Aortic Stenosis: Haemodynamic Benchmark and Metric Reliability Study

Harminder Gill, Joao Filipe Fernandes, Amanda Nio, Cameron Dockerill, Nili Shah, Naajia Ahmed, Jason Raymond, Shu Wang, Julio Sotelo, Jesus Urbina, Sergio Uribe, Ronak Rajani, Kawal Rhode, Pablo Lamata

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Aortic stenosis is a condition which is fatal if left untreated. Novel quantitative imaging techniques which better characterise transvalvular pressure drops are being developed but require refinement and validation. A customisable and cost-effective workbench valve phantom circuit capable of replicating valve mechanics and pathology was created. The reproducibility and relationship of differing haemodynamic metrics were assessed from ground truth pressure data alongside imaging compatibility. The phantom met the requirements to capture ground truth pressure data alongside ultrasound and magnetic resonance image compatibility. The reproducibility was successfully tested. The robustness of three different pressure drop metrics was assessed: whilst the peak and net pressure drops provide a robust assessment of the stenotic burden in our phantom, the peak-to-peak pressure drop is a metric that is confounded by non-valvular factors such as wave reflection. The peak-to-peak pressure drop is a metric that should be reconsidered in clinical practice. Graphical abstract: The left panel shows manufacture of low cost, functional valves. The central section demonstrates circuit layout, representative MRI and US images alongside gross valve morphologies. The right panel shows the different pressure drop metrics that were assessed for reproducibility[Figure not available: see fulltext.]

Original languageEnglish
Pages (from-to)862-873
Number of pages12
JournalJournal of Cardiovascular Translational Research
Volume16
Issue number4
DOIs
Publication statusPublished - Aug 2023
Externally publishedYes

Keywords

  • 3D printing
  • Aortic stenosis
  • Aortic valve
  • Haemodynamics

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