346 research outputs found
Assessment of myocardial scarring improves risk stratification in patients evaluated for cardiac defibrillator implantation
Society for Cardiovascular Magnetic Resonance (SCMR) recommended CMR protocols for scanning patients with active or convalescent phase COVID-19 infection
The aim of this document is to provide specific recommendations on the use of cardiovascular magnetic resonance (CMR) protocols in the era of the COVID-19 pandemic. In patients without COVID-19, standard CMR protocols should be used based on clinical indication as usual. Protocols used in patients who have known / suspected active COVID-19 or post COVID-19 should be performed based on the specific clinical question with an emphasis on cardiac function and myocardial tissue characterization. Short and dedicated protocols are recommended
Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta
Background and Objective: Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoratic aortic aneurysms (ATAA). To accurately reproduce in vivo hemodynamics, computational fluid dynamics (CFD) models must employ realistic inflow boundary conditions (BCs). However, the limited availability of in vivo velocity measurements, still makes researchers resort to idealized BCs. The aim of this study was to generate and thoroughly characterize a large dataset of synthetic 4D aortic velocity profiles sampled on a 2D cross-section along the ascending aorta with features similar to clinical cohorts of patients with ATAA. Methods: Time-resolved 3D phase contrast magnetic resonance (4D flow MRI) scans of 30 subjects with ATAA were processed through in-house code to extract anatomically consistent cross-sectional planes along the ascending aorta, ensuring spatial alignment among all planes and interpolating all velocity fields to a reference configuration. Velocity profiles of the clinical cohort were extensively characterized by computing flow morphology descriptors of both spatial and temporal features. By exploiting principal component analysis (PCA), a statistical shape model (SSM) of 4D aortic velocity profiles was built and a dataset of 437 synthetic cases with realistic properties was generated. Results: Comparison between clinical and synthetic datasets showed that the synthetic data presented similar characteristics as the clinical population in terms of key morphological parameters. The average velocity profile qualitatively resembled a parabolic-shaped profile, but was quantitatively characterized by more complex flow patterns which an idealized profile would not replicate. Statistically significant correlations were found between PCA principal modes of variation and flow descriptors. Conclusions: We built a data-driven generative model of 4D aortic inlet velocity profiles, suitable to be used in computational studies of blood flow. The proposed software system also allows to map any of the generated velocity profiles to the inlet plane of any virtual subject given its coordinate set
Cine-CMR quantified left atrial diameter - a simple index of left atrial remodeling that closely parallels chamber area and stratifies longitudinal atrial arrhythmic risk
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Papillary muscle infarction in relation to left ventricular infarct distribution and transmurality - assessment by delayed enhancement cardiac magnetic resonance imaging
This study used delayed enhancement CMR (DE-CMR) and invasive angiography to evaluate relationships between papillary muscle and left ventricular (LV) chamber wall infarction following ST segment elevation MI (STEMI). Results demonstrate that papillary muscle infarction (PMI) parallels infarct transmurality and contractile dysfunction within the adjacent LV wall
Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta
Numerical simulations of blood flow are a valuable tool to investigate the
pathophysiology of ascending thoracic aortic aneurysms (ATAA). To accurately
reproduce hemodynamics, computational fluid dynamics (CFD) models must employ
realistic inflow boundary conditions (BCs). However, the limited availability
of in vivo velocity measurements still makes researchers resort to idealized
BCs. In this study we generated and thoroughly characterized a large dataset of
synthetic 4D aortic velocity profiles suitable to be used as BCs for CFD
simulations. 4D flow MRI scans of 30 subjects with ATAA were processed to
extract cross-sectional planes along the ascending aorta, ensuring spatial
alignment among all planes and interpolating all velocity fields to a reference
configuration. Velocity profiles of the clinical cohort were extensively
characterized by computing flow morphology descriptors of both spatial and
temporal features. By exploiting principal component analysis (PCA), a
statistical shape model (SSM) of 4D aortic velocity profiles was built and a
dataset of 437 synthetic cases with realistic properties was generated.
Comparison between clinical and synthetic datasets showed that the synthetic
data presented similar characteristics as the clinical population in terms of
key morphological parameters. The average velocity profile qualitatively
resembled a parabolic-shaped profile, but was quantitatively characterized by
more complex flow patterns which an idealized profile would not replicate.
Statistically significant correlations were found between PCA principal modes
of variation and flow descriptors. We built a data-driven generative model of
4D aortic velocity profiles, suitable to be used in computational studies of
blood flow. The proposed software system also allows to map any of the
generated velocity profiles to the inlet plane of any virtual subject given its
coordinate set.Comment: 21 pages, 5 figures, 2 tables To be submitted to "Computer methods
and programs in biomedicine" Scripts: https://github.com/saitta-s/flow4D
Synthetic velocity profiles: //doi.org/10.5281/zenodo.725198
Novel insights by 4D Flow imaging on aortic flow physiology after valve-sparing root replacement with or without neosinuses
This study was undertaken to evaluate the flow dynamics in the aortic root after valve-sparing root replacement with and without neosinuses of Valsalva reconstruction, by exploiting the capability of 4D Flow imaging to measure in vivo blood velocity fields and 3D geometric flow patterns
Mid-wall fibrosis on delayed enhancement CMR - a marker for adverse left ventricular chamber remodeling independent of cardiomyopathic etiology
Utilization of cardiovascular magnetic resonance (CMR) imaging for resumption of athletic activities following COVID-19 infection: An expert consensus document on behalf of the American Heart Association Council on Cardiovascular Radiology and Intervention (CVRI) Leadership and endorsed by the Society for Cardiovascular Magnetic Resonance (SCMR)
The global pandemic of coronavirus disease 2019 (COVID-19) caused by infection with severe acute respiratory suyndrome coronavirus 2 (SARS-CoV-2) is now entering its 4th year with little evidence of abatement. As of December 2022, the World Health Organization Coronavirus (COVID-19) Dashboard reported 643 million cumulative confirmed cases of COVID-19 worldwide and 98 million in the United States alone as the country with the highest number of cases. While pneumonia with lung injury has been the manifestation of COVID-19 principally responsible for morbidity and mortality, myocardial inflammation and systolic dysfunction though uncommon are well-recognized features that also associate with adverse prognosis. Given the broad swath of the population infected with COVID-19, the large number of affected professional, collegiate, and amateur athletes raises concern regarding the safe resumption of athletic activity (return to play, RTP) following resolution of infection. A variety of different testing combinations that leverage the electrocardiogram, echocardiography, circulating cardiac biomarkers, and cardiovascular magnetic resonance (CMR) imaging have been proposed and implemented to mitigate risk. CMR in particular affords high sensitivity for myocarditis but has been employed and interpreted non-uniformly in the context of COVID-19 thereby raising uncertainty as to the generalizability and clinical relevance of findings with respect to RTP. This consensus document synthesizes available evidence to contextualize the appropriate utilization of CMR in the RTP assessment of athletes with prior COVID-19 infection to facilitate informed, evidence-based decisions, while identifying knowledge gaps that merit further investigation
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