超微血管成像技术诊断乳腺肿瘤的meta分析

doi:10.3969/j.issn.1004-583X.2024.02.002

摘要/Abstract

摘要：

目的采用meta分析方法评价超微血管成像技术(SMI)评估乳腺肿瘤良恶性的临床价值。方法系统搜索PubMed、Cochrane Library、Embase、CNKI、CBM、WANFANG、VIP中建库至2022年9月20日有关超微血流成像(super microvascular imaging, SMI)评估乳腺肿瘤良恶性的文献。由2名研究人员依据纳入及排除标准初筛文献并提取信息;运用QUADAS-2工具评估纳入原始文献质量,Review Manager 5.3绘制文献质量评估图,Stata 17.0计算SMI评估乳腺肿瘤的敏感度(SEN)、特异度(SPE)、阳性似然比(PLR)、阴性似然比(NLR)及诊断比值比(DOR),绘制综合受试者工作特征曲线(SROC),获得曲线下面积;绘制漏斗图进行发表偏倚评估。结果最终纳入15篇文献、1 769例乳腺肿瘤患者、共1 912个病灶,其中恶性结节916个、良性结节991个。Meta分析结果显示,SMI评估乳腺病变SEN、SPE、PLR、NLR、DOR及SROC曲线下面积分别为0.82[95%CI(0.79~0.84)]、0.87[95%CI(0.85~0.89)]、6.58[95%CI(4.58~9.43)]、0.19[95%CI(0.16~0.24)]、39.47[95%CI(27.18~57.31)]、0.93[95%CI(0.90~0.95)]。结论 SMI评估乳腺良恶性病变的鉴别具有较高的诊断准确性。

关键词: 超微血流成像, 乳腺肿瘤, 荟萃分析

Abstract:

Objective The purpose was to evaluate the value of superb microvascular imaging (SMI) for benign and malignant breast tumors by a meta-analysis. Methods We searched PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), WanFang, VIP for literature on the diagnosis of SMI for benign and malignant breast tumors from the time of building the database to September 20, 2022. Two researchers screened literature and extracted information based on inclusion and exclusion criteria. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was performed to assess the quality of the included primary literature, Review Manager 5.3 was conduted to plot the literature quality assessment chart, Stata 17.0 was used to calculate SMI for sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) of breast tumors. The area under the curve (AUC) was obtained by summary receiver operating characteristic (SROC) curve. Funnel plot was applicated to evaluate publication bias. Results Fifteen meta-analyses representing 1769 cases of breast tumor patients were included, with 1912 lesions (916 malignant nodules and 991 benign nodules). The results of the meta-analysis showed that the SEN, SPE, PLR, NLR, DOR and AUC of SROC curves for SMI in the assessment of breast lesions were 0.82 (95%CI 0.79 to 0.84), 0.87(95%CI 0.85 to 0.89), 6.58(95%CI 4.58 to 9.43), 0.19(95%CI 0.16 to 0.24), and 39.47(95%CI 27.18 to 57.31), 0.93(95%CI 0.90 to 0.95). Conclusion SMI has a high diagnostic accuracy in evaluating the differentiation of benign and malignant breast lesions.

Key words: superb microvascular imaging, breast lesions, meta-analysis

中图分类号:

R737.9

陈思晗, 熊虎, 税典雅, 高小瞻, 刘泽伟. 超微血管成像技术诊断乳腺肿瘤的meta分析[J]. 临床荟萃, 2024, 39(2): 108-114.

Chen Sihan, Xiong Hu, Shui Dianya, Gao Xiaozhan, Liu Zewei. Diagnostic of superb microvascular imaging for breast tumors: A meta-analysis[J]. Clinical Focus, 2024, 39(2): 108-114.

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链接本文: https://huicui.hebmu.edu.cn/CN/10.3969/j.issn.1004-583X.2024.02.002

https://huicui.hebmu.edu.cn/CN/Y2024/V39/I2/108

图/表 9

参考文献 26

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纳入研究	研究类型	超声仪器	病人数	纳入总数 (恶性/良性)(例)	患者年龄 (岁)	TP (例)	FP (例)	FN (例)	TN (例)
Yongfeng^[5] 2016	回顾性	TOSHIBA Aplio500	111	135(41/94)	18~65	40	18	1	76
Zhang^[6] 2019	回顾性	TOSHIBA Aplio500	232	236(121/115)	19~65	103	8	18	107
Zhu^[7] 2018	回顾性	TOSHIBA Aplio500	95	95(78/12)	22~73	78	2	8	12
Kim^[8] 2018	回顾性	TOSHIBA Aplio500	65	62(12/50)	28~80	10	6	2	44
Xiao^[9] 2016	回顾性	TOSHIBA Aplio400	132	132(58/74)	16~78	45	7	13	67
Cai^[10] 2021	回顾性	TOSHIBA Aplio500	224	238(138/100)	NA	64	4	48	109
张剑^[11] 2019	回顾性	TOSHIBA Aplio400	85	87(41/46)	33~80	30	12	8	28
肖露^[12] 2018	回顾性	TOSHIBA Aplio500	105	105(41/64)	36~63	38	22	3	42
李涛^[13] 2020	回顾性	TOSHIBA Aplio500	82	86(46/40)	17~76	40	2	6	38
李响^[14] 2015	回顾性	TOSHIBA Aplio500	134	146(47/99)	18~78	36	3	11	96
马燕^[15] 2015	回顾性	TOSHIBA Aplio400	70	78(38/40)	17~67	35	11	5	27
车丹丹^[16] 2019	回顾性	TOSHIBA Aplio400	82	88(40/48)	17~76	35	4	5	44
马燕^[17] 2016	回顾性	TOSHIBA Aplio400	122	138(60/78)	16~56	54	14	6	64
陈欣^[18] 2016	回顾性	TOSHIBA Aplio400	116	116(53/63)	16~78	42	6	11	57
毛怡然^[19] 2018	回顾性	TOSHIBA Aplio500	114	170(102/68)	19~86	84	9	18	59

纳入研究	研究类型	超声仪器	病人数	纳入总数 (恶性/良性)(例)	患者年龄 (岁)	TP (例)	FP (例)	FN (例)	TN (例)
Yongfeng^[5] 2016	回顾性	TOSHIBA Aplio500	111	135(41/94)	18~65	40	18	1	76
Zhang^[6] 2019	回顾性	TOSHIBA Aplio500	232	236(121/115)	19~65	103	8	18	107
Zhu^[7] 2018	回顾性	TOSHIBA Aplio500	95	95(78/12)	22~73	78	2	8	12
Kim^[8] 2018	回顾性	TOSHIBA Aplio500	65	62(12/50)	28~80	10	6	2	44
Xiao^[9] 2016	回顾性	TOSHIBA Aplio400	132	132(58/74)	16~78	45	7	13	67
Cai^[10] 2021	回顾性	TOSHIBA Aplio500	224	238(138/100)	NA	64	4	48	109
张剑^[11] 2019	回顾性	TOSHIBA Aplio400	85	87(41/46)	33~80	30	12	8	28
肖露^[12] 2018	回顾性	TOSHIBA Aplio500	105	105(41/64)	36~63	38	22	3	42
李涛^[13] 2020	回顾性	TOSHIBA Aplio500	82	86(46/40)	17~76	40	2	6	38
李响^[14] 2015	回顾性	TOSHIBA Aplio500	134	146(47/99)	18~78	36	3	11	96
马燕^[15] 2015	回顾性	TOSHIBA Aplio400	70	78(38/40)	17~67	35	11	5	27
车丹丹^[16] 2019	回顾性	TOSHIBA Aplio400	82	88(40/48)	17~76	35	4	5	44
马燕^[17] 2016	回顾性	TOSHIBA Aplio400	122	138(60/78)	16~56	54	14	6	64
陈欣^[18] 2016	回顾性	TOSHIBA Aplio400	116	116(53/63)	16~78	42	6	11	57
毛怡然^[19] 2018	回顾性	TOSHIBA Aplio500	114	170(102/68)	19~86	84	9	18	59

纳入文献	敏感度 95%CI	特异度 95%CI	阳性似然比 95%CI	阴性似然比 95%CI	诊断比值比 95%CI	SROC曲线下面积 95%CI
全部文献	0.82(0.79~0.84)	0.87(0.85~0.89)	6.58(4.58~9.43)	0.19(0.16~0.24)	39.47(27.18~57.31)	0.93(0.90~0.95)
删除6号	0.82(0.79~0.85)	0.87(0.85~0.89)	6.49(4.44~9.49)	0.18(0.13~0.26)	40.37(26.88~60.64)	0.91(0.88~0.93)
删除7号	0.82(0.79~0.84)	0.88(0.86~0.90)	7.10(4.90~10.29)	0.18(0.13~0.25)	44.11(32.18~60.45)	0.93(0.91~0.95)
删除6和7	0.86(0.83~0.88)	0.87(0.84~0.89)	6.68(4.63~9.65)	0.18(0.15~0.21)	44.94(32.31~62.50)	0.93(0.90~0.95)

纳入文献	敏感度 95%CI	特异度 95%CI	阳性似然比 95%CI	阴性似然比 95%CI	诊断比值比 95%CI	SROC曲线下面积 95%CI
全部文献	0.82(0.79~0.84)	0.87(0.85~0.89)	6.58(4.58~9.43)	0.19(0.16~0.24)	39.47(27.18~57.31)	0.93(0.90~0.95)
删除6号	0.82(0.79~0.85)	0.87(0.85~0.89)	6.49(4.44~9.49)	0.18(0.13~0.26)	40.37(26.88~60.64)	0.91(0.88~0.93)
删除7号	0.82(0.79~0.84)	0.88(0.86~0.90)	7.10(4.90~10.29)	0.18(0.13~0.25)	44.11(32.18~60.45)	0.93(0.91~0.95)
删除6和7	0.86(0.83~0.88)	0.87(0.84~0.89)	6.68(4.63~9.65)	0.18(0.15~0.21)	44.94(32.31~62.50)	0.93(0.90~0.95)