Test of a Retinal Nerve Fiber Bundle Trajectory Model Using Eyes With Glaucomatous Optic Neuropathy.
Test of a Retinal Nerve Fiber Bundle Trajectory Model Using Eyes With Glaucomatous Optic Neuropathy.
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DOI：
10.1167/tvst.11.7.7
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发表时间：
2022-07-08
影响因子：
3
通讯作者：
Hood, Donald Charles
中科院分区：
文献类型：
--
作者：
Zemborain, Zane Zenon;Tsamis, Emmanouil;La Bruna, Sol;Leshno, Ari;De Moraes, Carlos Gustavo;Hood, Donald Charles
为了测试预测青光眼患者光学相干断层扫描(OCT)视网膜神经纤维层(RNFL)概率/偏差图(p图)上看到的弧形图案的视网膜神经纤维束轨迹模型。在一个包含250只眼睛的数据库中，31只青光眼在OCT立方体扫描得出的RNFL P图上有清晰的弧形图案。从RNFL p-map中提取弧形图案的边界。接下来，通过归一化均方根差异分析，将弧形模型的轨迹与这些边界进行比较。该模型的参数β是可变的，并且为每个β找到了到边界的轨迹的最佳拟合的初始时钟时间位置。最后，将由弧形边缘最合适的初始时钟时间位置确定的区域与乳头周围视网膜神经纤维层(CpRNFL)轮廓上的异常区域进行比较。弧形模型的平均β、Sup和βInf参数最小化了轨迹和RNFL p图上弧形边界之间的巨大差异。此外，平均而言，由弧形边界最合适的初始时钟时间位置定义的cpRNFL区域中有68%是异常的(即低于≤5%的阈值)。弧形模型在预测RNFL p图上看到的弧形图案的边界方面表现良好。并对cpRNFL厚度图的相关异常区域进行了预测。该模型将有助于临床医生理解不同OCT图像之间的地形比较，并将改进结构-结构以及结构-功能一致性分析。
To test a model of retinal nerve fiber bundle trajectories that predicts the arcuate-shaped patterns seen on optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability/deviation maps (p-maps) in glaucomatous eyes. Thirty-one glaucomatous eyes from a database of 250 eyes had clear arcuate-shaped patterns on RNFL p-maps derived from an OCT cube scan. The borders of the arcuate patterns were extracted from the RNFL p-maps. Next, the trajectories from an arcuate model were compared against these borders via a normalized root-mean-square difference analysis. The model's parameter, β, was varied, and the best-fitting, initial clock-hour position of the trajectory to the border was found for each β. Finally, the regions, as determined by the arcuate border's best-fit, initial clock-hour positions, were compared against the abnormal regions on the circumpapillary retinal nerve fiber layer (cpRNFL) profile. The arcuate model's mean βSup and βInf parameters minimized large differences between the trajectories and the arcuate borders on the RNFL p-maps. Furthermore, on average, 68% of the cpRNFL regions defined by the arcuate border's best-fit, initial clock-hour positions were abnormal (i.e., below the ≤5% threshold). The arcuate model performed well in predicting the borders of arcuate patterns seen on RNFL p-maps. It also predicted the associated abnormal regions of the cpRNFL thickness plots. This model should prove useful in helping clinicians understand topographical comparisons among different OCT representations and should improve structure-structure, as well as structure-function agreement analyses.
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影响因子：
3
作者：
Turpin A;McKendrick AM
通讯作者：
McKendrick AM
影响因子：
4.4
作者：
Hood, Donald C.;Tsamis, Emmanouil;De Moraes, Carlos G.
通讯作者：
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影响因子：
3
作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
2
作者：
Hood, Donald C.;Zemborain, Zane Z.;De Moraes, Carlos Gustavo
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