April 2011
Volume 52, Issue 14
ARVO Annual Meeting Abstract  |   April 2011
Validation of Retmarker AMD for Quantification of Early Age-Related Maculopathy Features
Author Affiliations & Notes
  • Silvia N. Simao
    AIBILI, Coimbra, Portugal
  • Sandrina Nunes
    AIBILI, Coimbra, Portugal
  • Nelson Vilhena
    Critical Health SA, Coimbra, Portugal
  • Maria L. Cachulo
    AIBILI, Coimbra, Portugal
    Coimbra University Hospital, Coimbra, Portugal
  • José R. Abreu
    AIBILI, Coimbra, Portugal
    Coimbra University Hospital, Coimbra, Portugal
  • José Cunha-Vaz
    AIBILI, Coimbra, Portugal
  • Rufino Silva
    AIBILI, Coimbra, Portugal
    Coimbra University Hospital, Coimbra, Portugal
  • Footnotes
    Commercial Relationships  Silvia N. Simao, None; Sandrina Nunes, None; Nelson Vilhena, Critical Health SA (P); Maria L. Cachulo, None; José R. Abreu, None; José Cunha-Vaz, Alcon (C), Allergan (C), Eli-Lilly (C), Merck (C), Pfizer (C), Servier (C), Zeiss (C); Rufino Silva, Novartis (C)
  • Footnotes
    Support  Novartis
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 94. doi:
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      Silvia N. Simao, Sandrina Nunes, Nelson Vilhena, Maria L. Cachulo, José R. Abreu, José Cunha-Vaz, Rufino Silva; Validation of Retmarker AMD for Quantification of Early Age-Related Maculopathy Features. Invest. Ophthalmol. Vis. Sci. 2011;52(14):94.

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      © ARVO (1962-2015); The Authors (2016-present)

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To validate a new computer assisted grading tool for evaluating Age-Related Maculopaty (ARM) features using digital color fundus images.


Twenty-five RE/LE 45º digital stereoscopic colour fundus images were acquired from 48 participants, using a Topcon TRC- 50Dx mydriatic camera. Grading of ARM features was then performed by 3 senior ophthalmologists using the RetmarkerAMD (Critical Health SA), a computer assisted grading system that follows the International Classification Grading System guidelines, to check for agreement and validate the system. With the RetmarkerAMD, graders were able to pinpoint (draw-over) significant ARM features such as: Drusens using 5 circles with standard dimensions (C0: <63µm; C1: 63µm<125µm; C2: 125µm<175µm; C3: 175µm<250µm; C4: 250µm<500µm); Hyper and Hypopigmentation using standard size circles to document these alterations; Geographic Atrophy and Exudative Lesions using freehand drawing tools. For each lesion type the system used a unique color-code representation. The system overlay a standard grid dividing the eye fundus image in 10 sub-fields for graders geographic reference: Field 1 (central circle centered in fovea); Fields 2 to 8 (inner circles); Field 10 (outer circle). The system calculated automatically lesion number and area. The results were displayed onscreen in real time. The agreement between graders was tested using the kappa coefficient.


A good agreement was found for drusen greater or equal to 125µm, k=0.622 (95% CI=[0.438; 0.806]), for the number of drusen, k=0.753 (95% CI=[0.586; 0.920]) and for the total area occupied by the drusens. A fair agreement was found for the number of hard drusen (k=0.34) and a weaker agreement was found for the quantification of hyper and hypopigmentation (k=0.11 and k=0.06, respectively). The new software was found to be more effective, less time consuming (near 35% faster), allowing the identification of more lesions (near 32% than standard manual grading system) and the reduction of human error.


The RetmarkerAMD showed a good agreement between graders and reveals to be a less time consuming and more effective tool for ARM lesions detection. This system allows the quantification and localization of the different AMD features in the different sub-fields. It can be used as a platform for clinical trials and epidemiologic studies and is being used in an ongoing epidemiologic study for ARM in Portuguese population with an estimated number of 4000 participants.

Keywords: age-related macular degeneration • clinical (human) or epidemiologic studies: systems/equipment/techniques • clinical (human) or epidemiologic studies: prevalence/incidence 

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