Polar residual network model for assisting evaluation on rat myocardial infarction segment in myocardial contrast echocardiography

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

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.

目的观察极坐标残差网络(PResNet)模型辅助评估心肌声学造影(MCE)所示大鼠心肌梗死(MI)节段的价值。方法将25只雄性SD大鼠随机分为MI组(n=15)及假手术组(n=10)。对MI组以无损伤线结扎冠状动脉左前降支制备MI大鼠模型,假手术组开胸后不予特殊处置;1周后采集存活大鼠左心室短轴切面基底水平和乳头肌水平MCE图像;由低年资与高年资超声科医师各2名独立阅片,观察有、无PResNet模型辅助下不同年资医师评估MI节段的效能、平均解读用时及结果一致性。结果高年资医师有、无PResNet模型辅助下评估效能差异均无统计学意义(P均>0.05)。模型辅助下,低年资医师评估MI节段效能与高年资医师相当,相比无辅助显著提高(P均<0.01)。模型辅助下各医师平均解读用时均较无辅助显著缩短(P均<0.001)。无辅助时低年资医师间、低年资与高年资医师间的一致性中等(Kappa=0.692、0.542),模型辅助下一致性均为较好(Kappa=0.763、0.749)。结论PResNet模型可提高低年资超声医师评估大鼠MCE中MI节段的效能,缩短解读用时,并在一定程度上提高判断一致性。