Background Orthokeratology (ortho-k) is an overnight clinical contact lens wear technique to correct myopia and to reduce myopia progression wearing reverse-geometry rigid gas-permeable lenses. The lens fitting procedure in clinical… Click to show full abstract
Background Orthokeratology (ortho-k) is an overnight clinical contact lens wear technique to correct myopia and to reduce myopia progression wearing reverse-geometry rigid gas-permeable lenses. The lens fitting procedure in clinical practice usually requires subjective assessment of fluorescein pattern (fluorescein “bull’s eye” pattern). The aim of this study was to develop a novel tool for fluorescein pattern measurements to reduce subjective practitioner dependency, especially in inexperienced practitioners, in ortho-k practice. Methods A new MATLAB customized algorithm to measure the horizontal width of the four main zones of ortho-k fluorescein patterns (central bearing, tear reservoir, mid-peripheral bearing and edge lift) was designed. The algorithm was tested on a small image database consisting of 26 ortho-k fluorescein pattern images of 13 volunteers fitted with reverse geometry lenses (Seefree, Conoptica-Hecht Contactlinsen). The agreement between two independent observers and the ImageJ measurements was determined. Results The new clinical tool provided similar measurements to ImageJ software for the central bearing (4.20 ± 0.74 and 4.27 ± 0.69 mm; P = 0.21), tear reservoir (1.69 ± 0.41 and 1.69 ± 0.45 mm; P = 0.69), mid-peripheral bearing (1.17 ± 0.11 and 1.13 ± 0.10 mm; P < 0.01) and edge lift (0.48 ± 0.06 and 0.48 ± 0.06 mm; P = 0.81) zones. Good agreement between the software (limits of agreement lower than ±0.55 mm) and inter-observer measurements (limits of agreement lower than ±0.66 mm) was found. Conclusions The proposed clinical tool for semiautomatic fluorescein pattern measurements in ortho-k could help to reduce practitioner dependency in fluorescein pattern assessment with future potential to introduce prediction algorithms or artificial intelligence methods in myopia control management.
               
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