Wataganara Tuangsit, Rekhawasin Thanapa, Sompagdee Nalat, Viboonchart Sommai, Phithakwatchara Nisarat, Nawapun Katika
Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital, Bangkok 10700, Thailand.
Diagnostics (Basel). 2021 Aug 21;11(8):1511. doi: 10.3390/diagnostics11081511.
Realistic reconstruction of angioarchitecture within the morphological landmark with three-dimensional sonoangiography (three-dimensional power Doppler; 3D PD) may augment standard prenatal ultrasound and Doppler assessments. This study aimed to (a) present a technical overview, (b) determine additional advantages, (c) identify current challenges, and (d) predict trajectories of 3D PD for prenatal assessments. PubMed and Scopus databases for the last decade were searched. Although 307 publications addressed our objectives, their heterogeneity was too broad for statistical analyses. Important findings are therefore presented in descriptive format and supplemented with the authors' 3D PD images. Acquisition, analysis, and display techniques need to be personalized to improve the quality of flow-volume data. While 3D PD indices of the first-trimester placenta may improve the prediction of preeclampsia, research is needed to standardize the measurement protocol. In highly experienced hands, the unique 3D PD findings improve the diagnostic accuracy of placenta accreta spectrum. A lack of quality assurance is the central challenge to incorporating 3D PD in prenatal care. Machine learning may broaden clinical translations of prenatal 3D PD. Due to its operator dependency, 3D PD has low reproducibility. Until standardization and quality assurance protocols are established, its use as a stand-alone clinical or research tool cannot be recommended.
通过三维超声血管造影术(三维能量多普勒;3D PD)在形态学标志内对血管构筑进行逼真重建,可能会增强标准的产前超声和多普勒评估。本研究旨在(a)提供技术概述,(b)确定额外优势,(c)识别当前挑战,以及(d)预测3D PD在产前评估中的发展轨迹。检索了过去十年的PubMed和Scopus数据库。尽管有307篇出版物涉及我们的目标,但它们的异质性太大,无法进行统计分析。因此,重要发现以描述性形式呈现,并辅以作者的3D PD图像。采集、分析和显示技术需要个性化,以提高血流容积数据的质量。虽然孕早期胎盘的3D PD指标可能会改善子痫前期的预测,但需要进行研究以规范测量方案。在经验丰富的人员操作下,独特的3D PD发现可提高胎盘植入谱系的诊断准确性。缺乏质量保证是将3D PD纳入产前护理的核心挑战。机器学习可能会拓宽产前3D PD的临床应用。由于其对操作者的依赖性,3D PD的可重复性较低。在建立标准化和质量保证方案之前,不建议将其作为独立的临床或研究工具使用。