Meta-analysis of the diagnostic value of different imaging methods for peritoneal metastasis of ovarian cancer

doi:10.3877/cma.j.issn.2095-5782.2021.02.011

Abstract

Abstract:

Objective

To systematically evaluate the diagnostic value of CT, MRI, PET/CT imaging in peritoneal metastasis of ovarian cancer.

Methods

The Chinese and English databases were used to retrieve the diagnostic clinical trials of primary ovarian cancer with peritoneal metastasis on CT, MRI, PET/CT imaging. True positive, false positive, true negative, false negative and other raw data were extracted based on patients or lesions and were analyzed using the software Meta-Discl 1.4.The sensitivity (SEN), specificity (SPE) and diagnostic odds ratio (Diagnostic odds ratio, DOR) of CT, MRI and PET/CT imaging in the diagnosis of peritoneal metastasis of ovarian cancer were calculated.

Results

Sixteen articles were finally included. The results of the systematic review showed that in the analysis results based on patients,the SEN, SPE, and DOR values of CT imaging for peritoneal metastasis of ovarian cancer were 76% (95%CI: 70%~82%), 82% (95%CI: 77%~86%), 21.72 (95%CI: 4.74~99. 40), those of MRI imaging were 93% (95%CI: 83%~98%), 81% (95%CI: 73%~87%), 73.95 (95%CI: 20.56~265.98), and those of PET/CT imaging were 73% (95%CI: 63%~82%), 92% (95%CI: 84%~97%), 30.29 (95%CI: 3.95~232.55). In the analysis results based on the lesions, the SEN, SPE and DOR values of CT imaging for peritoneal metastasis of ovarian cancer were 72% (95%CI: 71%~74%), 86% (95%CI: 85%~87%) and 16.66 (95%CI: 4.23~65.58), those of MRI imaging were 87% (95%CI: 85%~90%), 91% (95%CI: 88%~92%), 68.28 (95%CI: 40.40~115.40), and those of PET/CT imaging were 63% (95%CI: 60%~66%), 87% (95%CI: 84%~90%), 14.38 (95%CI: 5.81~35.59).

Conclusions

MRI is the most sensitive and specific examination method and it is the best imaging method for evaluating peritoneal metastasis of ovarian cancer.

Key words: Ovarian cancer, Peritoneal metastasis, CT, MRI, PET/CT

Shiming Huang, Siyu Wu, Yongfeng Sun, Liang Yin, Jianlan Yue, Zhichun Lin. Meta-analysis of the diagnostic value of different imaging methods for peritoneal metastasis of ovarian cancer[J]. Chinese Journal of Interventional Radiology(Electronic Edition), 2021, 09(02): 177-182.

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References 31

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作者		发表时间	国家	平均年龄/岁	设计方法	金标准	病例入组时间	QUADAS
作者		发表时间	国家	平均年龄/岁	设计方法	金标准	病例入组时间	是	否/不清楚
基于患者的研究
	Lopez-Lopez V^[4]	2016	西班牙	54（27～78）	回顾性	病理	2008.01—2014.05	11	3
	Rubini G^[5]	2014	意大利	59.83（30～83）	回顾性	病理	NR	10	3
	Kim HW^[6]	2013	韩国	54（29～80）	回顾性	病理	2007.01—2010.06	12	2
	Dirisamer A^[7]	2009	奥地利	61（43～81）	回顾性	病理	2003.07—2005.08	13	1
	Coakley FV^[8]	2002	美国	55（28～81）	回顾性	病理	1996.06—2000.08	12	2
	Tempany CM^[9]	2000	美国	57（19～79）	前瞻性	病理	1993.05—1996.04	11	2
	Fujii S^[10]	2008	日本	62（30～83）	回顾性	病理	2005.01—2006.06	11	3
基于病灶的研究
	Ahmed SA^[11]	2019	埃及	51（22～72）	回顾性	病理	2014.01—2018.03	13	1
	Schmidt S^[12]	2015	瑞士	65（31～89）	前瞻性	病理	NR	11	3
	Michielsen K^[13]	2014	比利时	69.1（20～83）	前瞻性	病理	2010.10—2012.02	12	2
	Hynninen J^[14]	2013	芬兰	65（45～79）	前瞻性	病理	2009.10—2012.03	12	2
	Metser U^[15]	2011	加拿大	58.2（24～87）	回顾性	病理	2005.01—2008.03	13	1
	Choi HJ^[16]	2011	韩国	53.1（30～72）	回顾性	病理	2006.07—2008.01	12	2
	Funicelli L^[17]	2010	意大利	NR	回顾性	病理	2001—2008	11	3
	Prado JG^[18]	2019	西班牙	56±12.69	前瞻性	病理	2014.06—2017.01	12	2
	张圆^[19]	2019	中国	54.6（35～67）	回顾性	病理	2016.10—2017.11	12	2

作者		发表时间	国家	平均年龄/岁	设计方法	金标准	病例入组时间	QUADAS
作者		发表时间	国家	平均年龄/岁	设计方法	金标准	病例入组时间	是	否/不清楚
基于患者的研究
	Lopez-Lopez V^[4]	2016	西班牙	54（27～78）	回顾性	病理	2008.01—2014.05	11	3
	Rubini G^[5]	2014	意大利	59.83（30～83）	回顾性	病理	NR	10	3
	Kim HW^[6]	2013	韩国	54（29～80）	回顾性	病理	2007.01—2010.06	12	2
	Dirisamer A^[7]	2009	奥地利	61（43～81）	回顾性	病理	2003.07—2005.08	13	1
	Coakley FV^[8]	2002	美国	55（28～81）	回顾性	病理	1996.06—2000.08	12	2
	Tempany CM^[9]	2000	美国	57（19～79）	前瞻性	病理	1993.05—1996.04	11	2
	Fujii S^[10]	2008	日本	62（30～83）	回顾性	病理	2005.01—2006.06	11	3
基于病灶的研究
	Ahmed SA^[11]	2019	埃及	51（22～72）	回顾性	病理	2014.01—2018.03	13	1
	Schmidt S^[12]	2015	瑞士	65（31～89）	前瞻性	病理	NR	11	3
	Michielsen K^[13]	2014	比利时	69.1（20～83）	前瞻性	病理	2010.10—2012.02	12	2
	Hynninen J^[14]	2013	芬兰	65（45～79）	前瞻性	病理	2009.10—2012.03	12	2
	Metser U^[15]	2011	加拿大	58.2（24～87）	回顾性	病理	2005.01—2008.03	13	1
	Choi HJ^[16]	2011	韩国	53.1（30～72）	回顾性	病理	2006.07—2008.01	12	2
	Funicelli L^[17]	2010	意大利	NR	回顾性	病理	2001—2008	11	3
	Prado JG^[18]	2019	西班牙	56±12.69	前瞻性	病理	2014.06—2017.01	12	2
	张圆^[19]	2019	中国	54.6（35～67）	回顾性	病理	2016.10—2017.11	12	2

作者		诊断方法	病例数	病灶数	TP	FP	FN	TN	SEN（%）	SPE（%）	ACC（%）	PPV（%）	NPV（%）
基于患者的研究
	Lopez-Lopez V^[4]	CT	44	767	6	1	11	26	35.00	96.30	73.28	85.03	71.13
		PET/CT	46	767	4	2	13	27	24.00	93.00	67.73	66.00	68.00
	Rubini G^[5]	CT	79		23	14	20	22	53.57	60.87	56.86	62.50	51.85
		PET/CT	79		34	3	9	33	78.57	91.30	84.32	91.67	77.78
	Kim HW^[6]	CT	46		23	7	3	13	88.50	65.00	78.26	76.70	81.30
		PET/CT	46		25	2	1	18	96.20	90.00	93.48	92.60	94.70
	Dirisamer A^[7]	CT	62		26	1	5	30	83.87	96.77	90.32	96.30	85.71
	Coakley FV^[8]	CT	64		35	2	6	21	85.37	91.30	87.50	94.59	77.78
	Tempany CM^[9]	CT	212		46	30	4	132	92.00	81.48	83.96	60.53	97.06
		常规MRI	175		39	27	2	107	95.12	79.85	83.43	59.09	98.17
	Fujii S^[10]	MRI （DWI）	26		13	1	2	10	86.67	90.91	88.46	92.86	83.33
基于病灶的研究
	Ahmed SA^[11]	CT	85	925	725	20	50	130	93.55	86.67	92.43	97.90	72.20
	Schmidt S^[12]	CT	17	135	77	4	3	50	96.00	92.00	94.60	95.00	94.00
		MRI （DWI）	17	135	84	8	2	41	98.00	84.00	92.59	91.00	96.00
		PET/CT	17	135	80	2	4	49	95.00	96.00	95.65	98.00	92.00
	Michielsen K^[13]	CT	32	475	136	47	72	220	65.38	82.40	74.95	74.32	75.34
		MRI （DWI）	32	475	189	24	19	243	90.87	91.01	90.95	88.73	92.75
		PET/CT	32	475	108	39	100	228	51.92	85.39	70.74	73.47	69.51
	Hynninen J^[14]	CT	41	856	193	20	288	355	40.12	94.67	64.02	90.61	55.21
		PET/CT	41	713	237	25	226	225	51.19	90.00	64.80	90.46	49.89
	Metser U^[15]	CT	76	1 845	337	79	78	1 351	81.20	94.48	91.49	81.01	94.54
	Choi HJ^[16]	CT	57	741	114	135	137	355	45.42	72.45	63.29	45.78	72.15
	Funicelli L^[17]	CT	89	310	155	97	35	23	81.58	19.17	57.42	61.51	39.66
	Prado JG^[18]	MRI （DWI）	50	650	13	1	2	10	86.67	90.91	88.46	92.86	83.33
	张圆^[19]	MRI （DWI）	39	273	99	12	26	136	79.20	91.89	86.08	89.19	83.95

作者		诊断方法	病例数	病灶数	TP	FP	FN	TN	SEN（%）	SPE（%）	ACC（%）	PPV（%）	NPV（%）
基于患者的研究
	Lopez-Lopez V^[4]	CT	44	767	6	1	11	26	35.00	96.30	73.28	85.03	71.13
		PET/CT	46	767	4	2	13	27	24.00	93.00	67.73	66.00	68.00
	Rubini G^[5]	CT	79		23	14	20	22	53.57	60.87	56.86	62.50	51.85
		PET/CT	79		34	3	9	33	78.57	91.30	84.32	91.67	77.78
	Kim HW^[6]	CT	46		23	7	3	13	88.50	65.00	78.26	76.70	81.30
		PET/CT	46		25	2	1	18	96.20	90.00	93.48	92.60	94.70
	Dirisamer A^[7]	CT	62		26	1	5	30	83.87	96.77	90.32	96.30	85.71
	Coakley FV^[8]	CT	64		35	2	6	21	85.37	91.30	87.50	94.59	77.78
	Tempany CM^[9]	CT	212		46	30	4	132	92.00	81.48	83.96	60.53	97.06
		常规MRI	175		39	27	2	107	95.12	79.85	83.43	59.09	98.17
	Fujii S^[10]	MRI （DWI）	26		13	1	2	10	86.67	90.91	88.46	92.86	83.33
基于病灶的研究
	Ahmed SA^[11]	CT	85	925	725	20	50	130	93.55	86.67	92.43	97.90	72.20
	Schmidt S^[12]	CT	17	135	77	4	3	50	96.00	92.00	94.60	95.00	94.00
		MRI （DWI）	17	135	84	8	2	41	98.00	84.00	92.59	91.00	96.00
		PET/CT	17	135	80	2	4	49	95.00	96.00	95.65	98.00	92.00
	Michielsen K^[13]	CT	32	475	136	47	72	220	65.38	82.40	74.95	74.32	75.34
		MRI （DWI）	32	475	189	24	19	243	90.87	91.01	90.95	88.73	92.75
		PET/CT	32	475	108	39	100	228	51.92	85.39	70.74	73.47	69.51
	Hynninen J^[14]	CT	41	856	193	20	288	355	40.12	94.67	64.02	90.61	55.21
		PET/CT	41	713	237	25	226	225	51.19	90.00	64.80	90.46	49.89
	Metser U^[15]	CT	76	1 845	337	79	78	1 351	81.20	94.48	91.49	81.01	94.54
	Choi HJ^[16]	CT	57	741	114	135	137	355	45.42	72.45	63.29	45.78	72.15
	Funicelli L^[17]	CT	89	310	155	97	35	23	81.58	19.17	57.42	61.51	39.66
	Prado JG^[18]	MRI （DWI）	50	650	13	1	2	10	86.67	90.91	88.46	92.86	83.33
	张圆^[19]	MRI （DWI）	39	273	99	12	26	136	79.20	91.89	86.08	89.19	83.95

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