Patent foramen ovale (PFO) is a potential separation between the septum, primum and septum secundum located in the anterosuperior portion of the atrial septum. PFO is one of the main factors causing cryptogenic stroke which is the fifth leading cause of death in the United States. For PFO diagnosis, contrast transthoracic echocardiography (cTTE) is preferred as being a more robust method compared with others. However, the current PFO diagnosis through cTTE is extremely slow as it is proceeded manually by sonographers on echocardiography videos. Currently there is no publicly available dataset for this important topic in the community. In this paper, we present EchoCP, as the first echocardiography dataset in cTTE targeting PFO diagnosis. EchoCP consists of 30 patients with both rest and Valsalva maneuver videos which covers various PFO grades. We further establish an automated baseline method for PFO diagnosis based on the state-of-the-art cardiac chamber segmentation technique, which achieves 0.89 average mean Dice score, but only 0.60/0.67 mean accuracies for PFO diagnosis, leaving large room for improvement. We hope that the challenging EchoCP dataset can stimulate further research and lead to innovative and generic solutions that would have an impact in multiple domains. Our dataset is released.
翻译:PFO是导致美国第五大死亡原因之一的加密中风的主要因素之一。 PFO的诊断认为,对比切换式回声心动分析(cTTE)是一种较强的方法。然而,目前通过CTTE进行的PFO诊断非常缓慢,因为由回声心电图录像的声学学家手动进行。目前,没有关于社区这一重要主题的公开数据集。我们在此文件中介绍EchoCP,作为CTTE中第一组针对PFO诊断的回声心动数据集。EchoCP由30名有休息和Valsalva调控视频的病人组成,涵盖PFO的不同等级。我们进一步根据州-艺术心室分解技术,为PFO诊断建立了自动基线方法,该方法将达到0.89平均的Dice分数,但我们只有0.60/06的普通分数, 才能使PFO得到更大的分析。