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A 10-Year Retrospective Review of Prenatal Applications, Current Challenges and Future Prospects of Three-Dimensional Sonoangiography

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 additi...

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Detalles Bibliográficos
Autores principales: Wataganara, Tuangsit, Rekhawasin, Thanapa, Sompagdee, Nalat, Viboonchart, Sommai, Phithakwatchara, Nisarat, Nawapun, Katika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394388/
https://www.ncbi.nlm.nih.gov/pubmed/34441444
http://dx.doi.org/10.3390/diagnostics11081511
Descripción
Sumario: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.