Chinese Journal of Tissue Engineering Research ›› 2010, Vol. 14 ›› Issue (43): 8065-8068.doi: 10.3969/j.issn.1673-8225.2010.43.022

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A quantitative analysis system for myocardial contrast echocardiography based on eliminating particle swarm optimization clustering algorithm

Du Guo-qing1, Tian Jia-wei1, Guo Yan-hui○2, Su Yang1, Zhang Meng1   

  1. 1 Department of Ultrasound, Second Affiliated Hospital of Harbin Medical University, Key Laboratories of Myocardial Ischemia Mechanism and Treatment (Harbin M edical University), Ministry of Education, Harbin  150086, Heilongjiang Province, China; 2 Department of Computer Science, Utah State University, Logan, UT, 84341, USA
  • Online:2010-10-22 Published:2010-10-22
  • Contact: Tian Jia-wei, Master, Professor, Doctoral supervisor, Department of Ultrasound, Second Affiliated Hospital of Harbin Medical University, Key Laboratories of Myocardial Ischemia Mechanism and Treatment (Harbin Medical University), Ministry of Education, Harbin 150086, Heilongjiang Province, China 150086 duguoqing999@yahoo.com.cn
  • About author:Du Guo-qing☆, Doctor, Associate chief physician, Department of Ultrasound, Second Affiliated Hospital of Harbin Medical University, Key Laboratories of Myocardial Ischemia Mechanism and Treatment (Harbin Medical University), Ministry of Education, Harbin 150086, Heilongjiang Province, China duguoqing999@yahoo.com.cn
  • Supported by:

     the Natural Science Foundation of Heilongjiang Province, No. ZJY0707-02*; Heilongjiang Province Postdoctoral Foundation, No. LRB09-361*; Second Affiliated Hospital of HMU Doctoral Startup Foundation, No.BS2009-20*; Higher Specialized Research Foundation for the Doctoral Program of Ministry of Education No.20092307110017

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Abstract:

BACKGROUND: Myocardial contrast echocardiography (MCE) has been used to assess the myocardial capillary perfusion after thrombolytic therapy or percutaneous coronary intervention. The current interpretation of perfusion images by MCE is performed by visual qualitative analysis and drawn manually the region of interests. The accuracy of such analysis depends on the investigators’ experience, and lacks quantitative analysis.
OBJECTIVE: To evaluate the feasibility of a quantitative analysis system for MCE in assessing myocardial perfusion.
METHODS: Rabbit MCE images were collected, and processed automatically by quantitative analysis software based on eliminating particle swarm optimization (EPSO) clustering algorithm to obtain myocardial perfusion parameters.
RESULTS AND CONCLUSION:  ①Quantitative analysis software was used to identify automatically endocardium and epicardium and determine myocardial region; ②Six myocardial regions were dissected automatically; ③Calibrated myocardial contrast intensity (CI) of all segments was calculated automatically; ④Myocardial perfusion of all segments was color-coded according to calibrated CI, and the percentage of color-coded area was obtained; ⑤Myocardial perfusion distribution histogram was generated automatically. MCE image analysis system based on EPSO clustering algorithm in the quantitative assessment of myocardial microperfusion and identification of myocardial perfusion abnormalities has good feasibility and high value.

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