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

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

3. 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

4. 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

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

6. IOL power calculation

7. Prior myopic-LASIK/PRK

8. Prior myopic-LASIK/PRK

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

10. 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

11. Pop-up windows explain methods used

12. Prior hyperopic-LASIK/PRK

13. Prior RK

14. Monthly visits to the calculator in 2010

15. 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):

16. 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: ± 2.55 D (range 0.98 to D)

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

18. 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

19. 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)

20. 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

21. 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

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

23. 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

24. 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: ± 3.60 D (range to D)

25. OCT-based IOL power formula
ELP = * (AL – ACD) – 0.25 * Pp * 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):

26. 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.

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

28. 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

29. 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

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

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

32. 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).

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

34. 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:

35. 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)

36. 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

37. 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

38. Accuracy of IOL power calculation in eyes with prior RK

39. 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

40. 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

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

42. 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)

43. 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

44. 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

45. 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).

46. Refractive prediction error
UK NHS benchmark 52 33 30 59 78 85 10 20 40 50 60 70 80 90
% of eyes
+/ 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:

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

48. 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!

49. 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

50. 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

51. Thank you for your attention51