Semi-automatic vortex extraction in 4D PC-MRI cardiac blood flow data using line predicates

Stenosis to stented: decrease in flow disturbances following stent implantation of a diseased arteriovenous fistula

The arteriovenous fistula (AVF) is commonly faced with stenosis at the juxta-anastomotic (JXA) region of the vein. Implantation of a flexible nitinol stent across the stenosed JXA has led to the retention of functioning AVFs leading to the resulting AVF geometry being distinctly altered, thereby affecting the haemodynamic environment within it. In this study, large eddy simulations of the flow field within a patient-specific AVF geometry before and after stent implantation were conducted to detail the change in flow features. Although the diseased AVF had much lower flow rates, adverse flow features, such as recirculation zones and swirling flow at the anastomosis, and jet flow at the stenosis site were present. Larger velocity fluctuations (leading to higher turbulent kinetic energy) stemming from these flow features were apparent in the diseased AVF compared to the stented AVF. The unsteadiness at the stenosis created large regions of wall shear stress (WSS) fluctuations downstream of the stenosis site that were not as apparent in the stented AVF geometry. The larger pressure drop across the diseased vein, compared to the stented vein, was primarily caused by the constriction at the stenosis, potentially causing the lower flow rate. Furthermore, the WSS fluctuations in the diseased AVF could lead to further disease progression downstream of the stenosis. The change in bulk flow unsteadiness, pressure drop, and WSS behaviour confirms that the haemodynamic environment of the diseased AVF has substantially improved following the flexible stent implantation.

Bibliometric analysis of 100 top cited articles of heart failure-associated diseases in combination with machine learning

Objective

The aim of this paper is to analyze the application of machine learning in heart failure-associated diseases using bibliometric methods and to provide a dynamic and longitudinal bibliometric analysis of heart failure-related machine learning publications.

Materials and methods

Web of Science was screened to gather the articles for the study. Based on bibliometric indicators, a search strategy was developed to screen the title for eligibility. Intuitive data analysis was employed to analyze the top-100 cited articles and VOSViewer was used to analyze the relevance and impact of all articles. The two analysis methods were then compared to get conclusions.

Results

The search identified 3,312 articles. In the end, 2,392 papers were included in the study, which were published between 1985 and 2023. All articles were analyzed using VOSViewer. Key points of the analysis included the co-authorship map of authors, countries and organizations, the citation map of journal and documents and a visualization of keyword co-occurrence analysis. Among these 100 top-cited papers, with a mean of 122.9 citations, the most-cited article had 1,189, and the least cited article had 47. Harvard University and the University of California topped the list among all institutes with 10 papers each. More than one-ninth of the authors of these 100 top-cited papers wrote three or more articles. The 100 articles came from 49 journals. The articles were divided into seven areas according to the type of machine learning approach employed: Support Vector Machines, Convolutional Neural Networks, Logistic Regression, Recurrent Neural Networks, Random Forest, Naive Bayes, and Decision Tree. Support Vector Machines were the most popular method.

Conclusions

This analysis provides a comprehensive overview of the artificial intelligence (AI)-related research conducted in the field of heart failure, which helps healthcare institutions and researchers better understand the prospects of AI in heart failure and formulate more scientific and effective research plans. In addition, our bibliometric evaluation can assist healthcare institutions and researchers in determining the advantages, sustainability, risks, and potential impacts of AI technology in heart failure.

FlowNL: Asking the Flow Data in Natural Languages

Flow visualization is essentially a tool to answer domain experts' questions about flow fields using rendered images. Static flow visualization approaches require domain experts to raise their questions to visualization experts, who develop specific techniques to extract and visualize the flow structures of interest. Interactive visualization approaches allow domain experts to ask the system directly through the visual analytic interface, which provides flexibility to support various tasks. However, in practice, the visual analytic interface may require extra learning effort, which often discourages domain experts and limits its usage in real-world scenarios. In this paper, we propose FlowNL, a novel interactive system with a natural language interface. FlowNL allows users to manipulate the flow visualization system using plain English, which greatly reduces the learning effort. We develop a natural language parser to interpret user intention and translate textual input into a declarative language. We design the declarative language as an intermediate layer between the natural language and the programming language specifically for flow visualization. The declarative language provides selection and composition rules to derive relatively complicated flow structures from primitive objects that encode various kinds of information about scalar fields, flow patterns, regions of interest, connectivities, etc. We demonstrate the effectiveness of FlowNL using multiple usage scenarios and an empirical evaluation.

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 (TH_EX), maximum helical volume (HV_max), accumulated helical volume (HV_acc), accumulated helical volume length (HVL_acc), maximum forward velocity (maxV_for), maximum circumferential velocity (maxV_circ), 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 maxV_for 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 maxV_for and age- and gender-independent normal values regarding TH_EX, HV_max, HV_acc, HVL_acc, RD and _maxV_circ.

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.

A Review of Three-Dimensional Medical Image Visualization

Importance. Medical images are essential for modern medicine and an important research subject in visualization. However, medical experts are often not aware of the many advanced three-dimensional (3D) medical image visualization techniques that could increase their capabilities in data analysis and assist the decision-making process for specific medical problems. Our paper provides a review of 3D visualization techniques for medical images, intending to bridge the gap between medical experts and visualization researchers.Highlights. Fundamental visualization techniques are revisited for various medical imaging modalities, from computational tomography to diffusion tensor imaging, featuring techniques that enhance spatial perception, which is critical for medical practices. The state-of-the-art of medical visualization is reviewed based on a procedure-oriented classification of medical problems for studies of individuals and populations. This paper summarizes free software tools for different modalities of medical images designed for various purposes, including visualization, analysis, and segmentation, and it provides respective Internet links.Conclusions. Visualization techniques are a useful tool for medical experts to tackle specific medical problems in their daily work. Our review provides a quick reference to such techniques given the medical problem and modalities of associated medical images. We summarize fundamental techniques and readily available visualization tools to help medical experts to better understand and utilize medical imaging data. This paper could contribute to the joint effort of the medical and visualization communities to advance precision medicine.

Four-dimensional flow cardiovascular magnetic resonance in tetralogy of Fallot: a systematic review

BACKGROUND

Patients with repaired Tetralogy of Fallot (rTOF) often develop cardiovascular dysfunction and require regular imaging to evaluate deterioration and time interventions such as pulmonary valve replacement. Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) enables detailed assessment of flow characteristics in all chambers and great vessels. We performed a systematic review of intra-cardiac 4D flow applications in rTOF patients, to examine clinical utility and highlight optimal methods for evaluating rTOF patients.

METHODS

A comprehensive literature search was undertaken in March 2020 on Google Scholar and Scopus. A modified version of the Critical Appraisal Skills Programme (CASP) tool was used to assess and score the applicability of each study. Important clinical outcomes were assessed including similarities and differences.

RESULTS

Of the 635 articles identified, 26 studies met eligibility for systematic review. None of these were below 59% applicability on the modified CASP score. Studies could be broadly classified into four groups: (i) pilot studies, (ii) development of new acquisition methods, (iii) validation and (vi) identification of novel flow features. Quantitative comparison with other modalities included 2D phase contrast CMR (13 studies) and echocardiography (4 studies). The 4D flow study applications included stroke volume (18/26;69%), regurgitant fraction (16/26;62%), relative branch pulmonary artery flow(4/26;15%), systolic peak velocity (9/26;35%), systemic/pulmonary total flow ratio (6/26;23%), end diastolic and end systolic volume (5/26;19%), kinetic energy (5/26;19%) and vorticity (2/26;8%).

CONCLUSIONS

4D flow CMR shows potential in rTOF assessment, particularly in retrospective valve tracking for flow evaluation, velocity profiling, intra-cardiac kinetic energy quantification, and vortex visualization. Protocols should be targeted to pathology. Prospective, randomized, multi-centered studies are required to validate these new characteristics and establish their clinical use.

Automated Quantitative Extraction and Analysis of 4D flow Patterns in the Ascending Aorta: An intraindividual comparison at 1.5 T and 3 T

4D flow MRI enables quantitative assessment of helical flow. Current methods are susceptible to noise. To evaluate helical flow patterns in healthy volunteers and patients with bicuspid aortic valves (BAV) at 1.5 T and 3 T using pressure-based helix-extraction in 4D flow MRI. Two intraindividual 4D flow MRI examinations were performed at 1.5 T and 3 T in ten healthy volunteers (5 females, 32 ± 3 years) and 2 patients with BAV using different acceleration techniques (kt-GRAPPA and centra). Several new quantitative parameters for the evaluation of volumes [ml], lengths [mm] as well as temporal parameters [ms] of helical flow were introduced and analyzed using the software tool Bloodline. We found good correlations between measurements in volunteers at 1.5 T and 3 T regarding helical flow volumes (R = 0.98) and temporal existence (R = 0.99) of helices in the ascending aorta. Furthermore, we found significantly larger (11.7 vs. 77.6 ml) and longer lasting (317 vs. 769 ms) helices in patients with BAV than in volunteers. The assessed parameters do not depend on the magnetic field strength used for the acquisition. The technique of pressure-based extraction of 4D flow MRI pattern is suitable for differentiation of normal and pathological flow.

Identification of Vortex Cores in Cerebral Aneurysms on 4D Flow MRI

BACKGROUND AND PURPOSE

The complexity and instability of the vortex flow in aneurysms are factors related to the rupture risk of unruptured cerebral aneurysms. We identified aneurysm vortex cores on 4D flow MR imaging and examined the relationship of these factors with the characteristics of cerebral aneurysms.

MATERIALS AND METHODS

We subjected 40 aneurysms (37 unruptured, 3 ruptured) to 4D flow MR imaging. We visualized streamlines with velocities below the threshold-that is, a percentage value of the aneurysm maximum inflow velocity-and progressively decreased the threshold to identify vortex cores as thin, streamline bundles with minimum velocities. Complexity and stability were compared in aneurysms with a smooth surface and those with blebs or daughter sacs.

RESULTS

The threshold for visualizing vortex cores ranged from 3% to 13% of the maximum inflow velocity. Vortex cores could be visualized in 38 aneurysms; in 2, they were not visualized through the cardiac cycle. A simple flow pattern (single vortex core) was identified in 27 aneurysms; the other 13 exhibited a complex flow pattern. The cores were stable in 32 and unstable in 8 aneurysms. Significantly more aneurysms with-than-without blebs or daughter sacs had a complex flow pattern (P = .006). Of the 3 ruptured aneurysms, 1 aneurysm had an unstable vortex core; in the other 2, the vortex core was not visualized.

CONCLUSIONS

The identification of vortex cores on 4D flow MR imaging may help to stratify the rupture risk of unruptured cerebral aneurysms.

Classification of Blood Flow Patterns in Cerebral Aneurysms

We present a Cerebral Aneurysm Vortex Classification (CAVOCLA) that allows to classify blood flow in cerebral aneurysms. Medical studies assume a strong relation between the progression and rupture of aneurysms and flow patterns. To understand how flow patterns impact the vessel morphology, they are manually classified according to predefined classes. However, manual classifications are time-consuming and exhibit a high inter-observer variability. In contrast, our approach is more objective and faster than manual methods. The classification of integral lines, representing steady or unsteady blood flow, is based on a mapping of the aneurysm surface to a hemisphere by calculating polar-based coordinates. The lines are clustered and for each cluster a representative is calculated. Then, the polar-based coordinates are transformed to the representative as basis for the classification. Classes are based on the flow complexity. The classification results are presented by a detail-on-demand approach using a visual transition from the representative over an enclosing surface to the associated lines. Based on seven representative datasets, we conduct an informal interview with five domain experts to evaluate the system. They confirmed that CAVOCLA allows for a robust classification of intra-aneurysmal flow patterns. The detail-on-demand visualization enables an efficient exploration and interpretation of flow patterns.

Comparison of two accelerated 4D-flow sequences for aortic flow quantification

To compare two broadly used 4D-flow- with a 2D-flow-sequence in healthy volunteers, regarding absolute flow parameters, image quality (IQ), and eddy current correction (ECC). Forty volunteers (42 ± 11.8 years, 22 females) were examined with a 3T scanner. Thoracic aortic flow was assessed using a 3D-T2w-SPACE-STIR-sequence for morphology and two accelerated 4D-flow sequences for comparison, one with k-t undersampling and one with standard GRAPPA parallel-imaging. 2D-flow was used as reference standard. The custom-made software tool Bloodline enabled flow measurements for all analyses at the same location. Quantitative flow analyses were performed with and without ECC. One reader assessed pathline IQ (IQ-PATH) and occurrence of motion artefacts (IQ-ART) on a 3-point grading scale, the higher the better. k-t GRAPPA allowed a significant mean scan time reduction of 46% (17:56 ± 5:26 min vs. 10:40 ± 3:15 min) and provided significantly fewer motion artefacts than standard GRAPPA (IQ-ART 1.57 ± 0.55 vs. 0.84 ± 0.48; p < 0.001). Neither 4D-flow sequence significantly differed in flow volume nor peak velocity results with or without ECC. Nevertheless, the correlation between both 4D-flow sequences and 2D-flow was better with ECC; the k-t GRAPPA sequence performed best (R = 0.96 vs. 0.90). k-t GRAPPA 4D-flow was not inferior to a standard GRAPPA-sequence, showed fewer artefacts, comparable IQ and was almost two-fold faster.

Validation of two accelerated 4D flow MRI sequences at 3 T: a phantom study

Background

Four-dimensional (4D) flow magnetic resonance imaging (MRI) sequences with advanced parallel imaging have the potential to reduce scan time with equivalent image quality and accuracy compared with standard two-dimensional (2D) flow MRI. We compared 4D flow to standard 2D flow sequences using a constant and pulsatile flow phantom at 3 T.

Methods

Two accelerated 4D flow sequences (GRAPPA2 and k-t-GRAPPA5) were evaluated regarding the concordance of flow volumes, flow velocities, and reproducibility as well as dependency on measuring plane and velocity encoding (V_enc). The calculated flow volumes and peak velocities of the phantom were used as reference standard. Flow analysis was performed using the custom-made software “Bloodline”.

Results

No significant differences in flow volume were found between the 2D, both 4D flow MRI sequences, and the pump reference (p = 0.994) or flow velocities (p = 0.998) in continuous and pulsatile flow. An excellent correlation (R = 0.99–1.0) with a reference standard and excellent reproducibility of measurements (R = 0.99) was achieved for all sequences. A V_enc overestimated by up to two times had no impact on flow measurements. However, misaligned measuring planes led to an increasing underestimation of flow volume and mean velocity in 2D flow accuracy, while both 4D flow measurements were not affected. Scan time was significantly shorter for k-t-GRAPPA5 (1:54 ± 0:01 min, mean ± standard deviation) compared to GRAPPA2 (3:56 ± 0:02 min) (p = 0.002).

Conclusions

Both 4D flow sequences demonstrated equal agreement with 2D flow measurements, without impact of V_enc overestimation and plane misalignment. The highly accelerated k-t-GRAPPA5 sequence yielded results similar to those of GRAPPA2.

Vortical features for myocardial rotation assessment in hypertrophic cardiomyopathy using cardiac tagged magnetic resonance

Left ventricular rotational motion is a feature of normal and diseased cardiac function. However, classical torsion and twist measures rely on the definition of a rotational axis which may not exist. This paper reviews global and local rotation descriptors of myocardial motion and introduces new curl-based (vortical) features built from tensorial magnitudes, intended to provide better comprehension about fibrotic tissue characteristics mechanical properties. Fifty-six cardiomyopathy patients and twenty-two healthy volunteers have been studied using tagged magnetic resonance by means of harmonic phase analysis. Rotation descriptors are built, with no assumption about a regular geometrical model, from different approaches. The extracted vortical features have been tested by means of a sequential cardiomyopathy classification procedure; they have proven useful for the regional characterization of the left ventricular function by showing great separability not only between pathologic and healthy patients but also, and specifically, between heterogeneous phenotypes within cardiomyopathies.

Combined Visualization of Vessel Deformation and Hemodynamics in Cerebral Aneurysms

We present the first visualization tool that combines patient-specific hemodynamics with information about the vessel wall deformation and wall thickness in cerebral aneurysms. Such aneurysms bear the risk of rupture, whereas their treatment also carries considerable risks for the patient. For the patient-specific rupture risk evaluation and treatment analysis, both morphological and hemodynamic data have to be investigated. Medical researchers emphasize the importance of analyzing correlations between wall properties such as the wall deformation and thickness, and hemodynamic attributes like the Wall Shear Stress and near-wall flow. Our method uses a linked 2.5D and 3D depiction of the aneurysm together with blood flow information that enables the simultaneous exploration of wall characteristics and hemodynamic attributes during the cardiac cycle. We thus offer medical researchers an effective visual exploration tool for aneurysm treatment risk assessment. The 2.5D view serves as an overview that comprises a projection of the vessel surface to a 2D map, providing an occlusion-free surface visualization combined with a glyph-based depiction of the local wall thickness. The 3D view represents the focus upon which the data exploration takes place. To support the time-dependent parameter exploration and expert collaboration, a camera path is calculated automatically, where the user can place landmarks for further exploration of the properties. We developed a GPU-based implementation of our visualizations with a flexible interactive data exploration mechanism. We designed our techniques in collaboration with domain experts, and provide details about the evaluation.

Vortex Analysis of Intra-Aneurismal Flow in Cerebral Aneurysms

This study aims to develop an alternative vortex analysis method by measuring structure ofIntracranial aneurysm (IA) flow vortexes across the cardiac cycle, to quantify temporal stability of aneurismal flow. Hemodynamics were modeled in “patient-specific” geometries, using computational fluid dynamics (CFD) simulations. Modified versions of known λ₂ and Q-criterion methods identified vortex regions; then regions were segmented out using the classical marching cube algorithm. Temporal stability was measured by the degree of vortex overlap (DVO) at each step of a cardiac cycle against a cycle-averaged vortex and by the change in number of cores over the cycle. No statistical differences exist in DVO or number of vortex cores between 5 terminal IAs and 5 sidewall IAs. No strong correlation exists between vortex core characteristics and geometric or hemodynamic characteristics of IAs. Statistical independence suggests this proposed method may provide novel IA information. However, threshold values used to determine the vortex core regions and resolution of velocity data influenced analysis outcomes and have to be addressed in future studies. In conclusions, preliminary results show that the proposed methodology may help give novel insight toward aneurismal flow characteristic and help in future risk assessment given more developments.

Volumetric quantification of absolute local normalized helicity in patients with bicuspid aortic valve and aortic dilatation

PURPOSE

Absolute local normalized helicity (LNH) can differentiate flow alterations in the aorta between healthy controls and bicuspid aortic valve (BAV) patients.

METHODS

A total of 65 controls and 50 subjects with BAV underwent in vivo four-dimensional (4D) flow MRI. Data analysis included the three-dimensional (3D) segmentation of the thoracic aorta (ascending aorta, aortic arch, and descending aorta) and calculation of absolute LNH. The mean velocity in the entire aorta was used to identify peak systole, systolic deceleration, and middiastole. A sensitivity analysis was performed to identify the optimal absolute LNH threshold, comparing control and BAV groups. A reproducibility test was performed for 3D segmentation and absolute LNH.

RESULTS

Absolute LNH above 0.6 was significantly higher (P < 0.001) in BAV in comparison to controls for all aortic segments and cardiac time frames. Absolute LNH in the ascending aorta correlated with maximal aortic diameter (R = 0.83, P < 0.001, at peak systole; r = 0.84, P < 0.001, at systolic deceleration; R = 0.88, P < 0.001, at middiastole) and significantly increased (P < 0.001) with aortic stenosis severity. Intra- and interobserver errors were 5 ± 2% and 12 ± 6% for 3D segmentation and 7 ± 6% and 12 ± 7% for absolute LNH.

CONCLUSION

Absolute LNH can differentiate between controls and subjects with aortic dilatation, and was associated with maximal aortic diameter and aortic stenosis severity. Magn Reson Med 78:689-701, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Visualization and Analysis of Rotating Stall for Transonic Jet Engine Simulation

Identification of early signs of rotating stall is essential for the study of turbine engine stability. With recent advancements of high performance computing, high-resolution unsteady flow fields allow in depth exploration of rotating stall and its possible causes. Performing stall analysis, however, involves Significant effort to process large amounts of simulation data, especially when investigating abnormalities across many time steps. In order to assist scientists during the exploration process, we present a visual analytics framework to identify suspected spatiotemporal regions through a comparative visualization so that scientists are able to focus on relevant data in more detail. To achieve this, we propose efficient stall analysis algorithms derived from domain knowledge and convey the analysis results through juxtaposed interactive plots. Using our integrated visualization system, scientists can visually investigate the detected regions for potential stall initiation and further explore these regions to enhance the understanding of this phenomenon. Positive feedback from scientists demonstrate the efficacy of our system in analyzing rotating stall.

Rotation Invariant Vortices for Flow Visualization

We propose a new class of vortex definitions for flows that are induced by rotating mechanical parts, such as stirring devices, helicopters, hydrocyclones, centrifugal pumps, or ventilators. Instead of a Galilean invariance, we enforce a rotation invariance, i.e., the invariance of a vortex under a uniform-speed rotation of the underlying coordinate system around a fixed axis. We provide a general approach to transform a Galilean invariant vortex concept to a rotation invariant one by simply adding a closed form matrix to the Jacobian. In particular, we present rotation invariant versions of the well-known Sujudi-Haimes, Lambda-2, and Q vortex criteria. We apply them to a number of artificial and real rotating flows, showing that for these cases rotation invariant vortices give better results than their Galilean invariant counterparts.

Cluster Analysis of Vortical Flow in Simulations of Cerebral Aneurysm Hemodynamics

Computational fluid dynamic (CFD) simulations of blood flow provide new insights into the hemodynamics of vascular pathologies such as cerebral aneurysms. Understanding the relations between hemodynamics and aneurysm initiation, progression, and risk of rupture is crucial in diagnosis and treatment. Recent studies link the existence of vortices in the blood flow pattern to aneurysm rupture and report observations of embedded vortices -a larger vortex encloses a smaller one flowing in the opposite direction -whose implications are unclear. We present a clustering-based approach for the visual analysis of vortical flow in simulated cerebral aneurysm hemodynamics. We show how embedded vortices develop at saddle-node bifurcations on vortex core lines and convey the participating flow at full manifestation of the vortex by a fast and smart grouping of streamlines and the visualization of group representatives. The grouping result may be refined based on spectral clustering generating a more detailed visualization of the flow pattern, especially further off the core lines. We aim at supporting CFD engineers researching the biological implications of embedded vortices.

Quantitative Analysis of Vortical Blood Flow in the Thoracic Aorta Using 4D Phase Contrast MRI

Introduction

Phase contrast MRI allows for the examination of complex hemodynamics in the heart and adjacent great vessels. Vortex flow patterns seem to play an important role in certain vascular pathologies. We propose two- and three-dimensional metrics for the objective quantification of aortic vortex blood flow in 4D phase contrast MRI.

Materials and Methods

For two-dimensional vorticity assessment, a standardized set of 6 regions-of-interest (ROIs) was defined throughout the course of the aorta. For each ROI, a heatmap of time-resolved vorticity values ω→=∇v→ was computed. Evolution of minimum, maximum, and average values as well as opposing rotational flow components were analyzed. For three-dimensional analysis, vortex core detection was implemented combining the predictor-corrector method with λ₂ correction. Strength, elongation, and radial expansion of the detected vortex core were recorded over time. All methods were applied to 4D flow MRI datasets of 9 healthy subjects, 2 patients with mildly dilated aorta, and 1 patient with aortic aneurysm.

Results

Vorticity quantification in the 6 standardized ROIs enabled the description of physiological vortex flow in the healthy aorta. Helical flow developed early in the ascending aorta (absolute vorticity = 166.4±86.4 s^-1 at 12% of cardiac cycle) followed by maximum values in mid-systole in the aortic arch (240.1±45.2 s^-1 at 16%). Strength, elongation, and radial expansion of 3D vortex cores escalated in early systole, reaching a peak in mid systole (strength = 241.2±30.7 s^-1 at 17%, elongation = 65.1±34.6 mm at 18%, expansion = 80.1±48.8 mm² at 20%), before all three parameters similarly decreased to overall low values in diastole. Flow patterns were considerably altered in patient data: Vortex flow developed late in mid/end-systole close to the aortic bulb and no physiological helix was found in the aortic arch.

Conclusions

We have introduced objective measures for quantification of vortical flow in 4D phase contrast MRI. Vortex blood flow in the thoracic aorta could be consistently described in all healthy volunteers. In patient data, pathologically altered vortex flow was observed.

Automatic extraction of three-dimensional thoracic aorta geometric model from phase contrast MRI for morphometric and hemodynamic characterization

PURPOSE

To propose and assess a new method that automatically extracts a three-dimensional (3D) geometric model of the thoracic aorta (TA) from 3D cine phase contrast MRI (PCMRI) acquisitions.

METHODS

The proposed method is composed of two steps: segmentation of the TA and creation of the 3D geometric model. The segmentation algorithm, based on Level Set, was set and applied to healthy subjects acquired in three different modalities (with and without SENSE reduction factors). Accuracy was evaluated using standard quality indices. The 3D model is characterized by the vessel surface mesh and its centerline; the comparison of models obtained from the three different datasets was also carried out in terms of radius of curvature (RC) and average tortuosity (AT).

RESULTS

In all datasets, the segmentation quality indices confirmed very good agreement between manual and automatic contours (average symmetric distance < 1.44 mm, DICE Similarity Coefficient > 0.88). The 3D models extracted from the three datasets were found to be comparable, with differences of less than 10% for RC and 11% for AT.

CONCLUSION

Our method was found effective on PCMRI data to provide a 3D geometric model of the TA, to support morphometric and hemodynamic characterization of the aorta.

Predicate-Based Focus-and-Context Visualization for 3D Ultrasound

Direct volume visualization techniques offer powerful insight into volumetric medical images and are part of the clinical routine for many applications. Up to now, however, their use is mostly limited to tomographic imaging modalities such as CT or MRI. With very few exceptions, such as fetal ultrasound, classic volume rendering using one-dimensional intensity-based transfer functions fails to yield satisfying results in case of ultrasound volumes. This is particularly due its gradient-like nature, a high amount of noise and speckle, and the fact that individual tissue types are rather characterized by a similar texture than by similar intensity values. Therefore, clinicians still prefer to look at 2D slices extracted from the ultrasound volume. In this work, we present an entirely novel approach to the classification and compositing stage of the volume rendering pipeline, specifically designed for use with ultrasonic images. We introduce point predicates as a generic formulation for integrating the evaluation of not only low-level information like local intensity or gradient, but also of high-level information, such as non-local image features or even anatomical models. Thus, we can successfully filter clinically relevant from non-relevant information. In order to effectively reduce the potentially high dimensionality of the predicate configuration space, we propose the predicate histogram as an intuitive user interface. This is augmented by a scribble technique to provide a comfortable metaphor for selecting predicates of interest. Assigning importance factors to the predicates allows for focus-and-context visualization that ensures to always show important (focus) regions of the data while maintaining as much context information as possible. Our method naturally integrates into standard ray casting algorithms and yields superior results in comparison to traditional methods in terms of visualizing a specific target anatomy in ultrasound volumes.