Design and evaluation of a quantitative analysis software for myocardial contrast echocardiography
10.3877/cma.j.issn.1672-6448.2010.12.010
- VernacularTitle:自制心肌超声造影定量分析软件的设计与评价
- Author:
Guo-qing, DU
;
Jia-wei, TIAN
;
Min, REN
;
Yu-jie, LIU
;
Shuang-quan, JIANG
;
Yan-hui, GUO
;
Yang, SU
;
Meng, ZHANG
- Publication Type:Journal Article
- Keywords:
Echocardiography;
Contrast media;
Image processing,computer-aided;
Myocardial perfusion
- From:
Chinese Journal of Medical Ultrasound (Electronic Edition)
2010;07(12):2038-2046
- CountryChina
- Language:Chinese
-
Abstract:
Objective To evaluate the feasibility of quantitative analysis software for myocardial contrast echocardiography (MCE) in assessment of myocardial perfusion.Methods According to coronary occlusion and reperfusion at different times,rabbits were divided into two groups:15 min occlusion / 30 min reperfusion (group Ⅰ) and 120 min occlusion / 60 min reperfusion (group Ⅱ).MCE was performed on all rabbits at baseline,occlusion and after reperfusion,and its images were analyzed by a new quantitative analysis software based on eliminating particle swarm optimization (EPSO) clustering algorithm,by which obtain myocardial perfusion parameters.Results (1) The values of calibrated contrast intensity (CI) in risk segments of Groups Ⅰ and Ⅱ were significantly lower than those at baseline during occlusion (t =5.104 and t =4.327,P＜0.01).After reperfusion,calibrated CI in risk segments significantly improved in Group Ⅰ (t =2.933,P＜0.01) while those remained unchanged in Group Ⅱ (P＞0.05).(2) The areas of red-coded region in color-coded map and myocardial infarction in triphenyl-tetrazolium chloride (TTC) were (21.4±12.3)% and (18.0±9.5)%,respectively.The correlation between color-coded image and TTC was 0.89 (P＜0.01).(3) The histogram in all risk segments was skew distribution during occlusion.After reperfusion,the histogram in Group Ⅰ was normal distribution while that was still skewed distribution in Group Ⅱ.Conclusion The MCE image analysis software based on EPSO clustering algorithm in the quantitative assessment of myocardial microperfusion and identification of myocardial perfusion abnormalities was feasible and of high value.
