CT-based diagnosis of diffuse coronary artery disease on the basis of scaling power laws.

PURPOSE: To provide proof of concept for a diagnostic method to assess diffuse coronary artery disease (CAD) on the basis of coronary computed tomography (CT) angiography. MATERIALS AND METHODS: The study was approved by the Cleveland Clinic Institutional Review Board, and all subjects gave informed consent. Morphometric data from the epicardial coronary artery tree, determined with CT angiography in 120 subjects (89 patients with metabolic syndrome and 31 age- and sex-matched control subjects) were analyzed on the basis of the scaling power law. Results obtained in patients with metabolic syndrome and control subjects were compared statistically. RESULTS: The mean lumen cross-sectional area (ie, lumen cross-sectional area averaged over each vessel of an epicardial coronary artery tree) and sum of intravascular volume in patients with metabolic syndrome (0.039 cm(2) ± 0.015 [standard deviation] and 2.71 cm(3) ± 1.75, respectively) were significantly less than those in control subjects (0.054 cm(2)± 0.015 and 3.29 cm(3)± 1.77, respectively; P < .05). The length-volume power law showed coefficients of 27.0 cm(-4/3) ± 9.0 (R(2) = 0.91 ± 0.08) for patients with metabolic syndrome and 19.9 cm(-4/3) ± 4.3 (R(2) = 0.92 ± 0.07) for control subjects (P < .05). The probability frequency shows that more than 65% of patients with metabolic syndrome had a coefficient of 23 or more for the length-volume scaling power law, whereas approximately 90% of the control subjects had a coefficient of less than 23. CONCLUSION: The retrospective scaling analysis provides a quantitative rationale for diagnosis of diffuse CAD.

An Interactive Game with Virtual Reality Immersion to Improve Cultural Sensitivity in Health Care.

Purpose: Biased perceptions of individuals who are not part of one's in-groups tend to be negative and habitual. Because health care professionals are no less susceptible to biases than are others, the adverse impact of biases on marginalized populations in health care warrants continued attention and amelioration. Method: Two characters, a Syrian refugee with limited English proficiency and a black pregnant woman with a history of opioid use disorder, were developed for an online training simulation that includes an interactive life course experience focused on social determinants of health, and a clinical encounter in a community health center utilizing virtual reality immersion. Pre- and post-survey data were obtained from 158 health professionals who completed the simulation. Results: Post-simulation data indicated increased feelings of compassion toward the patient and decreased expectations about how difficult future encounters with the patient would be. With respect to attribution, after the simulation participants were less inclined to view the patient as primarily responsible for their situation, suggesting less impact of the fundamental attribution error. Conclusion: This training simulation aimed to utilize components of evidence-based prejudice habit breaking interventions, such as learning more about an individual's life experience to help minimize filling in gaps with stereotyped assumptions. Although training simulations cannot fully replicate or replace the advantages that come with real-world experience, they can heighten awareness in the increase of increasing the cultural sensitivity of clinicians in health care professions for improving health equity.

Ten Open Challenges in Medical Visualization.

The medical domain has been an inspiring application area in visualization research for many years already, but many open challenges remain. The driving forces of medical visualization research have been strengthened by novel developments, for example, in deep learning, the advent of affordable VR technology, and the need to provide medical visualizations for broader audiences. At IEEE VIS 2020, we hosted an Application Spotlight session to highlight recent medical visualization research topics. With this article, we provide the visualization community with ten such open challenges, primarily focused on challenges related to the visualization of medical imaging data. We first describe the unique nature of medical data in terms of data preparation, access, and standardization. Subsequently, we cover open visualization research challenges related to uncertainty, multimodal and multiscale approaches, and evaluation. Finally, we emphasize challenges related to users focusing on explainable AI, immersive visualization, P4 medicine, and narrative visualization.

Multi-Echo Quantitative Susceptibility Mapping for Strategically Acquired Gradient Echo (STAGE) Imaging.

PURPOSE: To develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging. METHODS: The proposed QSM reconstruction algorithm, referred to as "structurally constrained Susceptibility Weighted Imaging and Mapping" scSWIM, performs an ℓ 1 and ℓ 2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The measured susceptibility values from scSWIM for both simulated and in vivo data were compared to the: original susceptibility model (for simulated data only), the multi orientation COSMOS (for in vivo data only), truncated k-space division (TKD), iterative susceptibility weighted imaging and mapping (iSWIM), and morphology enabled dipole inversion (MEDI) algorithms. Goodness of fit was quantified by measuring the root mean squared error (RMSE) and structural similarity index (SSIM). Additionally, scSWIM was assessed in ten healthy subjects. RESULTS: The unique contrast and tissue boundaries from T1WE and iSWIM enable the accurate definition of edges of high susceptibility regions. For the simulated brain model without the addition of microbleeds and calcium, the RMSE was best at 5.21ppb for scSWIM and 8.74ppb for MEDI thanks to the reduced streaking artifacts. However, by adding the microbleeds and calcium, MEDI's performance dropped to 47.53ppb while scSWIM performance remained the same. The SSIM was highest for scSWIM (0.90) and then MEDI (0.80). The deviation from the expected susceptibility in deep gray matter structures for simulated data relative to the model (and for the in vivo data relative to COSMOS) as measured by the slope was lowest for scSWIM + 1%(-1%); MEDI + 2%(-11%) and then iSWIM -5%(-10%). Finally, scSWIM measurements in the basal ganglia of healthy subjects were in agreement with literature. CONCLUSION: This study shows that using a data fidelity term and structural constraints results in reduced noise and streaking artifacts while preserving structural details. Furthermore, the use of STAGE imaging with multi-echo and multi-flip data helps to improve the signal-to-noise ratio in QSM data and yields less artifacts.

Biophysical model of the spatial heterogeneity of myocardial flow.

The blood flow in the myocardium has significant spatial heterogeneity. The objective of this study was to develop a biophysical model based on detailed anatomical data to determine the heterogeneity of regional myocardial flow during diastole. The model predictions were compared with experimental measurements in a diastolic porcine heart in the absence of vessel tone using nonradioactive fluorescent microsphere measurements. The results from the model and experimental measurements showed good agreement. The relative flow dispersion in the arrested, vasodilated heart was found to be 44% and 48% numerically and experimentally, respectively. Furthermore, the flow dispersion was found to have fractal characteristics with fractal dimensions (D) of 1.25 and 1.27 predicted by the model and validated by the experiments, respectively. This validated three-dimensional model of normal diastolic heart will play an important role in elucidating the spatial heterogeneity of coronary blood flow, and serve as a foundation for understanding the interplay between cardiac mechanics and coronary hemodynamics.

Extraction of morphometry and branching angles of porcine coronary arterial tree from CT images.

The morphometry (diameters, length, and angles) of coronary arteries is related to their function. A simple, easy, and accurate image-based method to seamlessly extract the morphometry for coronary arteries is of significant value for understanding the structure-function relation. Here, the morphometry of large (> or = 1 mm in diameter) coronary arteries was extracted from computed tomography (CT) images using a recently validated segmentation algorithm. The coronary arteries of seven pigs were filled with Microfil, and the cast hearts were imaged with CT. The centerlines of the extracted vessels, the vessel radii, and the vessel lengths were identified for over 700 vessel segments. The extraction algorithm was based on a topological analysis of a vector field generated by normal vectors of the extracted vessel wall. The diameters, lengths, and angles of the right coronary artery, left anterior descending coronary artery, and left circumflex artery of all vessels > or = 1 mm in diameter were tabulated for the respective orders. It was found that bifurcations at orders 9-11 are planar ( approximately 90%). The relations between volume and length and area and length were also examined and found to scale as power laws. Furthermore, the bifurcation angles follow the minimum energy hypothesis but with significant scatter. Some of the applications of the semiautomated extraction of morphometric data in applications to coronary physiology and pathophysiology are highlighted.

Hierarchical Image Semantics Using Probabilistic Path Propagations for Biomedical Research.

Image segmentation is an important subtask in biomedical research applications, such as estimating the position and shape of a tumor. Unfortunately, advanced image segmentation methods are not widely applied in research applications as they often miss features, such as uncertainty communication, and may lack an intuitive approach for the use of the underlying algorithm. To solve this problem, this paper fuses a fuzzy and a hierarchical segmentation approach together, thus providing a flexible multiclass segmentation method based on probabilistic path propagations. By utilizing this method, analysts and physicians can map their mental model of image components and their composition to higher level objects. The probabilistic segmentation of higher order components is propagated along the user-defined hierarchy to highlight the potential of improvement resulting in each level of hierarchy by providing an intuitive representation. The effectiveness of this approach is demonstrated by evaluating our segmentations of biomedical datasets, comparing it to the state-of-the-art segmentation approaches, and an extensive user study.

Compensatory Enlargement of Ossabaw Miniature Swine Coronary Arteries in Diffuse Atherosclerosis.

Studies in human and non-human primates have confirmed the compensatory enlargement or positive remodeling (Glagov phenomenon) of coronary vessels in the presence of focal stenosis. To our knowledge, this is the first study to document arterial enlargement in a metabolic syndrome animal model with diffuse coronary artery disease (DCAD) in the absence of severe focal stenosis. Two different groups of Ossabaw miniature pigs were fed a high fat atherogenic diet for 4 months (Group I) and 12 months (Group II), respectively. Group I (6 pigs) underwent contrast enhanced computed tomographic angiography (CCTA) and intravascular ultrasound (IVUS) at baseline and after 4 months of high fat diet, whereas Group II (7 pigs) underwent only IVUS at 12 months of high fat diet. IVUS measurements of the left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries in Group I showed an average increase in their lumen cross-sectional areas (CSA) of 25.8%, 11.4%, and 43.4%, respectively, as compared to baseline. The lumen CSA values of LAD in Group II were found to be between the baseline and 4 months values in Group I. IVUS and CCTA measurements showed a similar trend and positive correlation. Fractional flow reserve (FFR) was 0.91±0.07 at baseline and 0.93±0.05 at 4 months with only 2.2%, 1.6% and 1% stenosis in the LAD, LCX and RCA, respectively. The relation between percent stenosis and lumen CSA shows a classical Glagov phenomenon in this animal model of DCAD.

IVUS validation of patient coronary artery lumen area obtained from CT images.

AIMS: Accurate computed tomography (CT)-based reconstruction of coronary morphometry (diameters, length, bifurcation angles) is important for construction of patient-specific models to aid diagnosis and therapy. The objective of this study is to validate the accuracy of patient coronary artery lumen area obtained from CT images based on intravascular ultrasound (IVUS). METHODS AND RESULTS: Morphometric data of 5 patient CT scans with 11 arteries from IVUS were reconstructed including the lumen cross sectional area (CSA), diameter and length. The volumetric data from CT images were analyzed at sub-pixel accuracy to obtain accurate vessel center lines and CSA. A new center line extraction approach was used where an initial estimated skeleton in discrete value was obtained using a traditional thinning algorithm. The CSA was determined directly without any circular shape assumptions to provide accurate reconstruction of stenosis. The root-mean-square error (RMSE) for CSA and diameter were 16.2% and 9.5% respectively. CONCLUSIONS: The image segmentation and CSA extraction algorithm for reconstruction of coronary arteries proved to be accurate for determination of vessel lumen area. This approach provides fundamental morphometric data for patient-specific models to diagnose and treat coronary artery disease.

Computed tomography-based diagnosis of diffuse compensatory enlargement of coronary arteries using scaling power laws.

Glagov's positive remodelling in the early stages of coronary atherosclerosis often results in plaque rupture and acute events. Because positive remodelling is generally diffused along the epicardial coronary arterial tree, it is difficult to diagnose non-invasively. Hence, the objective of the study is to assess the use of scaling power law for the diagnosis of positive remodelling of coronary arteries based on computed tomography (CT) images. Epicardial coronary arterial trees were reconstructed from CT scans of six Ossabaw pigs fed on a high-fat, high-cholesterol, atherogenic diet for eight months as well as the same number of body-weight-matched farm pigs fed on a lean chow (101.9±16.1 versus 91.5±13.1 kg). The high-fat diet Ossabaw pig model showed diffuse positive remodelling of epicardial coronary arteries. Good fit of measured coronary data to the length-volume scaling power law ( where L(c) and V(c) are crown length and volume) were found for both the high-fat and control groups (R(2) = 0.95±0.04 and 0.99±0.01, respectively). The coefficient, K(LV), decreased significantly in the high-fat diet group when compared with the control (14.6±2.6 versus 40.9±5.6). The flow-length scaling power law, however, was nearly unaffected by the positive remodelling. The length-volume and flow-length scaling power laws were preserved in epicardial coronary arterial trees after positive remodelling. K(LV) < 18 in the length-volume scaling relation is a good index of positive remodelling of coronary arteries. These findings provide a clinical rationale for simple, accurate and non-invasive diagnosis of positive remodelling of coronary arteries, using conventional CT scans.

Vortex visualization in ultra low Reynolds number insect flight.

We present the visual analysis of a biologically inspired CFD simulation of the deformable flapping wings of a dragonfly as it takes off and begins to maneuver, using vortex detection and integration-based flow lines. The additional seed placement and perceptual challenges introduced by having multiple dynamically deforming objects in the highly unsteady 3D flow domain are addressed. A brief overview of the high speed photogrammetry setup used to capture the dragonfly takeoff, parametric surfaces used for wing reconstruction, CFD solver and underlying flapping flight theory is presented to clarify the importance of several unsteady flight mechanisms, such as the leading edge vortex, that are captured visually. A novel interactive seed placement method is used to simplify the generation of seed curves that stay in the vicinity of relevant flow phenomena as they move with the flapping wings. This method allows a user to define and evaluate the quality of a seed's trajectory over time while working with a single time step. The seed curves are then used to place particles, streamlines and generalized streak lines. The novel concept of flowing seeds is also introduced in order to add visual context about the instantaneous vector fields surrounding smoothly animate streak lines. Tests show this method to be particularly effective at visually capturing vortices that move quickly or that exist for a very brief period of time. In addition, an automatic camera animation method is used to address occlusion issues caused when animating the immersed wing boundaries alongside many geometric flow lines. Each visualization method is presented at multiple time steps during the up-stroke and down-stroke to highlight the formation, attachment and shedding of the leading edge vortices in pairs of wings. Also, the visualizations show evidence of wake capture at stroke reversal which suggests the existence of previously unknown unsteady lift generation mechanisms that are unique to quad wing insects.

Validation of image-based method for extraction of coronary morphometry.

An accurate analysis of the spatial distribution of blood flow in any organ must be based on detailed morphometry (diameters, lengths, vessel numbers, and branching pattern) of the organ vasculature. Despite the significance of detailed morphometric data, there is relative scarcity of data on 3D vascular anatomy. One of the major reasons is that the process of morphometric data collection is labor intensive. The objective of this study is to validate a novel segmentation algorithm for semi-automation of morphometric data extraction. The utility of the method is demonstrated in porcine coronary arteries imaged by computerized tomography (CT). The coronary arteries of five porcine hearts were injected with a contrast-enhancing polymer. The coronary arterial tree proximal to 1 mm was extracted from the 3D CT images. By determining the centerlines of the extracted vessels, the vessel radii and lengths were identified for various vessel segments. The extraction algorithm described in this paper is based on a topological analysis of a vector field generated by normal vectors of the extracted vessel wall. With this approach, special focus is placed on achieving the highest accuracy of the measured values. To validate the algorithm, the results were compared to optical measurements of the main trunk of the coronary arteries with microscopy. The agreement was found to be excellent with a root mean square deviation between computed vessel diameters and optical measurements of 0.16 mm (<10% of the mean value) and an average deviation of 0.08 mm. The utility and future applications of the proposed method to speed up morphometric measurements of vascular trees are discussed.

Flow patterns in three-dimensional porcine epicardial coronary arterial tree.

The branching pattern of epicardial coronary arteries is clearly three-dimensional, with correspondingly complex flow patterns. The objective of the present study was to perform a detailed hemodynamic analysis using a three-dimensional finite element method in a left anterior descending (LAD) epicardial arterial tree, including main trunk and primary branches, based on computed tomography scans. The inlet LAD flow velocity was measured in an anesthetized pig, and the outlet pressure boundary condition was estimated based on scaling laws. The spatial and temporal wall shear stress (WSS), gradient of WSS (WSSG), and oscillatory shear index (OSI) were calculated and used to identify regions of flow disturbances in the vicinity of primary bifurcations. We found that low WSS and high OSI coincide with disturbed flows (stagnated, secondary, and reversed flows) opposite to the flow divider and lateral to the junction orifice of the main trunk and primary branches. High time-averaged WSSG occurs in regions of bifurcations, with the flow divider having maximum values. Low WSS and high OSI were found to be related through a power law relationship. Furthermore, zones of low time-averaged WSS and high OSI amplified for larger diameter ratio and high inlet flow rate. Hence, different focal atherosclerotic-prone regions may be explained by different physical mechanism associated with certain critical levels of low WSS, high OSI, and high WSSG, which are strongly affected by the diameter ratio. The implications of the flow patterns for atherogenesis are enumerated.

A novel method for visualization of entire coronary arterial tree.

The complexity of the coronary circulation especially in the deep layers largely evades experimental investigations. Hence, virtual/computational models depicting structure-function relation of the entire coronary vasculature including the deep layer are imperative. In order to interpret such anatomically based models, fast and efficient visualization algorithms are essential. The complexity of such models, which include vessels from the large proximal coronary arteries and veins down to the capillary level (3 orders of magnitude difference in diameter), is a challenging visualization problem since the resulting geometrical representation consists of millions of vessel segments. In this study, a novel method for rendering the entire porcine coronary arterial tree down to the first segments of capillaries interactively is described which employs geometry reduction and occlusion culling techniques. Due to the tree-shaped nature of the vasculature, these techniques exploit the geometrical topology of the object to achieve a faster rendering speed while still handling the full complexity of the data. We found a significant increase in performance combined with a more accurate, gap-less representation of the vessel segments resulting in a more interactive visualization and analysis tool for the entire coronary arterial tree. The proposed techniques can also be applied to similar data structures, such as neuronal trees, airway structures, bile ducts, and other tree-like structures. The utility and future applications of the proposed algorithms are explored.