Evaluation of inflow cannulation site for implantation of right-sided rotary ventricular assist device

Right heart dysfunction is one of the most serious complications following implantation of a left ventricular assist device (LVAD), often leading to the requirement for short or long term right ventricular support (RVAD). The inflow cannulation site induces major haemodynamic changes and so there is a need to optimize the site used depending on the patient's condition. Therefore, this study evaluated and compared the haemodynamic influence of right atrial (RAC) and right ventricular (RVC) inflow cannulation sites. An in-vitro, variable heart failure, mock circulation loop was used to compare RAC and RVC in mild and severe biventricular heart failure (BHF) conditions. In the severe BHF condition, higher ventricular ejection fraction (RAC: 13.6%, RVC: 32.7%) and thus improved heart chamber and RVAD washout was observed with RVC, which suggested this strategy might be preferable for long term support (ie. bridge to transplant or destination therapy) to reduce the risk of thrombus formation. In the mild BHF condition, higher pulmonary valve flow (RAC: 3.33 L/min, RVC: 1.97 L/min) and lower right ventricular stroke work (RAC: 0.10 W, RVC: 0.13 W) and volumes were recorded with RAC. These results indicate an improved potential for myocardial recovery, thus RAC should be chosen in this condition. This in-vitro study suggests that RVAD inflow cannulation site should be chosen on a patient-specific basis with a view to the support strategy to promote myocardial recovery or reduce the risk of long-term complications.

Left ventricular volume and valve gradient analysis using an Apple Macintosh computer

A description of a computer program to analyse cine angiograms of the heart and pressure waveforms to calculate valve gradients.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Mapping genetic influences on ventricular structure in twins

Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.

Mapping hippocampal and ventricular change in Alzheimer disease

We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Fifty-two high-resolution MRI scans were acquired from 12 AD patients (age: 68.4 ± 1.9 years) and 14 matched controls (age: 71.4 ± 0.9 years), each scanned twice (2.1 ± 0.4 years apart). 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

Corrigendum to "Mapping hippocampal and ventricular change in Alzheimer disease" [NeuroImage 22 (2004) 1754-1766] (DOI:10.1016/j.neuroimage.2004.03.040)

We recently noticed an error in the demographic data in this article. The validity of the findings and the conclusions of the paper is not affected. However, there is an error in the reported sample size and in the means and standard deviations of the subjects’ ages and MMSE scores. We would like to correct this error, which came to light when we were re-analyzing the data for a meta-analysis. The error occurred because an older version of a spreadsheet was incorrectly used when reporting the sample composition. Instead of examining 12 Alzheimer's disease patients and 14 healthy elderly controls, we in fact examined 17 Alzheimer’s disease patients and 14 healthy elderly controls. All maps and morphometric data reported in the paper are correct, except that the sample size was in fact slightly higher than that originally reported, and the maps computed in the paper were based on the larger sample (which included five more subjects in the Alzheimer’s disease group). All of the maps and figures in the paper are correct, and the conclusions of the paper are unchanged. We apologize for this error, which falls under the sole responsibility of the first author. The corrected demographic information appears below.

Feasibility of perflutren microsphere contrast transthoracic echocardiography in the visualization of ventricular endocardium during venovenous extracorporeal membrane oxygenation in a validated ovine model

Background: Transthoracic echocardiography (TTE) during extra corporeal membrane oxygenation (ECMO) is important but can be technically challenging. Contrast-specific TTE can improve imaging in suboptimal studies. These contrast microspheres are hydrodynamically labile structures. This study assessed the feasibility of contrast echocardiography (CE) during venovenous (VV) ECMO in a validated ovine model. Method: Twenty-four sheep were commenced on VV ECMO. Parasternal long-axis (Plax) and short-axis (Psax) views were obtained pre- and postcontrast while on VV ECMO. Endocardial definition scores (EDS) per segment were graded: 1 = good, 2 = suboptimal 3 = not seen. Endocardial border definition score index (EBDSI) was calculated for each view. Endocardial length (EL) in the Plax view for the left ventricle (LV) and right ventricle (RV) was measured. Results: Summation EDS data for the LV and RV for unenhanced TTE (UE) versus CE TTE imaging: EDS 1 = 289 versus 346, EDS 2 = 38 versus 10, EDS 3 = 33 versus 4, respectively. Wilcoxon matched-pairs rank-sign tests showed a significant ranking difference (improvement) pre- and postcontrast for the LV (P < 0.0001), RV (P < 0.0001) and combined ventricular data (P < 0.0001). EBDSI for CE TTE was significantly lower than UE TTE for the LV (1.05 ± 0.17 vs. 1.22 ± 0.38, P = 0.0004) and RV (1.06 ± 0.22 vs. 1.42 ± 0.47, P = 0.0.0006) respectively. Visualized EL was significantly longer in CE versus UE for both the LV (58.6 ± 11.0 mm vs. 47.4 ± 11.7 mm, P < 0.0001) and the RV (52.3 ± 8.6 mm vs. 36.0 ± 13.1 mm, P < 0.0001), respectively. Conclusions: Despite exposure to destructive hydrodynamic forces, CE is a feasible technique in an ovine ECMO model. CE results in significantly improved EDS and increased EL.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

A compliant, banded outflow cannula for decreased afterload sensitivity of rotary right ventricular assist devices

Biventricular support with dual rotary ventricular assist devices (VADs) has been implemented clinically with restriction of the right VAD (RVAD) outflow cannula to artificially increase afterload and, therefore, operate within recommended design speed ranges. However, the low preload and high afterload sensitivity of these devices increase the susceptibility of suction events. Active control systems are prone to sensor drift or inaccurate inferred (sensor-less) data, therefore an alternative solution may be of benefit. This study presents the in vitro evaluation of a compliant outflow cannula designed to passively decrease the afterload sensitivity of rotary RVADs and minimize left-sided suction events. A one-way fluid-structure interaction model was initially used to produce a design with suitable flow dynamics and radial deformation. The resultant geometry was cast with different initial cross-sectional restrictions and concentrations of a softening diluent before evaluation in a mock circulation loop. Pulmonary vascular resistance (PVR) was increased from 50 dyne s/cm5 until left-sided suction events occurred with each compliant cannula and a rigid, 4.5 mm diameter outflow cannula for comparison. Early suction events (PVR ∼ 300 dyne s/cm5) were observed with the rigid outflow cannula. Addition of the compliant section with an initial 3 mm diameter restriction and 10% diluent expanded the outflow restriction as PVR increased, thus increasing RVAD flow rate and preventing left-sided suction events at PVR levels beyond 1000 dyne s/cm5. Therefore, the compliant, restricted outflow cannula provided a passive control system to assist in the prevention of suction events with rotary biventricular support while maintaining pump speeds within normal ranges of operation.

Mechanism design of ventricular assist device

This research presents an innovative design approach for the development of high efficiency Ventricular assist device that can be used for long-term support a heart failure patient. Computational fluid dynamics (CFD) techniques were applied to the development and intensive analysis to improve the performance and reliability of the pump. From the CFD analysis, a prototype pump was created and evaluated on the mock circulation loop that simulate the human circulatory system environment to evaluate its performance in support varying heart conditions.

Computational fluid dynamics of a centrifugal heart pump as biventricular assist device(BVAD)

The results of a recent study have shown that there is a severe shortage of donor hearts to meet the demand of patients suffering from acute heart failures, and patients who received a left ventricular assist device (LVAD) have extended lives. However, some of them develop right heart failure syndrome, and these patients required a right ventricular assist device (RVAD). Hence, current research focus is in the development of a bi-ventricular assist device (Bi-VAD). Computational Fluid Dynamics (CFD) is useful for estimating blood damage for design of a Bi-VAD centrifugal heart pump to meet the demand of the left and right ventricles of a normal hearts with a flow rate of 5 lit/min and the supply pressure of 100 mmHg for the left ventricle and 20 mmHg for the right ventricle. Numerical studies have been conducted to predict pressure, flow rate, the velocity profiles, and streamlines in a continuous flow Bi-VAD using. Based on the predictions of numerical simulations, only few flow regions in the Bi-VAD exhibited signs of velocity profiles and stagnation points, thereby signifying potentially low levels of thrombogenesis.