Journal of Current Glaucoma Practice

Register      Login

VOLUME 15 , ISSUE 3 ( September-December, 2021 ) > List of Articles


Comparison of the Automated Pattern–Noise (PANO) Glaucoma Test with the HFA, an FDT Stimulus, and the Fundus Area Cup-to-disk Ratio

Thomas Hannen, Sylvain El-Khoury, Rajesh Patel, Faustin Ngounou, Paul-Rolf Preussner

Keywords : Frequency doubling technology, Glaucoma, Healthcare research, Humphrey field analyzer, Pattern–Noise, Visual field

Citation Information : Hannen T, El-Khoury S, Patel R, Ngounou F, Preussner P. Comparison of the Automated Pattern–Noise (PANO) Glaucoma Test with the HFA, an FDT Stimulus, and the Fundus Area Cup-to-disk Ratio. J Curr Glaucoma Pract 2021; 15 (3):132-138.

DOI: 10.5005/jp-journals-10078-1317

License: CC BY-NC 4.0

Published Online: 27-01-2022

Copyright Statement:  Copyright © 2021; The Author(s).


Aim and objective: To compare the results of a new automated glaucoma test—Pattern–Noise (PANO)—to the Humphrey Visual Field Analyzer-II (HFA), the fundus area cup-to-disk ratio (CDR), and a frequency doubling technology (FDT) stimulus. Materials and methods: This was a prospective study performed in the West-Region of Cameroon. Two hundred and nineteen eyes of 122 adult patients were included with a clinical suspicion of normal-tension or primary open-angle glaucoma and no other major ocular pathology. Eyes were examined with PANO, HFA (24-2 SITA standard), and FDT-stimulus in a randomized order followed by clinical assessment of the CDR. Results: Parametric correlation of the mean contrast threshold of PANO with the mean contrast threshold of FDT-stimulus, total deviation of HFA, and area CDR was 0.94, −0.85, and 0.62, respectively (p < 0.001 for all values). Spatial distribution of sensitivity thresholds is highly correlated (p < 0.001) at all points in the visual field between PANO and HFA. With cut-off values of 3 ± 1 dB for HFA mean deviation and 4 ± 1 for PANO mean contrast threshold and after eliminating borderline cases, PANO's sensitivity was 95% and specificity 60%. The mean patient age was 45.2 ± 15.8 years. Mean thresholds of PANO and FDT-stimulus decreased with increasing age. Mean examination time was 7.1 ± 1.8 minutes for PANO, 5.9 ± 1.3 minutes for HFA, and 4.7 ± 1.3 minutes for FDT-stimulus. The mean percentage of false-positives per examination was 4.95% for PANO, 4.62% (p = 0.025) for FDT-stimulus, and 2.10% for HFA. Conclusion: The results showed that PANO was successful in suspecting the presence of glaucoma. Pattern–Noise examination led to findings that were significantly correlated to HFA, FDT stimulus, and area CDR. Some patterns of defect were also correlated. Furthermore, PANO showed a reasonable examination time and error rate. Clinical significance: Affordable and robust visual field devices are lacking in large parts of the developing world. Comparing them to established methods is a prerequisite to their clinical use.

  1. Cook C, Foster P. Epidemiology of glaucoma: what's new? Canad J Ophthalmol 2012;47(3):223–226. DOI: 10.1016/j.jcjo.2012.02.003.
  2. Quigley HA. Number of people with glaucoma worldwide. Br J Ophthalmol 1996;80(5):389–393. DOI: 10.1136/bjo.80.5.389.
  3. Resnikoff S, Pascolini D, Etya'ale D, et al. Global data on visual impairment in the year 2002. Bullet World Health Organizat 2004;82(11):844–851. DOI: /S0042-96862004001100009.
  4. Preußner P-R, Großmann A, Ngounou F, et al. Glaucoma screening in western Cameroon. Graefe's Archi Clin Experim Ophthalmol 2009;247(12):1671–1675. DOI: 10.1007/s00417-009-1166-7.
  5. Buhrmann RR, Quigley HA, Barron Y, et al. Prevalence of glaucoma in a rural East African population. Investig Ophthalmol Visual Sci 2000;41(1):40–48.
  6. Ntim-Amponsah CT, Amoaku WMK, Ofosu-Amaah S, et al. Prevalence of glaucoma in an African population. Eye 2004;18(5):491–497. DOI: 10.1038/sj.eye.6700674.
  7. Öhnell H, Heijl A, Brenner L, et al. Structural and functional progression in the early manifest glaucoma trial. Ophthalmology 2016;123(6):1173–1180. DOI: 10.1016/j.ophtha.2016.01.039.
  8. Olsen AS, Alberti M, Serup L, et al. Glaucoma detection with damato multifixation campimetry online. Eye 2016;30(5):731–739. DOI: 10.1038/eye.2016.25.
  9. Ianchulev T, Pham P, Makarov V, et al. Peristat: a computer-based perimetry self-test for cost-effective population screening of glaucoma. Curr Eye Res 2005;30(1):1–6. DOI: 10.1080/02713680490522399.
  10. Johnson CA, Thapa S, Kong YXG, et al. Performance of an iPad application to detect moderate and advanced visual field loss in Nepal. Am J Ophthalmol 2017;182:147–154. DOI: 10.1016/j.ajo.2017.08.007.
  11. el-Khoury S, Hannen T, Dragnea DC, et al. Pattern noise (PANO): a new automated functional glaucoma test. Int Ophthalmol 2018;38(5):1993–2003. DOI: 10.1007/s10792-017-0690-4.
  12. Arora KS, Boland MV, Friedman DS, et al. The relationship between better-eye and integrated visual field mean deviation and visual disability. Ophthalmology 2013;120(12):2476–2484. DOI: 10.1016/j.ophtha.2013.07.020.
  13. Alencar LM, Medeiros FA. The role of standard automated perimetry and newer functional methods for glaucoma diagnosis and follow-up. Indian J Ophthalmol 2011;59(Suppl 1):S53–S58. DOI: 10.4103/0301-4738.73694.
  14. Quigley HA. Identification of glaucoma-related visual field abnormality with the screening protocol of frequency doubling technology. Am J Ophthalmol 1998;125(6):819–829. DOI: 10.1016/s0002-9394(98)00046-4.
  15. Tsai CS, Zangwill L, Gonzalez C, et al. Ethnic differences in optic nerve head topography. J Glauc 1995;4(4):248–257. DOI: 10.1097/00061198-199508000-00006.
  16. Analyzer OD. Racial differences in optic nerve head parameters. Arch Ophthalmol 1989;107(6):836–839. DOI: 10.1001/archopht.1989.01070010858029.
PDF Share
PDF Share

© Jaypee Brothers Medical Publishers (P) LTD.