will be reviewed.
文摘Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL(SN60WF,Alcon)at Miyata Eye Hospital were reviewed and analyzed.Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients,constants of the SRK/T and Haigis formulas were optimized.The SRK/T formula was adapted using a support vector regressor.Prediction errors in the use of adapted formulas as well as the SRK/T,Haigis,Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients.Mean prediction errors,median absolute errors,and percentages of eyes within±0.25 D,±0.50 D,and±1.00 D,and over+0.50 D of errors were compared among formulas.Results:The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas(P<0.001).In the absolute errors,the Hill-RBF and adapted methods were better than others.The performance of the Barrett Universal II was not better than the others for the patient group.There were the least eyes with hyperopic refractive errors(16.5%)in the use of the adapted formula.Conclusions:Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.
文摘Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL(SN60WF,Alcon)at Miyata Eye Hospital were reviewed and analyzed.Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients,constants of the SRK/T and Haigis formulas were optimized.The SRK/T formula was adapted using a support vector regressor.Prediction errors in the use of adapted formulas as well as the SRK/T,Haigis,Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients.Mean prediction errors,median absolute errors,and percentages of eyes within±0.25 D,±0.50 D,and±1.00 D,and over+0.50 D of errors were compared among formulas.Results:The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas(P<0.001).In the absolute errors,the Hill-RBF and adapted methods were better than others.The performance of the Barrett Universal II was not better than the others for the patient group.There were the least eyes with hyperopic refractive errors(16.5%)in the use of the adapted formula.Conclusions:Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.
文摘Background:Cataract surgery is the most common surgical procedure in ophthalmology.Biometry data and accurate intraocular lens(IOL)calculations are very important in achieving the desired refractive outcomes.The aim of this study was to compare measurements using a new optical low coherence reflectometry(OLCR)biometer(OA-2000)and the gold standard partial coherence interferometry(PCI)optical biometer(IOLMaster 500).Methods:Ocular biometry of cataract patients were measured by the OA-2000 and IOLMaster 500 to compare keratometry(K),axial length(AL),anterior chamber depth(ACD),white-to-white(WTW)diameter,and IOL power using the SRK/T formula.Results:One hundred and two eyes of 68 cataract patients were evaluated with the two optical biometers.The mean values of the AL,K,ACD,and WTW differed very little(OCLR biometer,23.12 mm,44.50 diopters(D),3.06,and 11.64 mm,respectively;PCI biometer,23.18 mm,44.6 D,3.15,and 11.86 mm,respectively),but the differences were significant(all,p≤0.05).The AL,K,and ACD showed excellent correlations(r=0.999,0.980,and 0.824,respectively;all p<0.001);however,there was a weak correlation of the WTW diameter between the two devices(r=0.256).The IOL powers using the SRK-T formula derived from both instruments were very similar,with an excellent correlation(r=0.989).The mean difference between the two instruments was 0.32 D.Conclusions:The OLCR biometer showed very a strong agreement with the standard PCI optical biometer for almost all ocular biometry measurements,except for the WTW diameter.Trial registration:TCTR20160614003;date 06/09/2016;‘retrospectively registered’.
