Accelerating 4D flow MRI by exploiting vector field divergence regularization

Santelli, Claudio; Loecher, Michael; Busch, Julia; Wieben, Oliver; Schaeffter, Tobias; Kozerke, Sebastian

doi:10.1002/mrm.25563

Cited by 26 publications

(25 citation statements)

References 42 publications

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“…More recently, self‐gated acquisition has been proposed for 4D flow imaging, closing the gap to human application . Second, undersampling strategies are required in order to significantly reduce total scan duration …”

Section: Discussionmentioning

confidence: 99%

Left ventricular blood flow patterns at rest and under dobutamine stress in healthy pigs

et al. 2018

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Intracardiac blood flow patterns are affected by the morphology of cardiac structures and are set up to support the heart's pump function. Exercise affects contractility and chamber size as well as pre‐ and afterload. The aim of this study was to test the feasibility of four‐dimensional phase contrast cardiovascular MRI under pharmacological stress and to study left ventricular blood flow under stress. 4D flow data were successfully acquired and analysed in 12 animals. During dobutamine infusion, heart rate and ejection fraction increased (82 ± 5 bpm versus 124 ± 3 bpm/46 ± 9% versus 65 ± 7%; both p < 0.05). A decrease in left ventricular end‐diastolic volume (72 ± 14 mL versus 55 ± 8 mL; p < 0.05) and end‐systolic volume (40 ± 15 mL versus 19 ± 6 mL; p < 0.05) but no change in stroke volume were observed. Trans‐mitral diastolic inflow velocity increased under dobutamine and the trajectory of inflowing blood was directed towards the anterior septum with increased inflow angle (26 ± 5°) when compared with controls (15 ± 2°). In 5/6 animals undergoing stress diastolic vortices developed later, and in 3/6 animals vortices collapsed earlier with significantly smaller cross‐sectional area during diastole. The vorticity index was not affected. Under the stress condition direct flow (% ejection within the next heart beat) increased from 43 ± 6% to 53 ± 8%. 4D MRI blood flow acquisition and analysis are feasible in pig hearts under dobutamine‐induced stress. Flow patterns characterized by high blood velocity and antero‐septally oriented diastolic inflow as well as decreased ventricular volumes are unfavourable conditions for diastolic vortex development under pharmacological stress, and cardiac output is increased by a rise in heart rate and directly ejected left ventricular blood volume.

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Section: Discussionmentioning

confidence: 99%

Left ventricular blood flow patterns at rest and under dobutamine stress in healthy pigs

et al. 2018

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“…Such an approach is permissible if the object phase can be represented using low‐order spatial harmonics. If, however, the object phase varies locally, as in or near vessels for example, optimization needs to employ separate magnitude and phase regularization . The proposed k ‐ b PCA method is able to resolve local phase variations, as shown for k ‐ t PCA accelerated flow measurements in the neck for example .…”

Section: Discussionmentioning

confidence: 94%

Enhancing intravoxel incoherent motion parameter mapping in the brain usingk‐bPCA

et al. 2018

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Intravoxel incoherent motion (IVIM) imaging of diffusion and perfusion parameters in the brain using parallel imaging suffers from local noise amplification. To address the issue, signal correlations in space and along the diffusion encoding dimension are exploited jointly using a constrained image reconstruction approach. IVIM imaging was performed on a clinical 3 T MR system with diffusion weighting along six gradient directions and 16 b‐values encoded per direction across a range of 0–900 s/mm2. Data were collected in 11 subjects, retrospectively undersampled in k‐space with net factors ranging from 2 to 6 and reconstructed using CG‐SENSE and the proposed k‐b PCA approach. Results of k‐b PCA and CG‐SENSE from retrospectively undersampled data were compared with those from the fully sampled reference. In addition, prospective single‐shot k‐b undersampling was implemented and data were acquired in five additional volunteers. IVIM parameter maps were derived using a segmented least‐squares method. The proposed k‐b PCA method outperformed CG‐SENSE in terms of reconstruction errors for effective undersampling factors of 3 and beyond. Undersampling artifacts were effectively removed with k‐b PCA up to sixfold undersampling. At net sixfold undersampling, relative errors (compared with the fully sampled reference) of image magnitude and IVIM parameters (D, f and D*) were (median ± interquartile range): 3.5 ± 3.7 versus 25.3 ± 25.8%, 2.7 ± 3.6 versus 14.2 ± 20.4%, 15.1 ± 26.1 versus 96.6 ± 67.4% and 14.8 ± 26.6 versus 100 ± 195.1% for k‐b PCA versus CG‐SENSE, respectively. Acquisition with sixfold prospective undersampling yielded average IVIM parameters in the brain of 0.79 ± 0.18 × 10−3 mm2/s for D, 7.35 ± 7.27% for f and 7.11 ± 2.39 × 10−3 mm2/s for D*. Constrained reconstruction using k‐b PCA improves IVIM parameter mapping from undersampled data when compared with CG‐SENSE reconstruction. Prospectively undersampled single‐shot echo planar imaging acquisition was successfully employed using k‐b PCA, demonstrating a reduction of image artifacts and noise relative to parallel imaging.

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“…However, there should be no divergence as blood is an incompressible fluid. Therefore, different techniques exist to filter divergence components [TDGSU11, BVP*13, SLB*16]. Mainly, they try to regularize the flow field by considering its physical properties such as curl, divergence or the flow's rotation behaviour.…”

Section: Flow Data Generation Pipelinementioning

confidence: 99%

Generation and Visual Exploration of Medical Flow Data: Survey, Research Trends and Future Challenges

Oeltze-Jafra

Meuschke

Neugebauer

et al. 2018

Computer Graphics Forum

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Simulations and measurements of blood and airflow inside the human circulatory and respiratory system play an increasingly important role in personalized medicine for prevention, diagnosis and treatment of diseases. This survey focuses on three main application areas. (1) Computational fluid dynamics (CFD) simulations of blood flow in cerebral aneurysms assist in predicting the outcome of this pathologic process and of therapeutic interventions. (2) CFD simulations of nasal airflow allow for investigating the effects of obstructions and deformities and provide therapy decision support. (3) 4D phase‐contrast (4D PC) magnetic resonance imaging of aortic haemodynamics supports the diagnosis of various vascular and valve pathologies as well as their treatment. An investigation of the complex and often dynamic simulation and measurement data requires the coupling of sophisticated visualization, interaction and data analysis techniques. In this paper, we survey the large body of work that has been conducted within this realm. We extend previous surveys by incorporating nasal airflow, addressing the joint investigation of blood flow and vessel wall properties and providing a more fine‐granular taxonomy of the existing techniques. From the survey, we extract major research trends and identify open problems and future challenges. The survey is intended for researchers interested in medical flow but also more general, in the combined visualization of physiology and anatomy, the extraction of features from flow field data and feature‐based visualization, the visual comparison of different simulation results and the interactive visual analysis of the flow field and derived characteristics.

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Accelerating 4D flow MRI by exploiting vector field divergence regularization

Abstract: Regularization of vector field divergence in image reconstruction from undersampled 4D flow data is a valuable approach to improve reconstruction accuracy of velocity vector fields.

Cited by 26 publications

References 42 publications

Left ventricular blood flow patterns at rest and under dobutamine stress in healthy pigs

Left ventricular blood flow patterns at rest and under dobutamine stress in healthy pigs

Enhancing intravoxel incoherent motion parameter mapping in the brain usingk‐bPCA

Generation and Visual Exploration of Medical Flow Data: Survey, Research Trends and Future Challenges

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