Peak cap stress calculations in coronary atherosclerotic plaques with an incomplete necrotic core geometry

Mechanical wall stress and wall shear stress are associated with atherosclerosis development in non-calcified coronary segments

BACKGROUND AND AIMS

Atherosclerotic plaque onset and progression are known to be affected by local biomechanical factors. While the role of wall shear stress (WSS) has been studied, the impact of another biomechanical factor, namely mechanical wall stress (MWS), remains poorly understood. In this study, we investigated the association of MWS, independently and combined with WSS, towards atherosclerosis in coronary arteries.

METHODS

Thirty-four human coronary arteries were analyzed using near-infrared spectroscopy intravascular ultrasound (NIRS-IVUS) and optical coherence tomography (OCT) at baseline and after 12 months. Baseline WSS and MWS were calculated using computational models, and wall thickness (ΔWT) and lipid-rich necrotic core size (ΔLRNC) change were measured in non-calcified coronary segments. The arteries were further divided into 1.5 mm/45° sectors and categorized as plaque-free or plaque sectors. For each category, associations between biomechanical factors (WSS & MWS) and changes in coronary wall (ΔWT & ΔLRNC) were studied using linear mixed models.

RESULTS

In plaque-free sectors, higher MWS (p < 0.001) was associated with greater vessel wall growth. Plaque sectors demonstrated wall thickness reduction over time, likely due to medical therapy, where higher levels of WSS and WMS, individually and combined, (p < 0.05) were associated with a greater reduction. Sectors with low MWS combined with high WSS demonstrated the highest LRNC increase (p < 0.01).

CONCLUSIONS

In this study, we investigated the association of the (largely-overlooked) biomechanical factor MWS with coronary atherosclerosis, individually and combined with WSS. Our results demonstrated that both MWS and WSS significantly correlate with atherosclerotic plaque initiation and development.

Coexistence of calcified- and lipid-containing plaque components and their association with incidental rupture points in acute coronary syndrome-causing culprit lesions: results from the prospective OPTICO-ACS study

AIMS

Rupture of the fibrous cap (RFC) represents the main pathophysiological mechanism causing acute coronary syndromes (ACS). Destabilization due to plaque biomechanics is considered to be importantly involved, exact mechanisms triggering plaque ruptures are, however, unknown. This study aims at characterizing the relation between plaque components and rupture points at ACS-causing culprit lesions in a large cohort of ACS-patients assessed by high-resolution intracoronary imaging.

METHODS AND RESULTS

Within the prospective, multicentric OPTICO-ACS study program, the ACS-causing culprit plaques of 282 consecutive patients were investigated following a standardized optical coherence tomography (OCT) imaging protocol. Each pullback was assessed on a frame-by-frame basis for the presence of lipid components (LC), calcium components (CC), and coexistence of both LC and CC (LCC) by two independent OCT-core labs. Of the 282 ACS-patients, 204 patients (72.3%) presented with ACS caused by culprit lesions with rupture of the fibrous cap (RFC-ACS) and 27.7% patients had ACS caused by culprit lesions with intact fibrous cap (IFC-ACS). When comparing RFC-ACS to IFC-ACS, a preferential occurrence of all three plaque components (LC, CC, and LCC) in RFC-ACS became apparent (P < 0.001). Within ruptured culprit lesions, the zone straight at the rupture point [extended rupture zone (RZ)] was characterized by similar (24.7% vs. 24.0%; P = ns) calcium content when compared with the proximal and distal border of the culprit lesion [border zone (BZ)]. The RZ displayed a significantly higher amount of both, LC (100% vs. 69.8%; P < 0.001) and LCC (22.7% vs. 6.8%; P < 0.001), when compared with the BZ. The relative component increase towards the RZ was particularly evident for LCC (+233.8%), while LC showed only a modest increase (+43.3%).

CONCLUSIONS

Calcified- and lipid-containing components characterize ruptured fibrous cap ACS-causing culprit lesions. Their coexistence is accelerated directly at the ruptured point, suggesting a pathophysiological contribution in the development of RFC-ACS.

Multicomponent Mechanical Characterization of Atherosclerotic Human Coronary Arteries: An Experimental and Computational Hybrid Approach

Atherosclerotic plaque rupture in coronary arteries, an important trigger of myocardial infarction, is shown to correlate with high levels of pressure-induced mechanical stresses in plaques. Finite element (FE) analyses are commonly used for plaque stress assessment. However, the required information of heterogenous material properties of atherosclerotic coronaries remains to be scarce. In this work, we characterized the component-wise mechanical properties of atherosclerotic human coronary arteries. To achieve this, we performed ex vivo inflation tests on post-mortem human coronary arteries and developed an inverse FE modeling (iFEM) pipeline, which combined high-frequency ultrasound deformation measurements, a high-field magnetic resonance-based artery composition characterization, and a machine learning-based Bayesian optimization (BO) with uniqueness assessment. By using the developed pipeline, 10 cross-sections from five atherosclerotic human coronary arteries were analyzed, and the Yeoh material model constants of the fibrous intima and arterial wall components were determined. This work outlines the developed pipeline and provides the knowledge of non-linear, multicomponent mechanical properties of atherosclerotic human coronary arteries.

Coronary plaque composition influences biomechanical stress and predicts plaque rupture in a morpho-mechanic OCT analysis

Plaque rupture occurs if stress within coronary lesions exceeds the protection exerted by the fibrous cap overlying the necrotic lipid core. However, very little is known about the biomechanical stress exerting this disrupting force. Employing optical coherence tomography (OCT), we generated plaque models and performed finite-element analysis to simulate stress distributions within the vessel wall in 10 ruptured and 10 non-ruptured lesions. In ruptured lesions, maximal stress within fibrous cap (peak cap stress [PCS]: 174 ± 67 vs. 52 ± 42 kPa, p<0.001) and vessel wall (maximal plaque stress [MPS]: 399 ± 233 vs. 90 ± 95 kPa, p=0.001) were significantly higher compared to non-ruptured plaques. Ruptures arose in the immediate proximity of maximal stress concentrations (angular distances: 21.8 ± 30.3° for PCS vs. 20.7 ± 23.7° for MPS); stress concentrations excellently predicted plaque rupture (area under the curve: 0.940 for PCS, 0.950 for MPS). This prediction of plaque rupture was superior to established vulnerability features such as fibrous cap thickness or macrophage infiltration. In conclusion, OCT-based finite-element analysis effectively assesses plaque biomechanics, which in turn predicts plaque rupture in patients. This highlights the importance of morpho-mechanic analysis assessing the disrupting effects of plaque stress.

Heart attacks are caused by a blockage in arteries that supply oxygen to the heart. This often happens when fatty deposits (or ‘plaques’) that line blood vessels break off and create a clot. To identify individuals most at risk of this occurring, physicians currently use symptoms, family history, blood tests, imaging and surgical procedures. But better methods are needed.

Imaging blockages in the arteries of individuals who died from heart attacks highlighted certain plaque characteristics that increase the risk of a rupture. Further understanding the forces that lead to these fatty deposits breaking off may help scientists to develop improved heart attack prediction methods.

Using patient-specific computer simulations, Milzi et al. show it is possible to predict where plaques are most likely to rupture in an individual, based on biomechanical stresses on the deposits in the artery. The models also showed how forces on the external layers of the plaque played a pivotal role in breakages.

More research is needed to confirm the results of this study and to develop automated ways for measuring the stress exerted on plaques in the arteries. If that research is successful, biomechanical analyses of artery plaques in routine patient assessments may one day allow physicians to predict heart attacks and provide life-saving preventive care.

Optical Coherence Tomography-Based Patient-Specific Residual Multi-Thrombus Coronary Plaque Models With Fluid-Structure Interaction for Better Treatment Decisions: A Biomechanical Modeling Case Study

Intracoronary thrombus from plaque erosion could cause fatal acute coronary syndrome (ACS). A conservative antithrombotic therapy has been proposed to treat ACS patients in lieu of stenting. It is speculated that the residual thrombus after aspiration thrombectomy would influence the prognosis of this treatment. However, biomechanical mechanisms affecting intracoronary thrombus remodeling and clinical outcome remain largely unknown. in vivo optical coherence tomography (OCT) data of a coronary plaque with two residual thrombi after antithrombotic therapy were acquired from an ACS patient with consent obtained. Three OCT-based fluid-structure interaction (FSI) models with different thrombus volumes, fluid-only, and structure-only models were constructed to simulate and compare the biomechanical interplay among blood flow, residual thrombus, and vessel wall mimicking different clinical situations. Our results showed that residual thrombus would decrease coronary volumetric flow rate by 9.3%, but elevate wall shear stress (WSS) by 29.4% and 75.5% at thrombi 1 and 2, respectively. WSS variations in a cardiac cycle from structure-only model were 12.1% and 13.5% higher at the two thrombus surfaces than those from FSI model. Intracoronary thrombi were subjected to compressive forces indicated by negative thrombus stress. Tandem intracoronary thrombus might influence coronary hemodynamics and solid mechanics differently. Computational modeling could be used to quantify biomechanical conditions under which patients could receive patient-specific treatment plan with optimized outcome after antithrombotic therapy. More patient studies with follow-up data are needed to continue the investigation and better understand mechanisms governing thrombus remodeling process.

Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid-structure interaction models and machine learning methods with patient follow-up data: a feasibility study

Background

Coronary plaque vulnerability prediction is difficult because plaque vulnerability is non-trivial to quantify, clinically available medical image modality is not enough to quantify thin cap thickness, prediction methods with high accuracies still need to be developed, and gold-standard data to validate vulnerability prediction are often not available. Patient follow-up intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography data were acquired to construct 3D fluid–structure interaction (FSI) coronary models and four machine-learning methods were compared to identify optimal method to predict future plaque vulnerability.

Methods

Baseline and 10-month follow-up in vivo IVUS and OCT coronary plaque data were acquired from two arteries of one patient using IRB approved protocols with informed consent obtained. IVUS and OCT-based FSI models were constructed to obtain plaque wall stress/strain and wall shear stress. Forty-five slices were selected as machine learning sample database for vulnerability prediction study. Thirteen key morphological factors from IVUS and OCT images and biomechanical factors from FSI model were extracted from 45 slices at baseline for analysis. Lipid percentage index (LPI), cap thickness index (CTI) and morphological plaque vulnerability index (MPVI) were quantified to measure plaque vulnerability. Four machine learning methods (least square support vector machine, discriminant analysis, random forest and ensemble learning) were employed to predict the changes of three indices using all combinations of 13 factors. A standard fivefold cross-validation procedure was used to evaluate prediction results.

Results

For LPI change prediction using support vector machine, wall thickness was the optimal single-factor predictor with area under curve (AUC) 0.883 and the AUC of optimal combinational-factor predictor achieved 0.963. For CTI change prediction using discriminant analysis, minimum cap thickness was the optimal single-factor predictor with AUC 0.818 while optimal combinational-factor predictor achieved an AUC 0.836. Using random forest for predicting MPVI change, minimum cap thickness was the optimal single-factor predictor with AUC 0.785 and the AUC of optimal combinational-factor predictor achieved 0.847.

Conclusion

This feasibility study demonstrated that machine learning methods could be used to accurately predict plaque vulnerability change based on morphological and biomechanical factors from multi-modality image-based FSI models. Large-scale studies are needed to verify our findings.

Biomechanical Stress Profiling of Coronary Atherosclerosis: Identifying a Multifactorial Metric to Evaluate Plaque Rupture Risk

OBJECTIVES

The purpose of this study was to derive a biomechanical stress metric that was based on the multifactorial assessment of coronary plaque morphology, likely related to the propensity of plaque rupture in patients.

BACKGROUND

Plaque rupture, the most frequent cause of coronary thrombosis, occurs at locations of elevated tensile stress in necrotic core fibroatheromas (NCFAs). Finite element modeling (FEM), typically used to calculate tensile stress, is computationally intensive and impractical as a clinical tool for locating rupture-prone plaques. This study derived a multifactorial stress equation (MSE) that accurately computes peak stress in NCFAs by combining the influence of several morphological parameters.

METHODS

Intravascular ultrasound and optical frequency domain imaging were conducted in 30 patients, and plaque morphological parameters were defined in 61 NCFAs. Multivariate regression analysis was applied to derive the MSE and compute a peak stress metric (PSM) that was based on the analysis of plaque morphological parameters. The accuracy of the MSE was determined by comparing PSM with FEM-derived peak stress values. The ability of the PSM in locating plaque rupture sites was tested in 3 additional patients.

RESULTS

The following parameters were found to be independently associated with peak stress: fibrous cap thickness (p < 0.0001), necrotic core angle (p = 0.024), necrotic core thickness (p < 0.0001), lumen area (p < 0.0001), necrotic core including calcium areas (p = 0.017), and plaque area (p = 0.003). The PSM showed excellent correlation (R = 0.85; p < 0.0001) with FEM-derived peak stress, thus confirming the accuracy of the MSE. In only 56% (n = 34) of plaques, the thinnest fibrous cap thickness was a determining parameter in identifying the cross section with highest PSM. In coronary segments with plaque ruptures, the MSE precisely located the rupture site.

CONCLUSIONS

The MSE shows potential to calculate the PSM in coronary lesions rapidly. However, further studies are warranted to investigate the use of biomechanical stress profiling for the prognostic evaluation of patients with atherosclerosis.

Diagnostic Tests for Vascular Calcification

Vascular calcification (VC) is the heterogeneous endpoint of multiple vascular insults, which varies by arterial bed, the layer of the arterial wall affected, and is propagated by diverse cellular and biochemical mechanisms. A variety of in vivo and ex vivo techniques have been applied to the analysis of VC in preclinical studies, but clinical examination has principally relied on a number of noninvasive and invasive imaging modalities for detection and quantitation. Most imaging methods suffer from suboptimal spatial resolution, leading to the inability to distinguish medial from intimal VC and insufficient sensitivity to detect microcalcifications that are indicative of active mineral deposition and of vulnerable plaques which may be prone to rupture. Serum biomarkers lack specificity for VC and cannot discriminate pathology. Overall, uncertainties surrounding the sensitivity and specificity of different VC testing modalities, the absence of a clear cause-effect relationship, and lack of any evidence-based diagnostic or therapeutic protocols in relation to VC testing in chronic kidney disease has yielded weak or ungraded recommendations for their use in clinical practice. While VC is recognized as a key manifestation of chronic kidney disease-mineral and bone disorder and those with an increasing burden of VC are considered to be at higher cardiovascular risk, routine screening is not currently recommended.

Vulnerable Plaque, Characteristics, Detection, and Potential Therapies

Plaque development and rupture are hallmarks of atherosclerotic vascular disease. Despite current therapeutic developments, there is an unmet necessity in the prevention of atherosclerotic vascular disease. It remains a challenge to determine at an early stage if atherosclerotic plaque will become unstable and vulnerable. The arrival of molecular imaging is receiving more attention, considering it allows for a better understanding of the biology of human plaque and vulnerabilities. Various plaque therapies with common goals have been tested in high-risk patients with cardiovascular disease. In this work, the process of plaque instability, along with current technologies for sensing and predicting high-risk plaques, is debated. Updates on potential novel therapeutic approaches are also summarized.

A Mechanical Approach for Smooth Surface Fitting to Delineate Vessel Walls in Optical Coherence Tomography Images

Automated analysis of vascular imaging techniques is limited by the inability to precisely determine arterial borders. Intravascular optical coherence tomography (OCT) offers unprecedented detail of artery wall structure and composition, but does not provide consistent visibility of the outer border of the vessel due to the limited penetration depth. Existing interpolation and surface fitting methods prove insufficient to accurately fill the gaps between the irregularly spaced and sometimes unreliably identified visible segments of the vessel outer border. This paper describes an intuitive, efficient, and flexible new method of 3D surface fitting and smoothing suitable for this task. An anisotropic linear-elastic mesh is fit to irregularly spaced and uncertain data points corresponding to visible segments of vessel borders, enabling the fully automated delineation of the entire inner and outer borders of diseased vessels in OCT images for the first time. In a clinical dataset, the proposed smooth surface fitting approach had great agreement when compared with human annotations: areas differed by just 11 ± 11% (0.93 ± 0.84 mm²), with a coefficient of determination of 0.89. Overlapping and non-overlapping area ratios were 0.91 and 0.18, respectively, with a sensitivity of 90.8 and specificity of 99.0. This spring mesh method of contour fitting significantly outperformed all alternative surface fitting and interpolation approaches tested. The application of this promising proposed method is expected to enhance clinical intervention and translational research using OCT.

Intraluminal Ultrasonic Palpation Imaging Technique Revisited for Anisotropic Characterization of Healthy and Atherosclerotic Coronary Arteries: A Feasibility Study

Accurate mechanical characterization of coronary atherosclerotic lesions remains essential for the in vivo detection of vulnerable plaques. Using intravascular ultrasound strain measurements and based on the mechanical response of a circular and concentric vascular model, E. I. Céspedes, C. L. de Korte and A. F. van der Steen developed an elasticity-palpography technique in 2000 to estimate the apparent stress-strain modulus palpogram of the thick subendoluminal arterial wall layer. More recently, this approach was improved by our group to consider the real anatomic shape of the vulnerable plaque. Even though these two studies highlighted original and promising approaches for improving the detection of vulnerable plaques, they did not overcome a main limitation related to the anisotropic mechanical behavior of the vascular tissue. The present study was therefore designed to extend these previous approaches by considering the orthotropic mechanical properties of the arterial wall and lesion constituents. Based on the continuum mechanics theory prescribing the strain field, an elastic anisotropy index was defined. This new anisotropic elasticity-palpography technique was successfully applied to characterize ten coronary plaque and one healthy vessel geometries of patients imaged in vivo with intravascular ultrasound. The results revealed that the anisotropy index-palpograms were estimated with a good accuracy (with a mean relative error of 26.8 ± 48.8%) compared with ground true solutions.

Intima heterogeneity in stress assessment of atherosclerotic plaques

Atherosclerotic plaque rupture is recognized as the primary cause of cardiac and cerebral ischaemic events. High structural plaque stresses have been shown to strongly correlate with plaque rupture. Plaque stresses can be computed with finite-element (FE) models. Current FE models employ homogeneous material properties for the heterogeneous atherosclerotic intima. This study aimed to evaluate the influence of intima heterogeneity on plaque stress computations. Two-dimensional FE models with homogeneous and heterogeneous intima were constructed from histological images of atherosclerotic human coronaries (n = 12). For homogeneous models, a single stiffness value was employed for the entire intima. For heterogeneous models, the intima was subdivided into four clusters based on the histological information and different stiffness values were assigned to the clusters. To cover the reported local intima stiffness range, 100 cluster stiffness combinations were simulated. Peak cap stresses (PCSs) from the homogeneous and heterogeneous models were analysed and compared. By using a global variance-based sensitivity analysis, the influence of the cluster stiffnesses on the PCS variation in the heterogeneous intima models was determined. Per plaque, the median PCS values of the heterogeneous models ranged from 27 to 160 kPa, and the PCS range varied between 43 and 218 kPa. On average, the homogeneous model PCS values differed from the median PCS values of heterogeneous models by 14%. A positive correlation (R² = 0.72) was found between the homogeneous model PCS and the PCS range of the heterogeneous models. Sensitivity analysis showed that the highest main sensitivity index per plaque ranged from 0.26 to 0.83, and the average was 0.47. Intima heterogeneity resulted in substantial changes in PCS, warranting stress analyses with heterogeneous intima properties for plaque-specific, high accuracy stress assessment. Yet, computations with homogeneous intima assumption are still valuable to perform sensitivity analyses or parametric studies for testing the effect of plaque geometry on PCS. Moreover, homogeneous intima models can help identify low PCS, stable type plaques with thick caps. Yet, for thin cap plaques, accurate stiffness measurements of the clusters in the cap and stress analysis with heterogeneous cap properties are required to characterize the plaque stability.

STRESS ANALYSIS OF INTERNAL CAROTID ARTERY WITH LOW STENOSIS LEVEL: THE EFFECT OF MATERIAL MODEL AND PLAQUE GEOMETRY

Stress concentration in carotid stenosis has been proven to assist plaque morphology in disease diagnosis and vulnerability. This work focuses on numerical analysis of stress and strain distribution in the cross-section of internal carotid artery using a 2D structure-only method. The influence of four different idealized plaque geometries (circle, ellipse, oval and wedge) is investigated. Numerical simulations are implemented utilizing linear elastic model along with four hyperelastic constitutive laws named neo-Hookean, Ogden, Yeoh and Mooney–Rivlin. Each case is compared to the real geometry. Results show significant strength of oval and wedged geometries in predicting stress and strain values. Our results emphasize that Yeoh and Ogden hyperelastic materials are more reliable in stress prediction with errors less than 3%. The same concept is observed in locating critical stresses where oval and wedged plaque geometries are the most accurate models. Similar results are observed in predicting maximum principal elastic strain with errors less than 1%. However, the strain distribution in idealized plaque models showed a considerable difference in comparison with real geometry.

Model-based cap thickness and peak cap stress prediction for carotid MRI

A rupture-prone carotid plaque can potentially be identified by calculating the peak cap stress (PCS). For these calculations, plaque geometry from MRI is often used. Unfortunately, MRI is hampered by a low resolution, leading to an overestimation of cap thickness and an underestimation of PCS. We developed a model to reconstruct the cap based on plaque geometry to better predict cap thickness and PCS. We used histological stained plaques from 34 patients. These plaques were segmented and served as the ground truth. Sections of these plaques contained 93 necrotic cores with a cap thickness <0.62mm which were used to generate a geometry-based model. The histological data was used to simulate in vivo MRI images, which were manually delineated by three experienced MRI readers. Caps below the MRI resolution (n=31) were (digitally removed and) reconstructed according to the geometry-based model. Cap thickness and PCS were determined for the ground truth, readers, and reconstructed geometries. Cap thickness was 0.07mm for the ground truth, 0.23mm for the readers, and 0.12mm for the reconstructed geometries. The model predicts cap thickness significantly better than the readers. PCS was 464kPa for the ground truth, 262kPa for the readers and 384kPa for the reconstructed geometries. The model did not predict the PCS significantly better than the readers. The geometry-based model provided a significant improvement for cap thickness estimation and can potentially help in rupture-risk prediction, solely based on cap thickness. Estimation of PCS estimation did not improve, probably due to the complex shape of the plaques.