A sloped piecemeal Gaussian model for characterising foveal pit shape.

摘要: Purpose High-quality optical coherence tomography (OCT) macular scans make it possible to distinguish a range of normal and diseased states by characterising foveal pit shape. Existing mathematical models lack the flexibility capture all known variations thus characterise with limited accuracy. This study aimed develop new model that provides more robust characterisation individual variations. Methods A Sloped Piecemeal Gaussian (SPG) model, consisting linear combination tilted line piecemeal function (two halves connected separate straight line), was developed fit retinal thickness data different degrees asymmetry bottom flatness. It fitted raw between two rims fovea improve The tested on 3488 from both eyes 581 young adults (376 myopes 206 non-myopes, mean (S.D.) age 21.9 (1.4) years). Estimates for thickness, wall height slope, depth width were derived best-fitting curve. Ten Difference same compared SPG goodness (by Root square error, RMSE), complexity Bayesian Information Criteria) fidelity. Results The produced excellent (mean RMSE = 4.25 3.89 μm; 95% CI: 4.20, 4.30 3.86, 3.93 fitting horizontal vertical profiles respectively). showed asymmetry, average nasal walls 17.6 (11.6) μm higher 0.96 (0.61)° steeper than temporal superior 7.0 (12.2) μm 0.41 (0.65)° inferior walls. also revealed continuum human shapes, round bottoms extended flat (up 563 μm). 49.1% best >30 μm wide. Compared other models, preferred overall based Criteria. Conclusions The is parsimonious improves upon accounting bottoms, providing an faithful typical shapes their variations. may be helpful in distinguishing shape refractive status as well characteristics such sex, ethnicity age.