Comparison of 2D and 4D Flow MRI in Neonates Without General Anesthesia

Sjöberg, Pia; Hedström, Erik; Fricke, Katrin; Frieberg, Petter; Weismann, Constance G.; Liuba, Petru; Carlsson, Marcus; Töger, Johannes

doi:10.1002/jmri.28303

Cited by 9 publications

(4 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, despite equal positions of the measurement planes at the atrium and aortic valve, differences in velocity measurements were still observed. It has been shown that 4D PC-MRI data may underestimate peak velocities [29], [30], which may account for the observed differences. Additionally, the spatial standard deviation in 4D PC-MRI measurements is larger than in the 2D PC-MRI data, thus a higher variation in velocity in the 4D PC-MRI data was obtained.…”

Section: Discussionmentioning

confidence: 99%

Multi-modal Phantom Experiments, mimicking Flow through the Mitral Heart Valve

Christierson,

Frieberg,

Lala

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

PurposeFluid-structure interaction (FSI) models are more commonly applied in medical research as computational power is increasing. However, understanding the accuracy of FSI models is crucial, especially in the context of heart valve disease in patient-specific models. Therefore, this study aimed to create a multi-modal benchmarking data set for FSI models, based on clinically important parameters, such as the pressure, velocity, and valve opening, with anin vitrophantom setup.MethodAnin vitrosetup was developed with a 3D-printed phantom mimicking the left heart, including a deforming mitral valve. A range of pulsatile flows was created with a computer-controlled motor-and-pump setup. Invasive catheter measurements, magnetic resonance imaging (MRI), and echocardiography (Echo) imaging were used to measure pressure and velocity in the domain. Furthermore, the valve opening was quantified based on cine MRI and Echo images.ResultThe experimental setup, with 0.5 % cycle-to-cycle variation, was successfully built and six different flow cases were investigated. Higher velocity through the mitral valve was observed for increased cardiac output. The pressure difference across the valve also followed this trend. The flow in the phantom was qualitatively assessed by the velocity profile in the ventricle and by streamlines obtained from 4D phase-contrast MRI.ConclusionA multi-modal set of validation data for FSI models has been created, based on parameters relevant for diagnosis of heart valve disease. All data is publicly available for future development of computational heart valve models.

show abstract

Section: Discussionmentioning

confidence: 99%

Multi-modal Phantom Experiments, mimicking Flow through the Mitral Heart Valve

Christierson,

Frieberg,

Lala

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…This would allow PEPT to measure both blood velocity and functional pressure drop over an occlusion, in contrast to conventional PET, which can only measure perfusion over tissue volumes [ 79 ]. Cardiac 4D phase-contrast CMR can measure flow at a resolution of 1.5x1.5x1.5 to 3×3×3 mm 3 [ 4 , 5 ] with a dependency on the users’ experience [ 80 ], which would limit their ability to measure flow across an occlusion.…”

Section: Discussionmentioning

confidence: 99%

“…Invasively, one can measure the pressure difference along a lesion during coronary angiography [ 1 ] to calculate the Fractional Flow Reserve (FFR), which links to the severity of the disease. To avoid invasive procedures, techniques such as coronary computed tomography (CT) [ 2 , 3 ], 4D MRI [ 4 , 5 ], and cardiac Positron Emission Tomography (PET) [ 6 ] have been used. However, all the current techniques are associated with various uncertainties and challenges.…”

Section: Introductionmentioning

confidence: 99%

Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking: An in-silico study

Keramati,

de Vecchi,

Rajani

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

Accurate velocity reconstruction is essential for assessing coronary artery disease. We propose a Gaussian process method to reconstruct the velocity profile using the sparse data of the positron emission particle tracking (PEPT) in a biological environment, which allows the measurement of tracer particle velocity to infer fluid velocity fields. We investigated the influence of tracer particle quantity and detection time interval on flow reconstruction accuracy. Three models were used to represent different levels of stenosis and anatomical complexity: a narrowed straight tube, an idealized coronary bifurcation with stenosis, and patient-specific coronary arteries with a stenotic left circumflex artery. Computational fluid dynamics (CFD), particle tracking, and the Gaussian process of kriging were employed to simulate and reconstruct the pulsatile flow field. The study examined the error and uncertainty in velocity profile reconstruction after stenosis by comparing particle-derived flow velocity with the CFD solution. Using 600 particles (15 batches of 40 particles) released in the main coronary artery, the time-averaged error in velocity reconstruction ranged from 13.4% (no occlusion) to 161% (70% occlusion) in patient-specific anatomy. The error in maximum cross-sectional velocity at peak flow was consistently below 10% in all cases. PEPT and kriging tended to overestimate area-averaged velocity in higher occlusion cases but accurately predicted maximum cross-sectional velocity, particularly at peak flow. Kriging was shown to be useful to estimate the maximum velocity after the stenosis in the absence of negative near-wall velocity.

show abstract

“…SNR and VNR improve with T1 shortening achieved by administering gadolinium-based contrast [ 48 , 49 ] or superparamagnetic iron oxide agent (ferumoxytol) [ 50 ]. Therefore, contrast administration to enhance image quality can be useful (but is not essential), especially in challenging cases such as neonates and dissections to enhance image quality, but good image quality can be achieved without contrast administration especially when scanning at 3T [ 51 , 52 ]. In adults, if contrast is given for other reasons, it is useful to perform the 4D Flow CMR acquisition after gadolinium-based contrast administration.…”

Section: Advised Acquisition Parameters For Clinical Usementioning

confidence: 99%

4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

Bissell

Raimondi

Ait-Alì

et al. 2023

Journal of Cardiovascular Magnetic Resonance

Self Cite

View full text Add to dashboard Cite

Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 ‘4D Flow CMR Consensus Statement’. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.

show abstract

Comparison of 2D and 4D Flow MRI in Neonates Without General Anesthesia

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 9 publications

References 41 publications

Multi-modal Phantom Experiments, mimicking Flow through the Mitral Heart Valve

Multi-modal Phantom Experiments, mimicking Flow through the Mitral Heart Valve

Using Gaussian process for velocity reconstruction after coronary stenosis applicable in positron emission particle tracking: An in-silico study

4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

Contact Info

Product

Resources

About