Advances in machine learning applications for cardiovascular 4D flow MRI

Four-dimensional flow magnetic resonance imaging (MRI) has evolved as a non-invasive imaging technique to visualize and quantify blood flow in the heart and vessels. Hemodynamic parameters derived from 4D flow MRI, such as net flow and peak velocities, but also kinetic energy, turbulent kinetic energy, viscous energy loss, and wall shear stress have shown to be of diagnostic relevance for cardiovascular diseases. 4D flow MRI, however, has several limitations. Its long acquisition times and its limited spatio-temporal resolutions lead to inaccuracies in velocity measurements in small and low-flow vessels and near the vessel wall. Additionally, 4D flow MRI requires long post-processing times, since inaccuracies due to the measurement process need to be corrected for and parameter quantification requires 2D and 3D contour drawing. Several machine learning (ML) techniques have been proposed to overcome these limitations. Existing scan acceleration methods have been extended using ML for image reconstruction and ML based super-resolution methods have been used to assimilate high-resolution computational fluid dynamic simulations and 4D flow MRI, which leads to more realistic velocity results. ML efforts have also focused on the automation of other post-processing steps, by learning phase corrections and anti-aliasing. To automate contour drawing and 3D segmentation, networks such as the U-Net have been widely applied. This review summarizes the latest ML advances in 4D flow MRI with a focus on technical aspects and applications. It is divided into the current status of fast and accurate 4D flow MRI data generation, ML based post-processing tools for phase correction and vessel delineation and the statistical evaluation of blood flow

Mitral valve regurgitation assessed by intraventricular CMR 4D-flow: a systematic review on the technological aspects and potential clinical applications.

Cardiac magnetic resonance (CMR) four-dimensional (4D) flow is a novel method for flow quantification potentially helpful in management of mitral valve regurgitation (MVR). In this systematic review, we aimed to depict the clinical role of intraventricular 4D-flow in MVR. The reproducibility, technical aspects, and comparison against conventional techniques were evaluated. Published studies on SCOPUS, MEDLINE, and EMBASE were included using search terms on 4D-flow CMR in MVR. Out of 420 screened articles, 18 studies fulfilled our inclusion criteria. All studies (n = 18, 100%) assessed MVR using 4D-flow intraventricular annular inflow (4D-flowAIM) method, which calculates the regurgitation by subtracting the aortic forward flow from the mitral forward flow. Thereof, 4D-flow jet quantification (4D-flowjet) was assessed in 5 (28%), standard 2D phase-contrast (2D-PC) flow imaging in 8 (44%) and the volumetric method (the deviation of left ventricle stroke volume and right ventricular stroke volume) in 2 (11%) studies. Inter-method correlations among the 4 MVR quantification methods were heterogeneous across studies, ranging from moderate to excellent correlations. Two studies compared 4D-flowAIM to echocardiography with moderate correlation. In 12 (63%) studies the reproducibility of 4D-flow techniques in quantifying MVR was studied. Thereof, 9 (75%) studies investigated the reproducibility of the 4D-flowAIM method and the majority (n = 7, 78%) reported good to excellent intra- and inter-reader reproducibility. Intraventricular 4D-flowAIM provides high reproducibility with heterogeneous correlations to conventional quantification methods. Due to the absence of a gold standard and unknown accuracies, future longitudinal outcome studies are needed to assess the clinical value of 4D-flow in the clinical setting of MVR

Getting the phase consistent: The importance of phase description in balanced steady-state free precession MRI of multicompartment systems

Purpose: Determine the correct mathematical phase description for balanced steady-state free precession (bSSFP) signals in multicompartment systems. Theory and Methods: Based on published bSSFP signal models, two distinct phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multicompartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these two distinct phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase-cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical-shift of the acetone-water mixtures. Results: Based on the choice of phase description, the simulated bSSFP profiles of water-acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of water-acetone mixtures, an observation which excludes the phase description that predicts an absence of destructive interference. The connection between the choice of phase description and predicted observation enables an unambiguous experimental identification of the correct phase description for multicompartment bSSFP profiles, which is consistent with Bloch equations. Conclusion: The study emphasizes that consistent phase descriptions are crucial for accurately describing multi-compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions.Comment: Submitted to Magn. Reson. Me

Septaly Oriented Mild Aortic Regurgitant Jets Negatively Influence Left Ventricular Blood Flow—Insights From 4D Flow MRI Animal Study

Objectives: Paravalvular leakage (PVL) and eccentric aortic regurgitation remain a major clinical concern in patients receiving transcatheter aortic valve replacement (TAVR), and regurgitant volume remains the main readout parameter in clinical assessment. In this work we investigate the effect of jet origin and trajectory of mild aortic regurgitation on left ventricular hemodynamics in a porcine model. Methods: A pig model of mild aortic regurgitation/PVL was established by transcatheter piercing and dilating the non-coronary (NCC) or right coronary cusp (RCC) of the aortic valve close to the valve annulus. The interaction between regurgitant blood and LV hemodynamics was assessed by 4D flow cardiovascular MRI. Results: Six RCC, six NCC, and two control animals were included in the study and with one dropout in the NCC group, the success rate of model creation was 93%. Regurgitant jets originating from NCC were directed along the ventricular side of the anterior mitral leaflet and integrated well into the diastolic vortex forming in the left ventricular outflow tract. However, jets from the RCC were orientated along the septum colliding with flow within the vortex, and progressing down to the apex. As a consequence, the presence as well as the area of the vortex was reduced at the site of impact compared to the NCC group. Impairment of vortex formation was localized to the area of impact and not the entire vortex ring. Blood from the NCC jet was largely ejected during the following systole, whereas ejection of large portion of RCC blood was protracted. Conclusions: Even for mild regurgitation, origin and trajectory of the regurgitant jet does cause a different effect on LV hemodynamics. Septaly oriented jets originating from RCC collide with the diastolic vortex, reduce its size, and reach the apical region of the left ventricle where blood resides extendedly. Hence, RCC jets display hemodynamic features which may have a potential negative impact on the long-term burden to the heart

Getting the phase consistent: The importance of phase description in balanced steady-state free precession MRI of multi-compartment systems.

PURPOSE Determine the correct mathematical phase description for balanced steady-state free precession (bSSFP) signals in multi-compartment systems. THEORY AND METHODS Based on published bSSFP signal models, different phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multi-compartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these different phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase-cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical shift of the acetone-water mixtures. RESULTS Based on the choice of phase description, the simulated bSSFP profiles of water-acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of water-acetone mixtures, supporting the theoretical description that predicts such interference effects. The connection between the choice of phase description and predicted observation enables unambiguous experimental identification of the correct phase description for multi-compartment bSSFP profiles, which is consistent with the Bloch equations. CONCLUSION The study emphasizes that consistent phase descriptions are crucial for accurately describing multi-compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions

Advances in machine learning applications for cardiovascular 4D flow MRI

Four-dimensional flow magnetic resonance imaging (MRI) has evolved as a non-invasive imaging technique to visualize and quantify blood flow in the heart and vessels. Hemodynamic parameters derived from 4D flow MRI, such as net flow and peak velocities, but also kinetic energy, turbulent kinetic energy, viscous energy loss, and wall shear stress have shown to be of diagnostic relevance for cardiovascular diseases. 4D flow MRI, however, has several limitations. Its long acquisition times and its limited spatio-temporal resolutions lead to inaccuracies in velocity measurements in small and low-flow vessels and near the vessel wall. Additionally, 4D flow MRI requires long post-processing times, since inaccuracies due to the measurement process need to be corrected for and parameter quantification requires 2D and 3D contour drawing. Several machine learning (ML) techniques have been proposed to overcome these limitations. Existing scan acceleration methods have been extended using ML for image reconstruction and ML based super-resolution methods have been used to assimilate high-resolution computational fluid dynamic simulations and 4D flow MRI, which leads to more realistic velocity results. ML efforts have also focused on the automation of other post-processing steps, by learning phase corrections and anti-aliasing. To automate contour drawing and 3D segmentation, networks such as the U-Net have been widely applied. This review summarizes the latest ML advances in 4D flow MRI with a focus on technical aspects and applications. It is divided into the current status of fast and accurate 4D flow MRI data generation, ML based post-processing tools for phase correction and vessel delineation and the statistical evaluation of blood flow

Insufficient slow-flow suppression mimicking aneurysm wall enhancement in magnetic resonance vessel wall imaging: a phantom study

OBJECTIVE: MR vessel wall imaging (VWI) is increasingly performed in clinical settings to support treatment decision-making regarding intracranial aneurysms. Aneurysm wall enhancement after contrast agent injection is expected to be related to aneurysm instability and rupture status. However, the authors hypothesize that slow-flow artifacts mimic aneurysm wall enhancement. Therefore, in this phantom study they assess the effect of slow flow on wall-like enhancement by using different MR VWI techniques. METHODS: The authors developed an MR-compatible aneurysm phantom model, which was connected to a pump to enable pulsatile inflow conditions. For VWI, 3D turbo spin echo sequences-both with and without motion-sensitized driven equilibrium (MSDE) and delay alternating with nutation for tailored excitation (DANTE) preparation pulses-were performed using a 3-T MR scanner. VWI was acquired both before and after Gd contrast agent administration by using two different pulsatile inflow conditions (2.5 ml/sec peak flow at 77 and 48 beats per minute). The intraluminal signal intensity along the aneurysm wall was analyzed to assess the performance of slow-flow suppression. RESULTS: The authors observed wall-like enhancement after contrast agent injection, especially in low pump rate settings. Preparation pulses, in particular the DANTE technique, improved the performance of slow-flow suppression. CONCLUSIONS: Near-wall slow flow mimics wall enhancement in VWI protocols. Therefore, VWI should be carefully interpreted. Preparation pulses improve slow-flow suppression, and therefore the authors encourage further development and clinical implementation of these techniques