A Predictive Method for Human Carotid Plaque Rupture Using In Vivo Serial MRI With Follow-Up Scan Showing Actual Rupture and MRI-Based 3D Models With Fluid-Structure Interactions

2011 ◽  
Author(s):  
Zheyang Wu ◽  
Chun Yang ◽  
Dalin Tang
Keyword(s):  
Atherosclerotic Plaque ◽  
Carotid Plaque ◽  
Plaque Rupture ◽  
3D Models ◽  
Mechanical Analysis ◽  
Predictive Method ◽  
Magnetic Resonance Imaging Mri ◽  
Serial Mri

It has been hypothesized that mechanical risk factors may be used to predict future atherosclerotic plaque rupture. Much progress has been made in computational modeling, medical imaging, and mechanical analysis for atherosclerotic plaque vulnerability assessment in recent years [1–2]. However, truly predictive methods to predict plaque rupture are currently lacking in the literature and practice. In this paper, we introduce a procedure using computational and statistical models based on serial magnetic resonance imaging (MRI) to quantify sensitivity and specificity of mechanical predictors and their combinations to identify the best candidate for rupture prediction. Serial MRI of carotid plaque from a patient with follow-up scan showing ulceration (rupture) was acquired and the actual appearance of ulceration was used as “gold standard” and validation for the predictive method.

scholarly journals In Vivo Serial MRI-Based Models and Statistical Methods to Quantify Sensitivity and Specificity of Mechanical Predictors for Carotid Plaque Rupture: Location and Beyond

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Zheyang Wu ◽  
Chun Yang ◽  
Dalin Tang
Keyword(s):  
Sensitivity And Specificity ◽  
Statistical Models ◽  
Carotid Plaque ◽  
Large Scale ◽  
Plaque Rupture ◽  
Maximum Shear Stress ◽  
Risk Indicators ◽  
Serial Mri

It has been hypothesized that mechanical risk factors may be used to predict future atherosclerotic plaque rupture. Truly predictive methods for plaque rupture and methods to identify the best predictor(s) from all the candidates are lacking in the literature. A novel combination of computational and statistical models based on serial magnetic resonance imaging (MRI) was introduced to quantify sensitivity and specificity of mechanical predictors to identify the best candidate for plaque rupture site prediction. Serial in vivo MRI data of carotid plaque from one patient was acquired with follow-up scan showing ulceration. 3D computational fluid-structure interaction (FSI) models using both baseline and follow-up data were constructed and plaque wall stress (PWS) and strain (PWSn) and flow maximum shear stress (FSS) were extracted from all 600 matched nodal points (100 points per matched slice, baseline matching follow-up) on the lumen surface for analysis. Each of the 600 points was marked “ulcer” or “nonulcer” using follow-up scan. Predictive statistical models for each of the seven combinations of PWS, PWSn, and FSS were trained using the follow-up data and applied to the baseline data to assess their sensitivity and specificity using the 600 data points for ulcer predictions. Sensitivity of prediction is defined as the proportion of the true positive outcomes that are predicted to be positive. Specificity of prediction is defined as the proportion of the true negative outcomes that are correctly predicted to be negative. Using probability 0.3 as a threshold to infer ulcer occurrence at the prediction stage, the combination of PWS and PWSn provided the best predictive accuracy with (sensitivity, specificity) = (0.97, 0.958). Sensitivity and specificity given by PWS, PWSn, and FSS individually were (0.788, 0.968), (0.515, 0.968), and (0.758, 0.928), respectively. The proposed computational-statistical process provides a novel method and a framework to assess the sensitivity and specificity of various risk indicators and offers the potential to identify the optimized predictor for plaque rupture using serial MRI with follow-up scan showing ulceration as the gold standard for method validation. While serial MRI data with actual rupture are hard to acquire, this single-case study suggests that combination of multiple predictors may provide potential improvement to existing plaque assessment schemes. With large-scale patient studies, this predictive modeling process may provide more solid ground for rupture predictor selection strategies and methods for image-based plaque vulnerability assessment.

3D In Vivo IVUS-Based Anisotropic FSI Models With Cyclic Bending for Human Coronary Atherosclerotic Plaque Mechanical Analysis

2009 ◽  
Author(s):  
Dalin Tang ◽  
Chun Yang ◽  
Jie Zheng ◽  
Pamela K. Woodard ◽  
Kristen Billiar ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Computational Models ◽  
Material Model ◽  
3D Models ◽  
Mechanical Analysis ◽  
Intraplaque Hemorrhage ◽  
Plaque Vulnerability ◽  
Cardiovascular Research ◽  
Cyclic Bending

Assessing atherosclerotic plaque vulnerability based on limited in vivo patient data has been a major challenge in cardiovascular research and clinical practice. Considerable advances in medical imaging technology have been made in recent years to identify vulnerable atherosclerotic carotid plaques in vivo with information about plaque components including lipid-rich necrotic pools, calcification, intraplaque hemorrhage, loose matrix, thrombosis, and ulcers, subject to resolution limitations of current technology [1]. Image-based computational models have also been developed which combine mechanical analysis with image technology aiming for more accurate assessment of plaque vulnerability and better diagnostic and treatment decisions [2]. However, 3D models with fluid-structure interactions (FSI), cyclic bending and anisotropic properties based on in vivo IVUS images for human coronary atherosclerotic plaques are lacking in the current literature. In this paper, we introduce 3D FSI models based on in vivo IVUS images to perform mechanical analysis for human coronary plaques. Cyclic bending is included to represent deformation caused by cardiac motion. An anisotropic material model was used for the vessel so that the models would be more realistic for more accurate computational flow and stress/strain predictions.

Differentiation of Vulnerable Carotid Plaques by Analysis of Calcium Content and Spectral Curve Slope using Gemstone Spectral Imaging

2021 ◽  
Author(s):  
Ze-Xin Fan ◽  
Xiao-Qing Li ◽  
Ting-Ting Yang ◽  
Shao-Jie Yuan ◽  
Tian-Tong Niu ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Carotid Plaque ◽  
Spectral Curve ◽  
Plaque Rupture ◽  
Spectral Imaging ◽  
Calcium Content ◽  
Carotid Atherosclerotic Plaque ◽  
Close Link ◽  
Gemstone Spectral Imaging ◽  
Hs Crp

Abstract Growing evidence indicates that vulnerable carotid plaque rupture is an important cause of stroke. However, fewer studies have been conducted to investigate the role of a novel gemstone spectral imaging (GSI) in assessment of vulnerable carotid plaque. In this study, we analyzed GSI data including calcium content of carotid atherosclerotic plaque and spectral curve slope, as well as serum high-sensitivity C-reactive protein (Hs-CRP), monocyte chemotactic protein-1 (MCP-1) levels in patients with carotid atherosclerotic plaque using the GSI-computed tomographic angiography (CTA) and immunoturbidimetry. The patients with unstable plaques demonstrated a significantly lower calcium content and higher spectral curve slope than the stable plaques group. In addition, the patients with unstable plaque showed an increase in Hs-CRP levels and MCP-1 levels compared with the stable plaque and normal controls (NC) group. The alternation in GSI calcium content and spectral curve slope reflects a close link between calcification and plaque instability, while derangement of Hs-CRP and MCP-1 is involved in the formation or development of vulnerable plaques. Taken together, our results strongly support the feasibility of using these serological and newly discovered imaging parameters as multiple potential biomarkers relevant to plaque vulnerability or stroke progression.

scholarly journals Advanced human carotid plaque progression correlates positively with flow shear stress using follow-up scan data: An in vivo MRI multi-patient 3D FSI study

2010 ◽  
Vol 43 (13) ◽  
pp. 2530-2538 ◽  
Author(s):  
Chun Yang ◽  
Gador Canton ◽  
Chun Yuan ◽  
Marina Ferguson ◽  
Thomas S. Hatsukami ◽  
...  
Keyword(s):  
Shear Stress ◽  
Carotid Plaque ◽  
Plaque Progression ◽  
Flow Shear ◽  
Flow Shear Stress ◽  
Scan Data ◽  
Human Carotid

Human Carotid Atherosclerotic Plaque Growth Function and Progression Simulation Using Meshless GFD and Statistical Methods Based on Multi-Year In Vivo MRI

2008 ◽  
Author(s):  
Chun Yang ◽  
Joseph D. Petruccelli ◽  
Zhongzhao Teng ◽  
Chun Yuan ◽  
Gador Canton ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Wall Thickness ◽  
Vessel Wall ◽  
Plaque Rupture ◽  
Patient Specific ◽  
Tracking Data ◽  
Plaque Progression ◽  
Vessel Wall Thickness ◽  
Plaque Growth

Atherosclerotic plaque rupture and progression have been the focus of intensive investigations in recent years. The mechanisms governing plaque progression and rupture process are not well understood. Using computational models based on patient-specific multi-year in vivo MRI data, our recent results indicated that 18 out of 21 patients studied showed significant negative correlation between plaque progression measured by vessel wall thickness increase (WTI) and plaque wall (structural) stress (PWS) [1]. In this paper, a computational procedure based on meshless generalized finite difference (MGFD) method and serial magnetic resonance imaging (MRI) data was introduced to simulate plaque progression. Participating patients were scanned three times (T1, T2, and T3, at intervals of approximately 18 months) to obtain plaque progression data. Vessel wall thickness (WT) changes were used as the measure for plaque progression. Starting from T2 plaque geometry, plaque progression was simulated by solving the solid model and adjusting wall thickness using plaque growth functions iteratively until time T3 is reached. Numerically simulated plaque progression showed very good agreement with actual plaque geometry at T3 given by MRI data. We believe this is the first time plaque progression simulation results based on multi-year patient-tracking data are reported. Multi-year tracking data and MRI-based progression simulation add time dimension to plaque vulnerability assessment and will improve prediction accuracy.

Computational Plaque Vulnerability Index for Atherosclerotic Carotid Plaque Assessment Based on In Vivo MR-Image

2008 ◽  
Author(s):  
Zhongzhao Teng ◽  
Xueying Huang ◽  
Chun Yuan ◽  
Gador Canton ◽  
Fei Liu ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Carotid Plaque ◽  
Vulnerability Index ◽  
Carotid Atherosclerotic Plaque ◽  
Plaque Vulnerability ◽  
Mr Image ◽  
Noninvasive Methods ◽  
Screening And Diagnosis

Carotid atherosclerotic plaque (CAP) may rupture without warning and cause acute cardiovascular syndromes such as stroke, which is the No.3 killer in USA and a leading cause of serious disabilities. Available screening and diagnosis techniques are insufficient to identify those victims before the event occurs. Noninvasive methods to identify new and emerging biomarkers to assess plaque vulnerability and predict possible rupture before the fatal event are urgently called for.

Stress analysis of carotid plaque rupture based on in vivo high resolution MRI

2006 ◽  
Vol 39 (14) ◽  
pp. 2611-2622 ◽  
Author(s):  
Zhi-Yong Li ◽  
Simon Howarth ◽  
Rikin A. Trivedi ◽  
Jean M. U-King-Im ◽  
Martin J. Graves ◽  
...  
Keyword(s):  
High Resolution ◽  
Stress Analysis ◽  
Carotid Plaque ◽  
Plaque Rupture ◽  
High Resolution Mri

scholarly journals Imaging of microglial activation in MS using PET: Research use and potential future clinical application

2016 ◽  
Vol 23 (4) ◽  
pp. 496-504 ◽  
Author(s):  
Laura Airas ◽  
Eero Rissanen ◽  
Juha Rinne
Keyword(s):  
Complex Disease ◽  
Treatment Options ◽  
Quantitative Information ◽  
Imaging Biomarkers ◽  
In Vivo Evaluation ◽  
Non Invasive ◽  
Positron Emission ◽  
Magnetic Resonance Imaging Mri

Multiple sclerosis (MS) is a complex disease, where several processes can be selected as a target for positron emission topography (PET) imaging. Unlike magnetic resonance imaging (MRI), PET provides specific and quantitative information, and unlike neuropathology, it can be non-invasively applied to living patients, which enables longitudinal follow-up of the MS pathology. In the study of MS, PET can be useful for in vivo evaluation of specific pathological characteristics at various stages of the disease. Increased understanding of the progressive MS pathology will enhance the treatment options of this undertreated condition. The ultimate goal of developing and expanding PET in the study of MS is to have clinical non-invasive in vivo imaging biomarkers of neuroinflammation that will help to establish prognosis and accurately measure response to therapeutics. This topical review provides an overview of the promises and challenges of the use of PET in MS.

scholarly journals Development of a Collagen Fibre Remodelling Rupture Risk Metric for Potentially Vulnerable Carotid Artery Atherosclerotic Plaques

2021 ◽  
Vol 12 ◽  
Author(s):  
Milad Ghasemi ◽  
Robert D. Johnston ◽  
Caitríona Lally
Keyword(s):  
Carotid Artery ◽  
Atherosclerotic Plaque ◽  
Mechanical Response ◽  
Plaque Rupture ◽  
Collagen Fibre ◽  
Local Stress ◽  
Patient Specific ◽  
Collagen Fibres ◽  
Magnetic Resonance Imaging Mri ◽  
Risk Metric

Atherosclerotic plaque rupture in carotid arteries can lead to stroke which is one of the leading causes of death or disability worldwide. The accumulation of atherosclerotic plaque in an artery changes the mechanical properties of the vessel. Whilst healthy arteries can continuously adapt to mechanical loads by remodelling their internal structure, particularly the load-bearing collagen fibres, diseased vessels may have limited remodelling capabilities. In this study, a local stress modulated remodelling algorithm is proposed to explore the mechanical response of arterial tissue to the remodelling of collagen fibres. This stress driven remodelling algorithm is used to predict the optimum distribution of fibres in healthy and diseased human carotid bifurcations obtained using Magnetic Resonance Imaging (MRI). In the models, healthy geometries were segmented into two layers: media and adventitia and diseased into four components: adventitia, media, plaque atheroma and lipid pool (when present in the MRI images). A novel meshing technique for hexahedral meshing of these geometries is also demonstrated. Using the remodelling algorithm, the optimum fibre patterns in various patient specific plaques are identified and the role that deviations from these fibre configurations in plaque vulnerability is shown. This study provides critical insights into the collagen fibre patterns required in carotid artery and plaque tissue to maintain plaque stability.

Stress Analysis of Carotid Atheroma in Transient Ischemic Attack Patients

2009 ◽  
Author(s):  
Hao Gao ◽  
Quan Long ◽  
Martin Graves ◽  
Jonathan H. Gillard ◽  
Zhi-Yong Li
Keyword(s):  
Magnetic Resonance ◽  
Stress Analysis ◽  
Atherosclerotic Plaque ◽  
Transient Ischemic Attack ◽  
Plaque Rupture ◽  
Magnetic Resonance Images ◽  
Patient Specific ◽  
Critical Information ◽  
Ischemic Attack

Rupture of atherosclerotic plaque is a major cause of mortality. Plaque stress analysis, based on patient-specific multi-sequence in vivo magnetic resonance images (MRI), can provide critical information for the understanding of plaque rupture and could eventually lead to plaque rupture prediction [1].

Sign in / Sign up

Export Citation Format

Share Document