Financial Disclosure I have a financial interest with the following companies: Abbott Medical Optics Alcon Calhoun Vision NuLens Optimedica Optivue  

IOL power calculations in post-LASIK/PRK eyes Douglas D. Koch, M.D. Cullen Eye Institute, Baylor College of Medicine, Houston, TX

Challenges Difficulties in determining true corneal refractive power Keratometric inaccuracy Invalid use of effective refractive index of cornea (1.3375) Problems in 3rd and 4th generation IOL formulas Inaccurate estimation of ELP Exception: Haigis formula 3

Methods proposed Various methods proposed in the literature Estimation of corneal powers IOL power adjustment Time consuming to perform calculations with various methods Developed online-based calculator http://www.ascrs.org

So many formulas. . So we developed: http://www.ascrs.org/

IOL power calculation

Prior myopic-LASIK/PRK

Prior myopic-LASIK/PRK

Double-K Holladay 1 and Haigis-L formulas 3 categories of formulas

3 categories Traditionally “Gold” standard KEY – accurate historical data Data error 1:1 ratio Use a fraction of ∆MR Data error ↓ to 20 – 30% Rely only on current data

Pop-up windows explain methods used

Prior hyperopic-LASIK/PRK

Prior RK

Monthly visits to the calculator in 2010

Evaluation of ASCRS IOL calculator To compare methods of calculating IOL power for cataract surgery in eyes with prior myopic LASIK  Wang, Hill and Koch. JCRS, 2010 Sep;36(9):1466-73

Patients 2 study centers Consecutive cases of IOL implantation in eyes with prior myopic-LASIK SN60WF 72 eyes of 57 patients included Mean age: 58 ± 8 years (range 42 to 77 years) Myopic LASIK correction: 5.10 ± 2.55 D (range 0.98 to 11.21 D)

Methods IOL prediction error Consistency of prediction performance = IOL implanted – IOL calculated Negative value  myopic results Consistency of prediction performance F-test for variances

4.0 2.0 0.0 -2.0 -4.0 IOL prediction error (D) Masket Clinical History Feiz-Mannis Corneal Bypass Adjusted EffRP Adjusted Atlas0-3 Modified-Masket Wang-Koch-Maloney Shammas Haigis-L Average IOL power

Variances of IOL prediction errors (SD2) - consistency of performance Pre-LASIK Ks + ∆ MR Clinical History Feiz-Mannis Corneal Bypass 2.06 2.53 1.99 ∆ MR Adjusted EffRP Adjusted Atlas0-3 Masket Modified-Masket 0.70 0.68 0.63 0.62 No prior data Wang-Koch-Maloney Shammas Haigis-L 0.66 * * Significant differences (all P<0.05 with Bonferroni correction)

Refractive prediction error Methods ± 0.5 D ± 1.0 D Pre-LASIK Ks + ∆MR* Clinical History Feiz-Mannis Corneal Bypass 44 37 69 60 68 ∆MR Adjusted EffRP Adjusted Atlas0-3 Masket Modified-Masket 62 64 57 67 86 90 91 No prior data Wang-Koch-Maloney Shammas Haigis-L 58 96 94 Proposed UK NHS benchmark in normal eyes*: 85% ±1.0 D 55% ±0.5 D Met benchmark in normal eyes but well below latest standards *Significant lower % with historical methods (P<0.05). Gale RP, et al. Benchmark standards for refractive outcomes after NHS cataract surgery. Eye. 2009;23:149-52

Summary Using double-K Holladay 1 formula Greater prediction errors and variances with methods requiring Pre-LASIK Ks and ∆MR Use 100% of historical data Superior and essentially equivalent results with: Methods using a fraction of ∆MR and Methods using no prior data

Optical coherence tomography (OCT) RTVue-CAM: an Fourier domain OCT system for both retinal and corneal imaging RTVue with CAM module

Net Corneal Power (NCP): Combines anterior & posterior curvature measurements from OCT meridional scans 1.5mm Rp Ra D n0 = 1 n1 = 1.376 n2 = 1.336 The RTVue system is fast enough map the cornea within 0.3 seconds. It can accurately measures both anterior and posterior curvature. The curvature values are used to calculate net corneal power. Measurements from 8 meridians are averaged. 23

Evaluation of OCT-based formula IOL power calculation in post-LASIK eyes 12 eyes at Cullen Eye Institute 8 eyes at Doheny Eye Institute Refractive correction: -4.04 ± 3.60 D (range -0.88 to -9.81 D)

OCT-based IOL power formula ELP = 0.711 * (AL – ACD) – 0.25 * Pp + 0.623 * ALadj + pACD – 8.11 Where AL = axial eye length (mm) ACD = Anterior chamber depth (mm) Pp = posterior corneal power (D) ALadj = sqrt(AL) if AL < 24.4mm sqrt(AL+0.8*(AL-24.4)), if AL > 24.4mm pACD = personalized ACD (ACD-constant) *Tang M, Li Y, Huang D. An Intraocular Lens Power Calculation Formula Based on Optical Coherence Tomography: a Pilot Study. J Refract Surg. 2010;26(6):430-437

Refractive prediction error Keratometry Method Best IOL Formula Prediction Error (D) Range (D) MAE Adjusted MAE (D) IOL-Master Haigis-L -0.23 ± 0.83 (-1.93, 1.30) 0.66 0.65* OCT OCT-based -0.01 ± 0.70 (-0.85, 1.79) 0.56 0.56* *P=0.65, n = 20 eyes of 15 subjects.

Refractive prediction error Within 0.5D: Haigis-L: 11/20 OCT: 10/20 Within 1D: Haigis-L: 15/20 OCT: 19/20

Summary Limitation: Further studies desirable Small numbers Performance of OCT-based IOL formula was not compared to many methods on the ASCRS calculator Further studies desirable

Recent study Accuracy of Galilei in IOL power calculation in eyes with prior myopic LASIK/PRK Consecutive cases of IOL implantation between April 08 to Feb. 11

Patients 19 eyes of 16 patients had all historical data Myopic LASIK correction: 4.28 ± 2.61 D (range 0.88 to 8.50 D)

Galilei Dual-Scheimpflug analyzer Total corneal power (TCP) Using Snell’s law Ray tracing through the anterior and posterior surfaces

Variance of IOL prediction error with methods using no prior data (n=39) Better consistency with Haigis-L compared to Galilei TCP (all P<0.05).

Refractive mean absolute error (MAE) with methods using no prior data (n=39) Haigis-L tended to have smaller MAE (all P>0.05).

Refractive prediction error with methods using no prior data (n=39) UK NHS benchmark 59 56 44 41 36 38 79 77 92 69 72 82 10 20 30 40 50 60 70 80 90 100 % of eyes +/- 0.5 D +/- 1.0 D 85% ±1.0 D 55% ±0.5 D Wang-Koch- Maloney Shammas Haigis-L TCP-2mm TCP-3mm TCP-4mm TCP-5mm Proposed benchmark for normal eyes: Gale RP, et al. Benchmark standards for refractive outcomes after NHS cataract surgery. Eye. 2009;23:149-52.

Refractive MAE with all methods (n=19) 1.2 Clinical History Feiz-Mannis Corneal Bypass Adjusted EffRP Adjusted Atlas0-3 Masket Modified-Masket Wang-Koch-Maloney Shammas Haigis-L TCP-2mm TCP-3mm TCP-4mm TCP-5mm  0.94 0.99 0.93 0.65 0.52 0.42 0.44 0.57 0.47 0.78 0.75 0.72 0.70 0.0 0.2 0.4 0.6 0.8 1.0 MAE (D) Galilei Significant greater MAE with methods using pre-LASIK Ks and ∆MR than those with  (all P<0.05)

Refractive prediction error with all methods (n=19) UK NHS benchmark 32 42 58 68 53 47 63 26 21 79 89 74 95 84 10 20 30 40 50 60 70 80 90 100 % of eyes +/- 0.5 D +/- 1.0D 85% ±1.0 D 55% ±0.5 D Clinical History Feiz-Mannis Corneal Bypass Adjusted EffRP Adjusted Atlas0-3 Masket Modified-Masket Wang-Koch-Maloney Shammas Haigis-L TCP-2mm TCP-3mm TCP-4mm TCP-5mm Galilei

Summary Refractive MAE with Galilei TCP Tended to be smaller than those with historical data Similar with other methods using no prior data % of eyes within 0.5 D of refractive prediction errors with Galilei Tended to be smaller than those with other methods using no prior data

Accuracy of IOL power calculation in eyes with prior RK

Purpose Because RK eyes have variable front and back curvatures, IOL calcs are especially challenging To evaluate the accuracy of 4 devices for calculating corneal power for IOL calculations in RK eyes undergoing cataract surgery IOLMaster, EyeSys, Atlas, Galilei

Methods Evaluate various corneal power values from Atlas and Galilei Select the best method for Atlas and Galilei Smallest variance (SD2) of IOL prediction error Compare accuracy among devices

Patients Consecutive cases of IOL implantation between April 08 to February 11 27 eyes of 18 patients, age 47 to 79 years

Variance of IOL prediction error with Atlas Atlaszone0-2 Atlaszone0-3 Atlaszone0-4 Atlaszone0-5 Atlasannuli1-3 Atlasannuli1-4 1.49 1.16 1.23 1.46 1.29 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Variance (D2)

Variance of IOL prediction error with Galilei 1.61 1.30 1.23 1.18 1.11 1.00 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 Variance (D2) TCPzone0-2 TCPzone0-3 TCPzone0-4 TCPzone0-5 TCPannuli1-3 TCPannuli1-4

Refractive mean numerical error (MNE) with different devices -0.42 -2.10 -0.12 -0.09 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 MNE (D) EyeSys EffRP IOLMasterK Atlaszone0-3 TCPannuli1-4

Refractive mean absolute error (MAE) with different devices 0.65 0.67 0.66 0.58 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 MAE (D) EyeSys EffRP IOLMasterK Atlaszone0-3 TCPannuli1-4 Galilei TCPannuli1-4 tended to produce smallest MAE (all P>0.05).

Refractive prediction error UK NHS benchmark 52 33 30 59 78 85 10 20 40 50 60 70 80 90 % of eyes +/- 0.50 D +/- 1.0 D 85% ±1.0 D 55% ±0.5 D EyeSys EffRP IOLMaster K Atlaszone0-3 TCPannuli1-4 Proposed benchmark for normal eyes: Gale RP, et al. Benchmark standards for refractive outcomes after NHS cataract surgery. Eye. 2009;23:149-52.

Galilei Needs further work to improve IOL calculations after LASIK Helpful in eyes that have undergone radial keratotomy

Summary Galilei TCP annular average 1-4 mm tended to have the most consistent performance in IOL power prediction Met the UK NHS benchmark standards for normal eyes Surprises still occur Need: more eyes and more sites!

Conclusion Galilei is a useful adjunct in IOL power calculations in post-LASIK/PRK eyes Getting better Recent new software Refining ongoing Galilei is a outstanding tool for RK eyes

Strategy Obtain topography measurements EyeSys Humphrey Atlas Galilei Input as many data as you could collect into the online calculator Rely on methods that rely only partially or not at all on historical data

Thank you for your attention 51