Combining multiple HRT parameters using the 'random forests' method improves the diagnostic accuracy of glaucoma in emmetropic and highly myopic eyes

Investigative Ophthalmology and Visual Science

Volumn 55, Issue 4, 2014, Pages 2482-2490

  Asaoka, Ryo ^a   Iwase, Aiko ^b   Tsutsumi, Tae ^a   Saito, Hitomi ^c   Otani, Shinichiro ^d   Miyata, Kazunori ^d   Murata, Hiroshi ^a   Mayama, Chihiro ^a   Araie, Makoto ^a,c  

^a UNIVERSITY OF TOKYO   (Japan)

^b Tajimi Iwase Eye Clinic   (Japan)

^c Mutual Aid Association of Public School Teachers   (Japan)

^d Miyata Eye Hospital   (Japan)

Author keywords

Glaucoma; Heidelberg retina tomograph; Random forests

Indexed keywords

ADULT; ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; EMMETROPIA; FEMALE; GLAUCOMA; HEIDELBERG RETINA TOMOGRAPHY; HIGH MYOPIA; HUMAN; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; OPEN ANGLE GLAUCOMA; OPTIC NERVE; OPTICAL TOMOGRAPHY; PRIORITY JOURNAL; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS; TOMOGRAPHY;

GLAUCOMA; HEIDELBERG RETINA TOMOGRAPH; RANDOM FORESTS;

ADULT; ALGORITHMS; DIAGNOSIS, DIFFERENTIAL; DIAGNOSTIC TECHNIQUES, OPHTHALMOLOGICAL; EMMETROPIA; FEMALE; GLAUCOMA, OPEN-ANGLE; HUMANS; MALE; MIDDLE AGED; MYOPIA; REPRODUCIBILITY OF RESULTS; RETINA; ROC CURVE; SEVERITY OF ILLNESS INDEX; TOMOGRAPHY;

EID: 84898922018     PISSN: 01460404     EISSN: 15525783     Source Type: Journal    
DOI: 10.1167/iovs.14-14009     Document Type: Article

References (72)

1. Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90:262-267.
2. Sommer A, Pollack I, Maumenee AE. Optic disc parameters and onset of glaucomatous field loss. I. Methods and progressive changes in disc morphology. Arch Ophthalmol. 1979;97:1444-1448.
3. Pederson JE, Anderson DR. The mode of progressive disc cupping in ocular hypertension and glaucoma. Arch Ophthalmol. 1980;98:490-495.
4. Quigley HA, Katz J, Derick RJ, Gilbert D, Sommer A. An evaluation of optic disc and nerve fiber layer examinations in monitoring progression of early glaucoma damage. Ophthalmology. 1992;99:19-28.
5. Sommer A, Miller NR, Pollack I, Maumenee AE, George T. The nerve fiber layer in the diagnosis of glaucoma. Arch Ophthalmol. 1977;95:2149-2156.
6. Sommer A, Katz J, Quigley HA, et al. Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss. Arch Ophthalmol. 1991;109:77-83.
7. Sommer A, Quigley HA, Robin AL, Miller NR, Katz J, Arkell S. Evaluation of nerve fiber layer assessment. Arch Ophthalmol. 1984;102:1766-1771.
8. Wollstein G, Garway-Heath DF, Fontana L, Hitchings RA. Identifying early glaucomatous changes. Comparison between expert clinical assessment of optic disc photographs and confocal scanning ophthalmoscopy. Ophthalmology. 2000; 107:2272-2277.
9. Swindale NV, Stjepanovic G, Chin A, Mikelberg. Automated analysis of normal and glaucomatous optic nerve head topography images. Invest Ophthalmol Vis Sci. 2000;41: 1730-1742.
10. Wollstein G, Garway-Heath DF, Hitchings RA. Identification of early glaucoma cases with the scanning laser ophthalmoscope. Ophthalmology. 1998;105:1557-1563.
11. Zangwill LM, Bowd C, Berry CC, et al. Discriminating between normal and glaucomatous eyes using the Heidelberg Retina Tomograph, GDx Nerve Fiber Analyzer, and Optical Coherence Tomograph. Arch Ophthalmol. 2001;119:85-993.
12. Reus NJ, de Graaf M, Lemij HG. Accuracy of GDx VCC, HRT I, and clinical assessment of stereoscopic optic nerve head photographs for diagnosing glaucoma. Br J Ophthalmol. 2007; 91:313-318.
13. Andreou PA, Wickremasinghe SS, Asaria RH, Tay E, Franks WA. A comparison of HRT II and GDx imaging for glaucoma detection in a primary care eye clinic setting. Eye (Lond). 2007;21:1050-1055.
14. Mitchell P, Hourihan F, Sandbach J, Wang JJ. The relationship between glaucoma and myopia: the Blue Mountains Eye Study. Ophthalmology. 1999;106:2010-2015.
15. Suzuki Y, Iwase A, Araie M, et al. Risk factors for open-angle glaucoma in a Japanese population: the Tajimi Study. Ophthalmology. 2006;113:1613-1617.
16. Xu L, Wang Y, Wang S, Wang Y, Jonas JB. High myopia and glaucoma susceptibility the Beijing Eye Study. Ophthalmology. 2007;114:216-220.
17. Perera SA, Wong TY, Tay WT, Foster PJ, Saw SM, Aung T. Refractive error, axial dimensions, and primary open-angle glaucoma: the Singapore Malay Eye Study. Arch Ophthalmol. 2010;128:900-905.
18. Liang YB, Friedman DS, Zhou Q, et al. Prevalence of primary open angle glaucoma in a rural adult Chinese population: the Handan Eye Study. Invest Ophthalmol Vis Sci. 2011;52:8250-8257.
19. How AC, Tan GS, Chan YH, et al. Population prevalence of tilted and torted optic discs among an adult Chinese population in Singapore: the Tanjong Pagar Study. Arch Ophthalmology. 2009;127:894-899.
20. Samarawickrama C, Mitchell P, Tong L, et al. Myopia-related optic disc and retinal changes in adolescent children from singapore. Ophthalmology. 2011;118:2050-2057.
21. Yamazaki Y, Yoshikawa K, Kunimatsu S, et al. Influence of myopic disc shape on the diagnostic precision of the Heidelberg Retina Tomograph. Jpn J Ophthalmol. 1999;43: 392-397.
22. Rudnicka AR, Owen CG, Nightingale CM, Cook DG, Whincup PH. Ethnic differences in the prevalence of myopia and ocular biometry in 10-and 11-year-old children: the Child Heart and Health Study in England (CHASE). Invest Ophthalmol Vis Sci. 2010;51:6270-6276.
23. Shimizu N, Nomura H, Ando F, Niino N, Miyake Y, Shimokata H. Refractive errors and factors associated with myopia in an adult Japanese population. Jpn J Ophthalmol. 2003;47:6-12.
24. Sawada A, Tomidokoro A, Araie M, Iwase A, Yamamoto T; Tajimi Study Group. Refractive errors in an elderly Japanese population: the Tajimi study. Ophthalmology. 2008;115:363-370, e363.
25. Hitchings RA, Spaeth GL. The optic disc in glaucoma. I: classification. Br J Ophthalmol. 1976;60:778-785.
26. Han J, Kamber M. Data Mining: Concepts and Techniques. Burlington: Morgan Kaufmann Publishers; 2006.
27. Mitchell TM. Machine Learning. New York: McGraw-Hill Higher Education; 1997.
28. Breiman L. Random forests. Mach Learn. 2001;45:5-32.
29. Strobl C, Boulesteix AL, Kneib T, Augustin T, Zeileis A. Conditional variable importance for random forests. BMC Bioinformatics. 2008;9:307.
30. Lunetta KL, Hayward LB, Segal J, Van Eerdewegh P. Screening large-scale association study data: exploiting interactions using random forests. BMC Genetics. 2004;5:32.
31. Segal MR, Cummings MP, Hubbard AE. Relating amino acid sequence to phenotype: analysis of peptide-binding data. Biometrics. 2001;57:632-642.
32. Mikelberg FS, Parfitt CM, Swindale NV, Graham SL, Drance SM, Gosine R. Ability of the heidelberg retina tomograph to detect early glaucomatous visual field loss. J Glaucoma. 1995;4:242-247.
33. Anderson DR, Patella VM. Automated Static Perimetry. St Louis: Mosby; 1999.
34. Tsutsumi T, Tomidokoro A, Saito H, Hashizume A, Iwase A, Araie M. Confocal scanning laser ophthalmoscopy in high myopic eyes in a population-based setting. Invest Ophthalmol Vis Sci. 2009;50:5281-5287.
35. Japkowicz N. Evaluating Learning Algorithms: A Classification Perspective. Cambridge: Cambridge University Press; 2011.
36. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837-845.
37. Demšar J. Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res. 2006;7:1-30.
38. Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.
39. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology. 1983;148:839-843.
40. Holm S. A simple sequentially rejective multiple test procedure. Scand J Stat. 1979;65-70.
41. Aickin M, Gensler H. Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods. Am J Public Health. 1996;86:726-728.
42. Oddone F, Centofanti M, Iester M, et al. Sector-based analysis with the Heidelberg Retinal Tomograph 3 across disc sizes and glaucoma stages: a multicenter study. Ophthalmology. 2009; 116:1106-1111, e1101-e1103.
43. Hart WM Jr, Becker B. The onset and evolution of glaucomatous visual field defects. Ophthalmology. 1982;89:268-279.
44. Heijl A, Lundqvist L. The frequency distribution of earliest glaucomatous visual field defects documented by automatic perimetry. Acta Ophthalmolo (Copenh). 1984;62:658-664.
45. Jonas JB, Dichtl A. Optic disc morphology in myopic primary open-angle glaucoma. Graefes Arch Clin Exp Ophthalmol. 1997;235:627-633.
46. Naithani P, Sihota R, Sony P, et al. Evaluation of optical coherence tomography and Heidelberg Retinal Tomography parameters in detecting early and moderate glaucoma. Invest Ophthalmol Vis Sci. 2007;48:3138-3145.
47. Ferreras A, Pablo LE, Larrosa JM, Polo V, Pajarín AB, Honrubia FM. Discriminating between normal and glaucoma-damaged eyes with the Heidelberg Retina Tomograph 3. Ophthalmology. 2008;115:775-781, e772.
48. Zheng Y, Wong TY, Lamoureux E, et al. Diagnostic ability of Heidelberg Retina Tomography in detecting glaucoma in a population setting: the Singapore Malay Eye Study. Ophthalmology. 2010;117:290-297.
49. Burgansky-Eliash Z, Wollstein G, Bilonick RA, et al. Glaucoma detection with the Heidelberg Retina Tomograph 3. Ophthalmology. 2007;114:466-471.
50. Harizman N, Zelefsky JR, Ilitchev E, Tello C, Ritch R, Liebmann JM. Detection of glaucoma using operator-dependent versus operator-independent classification in the Heidelberg Retinal Tomograph-III. Br J Ophthalmol. 2006;90:1390-1392.
51. Coops A, Henson DB, Kwartz AJ, Artes PH. Automated analysis of Heidelberg Retina Tomograph optic disc images by glaucoma probability score. Invest Ophthalmol Vis Sci. 2006;47:5348-5355.
52. Yip LW, Mikelberg FS. A comparison of the glaucoma probability score to earlier Heidelberg Retina Tomograph data analysis tools in classifying normal and glaucoma patients. J Glaucoma. 2008;17:513-516.
53. Takmaz T, Can I. Comparison of glaucoma probability score and Moorfields regression analysis to discriminate glaucomatous and healthy eyes. Eur J Ophthalmol. 2009;19:207-213.
54. Bozkurt B, Irkec M, Arslan U. Diagnostic accuracy of Heidelberg Retina Tomograph III classifications in a Turkish primary open-angle glaucoma population. Acta Ophthalmol. 2010;88:125-130.
55. Saito H, Tomidokoro A, Yanagisawa M, Iwase A, Araie M. Sensitivity and specificity with the glaucoma probability score in Heidelberg Retina Tomograph II in Japanese eyes. J Glaucoma. 2009;18:227-232.
56. Saito H, Tsutsumi T, Araie M, Tomidokoro A, Iwase A. Sensitivity and specificity of the Heidelberg Retina Tomograph II Version 3.0 in a population-based study: the Tajimi Study. Ophthalmology. 2009;116:1854-1861.
57. Tsutsumi T, Tomidokoro A, Araie M, Iwase A, Sakai H, Sawaguchi S. Planimetrically determined vertical cup/disc and rim width/disc diameter ratios and related factors. Invest Ophthalmol Vis Sci. 2012;53:1332-1340.
58. Bourne RR, Foster PJ, Bunce C, et al. The morphology of the optic nerve head in the Singaporean Chinese population (the Tanjong Pagar study): part 2-biometric and systemic associations. Br J Ophthalmol. 2008;92:310-314.
59. Ramrattan RS, Wolfs RC, Jonas JB, Hofman A, de Jong PT. Determinants of optic disc characteristics in a general population: the Rotterdam Study. Ophthalmology. 1999;106: 1588-1596.
60. Varma R, Tielsch JM, Quigley HA, et al. Race-, age-, gender-, and refractive error-related differences in the normal optic disc. Arch Ophthalmol. 1994;112:1068-1076.
61. Jonas JB, Thomas R, George R, Berenshtein E, Muliyil J. Optic disc morphology in south India: the Vellore Eye Study. Br J Ophthalmol. 2003;87:189-196.
62. Sekhar GC, Prasad K, Dandona R, John RK, Dandona L. Planimetric optic disc parameters in normal eyes: a population-based study in South India. Indian J Ophthalmol. 2001; 49:19-23.
63. Wang Y, Xu L, Zhang L, Yang H, Ma Y, Jonas JB. Optic disc size in a population based study in northern China: the Beijing Eye Study. Br J Ophthalmol. 2006;90:353-356.
64. Xu L, Wang Y, Yang H, Zhang L, Jonas JB. Size of the neuroretinal rim and optic cup and their correlations with ocular and general parameters in adult Chinese: the Beijing eye study. Br J Ophthalmol. 2007;91:1616-1619.
65. Heidelberg Retina Tomograph Glaucoma Module: Operating Instructions Software Version 3.0. Heidelberg, Germany; 2005.
66. Rao HL, Babu GJ, Sekhar GC. Comparison of the diagnostic capability of the Heidelberg Retina Tomographs 2 and 3 for glaucoma in the Indian population. Ophthalmology. 2010; 117:275-281.
67. Maroco J, Silva D, Rodrigues A, Guerreiro M, Santana I, de Mendonça A. Data mining methods in the prediction of Dementia: a real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests. BMC Res Notes. 2011;4:299.
68. Diaz-Uriarte R, Alvarez de Andres S. Gene selection and classification of microarray data using random forest. BMC Bioinformatics. 2006;7:3.
69. Douglas PK, Harris S, Yuille A, et al. Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief. NeuroImage. 2011;56:544-553.
70. Saw SM, Gazzard G, Koh D, et al. Prevalence rates of refractive errors in Sumatra, Indonesia. Invest Ophthalmol Vis Sci. 2002; 43:3174-3180.
71. Wong TY, Foster PJ, Hee J, et al. Prevalence and risk factors for refractive errors in adult Chinese in Singapore. Invest Ophthalmol Vis Sci. 2000;41:2486-2494.
72. Podos SM, Becker B, Morton WR. High myopia and primary open-angle glaucoma. Am J Ophthalmol. 1966;62:1038-1043.