Browsing by Author "Ruijsink, Bram"

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    A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis
    (2024) Machado, Ines; Puyol-Anton, Esther; Hammernik, Kerstin; Cruz, Gastao; Ugurlu, Devran; Olakorede, Ihsane; Oksuz, Ilkay; Ruijsink, Bram; Castelo-Branco, Miguel; Young, Alistair; Prieto, Claudia; Schnabel, Julia; King, Andrew
    Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent decades considerable effort has been put into accelerating scan times without compromising image quality or the accuracy of derived results. In this article, we present a fully-automated, quality-controlled integrated framework for reconstruction, segmentation and downstream analysis of undersampled cine CMR data. The framework produces high quality reconstructions and segmentations, leading to undersampling factors that are optimised on a scan-by-scan basis. This results in reduced scan times and automated analysis, enabling robust and accurate estimation of functional biomarkers. To demonstrate the feasibility of the proposed approach, we perform simulations of radial k-space acquisitions using in-vivo cine CMR data from 270 subjects from the UK Biobank (with synthetic phase) and in-vivo cine CMR data from 16 healthy subjects (with real phase). The results demonstrate that the optimal undersampling factor varies for different subjects by approximately 1 to 2 seconds per slice. We show that our method can produce quality-controlled images in a mean scan time reduced from 12 to 4 seconds per slice, and that image quality is sufficient to allow clinically relevant parameters to be automatically estimated to lie within 5% mean absolute difference.
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    Altered Aortic Hemodynamics and Relative Pressure in Patients with Dilated Cardiomyopathy
    (2022) Marlevi, David; Mariscal-Harana, Jorge; Burris, Nicholas S.; Sotelo, Julio; Ruijsink, Bram; Hadjicharalambous, Myrianthi; Asner, Liya; Sammut, Eva; Chabiniok, Radomir; Uribe, Sergio; Winter, Reidar; Lamata, Pablo; Alastruey, Jordi; Nordsletten, David
    Ventricular-vascular interaction is central in the adaptation to cardiovascular disease. However, cardiomyopathy patients are predominantly monitored using cardiac biomarkers. The aim of this study is therefore to explore aortic function in dilated cardiomyopathy (DCM). Fourteen idiopathic DCM patients and 16 controls underwent cardiac magnetic resonance imaging, with aortic relative pressure derived using physics-based image processing and a virtual cohort utilized to assess the impact of cardiovascular properties on aortic behaviour. Subjects with reduced left ventricular systolic function had significantly reduced aortic relative pressure, increased aortic stiffness, and significantly delayed time-to-pressure peak duration. From the virtual cohort, aortic stiffness and aortic volumetric size were identified as key determinants of aortic relative pressure. As such, this study shows how advanced flow imaging and aortic hemodynamic evaluation could provide novel insights into the manifestation of DCM, with signs of both altered aortic structure and function derived in DCM using our proposed imaging protocol.
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    Comprehensive Assessment of Left Intraventricular Hemodynamics Using a Finite Element Method: An Application to Dilated Cardiomyopathy Patients
    (2021) Franco, Pamela; Sotelo, Julio; Montalba, Cristian; Ruijsink, Bram; Kerfoot, Eric; Nordsletten, David; Mura, Joaquin; Hurtado, Daniel; Uribe, Sergio
    In this paper, we applied a method for quantifying several left intraventricular hemodynamic parameters from 4D Flow data and its application in a proof-of-concept study in dilated cardiomyopathy (DCM) patients. In total, 12 healthy volunteers and 13 DCM patients under treatment underwent short-axis cine b-SSFP and 4D Flow MRI. Following 3D segmentation of the left ventricular (LV) cavity and registration of both sequences, several hemodynamic parameters were calculated at peak systole, e-wave, and end-diastole using a finite element approach. Sensitivity, inter- and intra-observer reproducibility of hemodynamic parameters were evaluated by analyzing LV segmentation. A local analysis was performed by dividing the LV cavity into 16 regions. We found significant differences between volunteers and patients in velocity, vorticity, viscous dissipation, energy loss, and kinetic energy at peak systole and e-wave. Furthermore, although five patients showed a recovered ejection fraction after treatment, their hemodynamic parameters remained low. We obtained several hemodynamic parameters with high inter- and intra-observer reproducibility. The sensitivity study revealed that hemodynamic parameters showed a higher accuracy when the segmentation underestimates the LV volumes. Our approach was able to identify abnormal flow patterns in DCM patients compared to volunteers and can be applied to any other cardiovascular diseases.
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    Non-invasive local pulse wave velocity using 4D-flow MRI
    (2022) Mura, Joaquin; Sotelo, Julio; Mella, Hernan; Wong, James; Hussain, Tarique; Ruijsink, Bram; Uribe, Sergio
    Pulse Wave Velocity (PWV) corresponds to the velocity at which pressu r e waves, generated by the systolic contraction in the heart, propagate along the arterial tree. Due to the comple x interplay between blood flow and the artery wall, PWV is related to inherent mechanical properties and arterial morphology. PWV has been widely accepted as a biomarker and early predictor to evaluate global arterial distensibility. Sti l l , several local abnor-malities often remain hidden or difficult to detect using non-invasive techniques. Here, we introduce a novel method to efficiently construct a local estimate of PWV along the aorta using 4D-Flow MRI data. A geodesic distance map was used to track advancing pulses for efficient flow calculations, based on the observation that the propagation of velocity wavefronts strongly depends on the arterial morphology. This procedure allows us a robust evaluation of the local transit time due to the pulse wave at each position in the aorta. Moreover, the estimation of the local PWV map did not require centerlines, and the final result is projected back to 3D using the same geodesic map. We evaluated PWV values in healthy young and adult volunteers and patients with uni-ventricular physiology after a Fontan procedure. Ou r method is fast, semi-automatic, and depicts differences between young versus adult volunteers and young volunteers versus Fontan patients, showing consistent results compared to global methods. Remarkably, the technique could detect local differences of PWV on the aortic arch for al l subjects, being consistent with previous findings of reduced PWV in the aortic arch.