Evaluation of 4D flow MRI-based non-invasive pressure assessment in aortic coarctations

Abstract

Severity of aortic coarctation (CoA) is currently assessed by estimating trans-coarctation pressure drops through cardiac catheterization or echocardiography. In principle, more detailed information could be obtained non-invasively based on space-and time-resolved magnetic resonance imaging (4D flow) data. Yet the limitations of this imaging technique require testing the accuracy of 4D flow-derived hemodynamic quantities against other methodologies. With the objective of assessing the feasibility and accuracy of this non-invasive method to support the clinical diagnosis of CoA, we developed an algorithm (4DF-FEPPE) to obtain relative pressure distributions from 4D flow data by solving the Poisson pressure equation. 4DF-FEPPE was tested against results from a patient-specific fluid-structure interaction (FSI) simulation, whose patient-specific boundary conditions were prescribed based on 4D flow data. Since numerical simulations provide noise-free pressure fields on fine spatial and temporal scales, our analysis allowed to assess the uncertainties related to 4D flow noise and limited resolution. 4DF-FEPPE and FSI results were compared on a series of cross-sections along the aorta. Bland-Altman analysis revealed very good agreement between the two methodologies in terms of instantaneous data at peak systole, end-diastole and time-averaged values: biases (means of differences) were +0.4 mmHg,-1.1 mmHg and +0.6 mmHg, respectively. Limits of agreement (2 SD) were ±0.978 mmHg, ±1.06 mmHg and ±1.97 mmHg, respectively. Peak-to-peak and maximum trans-coarctation pressure drops obtained with 4DF-FEPPE differed from FSI results by 0.75 mmHg and-1.34 mmHg respectively. The present study considers important validation aspects of non-invasive pressure difference estimation based on 4D flow MRI, showing the potential of this technology to be more broadly applied to the clinical practice.

Patient-Specific Bicuspid Aortic Valve Biomechanics: A Magnetic Resonance Imaging Integrated Fluid–Structure Interaction Approach

“…However, exhaustive patient-tailored modeling could be derived from 4D Flow through non-invasive mapping of aortic relative pressures. 42 4D Flow estimation of aortic flow rate is also feasible, though, if compared to 2D PC-MRI, reported underestimation of net and peak aortic flow rate in part due to the relatively low 4D Flow temporal resolution. 18 In vivo coronary artery flow could be integrated through 2D PC-MRI sequences though several challenges are still related to the small size, tortuous path and extensive motion of the coronary vessels.…”

Qualitative and Quantitative Assessments of Blood Flow on Tears in Type B Aortic Dissection With Different Morphologies

“…4D flow MRI images were acquired using a 3-T clinical MR scanner (Magnetom Avanto; Siemens Medical Solutions, Erlangen, Germany) using the following parameters: flip angle 7 °; velocity encoding 150 cm/s in all directions; spatial resolution 1.85 × 1.85 × 2.5 mm 3 ; and temporal resolution 47-61 ms. Retrospective electrocardiographic gating was used to reconstruct 12-20 frames/cardiac cycle. Using custom-built MATLAB code, the volumes segmented from CT scans were registered onto the 4D flow image volumes (Saitta et al, 2019). Data were visualized and further post-processed with Paraview (Kitware, NY, United States).…”

4D Flow MRI hemodynamic benchmarking of surgical bioprosthetic valves

“…Relative pressure maps were finally computed by integration of the computed gradients through a multigrid finite element solver [17], already validated against gold-standard estimations provided by computational fluid dynamics models [20,27]. Specifically, the numerical PPE solution resulted in the relative pressure field p and a zero-pressure reference was imposed at the same location of the experimental P0 pressure port (Fig.…”