Automated keratoconus screening with corneal topography analysis.
Automated keratoconus screening with corneal topography analysis.
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DOI：
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发表时间：
1994-05
影响因子：
4.4
通讯作者：
N. Maeda;S. Klyce;M. Smolek;H. Thompson
中科院分区：
文献类型：
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作者：
N. Maeda;S. Klyce;M. Smolek;H. Thompson
目的：虽然由受过训练的专家对角膜地形图进行目视检查是有效的，但这种方法本身是主观的。可以检测异常地形模式并对其进行分类的定量分类方法将是有用的。开发了一种自动化系统，使用计算机辅助视频角膜镜检查将圆锥角膜模式与其他条件区分开来。方法将TMS-1型视频角膜内窥镜的8个指标进行判别分析，得到线性判别函数，并将线性判别函数与分类树相结合。100个具有各种诊断（圆锥角膜、正常、角膜移植术、表观角膜镜片术、准分子激光屈光性角膜切除术、根治性角膜切开术、角膜接触镜诱导的翘曲等）的角膜用于训练，并且100个额外角膜的验证集用于评估结果。结果22例临床诊断的圆锥角膜患者均被检测出，有3例假阳性（敏感性100%，特异性96%，准确性97%）。使用验证集，28例圆锥角膜病例中有25例被检测到，其中1例为假阳性病例，即移植角膜（敏感性89%，特异性99%，准确性96%）。结论该系统可作为临床圆锥角膜与其他角膜地形图的鉴别诊断方法。这种定量分类方法也有助于改进地形图的临床解释。
PURPOSE Although visual inspection of corneal topography maps by trained experts can be powerful, this method is inherently subjective. Quantitative classification methods that can detect and classify abnormal topographic patterns would be useful. An automated system was developed to differentiate keratoconus patterns from other conditions using computer-assisted videokeratoscopy. METHODS This system combined a classification tree with a linear discriminant function derived from discriminant analysis of eight indices obtained from TMS-1 videokeratoscope data. One hundred corneas with a variety of diagnoses (keratoconus, normal, keratoplasty, epikeratophakia, excimer laser photorefractive keratectomy, radical keratotomy, contact lens-induced warpage, and others) were used for training, and a validation set of 100 additional corneas was used to evaluate the results. RESULTS In the training set, all 22 cases of clinically diagnosed keratoconus were detected with three-false-positive cases (sensitivity 100%, specificity 96%, and accuracy 97%). With the validation set, 25 out of 28 keratoconus cases were detected with one false-positive case, which was a transplanted cornea (sensitivity 89%, specificity 99%, and accuracy 96%). CONCLUSIONS This system can be used as a screening procedure to distinguish clinical keratoconus from other corneal topographies. This quantitative classification method may also aid in refining the clinical interpretation of topographic maps.