Application of superb microvascular imaging in detection of blood flow in gout

doi:10.3877/cma.j.issn.1672-6448.2020.04.011

Abstract

Abstract:

Objective

To assess the application of superb microvascular imaging (SMI) in detecting blood flow in tophi and synovial hyperplasia.

Methods

A total of 68 non-acute gout patients were enrolled at Zhongshan Hospital of Fudan University from October 2017 to October 2018. The blood flow signals in tophi and synovial hyperplasia were detected by power Doppler imaging (PDI) and SMI respectively, and they were divided into four grades (0~3). The differences of blood flow grades detected in tophi and synovial hyperplasia by SMI and PDI were compared, and the correlation between blood flow grades and high-sensitivity C-reactive protein (hs-CRP) was calculated.

Results

There were statistically significant differences in gout duration and hs-CRP between groups with different frequency of attacks (0~5, 6~10, and >10 times/year) (P=0.006 and 0.003). The number of patients with high-grade (grades 2 and 3) tophi and synovial hyperplasia detected by SMI was significantly more than that by PDI, and the number of patients with low-grade (grades 0 and 1) was significantly less than that by PDI (Z=-5.385 and -2.842, respectively; P<0.001, =0.004). The SMI grade of synovial hyperplasia had the highest correlation with hs-CRP (r=0.721, P<0.001), followed by synovial hyperplasia grade, PDI grade of synovial hyperplasia, SMI grade of tophi, and PDI grade of tophi (r=0.570, 0.563, 0.532, and 0.399, respectively; P<0.001, <0.001, <0.001, and =0.007, respectively).

Conclusion

SMI is more sensitive in detecting blood flow in tophi and synovial hyperplasia than PDI. SMI grade of synovial hyperplasia has the highest correlation with hs-CRP, which can provide more valuable diagnostic information for gout activity assessment.

Key words: Gout, Ultrasonography, Microvascular imaging, Synovial hyperplasia, Tophus

Beilei Lu, Beijian Huang, Cuixian Li, Fengyang Zheng, Wenping Wang, Peilei Wang, Luxia Jing, Qun Wang. Application of superb microvascular imaging in detection of blood flow in gout[J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2020, 17(04): 353-358.

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URL: https://chaosheng.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1672-6448.2020.04.011

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Figures/Tables 5

References 13

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组别（次/年）	例数	年龄（岁，±s）	BMI（kg/m²，±s）	尿酸（mmol/L，±s）	持续时间（年，±s）	hs-CRP ［mg/L，M（Q_R）］	WBC（10⁹/L，±s）	ESR（mm/h，±s）
0~5	39	54.5±16.0	25.6±3.7	466.4±108.8	5.4±4.9	3.0（0.7，6.7）	8.5±3.0	28.5±16.8
6~10	13	59.0±17.8	25.7±3.1	477.7±133.1	8.0±5.1	5.9（2.9，69.7）^a	8.5±1.9	31.3±15.4
>10	16	56.2±11.1	27.3±6.6	503.8±142.7	10.5±6.2^b	10.3（5.2，66.2）^b	8.4±4.3	55.3±44.0
F/χ²值		0.407	0.798	0.555	5.570	13.257	0.057	0.941
P值		0.668	0.455	0.557	0.006	0.003	0.995	0.429

组别（次/年）	例数	年龄（岁，±s）	BMI（kg/m²，±s）	尿酸（mmol/L，±s）	持续时间（年，±s）	hs-CRP ［mg/L，M（Q_R）］	WBC（10⁹/L，±s）	ESR（mm/h，±s）
0~5	39	54.5±16.0	25.6±3.7	466.4±108.8	5.4±4.9	3.0（0.7，6.7）	8.5±3.0	28.5±16.8
6~10	13	59.0±17.8	25.7±3.1	477.7±133.1	8.0±5.1	5.9（2.9，69.7）^a	8.5±1.9	31.3±15.4
>10	16	56.2±11.1	27.3±6.6	503.8±142.7	10.5±6.2^b	10.3（5.2，66.2）^b	8.4±4.3	55.3±44.0
F/χ²值		0.407	0.798	0.555	5.570	13.257	0.057	0.941
P值		0.668	0.455	0.557	0.006	0.003	0.995	0.429

超声模式	例数	痛风石血流分级				滑膜增生血流分级
超声模式	例数	0级	1级	2级	3级	0级	1级	2级	3级
SMI	68	4	16	22	3	15	18	24	6
PDI	68	9	22	14	0	22	29	10	2
Z值		-5.385					-2.842
P值		<0.001					0.004

超声模式	例数	痛风石血流分级				滑膜增生血流分级
超声模式	例数	0级	1级	2级	3级	0级	1级	2级	3级
SMI	68	4	16	22	3	15	18	24	6
PDI	68	9	22	14	0	22	29	10	2
Z值		-5.385					-2.842
P值		<0.001					0.004

hs-CRP	例数	痛风石血流分级								滑膜增生血流分级
		SMI				PDI				SMI				PDI
		0级	1级	2级	3级	0级	1级	2级	3级	0级	1级	2级	3级	0级	1级	2级	3级
正常组（<3 mg/L）	25	3	10	2	0	6	7	2	0	11	8	2	0	14	6	1	0
轻度增高组（3~10 mg/L）	20	1	2	9	0	2	7	3	0	4	8	7	0	6	12	1	0
明显增高组（>10 mg/L）	23	0	5	10	3	1	9	8	0	0	2	15	6	2	11	8	2
χ²值		14.419				7.018				32.763				20.321
P值		0.030				0.001				<0.001				<0.001

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