A sloped piecemeal Gaussian model for characterising foveal pit shape.
A sloped piecemeal Gaussian model for characterising foveal pit shape.
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DOI：
10.1111/opo.12321
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发表时间：
2016-11
期刊：
影响因子：
--
通讯作者：
COMET Group
中科院分区：
文献类型：
--
作者：
Liu L;Marsh-Tootle W;Harb EN;Hou W;Zhang Q;Anderson HA;Norton TT;Weise KK;Gwiazda JE;Hyman L;COMET Group
高质量的光学相干断层扫描（OCT）黄斑扫描可以通过表征中央凹的形状来区分一系列正常和患病状态。现有的数学模型缺乏灵活性，以捕捉所有已知的坑的变化，从而以有限的准确度来识别坑。本研究旨在开发一种新的模型，提供一个更强大的个人凹窝变化的特点。一个倾斜的分段高斯（SPG）模型，由一个倾斜的线和一个分段高斯函数（高斯的两个半连接一个单独的直线）的线性组合，被开发来拟合视网膜厚度数据的灵活性，以适应不同程度的坑不对称性和坑底平坦度。它将原始凹坑数据拟合在中央凹的两个边缘之间以提高准确性。该模型在来自581名年轻人（376名近视患者和206名非近视患者，平均（S.D.）年龄21.9（1.4）岁。视网膜厚度，壁高度和斜率，坑深度和宽度的估计值来自最佳拟合模型曲线。将高斯模型和高斯差分模型的10种变化拟合到相同的扫描，并与SPG模型的拟合优度（通过均方根误差，RMSE）、模型复杂度（通过贝叶斯信息标准）和模型保真度进行比较。SPG模型具有极佳的拟合优度（平均RMSE = 4.25和3.89 μm; 95% CI：水平和垂直剖面拟合分别为4.20、4.30和3.86、3.93）。SPG模型显示窝不对称，鼻壁比颞壁平均高17.6（11.6）μm，陡0.96（0.61）°，上级壁比下壁平均高7.0（12.2）μm，陡0.41（0.65）°。SPG模型还揭示了人类中央凹形状的连续性，从圆形底部到延伸的平底（高达563 μm）。49.1%的中心凹轮廓最适合平底宽>30 μm。与其他测试模型相比，根据贝叶斯信息标准，SPG总体上是首选模型。SPG是一种新的简约的数学模型，通过考虑壁的不对称性和平坦的凹坑底部，改进了其他模型，提供了一个很好的拟合和更忠实的表征典型的中央凹凹坑形状及其已知的变化。这种新的模型可能有助于区分正常的中央凹形状变化的屈光状态以及其他特征，如性别，种族和年龄。
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 to capture all known pit variations and thus characterise the pit with limited accuracy. This study aimed to develop a new model that provides a more robust characterisation of individual foveal pit variations. A Sloped Piecemeal Gaussian (SPG) model, consisting of a linear combination of a tilted line and a piecemeal Gaussian function (two halves of a Gaussian connected by a separate straight line), was developed to fit retinal thickness data with the flexibility to characterise different degrees of pit asymmetry and pit bottom flatness. It fitted the raw pit data between the two rims of the fovea to improve accuracy. The model was tested on 3488 macular scans from both eyes of 581 young adults (376 myopes and 206 non-myopes, mean (S.D.) age 21.9 (1.4) years). Estimates for retinal thickness, wall height and slope, pit depth and width were derived from the best-fitting model curve. Ten variations of Gaussian and Difference of Gaussian models were fitted to the same scans and compared with the SPG model for goodness of fit (by Root mean square error, RMSE), model complexity (by the Bayesian Information Criteria) and model fidelity. The SPG model produced excellent goodness of fit (mean RMSE = 4.25 and 3.89 μm; 95% CI: 4.20, 4.30 and 3.86, 3.93 for fitting horizontal and vertical profiles respectively). The SPG model showed pit asymmetry, with average nasal walls 17.6 (11.6) μm higher and 0.96 (0.61)° steeper than temporal walls and average superior walls 7.0 (12.2) μm higher and 0.41 (0.65)° steeper than the inferior walls. The SPG model also revealed a continuum of human foveal shapes, from round bottoms to extended flat bottoms (up to 563 μm). 49.1% of foveal profiles were best fitted with a flat bottom >30 μm wide. Compared with the other tested models, the SPG was the preferred model overall based on the Bayesian Information Criteria. The SPG is a new parsimonious mathematical model that improves upon other models by accounting for wall asymmetry and flat pit bottoms, providing an excellent fit and more faithful characterisation of typical foveal pit shapes and their known variations. This new model may be helpful in distinguishing normal foveal shape variations by refractive status as well by other characteristics such as sex, ethnicity and age.
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影响因子：
--
作者：
Chan, A;Duker, JS;Schuman, JS
通讯作者：
Schuman, JS
影响因子：
4.2
作者：
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通讯作者：
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影响因子：
3.3
作者：
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通讯作者：
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影响因子：
1.4
作者：
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通讯作者：
Chun, Bo Young
影响因子：
4.2
作者：
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通讯作者：
Yoshimura, Nagahisa