Liang Fuxiang, Li Meixuan, Yao Liang, Wang Xiaoqin, Liu Jieting, Li Huijuan, Cao Liujiao, Liu Shidong, Song Yumeng, Song Bing
The First Hospital of Lanzhou University.
School of Public Health.
Medicine (Baltimore). 2019 Jul;98(29):e16326. doi: 10.1097/MD.0000000000016326.
Prostate cancer (PCa) is one of the most common primary malignancies in humans and the second leading cause of cancer-specific mortality among Western males. Computer-aided detection (CAD) systems have been developed for accurate and automated PCa detection and diagnosis, but the diagnostic accuracy of different CAD systems based on magnetic resonance imaging (MRI) for PCa remains controversial. The aim of this study is to systematically review the published evidence to investigate diagnostic accuracy of different CAD systems based on MRI for PCa.
We will conduct the systematic review and meta-analysis according to the Preferred Reporting Items for a systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA) guidelines. Cochrane library, PubMed, EMBASE and Chinese Biomedicine Literature Database will be systematically searched from inception for eligible articles, 2 independent reviewers will select studies on CAD-based MRI diagnosis of PCa and extract the requisite data. The quality of reporting evidence will be assessed using the quality assessment of diagnosis accuracy study (QUADAS-2) tool. Pooled sensitivity, specificity, and the area under the summary receiver operating characteristic (SROC) curves will be calculated to estimate the diagnostic accuracy of CAD system. In addition, we will conduct subgroup analyses according to the type of classifier of CAD systems used and the different prostate zoon.
This study will conduct a meta-analysis of current evidence to investigate the diagnostic accuracy of CAD systems based on MRI for PCa by calculating sensitivity, specificity, and SROC curves.
The conclusion of this study will provide evidence to judge whether CAD systems based on MRI have high diagnostic accuracy for PCa.
Ethics approval is not required for this systematic review as it will involve the collection and analysis of secondary data. The results of the review will be reported in international peer-reviewed journals.
CRD42019132543.
前列腺癌（PCa）是人类最常见的原发性恶性肿瘤之一，也是西方男性癌症特异性死亡的第二大主要原因。计算机辅助检测（CAD）系统已被开发用于准确、自动地检测和诊断PCa，但基于磁共振成像（MRI）的不同CAD系统对PCa的诊断准确性仍存在争议。本研究的目的是系统地回顾已发表的证据，以调查基于MRI的不同CAD系统对PCa的诊断准确性。
我们将根据诊断试验准确性研究的系统评价和Meta分析的首选报告项目（PRISMA-DTA）指南进行系统评价和Meta分析。从创刊开始，将系统检索Cochrane图书馆、PubMed、EMBASE和中国生物医学文献数据库中的符合条件的文章，2名独立的评审员将选择基于CAD的PCa MRI诊断研究并提取所需数据。将使用诊断准确性研究质量评估（QUADAS-2）工具评估报告证据的质量。计算合并敏感性、特异性和汇总接受者操作特征（SROC）曲线下的面积，以估计CAD系统的诊断准确性。此外，我们将根据所使用的CAD系统的分类器类型和不同的前列腺区域进行亚组分析。
本研究将对现有证据进行Meta分析，通过计算敏感性、特异性和SROC曲线来调查基于MRI的CAD系统对PCa的诊断准确性。
本研究的结论将为判断基于MRI的CAD系统对PCa是否具有高诊断准确性提供证据。
本系统评价不需要伦理批准，因为它将涉及二次数据的收集和分析。评价结果将在国际同行评审期刊上报告。
PROSPERO注册号：CRD42019132543。
