Polar residual network model for assisting evaluation on rat myocardial infarction segment in myocardial contrast echocardiography
10.13929/j.issn.1003-3289.2024.08.003
- VernacularTitle:极坐标残差网络模型辅助诊断心肌声学造影所示大鼠心肌梗死节段
- Author:
Wenqian SHEN
1
,
2
;
Yanhui GUO
;
Bo YU
;
Shuang CHEN
;
Hairu LI
;
Yan WU
;
You LI
;
Guoqing DU
Author Information
1. 中山大学孙逸仙纪念医院超声科,广东广州 510120
2. 哈尔滨医科大学附属第二医院超声医学科,黑龙江哈尔滨 150086
- Keywords:
myocardial infarction;
deep learning;
ultrasonography;
animal experimentation
- From:
Chinese Journal of Medical Imaging Technology
2024;40(8):1130-1134
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of polar residual network(PResNet)model for assisting evaluation on rat myocardial infarction(MI)segment in myocardial contrast echocardiography(MCE).Methods Twenty-five male SD rats were randomly divided into MI group(n=15)and sham operation group(n=10).MI models were established in MI group through ligation of the left anterior descending coronary artery using atraumatic suture,while no intervention was given to those in sham operation group after thoracotomy.MCE images of both basal and papillary muscle levels on the short axis section of left ventricles were acquired after 1 week,which were assessed independently by 2 junior and 2 senior ultrasound physicians.The evaluating efficacy of MI segment,the mean interpretation time and the consistency were compared whether under the assistance of PResNet model or not.Results No significant difference of efficacy of evaluation on MI segment was found for senior physicians with or without assistance of PResNet model(both P＞0.05).Under the assistance of PResNet model,the efficacy of junior physicians for diagnosing MI segment was significantly improved compared with that without the assistance of PResNet model(both P＜0.01),and was comparable to that of senior physicians.Under the assistance of PResNet model,the mean interpretation time of each physician was significantly shorter than that without assistance(all P＜0.001),and the consistency between junior physicians and among junior and senior physicians were both moderate(Kappa=0.692,0.542),which became better under the assistance(Kappa=0.763,0.749).Conclusion PResNet could improve the efficacy of junior physicians for evaluation on rat MI segment in MCE images,shorten interpretation time with different aptitudes,also improve the consistency to some extent.
