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磨玻璃密度 CT 影像学特征能否预测侵袭性?一项荟萃分析。

Can CT imaging features of ground-glass opacity predict invasiveness? A meta-analysis.

机构信息

Department of Radiology, Cixi People's Hospital, Cixi, Zhejiang, China.

Department of Radiology, Shangyu Hospital of Traditional Chinese Medicine Hospital Shaoxing, Shaoxing, Zhejiang, China.

出版信息

Thorac Cancer. 2018 Apr;9(4):452-458. doi: 10.1111/1759-7714.12604. Epub 2018 Feb 15.

Abstract

BACKGROUND

A meta-analysis was conducted to investigate the diagnostic performance of computed tomography (CT) imaging features of ground-glass opacity (GGO) to predict invasiveness.

METHODS

Two reviewers independently searched PubMed, Medline, Web of Science, Cochrane Embase and CNKI for relevant studies. CT imaging signs of bubble lucency, speculation, lobulated margin, and pleural indentation were used as diagnostic references to discriminate pre-invasive and invasive disease. The sensitivity, specificity, diagnostic odds ratio (DOR), summary receiver operating characteristic (SROC) curves, and the area under the SROC curve (AUC) were calculated to evaluate diagnostic efficiency.

RESULTS

Twelve studies were finally included. Diagnostic performance ranged from 0.41 to 0.52 for sensitivity and 0.56 to 0.63 for specificity. The diagnostic positive and negative likelihood ratios ranged from 1.03 to 2.13 and 0.52 to 1.05, respectively. The DORs of the GGO CT features for discriminating invasive disease ranged from 1.02 to 4.00. The area under the ROC curve was also low, with a range of 0.60 to 0.67 for discriminating pre-invasive and invasive disease.

CONCLUSION

The diagnostic value of a single CT imaging sign of GGO, such as bubble lucency, speculation, lobulated margin, or pleural indentation is limited for discriminating pre-invasive and invasive disease because of low sensitivity, specificity, and AUC.

摘要

背景

本研究进行了一项荟萃分析,旨在调查磨玻璃密度(GGO)的 CT 影像学特征预测侵袭性的诊断性能。

方法

两位审阅者独立检索了 PubMed、Medline、Web of Science、Cochrane Embase 和中国知网(CNKI)中相关的研究。将气泡征、空泡征、分叶状边缘和胸膜凹陷作为诊断参考,用于区分非侵袭性和侵袭性疾病。计算了灵敏度、特异性、诊断比值比(DOR)、汇总受试者工作特征(SROC)曲线和 SROC 曲线下面积(AUC),以评估诊断效率。

结果

最终纳入了 12 项研究。灵敏度的诊断性能范围为 0.41 至 0.52,特异性的诊断性能范围为 0.56 至 0.63。诊断阳性和阴性似然比的范围分别为 1.03 至 2.13 和 0.52 至 1.05。区分侵袭性疾病的 GGO CT 特征的 DOR 范围为 1.02 至 4.00。ROC 曲线下面积也较低,范围为 0.60 至 0.67,用于区分非侵袭性和侵袭性疾病。

结论

由于灵敏度、特异性和 AUC 较低,单个 GGO 的 CT 影像学特征(如气泡征、空泡征、分叶状边缘或胸膜凹陷)的诊断价值有限,无法区分非侵袭性和侵袭性疾病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fd7/5879054/036974f6f69f/TCA-9-452-g001.jpg

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