| 曹新玥,朱美霖,印隆林,刘一铭,吴颖.CT影像组学预测肾透明细胞癌病理分级:Meta分析[J].中国医学影像技术,2022,38(8):1197~1202 |
| CT影像组学预测肾透明细胞癌病理分级:Meta分析 |
| CT radiomics for predicting pathological grade of renal clear cell carcinoma: Meta-analysis |
| 投稿时间：2021-11-12 修订日期：2022-06-02 |
| DOI：10.13929/j.issn.1003-3289.2022.08.017 |
| 中文关键词: 肾肿瘤 病理学 体层摄影术,X线计算机 荟萃分析 影像组学 |
| 英文关键词:kidney neoplasms pathology tomography, X-ray computed meta-analysis radiomics |
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| 中文摘要: |
| 目的 采用Meta分析观察CT影像组学预测肾透明细胞癌(ccRCC)病理分级的价值。方法 检索建库至2021年1月PubMed、Web of Science、EMbase及中国知网、中国生物医学文献服务系统和万方医学网CT影像组学预测ccRCC病理分级相关文献,并进行筛选、质量评价及资料提取;以Stata 16.0软件行Meta分析。结果 纳入16篇文献、2 489例患者共2 495个ccRCC病灶。CT影像组学预测ccRCC病理分级无明显阈值效益(r=0.12,P＜0.01)而具有较高异质性(I2≥50%),其合并敏感度0.85、合并特异度0.86,阳性似然比6.00、阴性似然比0.18、诊断比值比34.00,曲线下面积0.92。结论 CT影像组学预测ccRCC病理分级效能较佳。 |
| 英文摘要: |
| Objective To observe the value of CT radiomics for predicting pathological grade of clear cell renal cell carcinoma (ccRCC) with meta-analysis. Methods Literature concerning predicting pathological grade of ccRCC based on CT radiomics in the PubMed, Web of Science, EMbase, CNKI, SinoMed and Wanfang Med Online were searched from the time of establishment to January 2021. Literature screening, quality evaluation and data extraction were performed. Stata 16.0 was used for meta-analysis. Results A total of 16 articles were enrolled, including 2 489 patients with 2 495 ccRCC lesions. There was no significant threshold benefit in predicting the pathological grade of ccRCC based on CT radiomics (r=0.12, P<0.01) but was high heterogeneous (I2 ≥ 50%). The combined sensitivity was 0.85(95%CI), combined specificity was 0.86(95%CI), positive likelihood ratio was 6.00(95%CI), negative likelihood ratio was 0.18(95%CI), the diagnostic odds ratio was 34.00(95%CI) and area under the curve was 0.92. Conclusion CT radiomics was effective for predicting pathological grade of ccRCC. |
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