Crabb, D. P.

Modarelli, A.

Montesano, G.

Rossetti, L. M.

City Research Online

              City, University of London Institutional RepositoryCitation: Montesano, G., Modarelli, A., Rossetti, L. M. and Crabb, D. P. ORCID: 0000-0001-8754-3902 (2018). Improving perimetric examination of the macular visual field using structural information. Investigative Ophthalmology & Visual Science, 59(9), 4990.. ISSN 0146-0404 This is the published version of the paper. This version of the publication may differ from the final published version. Permanent repository link:  http://openaccess.city.ac.uk/21782/Link to published version: Copyright and reuse: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to.City Research Online:            http://openaccess.city.ac.uk/            publications@city.ac.ukCity Research OnlineOPEN ACCESSARVO Annual Meeting Abstract  |   July 2018Improving perimetric examination of the macular visual ﬁeld usingstructural informationGiovanni Montesano; Antonio Modarelli; Luca Mario Rossetti; David P Crabb  Author A liations & NotesInvestigative Ophthalmology & Visual Science July 2018, Vol.59, 4990. doi:AbstractPurpose : To integrate structural information in testing strategy for macular visual  eld in glaucoma.Methods : one eye of 17 healthy and 31 glaucoma subjects was analysed. Macular OCT scan (Spectralis, Heidelberg Engineering) and 10-2perimetric test with the Compass fundus perimeter (CenterVue) were performed. We matched fundus images to precisely place tested locations on the OCT maps (Figure 1). Stimulus reactions (button pressing) were extracted and probability of seen curves at di erent values of local structural damage estimated. Thecurves were used to build priors for a structural ZEST (S-ZEST) strategy (Figure 1). We compared S-ZEST and ZEST simulating reliable (false positive rate = 0.03) and unreliable subjects (false positive rate = 0.13). For simulations, to accurately estimate true input thresholds in glaucoma subjects, we tested 12 patients with 8 points at 1 and 3 degrees from xation with 4-2 strategy, three times, taking the average. Data from fellow eye were used for healthy subjects. Mean absolute deviation (MAD) from input thresholds was calculated. Mean di erence ± standard error is reported.Results : S-ZEST reduced the number of presentations in normals (reduction per 68-locations test; reliable: 144.57 ± 0.27, 31%; unreliable: 166.75 ±0.27, 33%) and glaucomas (reduction per 8-location test; reliable: 6.28 ± 0.10, 13%; unreliable: 7.05 ± 0.10, 14%). Error was reduced in S-ZEST in glaucomas (MAD reduction per test; reliable: 0.13 ± 0.01 dB; unreliable: 0.33 ± 0.01 dB, Figure 2) and normals (MADreduction per test; reliable: 0.07 ± 0.002 dB; unreliable: 0.33 ± 0.002 dB). All p < 0.001.Conclusions : We used fundus perimetry to accurately model mean and variance of structural priors. S-ZEST e ciently allocates morepresentations for diseased locations, increasing precision and reducing overall test time.This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.View Original Download SlideFigure 1. Compass fundus image (left) and overlaid Spectralis fundus image after matching (middle). Red dots indicate tested locations. On theright, an example of the starting priors for S-ZEST of two locations with di erent ganglion cell damage. Tested locations were moved on theganglion cell map to account for Henle  bre displacement.View Original Download SlideFigure 2. MAD error (vertical axis) at di erent input thresholds (horizontal axis) for unreliable glaucoma subjects. Boxes enclose the interquartilerange, the green and red lines enclose the 95% and 99% quantiles respectively.This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.  

Improving perimetric examination of the macular visual field using structural information

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Improving perimetric examination of the macular visual field using structural information

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