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Dimensional Accuracy and Clinical Value of 3D Printed Models in Congenital Heart Disease: A Systematic Review and Meta-Analysis

机译:先天性心脏病的3D打印模型的尺寸精度和临床价值:系统评价和荟萃分析

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摘要

The aim of this paper is to summarize and evaluate results from existing studies on accuracy and clinical value of three-dimensional printed heart models (3DPHM) for determining whether 3D printing can significantly improve on how the congenital heart disease (CHD) is managed in current clinical practice. Proquest, Google Scholar, Scopus, PubMed, and Medline were searched for relevant studies until April 2019. Two independent reviewers performed manual data extraction and assessed the risk of bias of the studies using the tools published on National Institutes of Health (NIH) website. The following data were extracted from the studies: author, year of publication, study design, imaging modality, segmentation software, utility of 3DPHM, CHD types, and dimensional accuracy. R software was used for the meta-analysis. Twenty-four articles met the inclusion criteria and were included in the systematic review. However, only 7 studies met the statistical requirements and were eligible for meta-analysis. Cochran’s Q test demonstrated significant variation among the studies for both of the meta-analyses of accuracy of 3DPHM and the utility of 3DPHM in medical education. Analysis of all included studies reported the mean deviation between the 3DPHM and the medical images is not significant, implying that 3DPHM are highly accurate. As for the utility of the 3DPHM, it is reported in all relevant studies that the 3DPHM improve the learning experience and satisfaction among the users, and play a critical role in facilitating surgical planning of complex CHD cases. 3DPHM have the potential to enhance communication in medical practice, however their clinical value remains debatable. More studies are required to yield a more meaningful meta-analysis.
机译:本文的目的是总结和评估现有的关于三维打印心脏模型(3DPHM)的准确性和临床价值的研究结果,以确定3D打印是否可以显着改善当前如何处理先天性心脏病(CHD)临床实践。一直在搜索Proquest,Google Scholar,Scopus,PubMed和Medline,直到2019年4月为止。两名独立审稿人进行了人工数据提取,并使用了美国国立卫生研究院(NIH)网站上发布的工具评估了研究偏倚的风险。从研究中提取了以下数据:作者,出版年份,研究设计,成像方式,分割软件,3DPHM的实用性,CHD类型和尺寸精度。 R软件用于荟萃分析。符合纳入标准的二十四篇文章被纳入系统评价。但是,只有7项研究符合统计要求,并符合荟萃分析的条件。 Cochran的Q检验表明,在3DPHM准确性的荟萃分析和3DPHM在医学教育中的实用性方面,研究之间存在重大差异。对所有纳入研究的分析报告称,3DPHM和医学图像之间的平均偏差并不显着,这表明3DPHM是高度准确的。至于3DPHM的实用性,在所有相关研究中都报告说3DPHM可以改善用户的学习体验和满意度,并且在促进复杂的CHD病例的手术计划中起着关键作用。 3DPHM具有增强医学实践交流的潜力,但其临床价值仍有待商de。需要进行更多的研究才能得出更有意义的荟萃分析。

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