Jonatan Eriksson

Semi-automatic quantification of 4D left ventricular blood flow

BackgroundThe beating heart is the generator of blood flow through the cardiovascular system. Within the hearts own chambers, normal complex blood flow patterns can be disturbed by diseases. Methods for the quantification of intra-cardiac blood flow, with its 4D (3D+time) nature, are lacking. We sought to develop and validate a novel semi-automatic analysis approach that integrates flow and morphological data.MethodIn six healthy subjects and three patients with dilated cardiomyopathy, three-directional, three-dimensional cine phase-contrast cardiovascular magnetic resonance (CMR) velocity data and balanced steady-state free-precession long- and short-axis images were acquired. The LV endocardium was segmented from the short-axis images at the times of isovolumetric contraction (IVC) and isovolumetric relaxation (IVR). At the time of IVC, pathlines were emitted from the IVC LV blood volume and traced forwards and backwards in time until IVR, thus including the entire cardiac cycle. The IVR volume was used to determine if and where the pathlines left the LV. This information was used to automatically separate the pathlines into four different components of flow: Direct Flow, Retained Inflow, Delayed Ejection Flow and Residual Volume. Blood volumes were calculated for every component by multiplying the number of pathlines with the blood volume represented by each pathline. The accuracy and inter- and intra-observer reproducibility of the approach were evaluated by analyzing volumes of LV inflow and outflow, the four flow components, and the end-diastolic volume.ResultsThe volume and distribution of the LV flow components were determined in all subjects. The calculated LV outflow volumes [ml] (67 ± 13) appeared to fall in between those obtained by through-plane phase-contrast CMR (77 ± 16) and Doppler ultrasound (58 ± 10), respectively. Calculated volumes of LV inflow (68 ± 11) and outflow (67 ± 13) were well matched (NS). Low inter- and intra-observer variability for the assessment of the volumes of the flow components was obtained.ConclusionsThis semi-automatic analysis approach for the quantification of 4D blood flow resulted in accurate LV inflow and outflow volumes and a high reproducibility for the assessment of LV flow components.

Quantification of presystolic blood flow organization and energetics in the human left ventricle

Intracardiac blood flow patterns are potentially important to cardiac pumping efficiency. However, these complex flow patterns remain incompletely characterized both in health and disease. We hypothesized that normal left ventricular (LV) blood flow patterns would preferentially optimize a portion of the end-diastolic volume (LVEDV) for effective and rapid systolic ejection by virtue of location near and motion towards the LV outflow tract (LVOT). Three-dimensional cine velocity and morphological data were acquired in 12 healthy persons and 1 patient with dilated cardiomyopathy using MRI. A previously validated method was used for analysis in which the LVEDV was separated into four functional flow components based on the bloods locations at the beginning and end of the cardiac cycle. Each components volume, kinetic energy (KE), site, direction, and linear momentum relative to the LVOT were calculated. Of the four components, the LV inflow that passes directly to outflow in a single cardiac cycle (Direct Flow) had the largest volume. At the time of isovolumic contraction, Direct Flow had the greatest amount of KE and the most favorable combination of distance, angle, and linear momentum relative to the LVOT. Atrial contraction boosted the late diastolic KE of the ejected components. We conclude that normal diastolic LV flow creates favorable conditions for ensuing ejection, defined by proximity and energetics, for the Direct Flow, and that atrial contraction augments the end-diastolic KE of the ejection volume. The correlation of Direct Flow characteristics with ejection efficiency might be a relevant investigative target in cardiac failure.

4-D blood flow in the human right ventricle

Right ventricular (RV) function is a powerful prognostic indicator in many forms of heart disease, but its assessment remains challenging and inexact. RV dysfunction may alter the normal patterns of RV blood flow, but those patterns have been incompletely characterized. We hypothesized that, based on anatomic differences, the proportions and energetics of RV flow components would differ from those identified in the left ventricle (LV) and that the portion of the RV inflow passing directly to outflow (Direct Flow) would be prepared for effective systolic ejection as a result of preserved kinetic energy (KE) compared with other RV flow components. Three-dimensional, time-resolved phase-contrast velocity, and balanced steady-state free-precession morphological data were acquired in 10 healthy subjects using MRI. A previously validated method was used to separate the RV and LV end-diastolic volumes into four flow components and measure their volume and KE over the cardiac cycle. The RV Direct Flow: 1) followed a smoothly curving route that did not extend into the apical region of the ventricle; 2) had a larger volume and possessed a larger presystolic KE (0.4 ± 0.3 mJ) than the other flow components (P < 0.001 and P < 0.01, respectively); and 3) represented a larger part of the end-diastolic blood volume compared with the LV Direct Flow (P < 0.01). These findings suggest that diastolic flow patterns distinct to the normal RV create favorable conditions for ensuing systolic ejection of the Direct Flow component. These flow-specific aspects of RV diastolic-systolic coupling provide novel perspectives on RV physiology and may add to the understanding of RV pathophysiology.

Four-dimensional blood flow-specific markers of LV dysfunction in dilated cardiomyopathy

Aims Patients with mild heart failure (HF) who are clinically compensated may have normal left ventricular (LV) stroke volume (SV). Despite this, altered intra-ventricular flow patterns have been recognized in these subjects. We hypothesized that, compared with normal LVs, flow in myopathic LVs would demonstrate a smaller proportion of inflow volume passing directly to ejection and diminished the end-diastolic preservation of the inflow kinetic energy (KE). Methods and results In 10 patients with dilated cardiomyopathy (DCM) (49 ± 14 years, six females) and 10 healthy subjects (44 ± 17 years, four females), four-dimensional MRI velocity and morphological data were acquired. A previously validated method was used to separate the LV end-diastolic volume (EDV) into four flow components based on the bloods locations at the beginning and end of the cardiac cycle. KE was calculated over the cardiac cycle for each component. The EDV was larger (P = 0.021) and the ejection fraction smaller (P < 0.001) in DCM compared with healthy subjects; the SV was equivalent (DCM: 77 ± 19, healthy: 79 ± 16 mL). The proportion of the total LV inflow that passed directly to ejection was smaller in DCM (P = 0.000), but the end-diastolic KE/mL of the direct flow was not different in the two groups (NS). Conclusion Despite equivalent LVSVs, HF patients with mild LV remodelling demonstrate altered diastolic flow routes through the LV and impaired preservation of inflow KE at pre-systole compared with healthy subjects. These unique flow-specific changes in the flow route and energetics are detectable despite clinical compensation, and may prove useful as subclinical markers of LV dysfunction.

Turbulent kinetic energy in normal and myopathic left ventricles

To assess turbulent kinetic energy (TKE) within the left ventricle (LV) of healthy subjects using novel 4D flow magnetic resonance imaging (MRI) methods and to compare TKE values to those from a limited group of patients with a spectrum of dilated cardiomyopathy (DCM).

Automatic multi-vessel volume flow calculation with 4D flow CMR

Volume flow analysis is essential in the assessment of many cardiovascular diseases such as valvular regurgitation, intra-cardiac shunt, and complex congenital heart diseases. Clinically, CMR-based volume flow analysis is performed using 2D flow CMR. This requires user-dependent and time-consuming positioning of 2D planes in each vessel while the patient is still in the scanner. Previous studies have demonstrated that 4D flow CMR permits accurate volume flow assessment. However, retrospective plane-positioning and region-of-interest delineation requires time-consuming user interaction. The aim of this study was to develop an automatic method for volume flow analysis in the great thoracic vessels using 4D flow CMR. Methods The automatic multi-vessel volume flow calculation method is illustrated in Figure 1. An atlas (reference vessel segmentation) was created by manual segmentation of the great thoracic vessels in one healthy volunteer. The segmentation was done on a 3D PC-MRA which was derived from the 4D flow CMR data. Analysis planes for volume flow determination were positioned in the proximal ascending aorta and pulmonary trunk. For each subject, the atlas’ PC-MRA was registered to the subject’s PC-MRA. In this way, the atlas’ vessels and analysis planes were transformed into the subject’s vessels. The transformed atlas was transferred to all timeframes using the 4D flow CMR magnitude image, resulting in a time-resolved segmentation that follows the motion of the vessels over the cardiac cycle. Finally, the volume flow was automatically calculated for each plane using the time-resolved atlas as a mask to account for vessel location, shape and movement. The method was evaluated in a group of subjects composed of 10 healthy volunteers and 11 patients with heart failure of different etiologies. Results in the proximal ascending aorta were compared against volume flow values obtained by manual segmentation. Additionally, the pulmonary-to-aortic flow ratio (Qp/Qs) was assessed. Results

Atlas-based analysis of 4D flow CMR: Automated vessel segmentation and flow quantification

BackgroundFlow volume quantification in the great thoracic vessels is used in the assessment of several cardiovascular diseases. Clinically, it is often based on semi-automatic segmentation of a vessel throughout the cardiac cycle in 2D cine phase-contrast Cardiovascular Magnetic Resonance (CMR) images. Three-dimensional (3D), time-resolved phase-contrast CMR with three-directional velocity encoding (4D flow CMR) permits assessment of net flow volumes and flow patterns retrospectively at any location in a time-resolved 3D volume. However, analysis of these datasets can be demanding. The aim of this study is to develop and evaluate a fully automatic method for segmentation and analysis of 4D flow CMR data of the great thoracic vessels.MethodsThe proposed method utilizes atlas-based segmentation to segment the great thoracic vessels in systole, and registration between different time frames of the cardiac cycle in order to segment these vessels over time. Additionally, net flow volumes are calculated automatically at locations of interest. The method was applied on 4D flow CMR datasets obtained from 11 healthy volunteers and 10 patients with heart failure. Evaluation of the method was performed visually, and by comparison of net flow volumes in the ascending aorta obtained automatically (using the proposed method), and semi-automatically. Further evaluation was done by comparison of net flow volumes obtained automatically at different locations in the aorta, pulmonary artery, and caval veins.ResultsVisual evaluation of the generated segmentations resulted in good outcomes for all the major vessels in all but one dataset. The comparison between automatically and semi-automatically obtained net flow volumes in the ascending aorta resulted in very high correlation (r2=0.926). Moreover, comparison of the net flow volumes obtained automatically in other vessel locations also produced high correlations where expected: pulmonary trunk vs. proximal ascending aorta (r2=0.955), pulmonary trunk vs. pulmonary branches (r2=0.808), and pulmonary trunk vs. caval veins (r2=0.906).ConclusionsThe proposed method allows for automatic analysis of 4D flow CMR data, including vessel segmentation, assessment of flow volumes at locations of interest, and 4D flow visualization. This constitutes an important step towards facilitating the clinical utility of 4D flow CMR.

4D flow MRI can detect subtle right ventricular dysfunction in primary left ventricular disease

To investigate whether 4D flow magnetic resonance imaging (MRI) can detect subtle right ventricular (RV) dysfunction in primary left ventricular (LV) disease.

Altered Diastolic Flow Patterns and Kinetic Energy in Subtle Left Ventricular Remodeling and Dysfunction Detected by 4D Flow MRI

Aims 4D flow magnetic resonance imaging (MRI) allows quantitative assessment of left ventricular (LV) function according to characteristics of the dynamic flow in the chamber. Marked abnormalities in flow components’ volume and kinetic energy (KE) have previously been demonstrated in moderately dilated and depressed LV’s compared to healthy subjects. We hypothesized that these 4D flow-based measures would detect even subtle LV dysfunction and remodeling. Methods and Results We acquired 4D flow and morphological MRI data from 26 patients with chronic ischemic heart disease with New York Heart Association (NYHA) class I and II and with no to mild LV systolic dysfunction and remodeling, and from 10 healthy controls. A previously validated method was used to separate the LV end-diastolic volume (LVEDV) into functional components: direct flow, which passes directly to ejection, and non-ejecting flow, which remains in the LV for at least 1 cycle. The direct flow and non-ejecting flow proportions of end-diastolic volume and KE were assessed. The proportions of direct flow volume and KE fell with increasing LVEDV-index (LVEDVI) and LVESV-index (LVESVI) (direct flow volume r = -0.64 and r = -0.74, both P<0.001; direct flow KE r = -0.48, P = 0.013, and r = -0.56, P = 0.003). The proportions of non-ejecting flow volume and KE rose with increasing LVEDVI and LVESVI (non-ejecting flow volume: r = 0.67 and r = 0.76, both P<0.001; non-ejecting flow KE: r = 0.53, P = 0.005 and r = 0.52, P = 0.006). The proportion of direct flow volume correlated moderately to LVEF (r = 0.68, P < 0.001) and was higher in a sub-group of patients with LVEDVI >74 ml/m2 compared to patients with LVEDVI <74 ml/m2 and controls (both P<0.05). Conclusion Direct flow volume and KE proportions diminish with increased LV volumes, while non-ejecting flow proportions increase. A decrease in direct flow volume and KE at end-diastole proposes that alterations in these novel 4D flow-specific markers may detect LV dysfunction even in subtle or subclinical LV remodeling.

Assessment of left ventricular hemodynamic forces in healthy subjects and patients with dilated cardiomyopathy using 4D flow MRI

We hypothesized that the direction of global left ventricular (LV) hemodynamic forces during diastolic filling are concordant with the main flow axes in normal LVs, but that this pattern would be altered in dilated and dysfunctional LVs. Therefore, we aimed to assess the LV hemodynamic filling forces in a group of healthy subjects and compare them to the results from a group of patients with dilated cardiomyopathy (DCM). Ten healthy subjects and 10 DCM patients were enrolled. Morphological short‐ (SAx) and long‐axis (LAx) images and 4D flow MRI data were acquired at 1.5T. The LV pressure gradients were computed from the 4D flow data using the Navier–Stokes equations. By integrating the pressure gradients over the LV volume at each time frame, the magnitude and direction of the global hemodynamic force was calculated over the cardiac cycle. The hemodynamic forces acting in the SAx‐ and LAx‐directions were used to calculate the “SAx‐max/LAx‐max”‐ratio for the early (E‐wave) and late (A‐wave) diastolic filling. In the LAx‐plane, the temporal progression of the hemodynamic force followed a consistent pattern in the healthy subjects. The “SAx‐max/LAx‐max”‐ratio was significantly larger at both E‐wave (0.53 ± 0.15 vs. 0.23 ± 0.12, P < 0.0001) and A‐wave (0.44 ± 0.21 vs. 0.26 ± 0.09, P < 0.03) in the DCM patients compared to the healthy subjects. 4D flow MRI data allow quantification of LV hemodynamic forces acting on the LV myocardial wall. The LV hemodynamic filling forces showed a similar temporal progression among healthy subjects, whereas DCM patients had forces that were more heterogeneous in their direction and magnitude during diastole.