Quantitative normal values of helical flow, flow jets and wall shear stress of healthy volunteers in the ascending aorta.

OBJECTIVES 4D flow MRI enables quantitative assessment of helical flow. We sought to generate normal values and elucidate changes of helical flow (duration, volume, length, velocities and rotational direction) and flow jet (displacement, flow angle) as well as wall shear stress (WSS). METHODS We assessed the temporal helical existence (THEX), maximum helical volume (HVmax), accumulated helical volume (HVacc), accumulated helical volume length (HVLacc), maximum forward velocity (maxVfor), maximum circumferential velocity (maxVcirc), rotational direction (RD) and maximum wall shear stress (WSS) as reported elsewhere using the software tool Bloodline in 86 healthy volunteers (46 females, mean age 41 ± 13 years). RESULTS WSS decreased by 42.1% and maxVfor by 55.7% across age. There was no link between age and gender regarding the other parameters. CONCLUSION This study provides age-dependent normal values regarding WSS and maxVfor and age- and gender-independent normal values regarding THEX, HVmax, HVacc, HVLacc, RD and maxVcirc. KEY POINTS • 4D flow provides numerous new parameters; therefore, normal values are mandatory. • Wall shear stress decreases over age. • Maximum helical forward velocity decreases over age

4D flow imaging of the thoracic aorta: is there an added clinical value?

Four-dimensional (4D) flow MRI has emerged as a powerful non-invasive technique in cardiovascular imaging, enabling to analyse in vivo complex flow dynamics models by quantifying flow parameters and derived features. Deep knowledge of aortic flow dynamics is fundamental to better understand how abnormal flow patterns may promote or worsen vascular diseases. In the perspective of an increasingly personalized and preventive medicine, growing interest is focused on identifying those quantitative functional features which are early predictive markers of pathological evolution. The thoracic aorta and its spectrum of diseases, as the first area of application and development of 4D flow MRI and supported by an extensive experimental validation, represents the ideal model to introduce this technique into daily clinical practice. The purpose of this review is to describe the impact of 4D flow MRI in the assessment of the thoracic aorta and its most common affecting diseases, providing an overview of the actual clinical applications and describing the potential role of derived advanced hemodynamic measures in tailoring follow-up and treatment

Advanced Analysis Techniques for Intra-cardiac Flow Evaluation from 4D Flow MRI

Time-resolved 3D velocity-encoded MR imaging with velocity encoding in three directions (4D Flow) has emerged as a novel MR acquisition technique providing detailed information on flow in the cardiovascular system. In contrast to other clinically available imaging techniques such as echo-Doppler, 4D Flow MRI provides the 3D Flow velocity field within a volumetric region of interest over the cardiac cycle. This work reviews the most recent advances in the development and application of dedicated image analysis techniques for the assessment of intra-cardiac flow features from 4D Flow MRI.Novel image analysis techniques have been developed for extraction of relevant intra-cardiac flow features from 4D Flow MRI, which have been successfully applied in various patient cohorts and volunteer studies. Disturbed flow patterns have been linked with valvular abnormalities and ventricular dysfunction. Recent technical advances have resulted in reduced scan times and improvements in image quality, increasing the potential clinical applicability of 4D Flow MRI.4D Flow MRI provides unique capabilities for 3D visualization and quantification of intra-cardiac blood flow. Contemporary knowledge on 4D Flow MRI shows promise for further exploration of the potential use of the technique in research and clinical applications

Four-Dimensional Flow Magnetic Resonance Imaging and Applications in Cardiology

Blood flow through the heart and great vessels moves in three dimensions (3D) throughout time. However, the assessment of its 3D nature has been limited in the human body. Recent advances in magnetic resonance imaging (MRI) allow for the comprehensive visualization and quantification of in-vivo flow dynamics using four-dimensional (4D) flow MRI. In addition, this technique provides the opportunity to obtain advanced hemodynamic biomarkers such as vorticity, helicity, wall shear stress (WSS), pressure gradients, viscous energy loss (EL), and turbulent kinetic energy (TKE). This chapter will introduce 4D flow MRI which is currently used for blood flow visualization and advanced quantification of cardiac hemodynamic biomarkers. We will discuss its advantages relative to other in-vivo flow imaging techniques and describe its potential clinical applications in cardiology

Validation of 2D flow MRI for helical and vortical flows

Purpose The main objective of this study was to develop two-dimensional (2D) phase contrast (PC) methods to quantify the helicity and vorticity of blood flow in the aortic root. Methods This proof-of-concept study used four-dimensional (4D) flow cardiovascular MR (4D flow CMR) data of five healthy controls, five patients with heart failure with preserved ejection fraction and five patients with aortic stenosis (AS). A PC through-plane generated by 4D flow data was treated as a 2D PC plane and compared with the original 4D flow. Visual assessment of flow vectors was used to assess helicity and vorticity. We quantified flow displacement (FD), systolic flow reversal ratio (sFRR) and rotational angle (RA) using 2D PC. Results For visual vortex flow presence near the inner curvature of the ascending aortic root on 4D flow CMR, sFRR demonstrated an area under the curve (AUC) of 0.955, p8% for sFRR had a sensitivity of 82% and specificity of 100% for visual vortex presence. In addition, the average late systolic FD, a marker of flow eccentricity, also demonstrated an AUC of 0.909, p<0.001 for visual vortex flow. Manual systolic rotational flow angle change (ΔsRA) demonstrated excellent association with semiautomated ΔsRA (r=0.99, 95% CI 0.9907 to 0.999, p<0.001). In reproducibility testing, average systolic FD (FDsavg) showed a minimal bias at 1.28% with a high intraclass correlation coefficient (ICC=0.92). Similarly, sFRR had a minimal bias of 1.14% with an ICC of 0.96. ΔsRA demonstrated an acceptable bias of 5.72°-and an ICC of 0.99. Conclusion 2D PC flow imaging can possibly quantify blood flow helicity (ΔRA) and vorticity (FRR). These imaging biomarkers of flow helicity and vorticity demonstrate high reproducibility for clinical adoption

혈관 구조 분석 기반 혈류선 추출과 불투명도 변조를 이용한 혈류 가시화 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 신영길.With recent advances in acquisition and simulation of blood flow data, blood flow visualization has been widely used in medical imaging for the diagnosis and treatment of pathological vessels. The integral line based method has been most commonly employed to depict hemodynamic data because it exhibits a long term flow behavior useful for flow analysis. This method generates integral lines to be used as a basis for graphical representation by tracing the trajectory of a massless particle released on the vector field through a numerical integration. However, there are several unsolved problems when this previous method is applied to thin curved vascular structures. The first one is to locate a seeding plane, which is manually performed in the existing methods, thus yielding inconsistent visual results. The second one is the early termination of a line integration due to locally reversed flow and narrow tubular structure, which results in short flowlines comparing with the vessel length. And the last one is the line occlusion caused by the dense depiction of flowlines. Additionally, in blood flow visualization for clinical uses, it is essential to apparently exhibit abnormal flow relevant to vessel diseases. In this paper, we present an enhanced method that overcomes problems related to the integration based flow visualization and depicts hemodynamics in a more informative way for assisting the diagnosis process. Using the fact that blood flow passes through the inlet or outlet but is blocked by vessel wall, we firstly identify the vessel inlet or outlet by the orthogonality metric between flow velocity vector and vessel surface normal vector. Then, we generate seed points on the detected inlet or outlet by Poisson disk sampling. Therefore, we can achieve the automatic seeding that leads to a consistent and faster flow depiction by skipping the manual location of a seeding plane to initiate the line integration. In addition, we resolve the early terminated line integration by applying the tracing direction adaptively based on flow direction at each seed point and by performing the additional seeding near the terminated location. This solution enables to yield length-extended flowlines, which contribute to faithful flow visualization. Based on the observation that blood flow usually follows the vessel track if there is no obstacle or leak in the middle of a passage, we define the representative flowline for each branch by the vessel centerline. Then, we render flowlines by assigning the opacity according to their shape similarity with the vessel centerline so that flowlines similar to the vessel centerline are shown transparently, while different ones opaquely. Accordingly, our opacity modulation method enables flowlines with unusual flow pattern to appear more noticeable, while minimizing visual clutter and line occlusion. Finally, we introduce HSV (hue, saturation, value) color coding to simultaneously exhibit flow attributes such as local speed and residence time. This color coding gives a more realistic fading effect on the older particles or line segments by attenuating the saturation according to the residence time. Hence, it supports users in comprehending intuitively multiple information at once. Experimental results show that our technique is well suitable to depict blood flow in vascular structures.Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Statement 3 1.3 Main Contribtion 7 1.4 Organization of the Dissertation 8 Chapter 2 Related Works 9 2.1 Flow and Velocity Vector 9 2.2 Flow Visualization 10 2.3 Blood Flow Visualization 16 2.3.1 Geometric Method 16 2.3.2 Feature-Based Method 18 2.3.3 Partition-Based Method 19 Chapter 3 Integration based Flowline Extraction 22 3.1 Overview 22 3.2 Seeding 23 3.3 Barycentric Coordinate Conversion 24 3.4 Cell Searching 26 3.5 Velocity Vector Calculation 27 3.6 Advection 28 3.7 Step Size Adaptation 30 Chapter 4 Blood Flow Visualization using Flow and Geometric Analysis 32 4.1 Preprocessing 33 4.2 Inlet or Outlet based Seeding 35 4.3 Tracing 39 4.3.1 Flow based Bidirectional Tracing 39 4.3.2 Additional Seeding for Length Extended Line Integration 41 4.4 Opacity Modulation 43 4.4.1 Global Opacity 45 4.4.2 Local Opacity 46 4.4.3 Opacity Adjustment 52 4.4.4 Blending 53 4.5 HSV Color Coding 54 4.6 Vessel Rendering 58 4.6.1 Vessel Smoothing 59 4.6.2 Vessel Contour Enhancement 60 4.7 Flowline Drawing 61 4.7.1 Line Illumination 61 4.7.2 Line Halo 63 4.8 Animation 64 Chapter 5 Experimental Results 67 5.1 Evaluation on Seeding 69 5.2 Evaluation on Tracing 74 5.3 Evaluation on Opacity Modulation 82 5.4 Parameter Study 85 Chapter 6 Conclusion 87 Bibliography 89 초 록 99Docto