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基于Scheimpflug原理的角膜地形图与生物力学评估相结合以增强圆锥角膜检测

Integration of Scheimpflug-Based Corneal Tomography and Biomechanical Assessments for Enhancing Ectasia Detection.

作者信息

Ambrósio Renato, Lopes Bernardo T, Faria-Correia Fernando, Salomão Marcella Q, Bühren Jens, Roberts Cynthia J, Elsheikh Ahmed, Vinciguerra Riccardo, Vinciguerra Paolo

出版信息

J Refract Surg. 2017 Jul 1;33(7):434-443. doi: 10.3928/1081597X-20170426-02.

Abstract

PURPOSE

To present the Tomographic and Biomechanical Index (TBI), which combines Scheimpflugbased corneal tomography and biomechanics for enhancing ectasia detection.

METHODS

Patients from different continents were retrospectively studied. The normal group included 1 eye randomly selected from 480 patients with normal corneas and the keratoconus group included 1 eye randomly selected from 204 patients with keratoconus. There were two groups: 72 ectatic eyes with no surgery from 94 patients with very asymmetric ectasia (VAE-E group) and the fellow eyes of these patients with normal topography (VAE-NT group). Pentacam HR and Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany) parameters were analyzed and combined using different artificial intelligence methods. The accuracies for detecting ectasia of the Belin/Ambrósio Deviation (BAD-D) and Corvis Biomechanical Index (CBI) were compared to the TBI, considering the areas under receiver operating characteristic curves (AUROCs).

RESULTS

The random forest method with leave-one-out cross-validation (RF/LOOCV) provided the best artificial intelligence model. The AUROC for detecting ectasia (keratoconus, VAE-E, and VAE-NT groups) of the TBI was 0.996, which was statistically higher (DeLong et al., P < .001) than the BAD-D (0.956) and CBI (0.936). The TBI cut-off value of 0.79 provided 100% sensitivity for detecting clinical ectasia (keratoconus and VAE-E groups) with 100% specificity. The AUROCs for the TBI, BAD-D, and CBI were 0.985, 0.839, and 0.822 in the VAE-NT group (DeLong et al., P < .001). An optimized TBI cut-off value of 0.29 provided 90.4% sensitivity with 96% specificity in the VAE-NT group.

CONCLUSIONS

The TBI generated by the RF/LOOCV provided greater accuracy for detecting ectasia than other techniques. The TBI was sensitive for detecting subclinical (fruste) ectasia among eyes with normal topography in very asymmetric patients. The TBI may also confirm unilateral ectasia, potentially characterizing the inherent ectasia susceptibility of the cornea, which should be the subject of future studies. [J Refract Surg. 2017;33(7):434-443.].

摘要

目的

介绍断层扫描与生物力学指数(TBI),该指数结合了基于Scheimpflug的角膜断层扫描和生物力学技术以增强对角膜扩张的检测。

方法

对来自不同大洲的患者进行回顾性研究。正常组包括从480例角膜正常的患者中随机选取的1只眼,圆锥角膜组包括从204例圆锥角膜患者中随机选取的1只眼。研究分为两组:94例非常不对称性角膜扩张(VAE-E组)患者中72只未经手术的扩张眼以及这些患者中地形图正常的对侧眼(VAE-NT组)。分析Pentacam HR和Corvis ST(德国韦茨拉尔Oculus Optikgeräte GmbH公司)参数,并使用不同的人工智能方法进行组合。将贝林/安布罗西奥偏差(BAD-D)和Corvis生物力学指数(CBI)检测角膜扩张的准确性与TBI进行比较,考虑受试者操作特征曲线下面积(AUROC)。

结果

留一法交叉验证的随机森林方法(RF/LOOCV)提供了最佳的人工智能模型。TBI检测角膜扩张(圆锥角膜、VAE-E组和VAE-NT组)的AUROC为0.996,在统计学上高于BAD-D(0.956)和CBI(0.936)(德朗等人,P <.001)。TBI临界值为0.79时,检测临床角膜扩张(圆锥角膜和VAE-E组)的敏感性为100%,特异性为100%。在VAE-NT组中,TBI、BAD-D和CBI的AUROC分别为0.985、0.839和0.822(德朗等人,P <.001)。优化后的TBI临界值为0.29时,在VAE-NT组中敏感性为90.4%,特异性为96%。

结论

RF/LOOCV生成的TBI在检测角膜扩张方面比其他技术具有更高的准确性。TBI对检测非常不对称患者中地形图正常的眼中的亚临床(早期)角膜扩张很敏感。TBI还可能证实单侧角膜扩张,潜在地表征角膜固有的扩张易感性,这应是未来研究的主题。[《屈光手术杂志》。2017;33(7):434 - 443。]

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