Prediction of Function in ABCA4-Related Retinopathy Using Ensemble Machine Learning
Prediction of Function in ABCA4-Related Retinopathy Using Ensemble Machine Learning
复制标题
DOI：
10.3390/jcm9082428
复制
发表时间：
2020-08-01
影响因子：
3.9
通讯作者：
Holz, Frank G.
中科院分区：
文献类型：
--
作者：
Mueller, Philipp L.;Treis, Tim;Holz, Frank G.
全视野视网膜电图（ERG）和最佳矫正视力（BCVA）测量已被证明对隐性Stargardt病（也称为“ABCA 4相关视网膜病变”）具有预后价值。这些功能测试可作为新兴干预性临床试验中的性能-结局-测量（PerfO），但效用受到变异性和患者负担的限制。为了解决这些局限性，评估了一种基于集成机器学习的方法，以区分患者和对照组，并根据ERG（“推断ERG”）和视觉障碍（“推断视觉障碍”）以及基于显微结构成像（利用谱域光学相干断层扫描）和患者数据的BCVA值（“推断BCVA”）预测疾病类别。“推断ERG”和“推断视力损害”的准确性高达99.53 ± 1.02%。BCVA值的预测（“推断BCVA”）在高达85.31%的眼睛中实现了+/- 0.3LogMAR的精度。排列重要性分析显示，中心凹状态是BCVA预测的最重要特征，而外核层和感光细胞内外段的厚度以及发病年龄对所有预测都有很高的排名。本文中的“推断的ERG”、“推断的视觉障碍”和“推断的BCVA”表示视网膜微结构的不同功能效应的准确估计，并且提供准功能参数，其具有用于精细患者评估和潜在的未来治疗效应或疾病进展的调查的潜力。
Full-field electroretinogram (ERG) and best corrected visual acuity (BCVA) measures have been shown to have prognostic value for recessive Stargardt disease (also called "ABCA4-related retinopathy"). These functional tests may serve as a performance-outcome-measure (PerfO) in emerging interventional clinical trials, but utility is limited by variability and patient burden. To address these limitations, an ensemble machine-learning-based approach was evaluated to differentiate patients from controls, and predict disease categories depending on ERG ('inferred ERG') and visual impairment ('inferred visual impairment') as well as BCVA values ('inferred BCVA') based on microstructural imaging (utilizing spectral-domain optical coherence tomography) and patient data. The accuracy for 'inferred ERG' and 'inferred visual impairment' was up to 99.53 +/- 1.02%. Prediction of BCVA values ('inferred BCVA') achieved a precision of +/- 0.3LogMAR in up to 85.31% of eyes. Analysis of the permutation importance revealed that foveal status was the most important feature for BCVA prediction, while the thickness of outer nuclear layer and photoreceptor inner and outer segments as well as age of onset highly ranked for all predictions. 'Inferred ERG', 'inferred visual impairment', and 'inferred BCVA', herein, represent accurate estimates of differential functional effects of retinal microstructure, and offer quasi-functional parameters with the potential for a refined patient assessment, and investigation of potential future treatment effects or disease progression.