ArticleInterface focus2025
Non-invasive quantification of pressure drops in stenotic intracranial vessels: using deep learning-enhanced 4D flow MRI to characterize the regional haemodynamics of the pulsing brain.
Article in Interface focus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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Who cites it
3 citing papers in PubMed.
- Uncertainty-aware automated labeling of intracranial arteries using deep learning.BMC medical imaging · 2026Article
- Uncertainty Quantification in Hemodynamic Metrics from 4D Flow MRI with Super-resolution in a Carotid Bifurcation Model.Journal of imaging informatics in medicine · 2026Article
- Non-invasive quantification of pressure drops in stenotic intracranial vessels: using deep learning-enhanced 4D flow MRI to characterize the regional haemodynamics of the pulsing brain.Interface focus · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stenosis of major intracranial arteries is a significant cause of stroke, with assessment of trans-stenotic pressure drops being a key marker of functional stenosis severity. Non-invasive methods for quantifying intracranial pressure changes are hence crucial; however, the narrow and tortuous cerebrovascular network poses challenges to traditional assessment methods such as transcranial Doppler. This study investigates the use of novel deep learning-enhanced super-resolution (SR) four-dimensional (4D) flow magnetic resonance imaging (MRI) in combination with a physics-informed virtual work-energy relative pressure technique to quantify pressure drops across stenotic intracranial arteries. Performance was validated in intracranial-mimicking
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Registered trials
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