Perimetry: Tech type proliferation

Here’s sage advice on dealing with readings.

Perimetry: Tech type proliferation

Here’s sage advice on dealing with readings.

By Anmol Lamba, MD and Iqbal “Ike” K. Ahmed, MD

Industry continues to offer choices in perimetry technologies. A brief count includes relative newcomers: frequency doubling technology (FDT, Carl Zeiss Meditec), flicker-defined form (FDF, Heidelberg/Oculus/Haag-Streit), and short-wavelength automated perimetry (SWAP); along with the more established standard achromatic perimetry (SAP, Carl Zeiss Meditec/Heidelberg/Oculus/Haag Streit/CenterVue). Fundus perimetry (or microperimetry) has also gained traction in glaucoma management (CenterVue) after initial use in assessing macular pathology.

Left: Compass, Automated Fundus Perimeter, Right: A Compass printout superimposing 24-2 visual field data on a fundus image.

But with choice comes the need to match apples to apples. The multiple aspects of any perimetric test may be manipulated differently by different studies and can make comparisons across studies difficult. Also, because no standard exists for finding visual field defects, researchers may use different definitions for glaucomatous damage.

And then there is the problem of identifying glaucoma progression. In this article, we will discuss the aforementioned issues and their related consequences.

The perimetric test. Or tests.

Why is comparison across clinical studies difficult?

    1. Mechanism of action. Technologies such as FDT or SWAP present different stimuli that theoretically test different cellular pathways.

    2. Presented stimuli. Separate studies might test the same technologies but will use a differing number of stimuli within various degrees of central vision. Developed patterns such as 24-2 or 10-2 assess 24 or 10 degrees of vision respectively. For adjusting stimuli frequency and pattern, established algorithms such as Swedish interactive testing algorithm (SITA) exist along with Zippy Estimation by Potential Testing (ZEST), Adaptive Staircase Threshold Algorithm (ASTA), Continuous Light Incremental Perimetry (CLIP), Tendency Oriented Perimetry (TOP), and so on.

    3. Interpretation of results. Various output values that might be presented across all perimeters, such as mean deviation or pattern standard deviation, may measure different things. For example, SAP depends on the patient’s ability to discriminate varying light intensities, whereas FDT measures contrast sensitivity.1

Study design

Many aspects of study design affect comparison. In lieu of a true gold standard for detecting VF defects, different studies may use different definitions of glaucomatous damage.2 Others may look for concurrent validity by correlation with other metrics of glaucoma progression, such as optical coherence tomography (OCT) measurements or optic nerve head appearance.2,3 Even when standardization controls the above across studies, differences in outcome may occur among different patient populations. For example, for reasons yet to be elucidated, some technologies may detect VF defects earlier than others in one subset of patients but not another.1,4-6

Glaucoma progression

Comparison of technologies gets further complicated when perimetry aims to tackle a key tenet of glaucoma management: identifying progression. We need methods to detect VF loss early and to identify the patients who progress at a faster rate and might need more intensive care. This need has not gone unanswered — one review found that at least 301 models of perimetric progression have been developed.2

Broadly, most models are either trend based (tracking deterioration over time) or event based (highlighting significant deviations from baseline data).2 The incidence of progression found in any population is highly dependent on the model used,3 and frequency of VF testing7 and reliability of baseline data (with SAP often having high test-retest variability8) affect the models themselves. When detecting progression across technologies, the model may influence results as well — most models were developed from trials that used SAP.3 Also, some technologies may show superiority in identifying progression when one model is used but not another.9

Current comparative literature

Across many studies, some trends have emerged. For example, FDT and FDF may pick up visual field defects in early glaucoma that SAP has not detected5,10,11, predicting future defects that develop on SAP.10,12 In early glaucoma, they may also be more strongly correlated with findings on OCT13-15 than SAP. SAP is likely similar to these technologies for monitoring progression of established glaucoma4,16 (when using trend analysis), but FDT may have more utility in progression of early glaucoma.17 FDT is well liked by patients relative to SAP and SWAP18 (possibly because it is a shorter test).8 SWAP, despite promising evidence early in its development, has generally not been shown to be superior to SAP.19,20 SWAP results have also been more greatly affected by ceiling effects,21 cataracts21 and test-retest variability.8 FDF may also be prone to ceiling effects.22 As mentioned, VF defects may be identified in different patients by different technologies in different areas of the field, and structural defects may not concurrently present in affected areas.

Model of care

These developments lead us towards a model of care in which possible glaucoma suspects might need screening by various modalities of testing so clinicians can identify the greatest number of patients at risk.5,14 No current algorithm exists on how to drive these screening decisions. Additionally, this isn’t an ideal future for glaucoma management. Patients would be subjected to more testing and increased economic burden, and we lack data on patient-centered clinical significance of finding visual field defects using these modalities.

Left: The original HFA, released in 1984, Right: The HFA-3, released in 2015.

As with any new technology, clinicians are also accustomed to years of interpreting the results of standard diagnostic tools such as SAP, which could be a barrier to adoption. The differences between the machines would require training in their nuances, as well as readily available, standardized, normative data that aid in interpretation across all modalities, especially if data recommend converting from one strategy to another at various severities of illness.22

Improving standards

Innovation in perimetry has thus looked toward the improvement of current established standards. Studies have found that a 10-2 test, with more points that are closely clustered within 10 degrees of central vision, may pick up VF defects in glaucoma that are not recognized by the more standard 24-223,24 and 30-2 tests.25 It has been recently proposed that the addition of some high yield stimuli featured in a 10-2 test be incorporated into these other tests.26

Another issue with current standards is fixation. Fixation losses during SAP affect the reliability of testing and often require longer or repeat testing at the same time point. This is an inherent, well-documented issue: not only can fixation instability be found in any patient,27 but fixation itself can deteriorate with advancing glaucoma.28 The answer has been to incorporate microperimetry into VF testing.29 This allows the ability to track landmarks on the retina live and adjust stimuli projection with loss of fixation. Studies have found that this technique can identify all areas of VF loss on a standard SAP test but then also identify additional areas of loss.30,31 In one study, the majority of these additional areas correlated with decreased macular thickness on OCT.31 However, another study examining the relationship between SAP or microperimetry and macular thickness found the same relationship across both methods.32 While microperimetry has been shown to have decreased variability and shorter testing time than SAP,33 it is not yet elucidated whether this has an actual effect on repeat testing.

Most literature on microperimetry shows use of the MP-1 microperimeter (Nidek Instruments), the SLO-MP (Optos) or the MAIA (CenterVue) to assess the utility of microperimetry. Microperimetry (with an added slit lamp ophthalmoscope) has only been formally introduced in glaucoma management recently via the Compass (CenterVue). It is marketed as the first microperimeter that can perform 24-2 fields and incorporates SAP testing strategies. Initial clinical evaluation has been promising for comparability to the Humphrey Field Analyzer (HFA; Carl Zeiss Meditec).29 The study used full threshold testing on the Compass, which yielded test times that were much longer than the HFA (which used SITA). CenterVue has since introduced the ZEST algorithm to lower testing times.

Octopus Polar Analysis mapping the visual field defects along nerve fiber layers, superimposing the data on an optic nerve head.

The HFA is the most commonly tested product in the SAP literature.2 Since the first model, released in 1984, the product has been upgraded numerous times, culminating most recently with the third model released in 2015. The machine provides a visual field index (VFI) indicating a percentage of global loss of vision and tracks its rate of deterioration to provide a trend-based progression analysis. It also uses this metric along with the findings of the Early Manifest Glaucoma trial34 in an event-based progression analysis (Glaucoma Progression Analysis; GPA). VFI trends are accurate when the baseline indicates more than 90% preserved vision.35 Both VFI and GPA tend to have high specificity with lower sensitivities, thus patients marked as non-progressors should still be evaluated with a fair degree of scrutiny.36-38 Over previous iterations, the third model of the Humphrey adds automatic refraction and gaze tracking images at individual foci to discriminate between artifacts and true VF loss.

Unlike the HFA or Compass, the Octopus (Haag-Streit), Twinfield (Oculus) and Edge perimeters (Heidelberg) all perform SAP and FDF. Each has a novel testing algorithm to lower test times (TOP, CLIP and ASTA, respectively) with different trend analysis software (cluster trend analysis, threshold noiseless trends and functional change analysis, respectively). Varying degrees of literature attest to similar levels of sensitivity, specificity, accuracy and precision. Of particular note for these perimeters are Polar Analysis software in the Octopus and the recent addition of the SPARK strategy to the Twinfield. SPARK aims to control intra-test fluctuation by averaging fewer testing points of greater importance.39 Polar Analysis, in a similar fashion to the Compass, superimposes VF data onto an image of the optic nerve head40 to allow for structure-function correlations.


Each brand has made advances in the field of perimetry, but while any given study compares some combination of these techniques, no study has compared all perimeters. Additionally, due to the limitations in research methodology mentioned above, there is no true consensus on superiority. What may be most important when picking a perimeter is consistency across patients to avoid errors that may arise when comparing one result with another.

Perimetry is an evolving, complicated field that continues to challenge clinicians and researchers alike. While the community fixates on the development of better models of VF detection and progression, it is important to appraise such innovation and not lose sight of the more patient-centered outcomes that hover in the periphery. OM


1. Liu S, Yu M, Weinreb RN, et al. Frequency foubling technology perimetry for detection of visual field progression in glaucoma: A pointwise linear regression analysis eetection of visual field progression in glaucoma. Investigative ophthalmology & visual science. 2014;55:2862-2869.

2. Ernest PJ, Schouten JS, Beckers HJ, Hendrikse F, Prins MH, Webers CA. The evidence base to select a method for assessing glaucomatous visual field progression. Acta ophthalmologica. 2012;90:101-108.

3. Ernest PJ, Viechtbauer W, Schouten JS, Beckers HJ, Hendrikse F, Prins MH, Webers CA. The influence of the assessment method on the incidence of visual field progression in glaucoma: a network meta‐analysis. Acta ophthalmologica. 2012;90:10-19.

4. Hu R, Wang C, Gu Y, Racette L. Comparison of Standard Automated Perimetry, Short-Wavelength Automated Perimetry, and Frequency-Doubling Technology Perimetry to Monitor Glaucoma Progression. Medicine. 2016;95:e2618.

5. Horn FK, Scharch V, Mardin CY, Lämmer R, Kremers J. Comparison of frequency doubling and flicker defined form perimetry in early glaucoma. Graefe’s Archive for Clinical and Experimental Ophthalmology. 2016;254:9379-746.

6. Havvas I, Papaconstantinou D, Moschos MM, Theodossiadis PG, Andreanos V, Ekatomatis P, Vergados I, Andreanos D. Comparison of SWAP and SAP on the point of glaucoma conversion. Clinical ophthalmology (Auckland, NZ). 2013;7:1805.

7. Nouri-Mahdavi K, Zarei R, Caprioli J. Influence of visual field testing frequency on detection of glaucoma progression with trend analyses. Archives of ophthalmology. 2011;129:1521-1527.

8. Nouri-Mahdavi K. Selecting visual field tests and assessing visual field deterioration in glaucoma. Canadian Journal of Ophthalmology/Journal Canadien d’Ophtalmologie. 2014;49:497-505.

9. Haymes SA, Hutchison DM, McCormick TA, Varma DK, Nicolela MT, LeBlanc RP, Chauhan BC. Glaucomatous visual field progression with frequency-doubling technology and standard automated perimetry in a longitudinal prospective study. Investigative ophthalmology & visual science. 2005;46:547-554.

10. Fan X, Wu LL, Ma ZZ, Xiao GG, Liu F. Usefulness of frequency-doubling technology for perimetrically normal eyes of open-angle glaucoma patients with unilateral field loss. Ophthalmology. 2010;117:1530-1537.

11. Reznicek L, Lamparter J, Vogel M, Kampik A, Hirneiß C. Flicker defined form perimetry in glaucoma suspects with normal achromatic visual fields. Current eye research. 2015;40:683-689.

12. Meira-Freitas D, Tatham AJ, Lisboa R, Kuang TM, Zangwill LM, Weinreb RN, Girkin CA, Liebmann JM, Medeiros FA. Predicting progression of glaucoma from rates of frequency doubling technology perimetry change. Ophthalmology. 2014;121:498-507.

13. Horn FK, Tornow RP, Jünemann AG, Laemmer R, Kremers J. Perimetric Measurements With Flicker-Defined Form Stimulation in Comparison With Conventional Perimetry and Retinal Nerve Fiber MeasurementsFlicker-Defined Form Stimulation. Investigative ophthalmology & visual science. 2014;55:2317-2323.

14. Prokosch V, Eter N. Correlation between early retinal nerve fiber layer loss and visual field loss determined by three different perimetric strategies: white-on-white, frequency-doubling, or flicker-defined form perimetry. Graefe’s Archive for Clinical and Experimental Ophthalmology. 2014;252:1599-1606.

15. Lamparter J, Russell RA, Schulze A, Schuff AC, Pfeiffer N, Hoffmann EM. Structure-Function Relationship between FDF, FDT, SAP, and Scanning Laser Ophthalmoscopy in Glaucoma PatientsStructure-Function Relationship in Glaucoma Patients. Investigative ophthalmology & visual science. 2012;53:7553-7559.

16. Redmond T, O’Leary N, Hutchison DM, Nicolela MT, Artes PH, Chauhan BC. Visual field progression with frequency-doubling matrix perimetry and standard automated perimetry in patients with glaucoma and in healthy controls. JAMA ophthalmology. 2013;131:1565-1572.

17. Liu S, Yu M, Weinreb RN, Lai G, Lam DS, Leung CK. Frequency-doubling technology perimetry for detection of the development of visual field defects in glaucoma suspect eyes: a prospective study. JAMA ophthalmology. 2014;132:77-83.

18. Gardiner SK, Demirel S. Assessment of patient opinions of different clinical tests used in the management of glaucoma. Ophthalmology.115:2127-2131.

19. Bengtsson B, Heijl A. Diagnostic sensitivity of fast blue–yellow and standard automated perimetry in early glaucoma: a comparison between different test programs. Ophthalmology. 2006;113:1092-1097.

20. van der Schoot J, Reus NJ, Colen TP, Lemij HG. The ability of short-wavelength automated perimetry to predict conversion to glaucoma. Ophthalmology. 2010;117:30-34.

21. Alencar LM, Medeiros FA. The role of standard automated perimetry and newer functional methods for glaucoma diagnosis and follow-up. Indian journal of ophthalmology. 2011;59:53.

22. Horn FK, Kremers J, Mardin CY, Jünemann AG, Adler W, Tornow RP. Flicker-defined form perimetry in glaucoma patients. Graefe’s Archive for Clinical and Experimental Ophthalmology. 2015;253:447-455.

23. Traynis I, De Moraes CG, Raza AS, Liebmann JM, Ritch R, Hood DC. Prevalence and nature of early glaucomatous defects in the central 10 of the visual field. JAMA ophthalmology. 2014;132:291-297.

24. Rao HL, Begum VU, Khadka D, Mandal AK, Senthil S, Garudadri CS. Comparing glaucoma progression on 24-2 and 10-2 visual field examinations. PloS one. 2015;10:e0127233.

25. Asaoka R. Mapping glaucoma patients’ 30-2 and 10-2 visual fields reveals clusters of test points damaged in the 10-2 grid that are not sampled in the sparse 30-2 grid. PloS one. 2014;9:e98525.

26. Chen S, McKendrick AM, Turpin A. Choosing two points to add to the 24-2 pattern to better describe macular visual field damage due to glaucoma. British Journal of Ophthalmology. 2015;99:1236-1239.

27. Demirel S, Vingrys AJ. Eye movements during perimetry and the effect that fixational instability has on perimetric outcomes. Journal of glaucoma. 1994;3:28-35.

28. Shi Y, Liu M, Wang X, Zhang C, Huang P. Fixation behavior in primary open angle glaucoma at early and moderate stage assessed by the MicroPerimeter MP-1. Journal of glaucoma. 2013;22:169-173.

29. Rossetti L, Digiuni M, Rosso A, Riva R, Barbaro G, Smolek MK, Orzalesi N, De Cilla S, Autelitano A, Fogagnolo P. Compass: Clinical evaluation of a new instrument for the diagnosis of glaucoma. PloS one. 2015;103:e0122157.

30. Ratra V, Ratra D, Gupta M, Vaitheeswaran K. Comparison between Humphrey Field Analyzer and Micro Perimeter 1 in normal and glaucoma subjects. Oman journal of ophthalmology. 2012;52:97.

31. Lima VC, Prata TS, De Moraes CG, Kim J, Seiple W, Rosen RB, Liebmann JM, Ritch R. A comparison between microperimetry and standard achromatic perimetry of the central visual field in eyes with glaucomatous paracentral visual-field defects. British Journal of Ophthalmology. 2010;94:64-67.

32. Rao HL, Januwada M, Hussain RS, Pillutla LN, Begum VU, Chaitanya A, Senthil S, Garudadri CS. Comparing the structure–function relationship at the macula with standard automated perimetry and MicroperimetryStructure–function relationship at macula with SAP and MP. Investigative ophthalmology & visual science. 2015;5613:8063-8068.

33. Kulkarni SV, Coupland SG, Stitt DM, Hamilton J, Brownstein JJ, Damji KF. Efficacy of SLO-Microperimetry and Humphrey for evaluating macular sensitivity changes in advanced glaucoma. Canadian Journal of Ophthalmology/Journal Canadien d’Ophtalmologie. 2013;48:406-412.

34. Heijl A, Leske MC, Bengtsson B, Hyman L, Bengtsson B, Hussein M. Reduction of intraocular pressure and glaucoma progression: results from the Early Manifest Glaucoma Trial. Archives of ophthalmology. 2002;120:1268-1279.

35. Talbot R, Goldberg I, Kelly P. Evaluating the accuracy of the visual field index for the Humphrey Visual Field Analyzer in patients with mild to moderate glaucoma. American journal of ophthalmology. 2013;156:1272-1276.

36. Ang GS, Mustafa MS, Scott N, Diaz-Aleman VT, Azuara-Blanco A. Perimetric progression in open angle glaucoma and the Visual Field Index (VFI). Journal of glaucoma. 2011;20:223-227.

37. Tanna AP, Budenz DL, Bandi J, Feuer WJ, Feldman RM, Herndon LW, Rhee DJ, Whiteside-de Vos J, Huang J, Anderson DR. Glaucoma Progression Analysis software compared with expert consensus opinion in the detection of visual field progression in glaucoma. Ophthalmology. 2012;119:468-473.

38. Artes PH, O’Leary N, Nicolela MT, Chauhan BC, Crabb DP. Visual field progression in glaucoma: what is the specificity of the guided progression analysis?. Ophthalmology. 2014;121:2023-2027.

39. de la Rosa MG, Gonzalez-Hernandez M. A strategy for averaged estimates of visual field threshold: spark. Journal of glaucoma. 2013;22:284-289.

40. Holló G, Naghizadeh F. Evaluation of Octopus Polar Trend Analysis for detection of glaucomatous progression. European journal of ophthalmology. 2013;24:862-868.

About the Authors

Dr. Anmol Lamba is a glaucoma and advanced anterior segment research fellow in the department of Ophthalmology and Vision Sciences at the University of Toronto.

Dr. Iqbal “Ike” K. Ahmed is a complex-cataract, glaucoma, and anterior segment surgeon. He is an assistant professor and research director at the University of Toronto, and a clinical professor at the University of Utah.