丙型肝炎病毒基因分型：用于Versant丙型肝炎病毒基因分型线探针检测2.0版的Web 2.0解读与分析平台。
Hepatitis C Virus Genie: A Web 2.0 Interpretation and Analytics Platform for the Versant Hepatitis C Virus Genotype Line Probe Assay Version 2.0.
作者信息
Dussaq Alex M, Soni Abha, Willey Christopher, Park Seung L, Harada Shuko
机构信息
Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, USA.
Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, AL, USA.
出版信息
J Pathol Inform. 2017 Oct 3;8:41. doi: 10.4103/jpi.jpi_44_17. eCollection 2017.
CONTEXT
Hepatitis C virus (HCV) genotyping at our institution is performed using the Versant HCV genotype 2.0 Line Probe Assay (LiPA). The last steps of this procedure are manual, laborious, and error-prone process that involves the comparison of the banding pattern on a test strip to a physical reference table.
AIM
We developed a web-based HCV genotype interpretation platform that utilizes a scanned image to generate the genotypes, thus minimizing interpretation time and reducing error.
SUBJECTS AND METHODS
HCV Genie 2 utilizes a database of banding patterns in conjuncture with image analysis algorithms to determine the genotype for any number of scanned LiPA strips. HCV Genie 2 is built with client-side JavaScript; allowing the program to run in the user' browser rather than on an unknown server, essentially eliminating data and patient privacy concerns.
RESULTS
HCV Genie 2 was tested over 2 months and proved identical to human expert interpretation for 148 samples (>1000 bands identified). Manual intervention was required only for two faint bands and one false-positive band; this was done utilizing the built-in-user interface. Utilizing the original method, the trained laboratory technician interpretation time for 16 samples was 13.8 (±0.96) min as compared to 5.0 (±1.09) min with HCV Genie 2, a 63.8% decrease. In addition to the time savings, the new method provides an additional validation step, which decreases the potential for errors.
CONCLUSIONS
Our institution has moved exclusively to utilize the new techniques and tools described here. Both experienced technicians and the molecular pathologists at our institution prefer the workflow using HCV Genie. It is easier for the technicians to prepare and document, and the pathologists are more rapidly able to review and confirm results. The use of this tool will lead to increase the quality of patient care delivered through this test methodology by decreasing the potential for error. The algorithms developed here can be ported to similar band identification platforms, most directly to other LiPAs.
背景
我们机构使用Versant HCV基因型2.0线性探针分析（LiPA）进行丙型肝炎病毒（HCV）基因分型。该程序的最后几步是人工操作，费力且容易出错，涉及将测试条上的条带模式与物理参考表进行比较。
目的
我们开发了一个基于网络的HCV基因型解读平台，该平台利用扫描图像生成基因型，从而最大限度地减少解读时间并减少错误。
对象和方法
HCV Genie 2结合图像分析算法利用条带模式数据库来确定任意数量扫描LiPA条带的基因型。HCV Genie 2是用客户端JavaScript构建的；允许程序在用户浏览器中运行而不是在未知服务器上，基本上消除了数据和患者隐私问题。
结果
HCV Genie 2经过2个月的测试，对于148个样本（识别出超过1000条带）证明与人类专家解读结果相同。仅对两条模糊条带和一条假阳性条带需要人工干预；这是利用内置用户界面完成的。使用原始方法，训练有素的实验室技术人员对16个样本的解读时间为13.8（±0.96）分钟，而使用HCV Genie 2为5.0（±1.09）分钟，减少了63.8%。除了节省时间外，新方法还提供了额外的验证步骤，减少了出错的可能性。
结论
我们机构已完全转向使用此处描述的新技术和工具。我们机构的经验丰富的技术人员和分子病理学家都更喜欢使用HCV Genie的工作流程。技术人员准备和记录更容易，病理学家能够更快地审查和确认结果。使用该工具将通过降低出错可能性来提高通过这种测试方法提供的患者护理质量。这里开发的算法可以移植到类似的条带识别平台，最直接的是移植到其他LiPA。
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