Erenbourg Anna, Barber Tracie, Cecotti Vera, Faiola Stefano, Fantasia Ilaria, Stampaljia Tamara, Avnet Hagai, Radzymińska-Chruściel Beata, Meriki Neama, Welsh Alec
UNSW School of Clinical Medicine, Perinatal Imaging Research Group (PIRG), Level 0, Royal Hospital for Women, Barker Street (Locked Bag 2000), Sydney, NSW, 2031, Australia.
UNSW School of Mechanical & Manufacturing Engineer, Ainsworth Building, Level 4, Room 401A, Kensington Campus, Sydney, NSW, 2031, Australia.
BMC Pregnancy Childbirth. 2025 Jan 30;25(1):99. doi: 10.1186/s12884-025-07145-7.
Congenital heart disease (CHD) is the most common fetal malformation, and it can result first in cardiac remodeling and dysfunction and later in cardiac failure and hydrops. A limited number of studies have evaluated cardiac function in fetuses affected by CHD. Functional parameters could potentially identify fetuses at risk of cardiac failure before its development. However, these techniques have not translated from research to clinical settings, due to a lack of standardization and poor repeatability. We seek to evaluate whether application of automated techniques to a cohort with fetal pathology could overcome these factors.
A multicenter cohort study will be carried out in eight teaching hospitals across Europe, Australia, and Middle East. Based on a previous observed standard deviation, a total sample of 381 pregnancies is required to achieve 80% power to detect a difference of 0.03 in mean myocardial performance index (MPI) with a two-sided type I error rate of 5%. After adjustments allowing for patient exclusions or incomplete datasets, a total of 330 healthy singleton pregnancies and 165 diagnosed with CHD will be recruited. Two fetal cardiac function evaluations at 19 + 6-28 + 6 and 32 + 6-36 + 6 weeks will be offered assessing automated pulsed wave doppler (PWD) MPI, spatio-temporal image correlation (STIC) annular and septal plane excursion (TAPSE, MAPSE and SAPSE), alongside cardiac morphometric and Doppler evaluations of flow across the valves. A secondary nested case-control study will evaluate fetuses with hydrops compared to those without. Differences in functional parameters between cases and controls and over time will be assessed using generalized linear mixed models. Logistic regression will estimate the association between cardiac parameters and hydrops' incidence.
This study will provide evidence as to whether automated functional parameters could be significantly different in pregnancy affected by CHD versus healthy pregnancies. The primary objective is to compare automated PWD-MPI and STIC TAPSE, MAPSE and SAPSE in fetuses affected by CHD versus healthy. The secondary objective is to estimate whether these automated parameters could improve the predictive value of the classical cardiovascular profile score in case of hydrops.
The study protocol has been registered in the ClinicalTrials.gov Protocol Registration System, identification number NCT05698277.
先天性心脏病(CHD)是最常见的胎儿畸形,它首先会导致心脏重塑和功能障碍,随后会引发心力衰竭和水肿。仅有少数研究评估了患有CHD的胎儿的心脏功能。功能参数有可能在心力衰竭发生前识别出有风险的胎儿。然而,由于缺乏标准化和可重复性差,这些技术尚未从研究转化到临床应用中。我们试图评估将自动化技术应用于患有胎儿疾病的队列是否能克服这些因素。
将在欧洲、澳大利亚和中东的八家教学医院开展一项多中心队列研究。根据先前观察到的标准差,总共需要381例妊娠样本,以80%的检验效能检测平均心肌性能指数(MPI)相差0.03,双侧I型错误率为5%。在考虑患者排除或不完整数据集进行调整后,将总共招募330例健康单胎妊娠和165例诊断为CHD的妊娠。将在19 + 6至28 + 6周以及32 + 6至36 + 6周进行两次胎儿心脏功能评估,评估自动脉冲波多普勒(PWD)MPI、时空图像相关(STIC)环形和间隔平面偏移(TAPSE、MAPSE和SAPSE),以及跨瓣膜血流的心脏形态测量和多普勒评估。一项二级嵌套病例对照研究将评估有水肿的胎儿与无水肿的胎儿。将使用广义线性混合模型评估病例与对照之间以及随时间变化的功能参数差异。逻辑回归将估计心脏参数与水肿发生率之间的关联。
本研究将提供证据,证明在患有CHD的妊娠与健康妊娠中,自动化功能参数是否存在显著差异。主要目标是比较患有CHD的胎儿与健康胎儿的自动PWD - MPI和STIC TAPSE、MAPSE和SAPSE。次要目标是估计在水肿情况下,这些自动化参数是否能提高经典心血管轮廓评分的预测价值。
该研究方案已在ClinicalTrials.gov方案注册系统中注册,识别号为NCT05698277。