Dataset Information

Left Ventricular Flow Analysis.

ABSTRACT:

Background

Cardiac remodeling, after a myocardial insult, often causes progression to heart failure. The relationship between alterations in left ventricular blood flow, including kinetic energy (KE), and remodeling is uncertain. We hypothesized that increasing derangements in left ventricular blood flow would relate to (1) conventional cardiac remodeling markers, (2) increased levels of biochemical remodeling markers, (3) altered cardiac energetics, and (4) worsening patient symptoms and functional capacity. Methods Thirty-four dilated cardiomyopathy patients, 30 ischemic cardiomyopathy patients, and 36 controls underwent magnetic resonance including 4-dimensional flow, BNP (brain-type natriuretic peptide) measurement, functional capacity assessment (6-minute walk test), and symptom quantification. A subgroup of dilated cardiomyopathy and control subjects underwent cardiac energetic assessment. Left ventricular flow was separated into 4 components: direct flow, retained inflow, delayed ejection flow, and residual volume. Average KE throughout the cardiac cycle was calculated.

Results

Patients had reduced direct flow proportion and direct-flow average KE compared with controls ( P<0.0001). The residual volume proportion and residual volume average KE were increased in patients ( P<0.0001). Importantly, in a multiple linear regression model to predict the patient's 6-minute walk test, the independent predictors were age (β=-0.3015; P=0.019) and direct-flow average KE (β=0.280, P=0.035; R² model, 0.466, P=0.002). In contrast, neither ejection fraction nor left ventricular volumes were independently predictive.

Conclusions

This study demonstrates an independent predictive relationship between the direct-flow average KE and a prognostic measure of functional capacity. Intracardiac 4-dimensional flow parameters are novel biomarkers in heart failure and may provide additive value in monitoring new therapies and predicting prognosis.

SUBMITTER: Stoll VM

PROVIDER: S-EPMC6544522 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Left Ventricular Flow Analysis.

Stoll Victoria M VM Hess Aaron T AT Rodgers Christopher T CT Bissell Malenka M MM Dyverfeldt Petter P Ebbers Tino T Myerson Saul G SG Carlhäll Carl-Johan CJ Neubauer Stefan S

Circulation. Cardiovascular imaging 20190501 5

<h4>Background</h4>Cardiac remodeling, after a myocardial insult, often causes progression to heart failure. The relationship between alterations in left ventricular blood flow, including kinetic energy (KE), and remodeling is uncertain. We hypothesized that increasing derangements in left ventricular blood flow would relate to (1) conventional cardiac remodeling markers, (2) increased levels of biochemical remodeling markers, (3) altered cardiac energetics, and (4) worsening patient symptoms an ...[more]

PMID: 31109184

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Project description:BackgroundThe beating heart is the generator of blood flow through the cardiovascular system. Within the heart's 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.

Project description:AimsContinuous-flow left ventricular assist devices (CF-LVADs) have become a standard of care in end-stage heart failure. Limited data exist comparing outcomes of HeartMate3 (HM3) and HeartWare HVAD (HW). We aimed to compare midterm outcomes of these devices.Methods and resultsInvestigator-initiated retrospective-observational comparative analysis of all patients who underwent primary LVAD implantation of either HM3 or HW at our centre between January 2010 and December 2020. Data were derived from a prospective registry. Primary endpoints were all-cause mortality and heart transplantation. Secondary endpoints included device-related major adverse cardiac and cerebrovascular events, which included major bleeding, major neurological dysfunction (defined as persisting neurological impairment for ≥24 h), device-related major infection (excluding driveline infections), major device malfunctions leading to re-intervention or partial device exchange (pump failure, outflow-graft twist or failure, controller failure, battery failure, patient cable failure, but excluding pump thrombosis), and pump thrombosis. Further secondary endpoints included right heart failure, gastrointestinal bleeding, driveline infections, and surgical re-interventions. The secondary outcomes were analysed not only for the first event but also for recurrent events. The analysis included competing risks analysis and recurrent event regression analysis, with adjustment for confounders age, gender, body mass index (BMI), and Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) level. Out of 106 primary CF-LVAD implantations, 36 (34%) received HM3 and 70 (66%) received HW. Median follow-up was 1.48 years [interquartile range 0.67, 2.41]. HM3 was more often implanted in men (91.7% vs. 72.9%, P = 0.024); patients were older (median 61 years [54, 66.5] vs. 52.5 years [43, 60], P < 0.001), had a higher BMI (median 26.7 kg/m2 [23.4, 29.0] vs. 24.3 kg/m2 [20.7, 27.4], P = 0.013), had more comorbidities, and were more likely targeted for destination therapy (36.1% vs. 14.3%, P = 0.010). Death occurred in 33.3% of HM3 patients, compared with 22.9% of HW patients, P = 0.247 (probability of survival at 4 years, 54.7% vs. 74.1%, P = 0.296). After adjustment for confounders, we observed a significant six-fold risk increase in device malfunctions for HW [hazard ratio (HR) 6.49, 95% confidence interval (CI) [1.89, 22.32], P = 0.003], but no significant differences in pump thrombosis (P = 0.173) or overall survival (P = 0.801).ConclusionsComparing midterm outcomes between HM3 and HW for LVAD support from a prospective registry, HW patients had a significantly higher risk of device malfunctions. No significant differences were evident between devices in overall survival and in respect to most outcomes.

Dataset Information

Left Ventricular Flow Analysis.

Background

Results

Conclusions

Publications

Left Ventricular Flow Analysis.

Similar Datasets

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