目的:对流出设施测量的声像图分级。

IF 2.6 3区 医学 Q2 OPHTHALMOLOGY
Arthur J Sit, Carol B Toris, Vikas Gulati, Arash Kazemi, Jesse Gilbert, Shan Fan, David M Reed, David O Hodge, Sayoko E Moroi
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引用次数: 0

摘要

目的:张力描记术是无创测量房水流出设施的标准方法。然而,语调追踪质量的评估目前是主观的,接受低质量数据或不恰当地丢弃有效数据可能会导致结果偏差。本研究的目的是建立一种客观的方法来评估张力描记的质量。方法:作为一项正在进行的多中心房水动力学研究的一部分,我们对青光眼和高眼压患者进行了气体图示踪。在2分钟内以40 Hz的频率数字测量眼内压(IOP)。每次跟踪得到线性最佳拟合线的均方根误差(RMSE)。每个追踪也由7名经验丰富的拓印师使用1(最差)到10(最佳)的质量等级(专家评分)进行评分。使用一组35个跟踪的参考数据,使用对数曲线确定RMSE值与Expert分数之间的关系。这个关系被用来计算20个跟踪的第二个测试集的预测分数。使用对数曲线来解释专家分数的固定范围和RMSE值的无界上限。使用Bland-Altman分析评估预测分数与专家分数之间的差异。结果:预测评分与专家评分有很强的相关性(R = 0.94)。专家评分与预测评分的平均差值为-1.01±0.84,一致性限在-2.65和+0.63之间。结论:可以使用拟合线的RMSE和计算与专家评分者给出的分数密切匹配的预测质量分数来进行客观的气动图跟踪评估。翻译相关性:音素追踪质量现在可以客观地评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Objective Grading of Tonography Tracings for the Measurement of Outflow Facility.

Purpose: Tonography is the standard method for non-invasive measurement of aqueous humor outflow facility. However, assessment of tonography tracing quality is currently subjective, and acceptance of poor-quality data or inappropriately discarding valid data can bias results. The purpose of this study was to develop an objective method for assessing the quality of tonography tracings.

Methods: Pneumatonography tracings were obtained from glaucoma and ocular hypertension patients as part of an ongoing multicenter study of aqueous humor dynamics. Intraocular pressure (IOP) was captured digitally at 40 Hz over 2 minutes. Root mean square error (RMSE) of a linear best-fit line was obtained for each tracing. Each tracing was also graded by seven experienced tonographers using a scale of 1 (worst) to 10 (best) for quality (Expert score). A Reference set of 35 tracings was used to determine the relationship between RMSE values and Expert scores using a logarithmic curve. This relationship was used to calculate a predicted score in a second Test set of 20 tracings. A logarithmic curve was used to account for the fixed range of Expert scores and unbounded upper range for RMSE values. The differences between the predicted scores and the Expert scores were evaluated using Bland-Altman analysis.

Results: There was a very strong correlation between predicted and Expert scores (R = 0.94). The mean difference between Expert and predicted scores was -1.01 ± 0.84, and the limits of agreement were between -2.65 and +0.63.

Conclusions: Objective assessment of pneumatonography tracings can be performed using RMSE of a fitted line and calculation of a predicted quality score that closely matches scores given by expert graders.

Translational relevance: Tonography tracing quality can now be objectively assessed.

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来源期刊
Translational Vision Science & Technology
Translational Vision Science & Technology Engineering-Biomedical Engineering
CiteScore
5.70
自引率
3.30%
发文量
346
审稿时长
25 weeks
期刊介绍: Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO. The journal covers a broad spectrum of work, including but not limited to: Applications of stem cell technology for regenerative medicine, Development of new animal models of human diseases, Tissue bioengineering, Chemical engineering to improve virus-based gene delivery, Nanotechnology for drug delivery, Design and synthesis of artificial extracellular matrices, Development of a true microsurgical operating environment, Refining data analysis algorithms to improve in vivo imaging technology, Results of Phase 1 clinical trials, Reverse translational ("bedside to bench") research. TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.
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