ReviewJournal of medical ultrasound
Reimagining Placental Perfusion in Preeclampsia: Integrating Doppler Ultrasound, Three-dimensional Vascular Indices, and Predictive Artificial Intelligence.
Review in Journal of medical ultrasound. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Preeclampsia remains a major cause of maternal and fetal morbidity worldwide, originating from abnormal placental development and reduced perfusion. Conventional Doppler indices, although widely used, are limited in sensitivity, reproducibility, and early detection. Advances in three-dimensional power Doppler ultrasound (3D PD-US) and its vascular indices - vascularization index (VI), flow index (FI), and vascular FI (VFI) - offer semiquantitative evaluation of intraplacental microvascular function. Following Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guidelines, this structured narrative synthesis reviewed literature from PubMed, Scopus, and EMBASE (2000-July 2025). A total of 1174 records were identified; after removing 328 duplicates, 846 titles and abstracts were screened, 137 full-text articles were assessed for eligibility, and 74 studies were included in the final synthesis assessing Doppler-based perfusion, biomarkers, or artificial intelligence (AI) integration in preeclampsia. Findings consistently demonstrate reduced VI, FI, and VFI in affected pregnancies, with FI showing the strongest reproducibility across cohorts. Emerging AI models trained on voxel-level Doppler data and angiogenic biomarkers such as placental growth factor and soluble fms-like tyrosine kinase-1 achieved high predictive accuracies (area under the curve 0.85-0.91) for early disease risk, although external validation remains limited. Integration of 3D PD-US indices with AI and biomarkers may enable early risk stratification, personalized monitoring, and informed timing of intervention. Heterogeneity in imaging protocols and the absence of meta-analytic pooling remain key limitations. Placental perfusion, re-envisioned through advanced imaging and AI analytics, emerges as a cornerstone biomarker for anticipatory, precision-based obstetric care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.