Atherosclerosis imaging

ESC CardioMed ◽  
2018 ◽  
pp. 524-528
Author(s):  
Chun Yuan ◽  
Zach Miller ◽  
Jianming Cai
Keyword(s):  
Atherosclerotic Plaque ◽  
Large Scale ◽  
Three Dimensional ◽  
Plaque Imaging ◽  
Fibrous Cap ◽  
Intraplaque Haemorrhage ◽  
Clinical Events ◽  
Flexible Imaging ◽  
Atherosclerosis Imaging

Atherosclerosis imaging goes beyond the simple identification of luminal stenosis. Besides stenosis measurement, there are two main motivations for atherosclerosis imaging: one is to identify the so-called vulnerable plaque, defined as atherosclerotic plaque that poses increased risk of rupture and clinical events, such as heart attack or stroke; the other is to identify ‘positively remodelled’ plaques—plaques that grow outward from the lumen but cause minimal or no stenosis. Cardiovascular magnetic resonance (CMR) has histologically validated capabilities to characterize carotid plaque features in vivo, including a lipid-rich necrotic core, fibrous cap, intraplaque haemorrhage (IPH), calcification, and inflammation. A multicontrast two-dimensional imaging approach has been used in many prospective studies relating baseline CMR characteristics of carotid atherosclerosis with plaque progression and clinical events. These studies have demonstrated the importance of detecting IPH, lipid-rich necrotic cores, and fibrous caps. Building on these findings, a number of three-dimensional CMR techniques have been recently developed that allow higher spatial resolution plaque imaging and easier application clinically with short scan times. Three-dimensional plaque imaging offers flexible imaging plane and view angle analysis, large coverage, multivascular beds capability, and is a fast and cost-effective screening for clinical use. Atherosclerosis imaging has also been applied to detect plaques in other vascular beds such as the coronary artery, intracranial artery, and peripheral artery, although each bed comes with unique imaging needs. Large-scale studies are needed to determine the impact of atherosclerotic plaque CMR on patient outcomes.

Intra-individual comparison of carotid and femoral atherosclerotic plaque features with in vivo MR plaque imaging

2015 ◽  
Vol 31 (8) ◽  
pp. 1611-1618 ◽  
Author(s):  
Andreas Helck ◽  
Nicola Bianda ◽  
Gador Canton ◽  
Chun Yuan ◽  
Daniel S. Hippe ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Plaque Imaging ◽  
Individual Comparison

Non-invasive imaging of the vulnerable atherosclerotic plaque

2021 ◽  
pp. 467-480
Author(s):  
Rong Bing ◽  
David E. Newby ◽  
Jagat Narula ◽  
Marc R. Dweck
Keyword(s):  
Atherosclerotic Plaque ◽  
Vulnerable Plaque ◽  
Plaque Rupture ◽  
Imaging Techniques ◽  
Risk Scores ◽  
Plaque Imaging ◽  
Vulnerable Atherosclerotic Plaque ◽  
Acute Thrombosis ◽  
Non Invasive ◽  
Clinical Events

Cardiovascular disease remains the leading cause of death globally despite advances in medical therapy and risk stratification; ischaemic heart disease was responsible for an estimated 9.5 million deaths in 2016. To address this ongoing global burden of morbidity and mortality, there is a need for more sophisticated methods of diagnosis and prognostication, above and beyond clinical risk scores alone. The majority of myocardial infarction occurs due to ruptured atherosclerotic plaque, leading to acute thrombosis and coronary occlusion. For decades, the concept of the vulnerable plaque—plaques prone to rupture or thrombotic complications—has been central to our understanding of the pathophysiology of acute coronary syndromes. More recently, there has been a shift towards identifying the vulnerable patient through assessment of total atherosclerotic disease burden, in recognition of the fact that most plaque rupture events do not lead to clinical events. Moreover, demonstrating a strong causal link between vulnerable plaques and clinical events has previously proven difficult due to limitations in available invasive and non-invasive imaging modalities. However, we now have an array of imaging techniques that hold great potential for the advancement of vulnerable plaque imaging. These modalities are the subject of state-of-the-art clinical research, aiming to develop the role of atherosclerotic plaque imaging in modern clinical practice and ultimately to improve patient outcomes.

High Resolution Magnetic Resonance Imaging of Resected Plaque

1997 ◽  
Vol 3 (S2) ◽  
pp. 309-310
Author(s):  
D. Saloner
Keyword(s):  
Atherosclerotic Plaque ◽  
Carotid Bifurcation ◽  
Surgical Removal ◽  
Strongly Correlated ◽  
Clinical Events ◽  
Significant Events ◽  
Diseased Vessel ◽  
Clinically Significant ◽  
Substantial Interest

Atherosclerotic plaque at the carotid bifurcation is strongly correlated with the incidence of clinically significant events, such as transient ischemie attacks or stroke. Large multi-center trials have demonstrated that surgical removal of the atheroma is more effective in reducing these clinical events than is medical treatment alone. Patients are selected for surgery from an assessment of the severity of disease at the carotid bifurcation. The measure of disease severity is conventionally taken to be the degree of narrowing of the diseased vessel compared to a normal segment of vessel. However, using this criterion alone, many patients receive endarterectomy surgery who would probably not have progressed to other neurological events, while others are excluded who do progress to neurological events. For this reason, there is substantial interest in methods that could evaluate the composition of the atherosclerotic plaque in vivo, with the hope that this information would improve the predictive power of pre-surgical imaging of the diseased vessel.

scholarly journals High-resolution three-dimensional in vivo imaging of atherosclerotic plaque

1999 ◽  
Vol 42 (4) ◽  
pp. 762-771 ◽  
Author(s):  
Gerard T. Luk-Pat ◽  
Garry E. Gold ◽  
Eric W. Olcott ◽  
Bob S. Hu ◽  
Dwight G. Nishimura
Keyword(s):  
High Resolution ◽  
Atherosclerotic Plaque ◽  
In Vivo Imaging ◽  
Three Dimensional

scholarly journals Segmentation-less, automated vascular vectorization robustly extracts neurovascular network statistics from in vivo two-photon images

2020 ◽  
Author(s):  
Samuel A. Mihelic ◽  
William A. Sikora ◽  
Ahmed M. Hassan ◽  
Michael R. Williamson ◽  
Theresa A. Jones ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Statistical Power ◽  
Large Scale ◽  
Performance Metrics ◽  
Three Dimensional ◽  
Vascular Anatomy ◽  
Input Image ◽  
Network Graph ◽  
Two Photon

AbstractRecent advances in two-photon microscopy (2PM) have allowed large scale imaging and analysis of cortical blood vessel networks in living mice. However, extracting a network graph and vector representations for vessels remain bottlenecks in many applications. Vascular vectorization is algorithmically difficult because blood vessels have many shapes and sizes, the samples are often unevenly illuminated, and large image volumes are required to achieve good statistical power. State-of-the-art, three-dimensional, vascular vectorization approaches require a segmented/binary image, relying on manual or supervised-machine annotation. Therefore, voxel-by-voxel image segmentation is biased by the human annotator/trainer. Furthermore, segmented images oftentimes require remedial morphological filtering before skeletonization/vectorization. To address these limitations, we propose a vectorization method to extract vascular objects directly from unsegmented images. The Segmentation-Less, Automated, Vascular Vectorization (SLAVV) source code in MATLAB is openly available on GitHub. This novel method uses simple models of vascular anatomy, efficient linear filtering, and low-complexity vector extraction algorithms to remove the image segmentation requirement, replacing it with manual or automated vector classification. SLAVV is demonstrated on three in vivo 2PM image volumes of microvascular networks (capillaries, arterioles and venules) in the mouse cortex. Vectorization performance is proven robust to the choice of plasma- or endothelial-labeled contrast, and processing costs are shown to scale with input image volume. Fully-automated SLAVV performance is evaluated on various, simulated 2PM images based on the large, [1.4, 0.9, 0.6] mm input image, and performance metrics show greater robustness to image quality than an intensity-based thresholding approach.

Animal models of atherosclerosis and magnetic resonance imaging for monitoring plaque progression

Vascular ◽  
2014 ◽  
Vol 22 (3) ◽  
pp. 221-237 ◽  
Author(s):  
Antoine Millon ◽  
Emmanuelle Canet-Soulas ◽  
Loic Boussel ◽  
Zahi Fayad ◽  
Philippe Douek
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Animal Models ◽  
Atherosclerotic Plaque ◽  
Atherosclerotic Plaques ◽  
Resonance Imaging ◽  
Human Atherosclerotic Plaque ◽  
Clinical Events ◽  
Vulnerable Plaques

Atherosclerosis, the main cause of heart attack and stroke, is the leading cause of death in most modern countries. Preventing clinical events depends on a better understanding of the mechanism of atherosclerotic plaque destabilization. Our knowledge on the characteristics of vulnerable plaques in humans has grown past decades. Histological studies have provided a precise definition of high-risk lesions and novel imaging methods for human atherosclerotic plaque characterization have made significant progress. However the pathological mechanisms leading from stable lesions to the formation of vulnerable plaques remain uncertain and the related clinical events are unpredictable. An animal model mimicking human plaque destablization is required as well as an in vivo imaging method to assess and monitor atherosclerosis progression. Magnetic resonance imaging (MRI) is increasingly used for in vivo assessment of atherosclerotic plaques in the human carotids. MRI provides well-characterized morphological and functional features of human atherosclerotic plaque which can be also assessed in animal models. This review summarizes the most common species used as animal models for experimental atherosclerosis, the techniques to induce atherosclerosis and to obtain vulnerable plaques, together with the role of MRI for monitoring atherosclerotic plaques in animals.

scholarly journals Nanoanalytical analysis of bisphosphonate-driven alterations of microcalcifications using a 3D hydrogel system and in vivo mouse model

2021 ◽  
Vol 118 (14) ◽  
pp. e1811725118
Author(s):  
Jessica L. Ruiz ◽  
Joshua D. Hutcheson ◽  
Luis Cardoso ◽  
Amirala Bakhshian Nik ◽  
Alexandra Condado de Abreu ◽  
...  
Keyword(s):  
Vascular Calcification ◽  
Cardiovascular Events ◽  
Plaque Rupture ◽  
Three Dimensional ◽  
Element Analysis ◽  
Fibrous Cap ◽  
3D Collagen ◽  
Atherosclerotic Plaque Rupture

Vascular calcification predicts atherosclerotic plaque rupture and cardiovascular events. Retrospective studies of women taking bisphosphonates (BiPs), a proposed therapy for vascular calcification, showed that BiPs paradoxically increased morbidity in patients with prior acute cardiovascular events but decreased mortality in event-free patients. Calcifying extracellular vesicles (EVs), released by cells within atherosclerotic plaques, aggregate and nucleate calcification. We hypothesized that BiPs block EV aggregation and modify existing mineral growth, potentially altering microcalcification morphology and the risk of plaque rupture. Three-dimensional (3D) collagen hydrogels incubated with calcifying EVs were used to mimic fibrous cap calcification in vitro, while an ApoE−/− mouse was used as a model of atherosclerosis in vivo. EV aggregation and formation of stress-inducing microcalcifications was imaged via scanning electron microscopy (SEM) and atomic force microscopy (AFM). In both models, BiP (ibandronate) treatment resulted in time-dependent changes in microcalcification size and mineral morphology, dependent on whether BiP treatment was initiated before or after the expected onset of microcalcification formation. Following BiP treatment at any time, microcalcifications formed in vitro were predicted to have an associated threefold decrease in fibrous cap tensile stress compared to untreated controls, estimated using finite element analysis (FEA). These findings support our hypothesis that BiPs alter EV-driven calcification. The study also confirmed that our 3D hydrogel is a viable platform to study EV-mediated mineral nucleation and evaluate potential therapies for cardiovascular calcification.

scholarly journals Segmentation-Less, Automated, Vascular Vectorization

2021 ◽  
Vol 17 (10) ◽  
pp. e1009451
Author(s):  
Samuel A. Mihelic ◽  
William A. Sikora ◽  
Ahmed M. Hassan ◽  
Michael R. Williamson ◽  
Theresa A. Jones ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Statistical Power ◽  
Large Scale ◽  
Volume Fraction ◽  
Three Dimensional ◽  
Vascular Anatomy ◽  
Input Image ◽  
Segmented Images ◽  
Vessel Networks

Recent advances in two-photon fluorescence microscopy (2PM) have allowed large scale imaging and analysis of blood vessel networks in living mice. However, extracting network graphs and vector representations for the dense capillary bed remains a bottleneck in many applications. Vascular vectorization is algorithmically difficult because blood vessels have many shapes and sizes, the samples are often unevenly illuminated, and large image volumes are required to achieve good statistical power. State-of-the-art, three-dimensional, vascular vectorization approaches often require a segmented (binary) image, relying on manual or supervised-machine annotation. Therefore, voxel-by-voxel image segmentation is biased by the human annotator or trainer. Furthermore, segmented images oftentimes require remedial morphological filtering before skeletonization or vectorization. To address these limitations, we present a vectorization method to extract vascular objects directly from unsegmented images without the need for machine learning or training. The Segmentation-Less, Automated, Vascular Vectorization (SLAVV) source code in MATLAB is openly available on GitHub. This novel method uses simple models of vascular anatomy, efficient linear filtering, and vector extraction algorithms to remove the image segmentation requirement, replacing it with manual or automated vector classification. Semi-automated SLAVV is demonstrated on three in vivo 2PM image volumes of microvascular networks (capillaries, arterioles and venules) in the mouse cortex. Vectorization performance is proven robust to the choice of plasma- or endothelial-labeled contrast, and processing costs are shown to scale with input image volume. Fully-automated SLAVV performance is evaluated on simulated 2PM images of varying quality all based on the large (1.4×0.9×0.6 mm3 and 1.6×108 voxel) input image. Vascular statistics of interest (e.g. volume fraction, surface area density) calculated from automatically vectorized images show greater robustness to image quality than those calculated from intensity-thresholded images.

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