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Richard G. Weleber, Travis B. Smith, Dawn Peters, Elvira N. Chegarnov, Scott P. Gillespie, Peter J. Francis, Stuart K. Gardiner, Jens Paetzold, Janko Dietzsch, Ulrich Schiefer, Chris A. Johnson; VFMA: Topographic Analysis of Sensitivity Data From Full-Field Static Perimetry. Trans. Vis. Sci. Tech. 2015;4(2):14. doi: https://doi.org/10.1167/tvst.4.2.14.
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© ARVO (1962-2015); The Authors (2016-present)
To analyze static visual field sensitivity with topographic models of the hill of vision (HOV), and to characterize several visual function indices derived from the HOV volume.
A software application, Visual Field Modeling and Analysis (VFMA), was developed for static perimetry data visualization and analysis. Three-dimensional HOV models were generated for 16 healthy subjects and 82 retinitis pigmentosa patients. Volumetric visual function indices, which are measures of quantity and comparable regardless of perimeter test pattern, were investigated. Cross-validation, reliability, and cross-sectional analyses were performed to assess this methodology and compare the volumetric indices to conventional mean sensitivity and mean deviation. Floor effects were evaluated by computer simulation.
Cross-validation yielded an overall R2 of 0.68 and index of agreement of 0.89, which were consistent among subject groups, indicating good accuracy. Volumetric and conventional indices were comparable in terms of test–retest variability and discriminability among subject groups. Simulated floor effects did not negatively impact the repeatability of any index, but large floor changes altered the discriminability for regional volumetric indices.
VFMA is an effective tool for clinical and research analyses of static perimetry data. Topographic models of the HOV aid the visualization of field defects, and topographically derived indices quantify the magnitude and extent of visual field sensitivity.
VFMA assists with the interpretation of visual field data from any perimetric device and any test location pattern. Topographic models and volumetric indices are suitable for diagnosis, monitoring of field loss, patient counseling, and endpoints in therapeutic trials.
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