Multi-line adaptive perimetry (MAP): A new procedure for quantifying visual field integrity for rapid assessment of macular diseases

Academic Article


  • Purpose: In order to monitor visual defects associated with macular degeneration (MD), we present a new psychophysical assessment called multiline adaptive perimetry (MAP) that measures visual field integrity by simultaneously estimating regions associated with perceptual distortions (metamorphopsia) and visual sensitivity loss (scotoma). Methods: We first ran simulations of MAP with a computerized model of a human observer to determine optimal test design characteristics. In experiment 1, predictions of the model were assessed by simulating metamorphopsia with an eye-tracking device with 20 healthy vision participants. In experiment 2, eight patients (16 eyes) with macular disease completed two MAP assessments separated by about 12 weeks, while a subset (10 eyes) also completed repeated Macular Integrity Assessment (MAIA) microperimetry and Amsler grid exams. Results: Results revealed strong repeatability of MAP and high accuracy, sensitivity, and specificity (0.89, 0.81, and 0.90, respectively) in classifying patient eyes with severe visual impairment. We also found a significant relationship in terms of the spatial patterns of performance across visual field loci derived from MAP and MAIA microperimetry. However, there was a lack of correspondence between MAP and subjective Amsler grid reports in isolating perceptually distorted regions. Conclusions: These results highlight the validity and efficacy of MAP in producing quantitative maps of visual field disturbances, including simultaneous mapping of metamorphopsia and sensitivity impairment. Translational Relevance: Future work will be needed to assess applicability of this examination for potential early detection of MD symptoms and/or portable assessment on a home device or computer.
  • Digital Object Identifier (doi)

    Author List

  • Thurman SM; Maniglia M; Davey PG; Biles MK; Visscher KM; Seitz AR
  • Volume

  • 7
  • Issue

  • 5