Optical Coherence Tomography-Derived Changes in Plaque Structural Stress Over the Cardiac Cycle: A New Method for Plaque Biomechanical Assessment.

Introduction: Cyclic plaque structural stress has been hypothesized as a mechanism for plaque fatigue and eventually plaque rupture. A novel approach to derive cyclic plaque stress in vivo from optical coherence tomography (OCT) is hereby developed. Materials and Methods: All intermediate lesions from a previous OCT study were enrolled. OCT cross-sections at representative positions within each lesion were selected for plaque stress analysis. Detailed plaque morphology, including plaque composition, lumen and internal elastic lamina contours, were automatically delineated. OCT-derived vessel and plaque morphology were included in a 2-dimensional finite element analysis, loaded with patient-specific intracoronary pressure tracing data, to calculate the changes in plaque structural stress (ΔPSS) on vessel wall over the cardiac cycle. Results: A total of 50 lesions from 41 vessels were analyzed. A significant ΔPSS gradient was observed across the plaque, being maximal at the proximal shoulder (45.7 [32.3, 78.6] kPa), intermediate at minimal lumen area (MLA) (39.0 [30.8, 69.1] kPa) and minimal at the distal shoulder (35.1 [28.2, 72.3] kPa; p = 0.046). The presence of lipidic plaques were observed in 82% of the diseased segments. Larger relative lumen deformation and ΔPSS were observed in diseased segments, compared with normal segments (percent diameter change: 8.2 ± 4.2% vs. 6.3 ± 2.3%, p = 0.04; ΔPSS: 59.3 ± 48.2 kPa vs. 27.5 ± 8.2 kPa, p < 0.001). ΔPSS was positively correlated with plaque burden (r = 0.37, p < 0.001) and negatively correlated with fibrous cap thickness (r = -0.25, p = 0.004). Conclusions: ΔPSS provides a feasible method for assessing plaque biomechanics in vivo from OCT images, consistent with previous biomechanical and clinical studies based on different methodologies. Larger ΔPSS at proximal shoulder and MLA indicates the critical sites for future biomechanical assessment.

Image-based modeling for better understanding and assessment of atherosclerotic plaque progression and vulnerability: data, modeling, validation, uncertainty and predictions.

Medical imaging and image-based modeling have made considerable progress in recent years in identifying atherosclerotic plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. However, a clear understanding is needed about what we have achieved and what is really needed to translate research to actual clinical practices and bring benefits to public health. Lack of in vivo data and clinical events to serve as gold standard to validate model predictions is a severe limitation. While this perspective paper provides a review of the key steps and findings of our group in image-based models for human carotid and coronary plaques and a limited review of related work by other groups, we also focus on grand challenges and uncertainties facing the researchers in the field to develop more accurate and predictive patient screening tools.

Image-based modeling and precision medicine: patient-specific carotid and coronary plaque assessment and predictions.

Atherosclerotic plaques may rupture without warning and cause acute cardiovascular events such as heart attack and stroke. Current clinical screening tools are insufficient to identify those patients with risks early and prevent the adverse events from happening. Medical imaging and image-based modeling have made considerable progress in recent years in identifying plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. The key steps and factors in image-based models for human carotid and coronary plaques were illustrated, as well as grand challenges facing the researchers in the field to develop more accurate screening tools.

IVUS-based computational modeling and planar biaxial artery material properties for human coronary plaque vulnerability assessment.

Image-based computational modeling has been introduced for vulnerable atherosclerotic plaques to identify critical mechanical conditions which may be used for better plaque assessment and rupture predictions. In vivo patient-specific coronary plaque models are lagging due to limitations on non-invasive image resolution, flow data, and vessel material properties. A framework is proposed to combine intravascular ultrasound (IVUS) imaging, biaxial mechanical testing and computational modeling with fluid-structure interactions and anisotropic material properties to acquire better and more complete plaque data and make more accurate plaque vulnerability assessment and predictions. Impact of pre-shrink-stretch process, vessel curvature and high blood pressure on stress, strain, flow velocity and flow maximum principal shear stress was investigated.

Multi-Physics MRI-Based Two-Layer Fluid-Structure Interaction Anisotropic Models of Human Right and Left Ventricles with Different Patch Materials: Cardiac Function Assessment and Mechanical Stress Analysis.

Multi-physics right and left ventricle (RV/LV) fluid-structure interaction (FSI) models were introduced to perform mechanical stress analysis and evaluate the effect of patch materials on RV function. The FSI models included three different patch materials (Dacron scaffold, treated pericardium, and contracting myocardium), two-layer construction, fiber orientation, and active anisotropic material properties. The models were constructed based on cardiac magnetic resonance (CMR) images acquired from a patient with severe RV dilatation and solved by ADINA. Our results indicate that the patch model with contracting myocardium leads to decreased stress level in the patch area, improved RV function and patch area contractility.

Image-Based Patient-Specific Ventricle Models with Fluid-Structure Interaction for Cardiac Function Assessment and Surgical Design Optimization.

Recent advances in medical imaging technology and computational modeling techniques are making it possible that patient-specific computational ventricle models be constructed and used to test surgical hypotheses and replace empirical and often risky clinical experimentation to examine the efficiency and suitability of various reconstructive procedures in diseased hearts. In this paper, we provide a brief review on recent development in ventricle modeling and its potential application in surgical planning and management of tetralogy of Fallot (ToF) patients. Aspects of data acquisition, model selection and construction, tissue material properties, ventricle layer structure and tissue fiber orientations, pressure condition, model validation and virtual surgery procedures (changing patient-specific ventricle data and perform computer simulation) were reviewed. Results from a case study using patient-specific cardiac magnetic resonance (CMR) imaging and right/left ventricle and patch (RV/LV/Patch) combination model with fluid-structure interactions (FSI) were reported. The models were used to evaluate and optimize human pulmonary valve replacement/insertion (PVR) surgical procedure and patch design and test a surgical hypothesis that PVR with small patch and aggressive scar tissue trimming in PVR surgery may lead to improved recovery of RV function and reduced stress/strain conditions in the patch area.

Quantitative assessment of coronary artery plaque vulnerability by high-resolution magnetic resonance imaging and computational biomechanics: a pilot study ex vivo.

The risk of atherosclerotic plaque disruption is thought to be closely related to plaque composition and rupture triggers such as external mechanical forces. The purpose of this study was to integrate MR imaging and computational techniques for the quantification of plaque vulnerability with morphologic data and biomechanical stress/strain distributions that were all based on high-resolution MR images of coronary artery plaque specimens ex vivo. Twenty-two coronary artery plaque specimens were selectively collected from 10 cadavers. Multislice T(2)-weighted spin echo images were acquired with a resolution of 100 x 100 microm(2). Histopathological images were used as the gold standard for the identification of plaque components and vulnerability. Plaque components were classified on MR images, and the stress/strain components were calculated with a two-dimensional computational model with fluid-structure interactions. As expected, vulnerable plaques appeared to result from a large lipid pool, a thin fibrous cap, and some critical stress/strain conditions. An empiric vulnerability marker was derived and was closely related to the vulnerability score that was determined through pathologic examination. Noninvasive quantification of the MR contrast and mechanical properties of plaque may provide a comprehensive biomarker for the assessment of vulnerability of atherosclerotic plaques.

Local maximal stress hypothesis and computational plaque vulnerability index for atherosclerotic plaque assessment.

It is believed that atherosclerotic plaque rupture may be related to maximal stress conditions in the plaque. More careful examination of stress distributions in plaques reveals that it may be the local stress/strain behaviors at critical sites such as very thin plaque cap and locations with plaque cap weakness that are more closely related to plaque rupture risk. A "local maximal stress hypothesis" and a stress-based computational plaque vulnerability index (CPVI) are proposed to assess plaque vulnerability. A critical site selection (CSS) method is proposed to identify critical sites in the plaque and critical stress conditions which are be used to determine CPVI values. Our initial results based on 34 2D MRI slices from 14 human coronary plaque samples indicate that CPVI plaque assessment has an 85% agreement rate (91% if the square root of stress values is used) with assessment given by histopathological analysis. Large-scale and long-term patient studies are needed to further validate our findings for more accurate quantitative plaque vulnerability assessment.