Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
复制标题
DOI：
10.1038/s41598-019-54653-6
复制
发表时间：
2019-12-02
影响因子：
4.6
通讯作者：
Medeiros, Felipe A.
中科院分区：
文献类型：
--
作者：
Berchuck, Samuel I.;Mukherjee, Sayan;Medeiros, Felipe A.
在这篇手稿中，我们开发了一种深度学习算法来改进对青光眼进展速度的估计和对未来青光眼视野丧失模式的预测。使用3832名患者的29,161个视野，对广义变分自动编码器(VAE)进行了训练，以学习标准自动视野(SAP)视野的低维表示。VAE是在90%的数据样本上进行训练的，在患者水平上进行随机化。使用剩下的10%，产生进展率和预测值，分别与SAP平均偏差(MD)率和逐点(PW)回归预测值进行比较。VAE潜伏期的纵向变化率(例如，8个维度)在距基线2年(25%对9%)和4年(35%对15%)时检测到的进展比例明显高于MD。早期，VAE改善了对PW的预测，与前三次相比，预测第4次、第6次和第8次的平均绝对误差要小得多(例如，第八次访问：VAE8：5.14dBvs Pw：8.07db；P<；0.001)。深层VAE可用于评估青光眼的进展速度和轨迹，另外一个好处是它是一种能够预测未来视野损害模式的生成性技术。
In this manuscript we develop a deep learning algorithm to improve estimation of rates of progression and prediction of future patterns of visual field loss in glaucoma. A generalized variational auto-encoder (VAE) was trained to learn a low-dimensional representation of standard automated perimetry (SAP) visual fields using 29,161 fields from 3,832 patients. The VAE was trained on a 90% sample of the data, with randomization at the patient level. Using the remaining 10%, rates of progression and predictions were generated, with comparisons to SAP mean deviation (MD) rates and point-wise (PW) regression predictions, respectively. The longitudinal rate of change through the VAE latent space (e.g., with eight dimensions) detected a significantly higher proportion of progression than MD at two (25% vs. 9%) and four (35% vs 15%) years from baseline. Early on, VAE improved prediction over PW, with significantly smaller mean absolute error in predicting the 4th, 6th and 8th visits from the first three (e.g., visit eight: VAE8: 5.14 dB vs. PW: 8.07 dB; P < 0.001). A deep VAE can be used for assessing both rates and trajectories of progression in glaucoma, with the additional benefit of being a generative technique capable of predicting future patterns of visual field damage.