18 research outputs found
QUANTIFICATION OF CORONARY FLOW VELOCITY VIA CONTRAST DISPERSION PATTERNS: INSIGHTS FROM COMPUTATIONAL MODELING AND COMPUTED TOMOGRAPHY EXPERIMENTS
Advances in multi-detector cardiac computed tomography (CT) have expanded its use beyond coronary atherosclerosis to a suite of functional myocardial imaging options that now closely parallels magnetic resonance imaging; including ventricular function, viability and perfusion. Despite these advances, there are currently no existing CT based methods to assess coronary luminal blood flow/hemodynamics.
Recent studies have shown that CT derived axial transluminal contrast gradients (TCG) are greater in coronary arteries with atherosclerotic lesions when compared with normal arteries; suggesting TCG may be related to local coronary hemodynamics. Despite this provocative observation, the basic mechanisms responsible for TCG and their possible connection with coronary hemodynamics have not been explained.
In the current work, we hypothesize that TCG is related to the temporal gradients of the contrast bolus and that TCG encodes coronary flow velocity. An analytical relationship between spatial (TCG) and temporal measurements of contrast dispersion is proposed and this allows for estimation of coronary flow velocity from TCG. This is a novel method (called transluminal attenuation flow encoding-TAFE) integrates: a) anatomic features of the coronary vessels, b) TCG and c) temporal gradients in contrast associated with the arterial input function (AIF) that are readily available in conventional CT to allow non-invasive CT derived coronary flow quantification.
The TAFE formulation is validated in computational models as well as in CT-compatible experimental phantom studies with configurations that mimic coronary vessels. The experimental studies revealed factors that were absent in computational modeling including imaging artifacts and imaging reconstruction kernels where by imaging analysis TAFE has been modified.
In addition, computational simulations of the aortic arch including a semi-patient specific aortic valve model were performed to study contrast dispersion through the arch. This study was done to assess a key assumption in TAFE, that the clinically available AIF at the descending aorta can be used as an accurate estimate of the AIF at the coronary ostium.. The work provides support for the ability of TAFE to provide quantitative estimates of coronary flow velocity but also reveals a number of issues that require further assessment for improved accuracy of TAFE
Physiology and coronary artery disease: emerging insights from computed tomography imaging based computational modeling
Improvements in spatial and temporal resolution now permit robust high quality characterization of presence, morphology and composition of coronary atherosclerosis in computed tomography (CT). These characteristics include high risk features such as large plaque volume, low CT attenuation, napkin-ring sign, spotty calcification and positive remodeling. Because of the high image quality, principles of patient-specific computational fluid dynamics modeling of blood flow through the coronary arteries can now be applied to CT and allow the calculation of local lesion-specific hemodynamics such as endothelial shear stress, fractional flow reserve and axial plaque stress. This review examines recent advances in coronary CT image-based computational modeling and discusses the opportunity to identify lesions at risk for rupture much earlier than today through the combination of anatomic and hemodynamic information
QUANTIFICATION OF CORONARY FLOW VELOCITY VIA CONTRAST DISPERSION PATTERNS: INSIGHTS FROM COMPUTATIONAL MODELING AND COMPUTED TOMOGRAPHY EXPERIMENTS
Advances in multi-detector cardiac computed tomography (CT) have expanded its use beyond coronary atherosclerosis to a suite of functional myocardial imaging options that now closely parallels magnetic resonance imaging; including ventricular function, viability and perfusion. Despite these advances, there are currently no existing CT based methods to assess coronary luminal blood flow/hemodynamics.
Recent studies have shown that CT derived axial transluminal contrast gradients (TCG) are greater in coronary arteries with atherosclerotic lesions when compared with normal arteries; suggesting TCG may be related to local coronary hemodynamics. Despite this provocative observation, the basic mechanisms responsible for TCG and their possible connection with coronary hemodynamics have not been explained.
In the current work, we hypothesize that TCG is related to the temporal gradients of the contrast bolus and that TCG encodes coronary flow velocity. An analytical relationship between spatial (TCG) and temporal measurements of contrast dispersion is proposed and this allows for estimation of coronary flow velocity from TCG. This is a novel method (called transluminal attenuation flow encoding-TAFE) integrates: a) anatomic features of the coronary vessels, b) TCG and c) temporal gradients in contrast associated with the arterial input function (AIF) that are readily available in conventional CT to allow non-invasive CT derived coronary flow quantification.
The TAFE formulation is validated in computational models as well as in CT-compatible experimental phantom studies with configurations that mimic coronary vessels. The experimental studies revealed factors that were absent in computational modeling including imaging artifacts and imaging reconstruction kernels where by imaging analysis TAFE has been modified.
In addition, computational simulations of the aortic arch including a semi-patient specific aortic valve model were performed to study contrast dispersion through the arch. This study was done to assess a key assumption in TAFE, that the clinically available AIF at the descending aorta can be used as an accurate estimate of the AIF at the coronary ostium.. The work provides support for the ability of TAFE to provide quantitative estimates of coronary flow velocity but also reveals a number of issues that require further assessment for improved accuracy of TAFE
A Highly Automated Computational Method for Modeling of Intracranial Aneurysm Hemodynamics
Intracranial aneurysms manifest in a vast variety of morphologies and their growth and rupture risk are subject to patient-specific conditions that are coupled with complex, non-linear effects of hemodynamics. Thus, studies that attempt to understand and correlate rupture risk to aneurysm morphology have to incorporate hemodynamics, and at the same time, address a large enough sample size so as to produce reliable statistical correlations. In order to perform accurate hemodynamic simulations for a large number of aneurysm cases, automated methods to convert medical imaging data to simulation-ready configuration with minimal (or no) human intervention are required. In the present study, we develop a highly-automated method based on the immersed boundary method framework to construct computational models from medical imaging data which is the key idea is the direct use of voxelized contrast information from the 3D angiograms to construct a level-set based computational “mask” for the hemodynamic simulation. Appropriate boundary conditions are provided to the mask and the dynamics of blood flow inside the vessels and aneurysm is simulated by solving the Navier-Stokes equations on the Cartesian grid using the sharp-interface immersed boundary method. The present method does not require body conformal surface/volume mesh generation or other intervention for model clean-up. The viability of the proposed method is demonstrated for a number of distinct aneurysms derived from actual, patient-specific data
Flow Dynamics in the Aortic Arch and Its Effect on the Arterial Input Function in Cardiac Computed Tomography
Computational Study of Computed Tomography Contrast Gradients in Models of Stenosed Coronary Arteries
Effect of Wall Elasticity on Hemodynamics and Wall Shear Stress in Patient-Specific Simulations in the Coronary Arteries
Sex Differences in Left Ventricular Remodeling and Outcomes in Chronic Aortic Regurgitation
BACKGROUND
Left ventricular (LV) dilatation is a key compensatory feature in patients with chronic aortic regurgitation (AR). However, sex-differences in LV remodeling and outcomes in chronic AR have been poorly investigated so far.
METHODS
We performed cardiovascular magnetic resonance imaging (CMR) including phase-contrast velocity-encoded imaging for the measurement of regurgitant fraction (RegF) at the sinotubular junction, in consecutive patients with at least mild AR on echocardiography. We assessed LV size (end-diastolic volume indexed to body surface area, LVEDV/BSA) and investigated sex differences between LV remodeling and increasing degrees of AR severity. Cox-regression models were used to test differences in outcomes between men and women using a composite of heart failure hospitalization, unscheduled AR intervention, and cardiovascular death.
RESULTS
270 consecutive patients (59.6% male, 59.8 ± 20.8 y/o, 59.6% with at least moderate AR on echocardiography) were included. On CMR, mean RegF was 18.1 ± 17.9% and a total of 65 (24.1%) had a RegF ≥ 30%. LVEDV/BSA was markedly closer related with AR severity (RegF) in men compared to women. Each 1-SD increase in LVEDV/BSA (mL/m) was associated with a 9.7% increase in RegF in men and 5.9% in women, respectively (p-value for sex-interaction < 0.001). Based on previously published reference values, women-in contrast to men-frequently had a normal LV size despite severe AR (e.g., for LVEDV/BSA on CMR: 35.3% versus 8.7%, p < 0.001). In a Cox-regression model adjusted for age, LVEDV/BSA and RegF, women were at significantly higher risk for the composite endpoint when compared to men (adj. HR 1.81 (95%CI 1.09-3.03), p = 0.022).
CONCLUSION
In patients with chronic AR, LV remodeling is a hallmark feature in men but not in women. Severity of AR may be underdiagnosed in female patients in the absence of LV dilatation. Future studies need to address the dismal prognosis in female patients with chronic AR
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Computed tomography-based fat and muscle characteristics are associated with mortality after transcatheter aortic valve replacement
BackgroundComputed tomography (CT)-based fat and muscle measures are associated with outcome in large populations. We tested if muscle and fat characteristics are associated with long-term outcomes after TAVR.MethodsWe included 403 clinical CTs performed prior to TAVR at our center between 2008 and 2016, measuring area (cm2) and density (Hounsfield units, HU) of both psoas muscles (PM), subcutaneous adipose (SAT), and visceral adipose tissue (VAT). Area measures were indexed to height, log-transformed and both area and density were standardized for analysis. We assessed the association of each measure with all-cause mortality (adjusted for age, sex, body mass index (BMI), and the Society of Thoracic Surgeons (STS) risk score.ResultsOf the 403 individuals (83 ± 8 years; 52% female), 167 (41.4%) died during a median follow-up of 458 days (interquartile range IQR 297-840). Fat measures were feasible and rapid. Fat area was available in 242 (60%) patients with an adequate field of view. Individuals with the lowest PM area, SAT area or VAT area exhibited the highest hazard of mortality. In addition, greater SAT density was associated with a higher mortality hazard (adjusted HR per standard deviation increase in density = 1.35, 95%CI 1.10-1.67, P = 0.005).ConclusionRapid CT-based tissue characterization is feasible in patients referred for TAVR. Decreased PM area and increased SAT density are associated with long-term mortality after TAVR, even after accounting for age, sex, BMI, and STS score. Further studies are necessary to interrogate sex-specific relationships between CT tissue metrics and mortality and whether CT measures are incremental to well-established frailty metrics
Sex Differences in Left Ventricular Remodeling and Outcomes in Chronic Aortic Regurgitation
Background: Left ventricular (LV) dilatation is a key compensatory feature in patients with chronic aortic regurgitation (AR). However, sex-differences in LV remodeling and outcomes in chronic AR have been poorly investigated so far. Methods: We performed cardiovascular magnetic resonance imaging (CMR) including phase-contrast velocity-encoded imaging for the measurement of regurgitant fraction (RegF) at the sinotubular junction, in consecutive patients with at least mild AR on echocardiography. We assessed LV size (end-diastolic volume indexed to body surface area, LVEDV/BSA) and investigated sex differences between LV remodeling and increasing degrees of AR severity. Cox-regression models were used to test differences in outcomes between men and women using a composite of heart failure hospitalization, unscheduled AR intervention, and cardiovascular death. Results: 270 consecutive patients (59.6% male, 59.8 ± 20.8 y/o, 59.6% with at least moderate AR on echocardiography) were included. On CMR, mean RegF was 18.1 ± 17.9% and a total of 65 (24.1%) had a RegF ≥ 30%. LVEDV/BSA was markedly closer related with AR severity (RegF) in men compared to women. Each 1-SD increase in LVEDV/BSA (mL/m2) was associated with a 9.7% increase in RegF in men and 5.9% in women, respectively (p-value for sex-interaction < 0.001). Based on previously published reference values, women—in contrast to men—frequently had a normal LV size despite severe AR (e.g., for LVEDV/BSA on CMR: 35.3% versus 8.7%, p < 0.001). In a Cox-regression model adjusted for age, LVEDV/BSA and RegF, women were at significantly higher risk for the composite endpoint when compared to men (adj. HR 1.81 (95%CI 1.09–3.03), p = 0.022). Conclusion: In patients with chronic AR, LV remodeling is a hallmark feature in men but not in women. Severity of AR may be underdiagnosed in female patients in the absence of LV dilatation. Future studies need to address the dismal prognosis in female patients with chronic AR