Flow interactions with cells and tissues: cardiovascular flows and fluid-structure interactions. Sixth International Bio-Fluid Mechanics Symposium and Workshop, March 28-30, 2008, Pasadena, California

Multi-patient study for coronary vulnerable plaque model comparisons: 2D/3D and fluid-structure interaction simulations

Several image-based computational models have been used to perform mechanical analysis for atherosclerotic plaque progression and vulnerability investigations. However, differences of computational predictions from those models have not been quantified at multi-patient level. In vivo intravascular ultrasound (IVUS) coronary plaque data were acquired from seven patients. Seven 2D/3D models with/without circumferential shrink, cyclic bending and fluid–structure interactions (FSI) were constructed for the seven patients to perform model comparisons and quantify impact of 2D simplification, circumferential shrink, FSI and cyclic bending plaque wall stress/strain (PWS/PWSn) and flow shear stress (FSS) calculations. PWS/PWSn and FSS averages from seven patients (388 slices for 2D and 3D thin-layer models) were used for comparison. Compared to 2D models with shrink process, 2D models without shrink process overestimated PWS by 17.26%. PWS change at location with greatest curvature change from 3D FSI models with/without cyclic bending varied from 15.07% to 49.52% for the seven patients (average = 30.13%). Mean Max-FSS, Min-FSS and Ave-FSS from the flow-only models under maximum pressure condition were 4.02%, 11.29% and 5.45% higher than those from full FSI models with cycle bending, respectively. Mean PWS and PWSn differences between FSI and structure-only models were only 4.38% and 1.78%. Model differences had noticeable patient variations. FSI and flow-only model differences were greater for minimum FSS predictions, notable since low FSS is known to be related to plaque progression. Structure-only models could provide PWS/PWSn calculations as good approximations to FSI models for simplicity and time savings in calculation.

Combining IVUS and Optical Coherence Tomography for More Accurate Coronary Cap Thickness Quantification and Stress/Strain Calculations: A Patient-Specific Three-Dimensional Fluid-Structure Interaction Modeling Approach

Accurate cap thickness and stress/strain quantifications are of fundamental importance for vulnerable plaque research. Virtual histology intravascular ultrasound (VH-IVUS) sets cap thickness to zero when cap is under resolution limit and IVUS does not see it. An innovative modeling approach combining IVUS and optical coherence tomography (OCT) is introduced for cap thickness quantification and more accurate cap stress/strain calculations. In vivo IVUS and OCT coronary plaque data were acquired with informed consent obtained. IVUS and OCT images were merged to form the IVUS + OCT data set, with biplane angiography providing three-dimensional (3D) vessel curvature. For components where VH-IVUS set zero cap thickness (i.e., no cap), a cap was added with minimum cap thickness set as 50 and 180 μm to generate IVUS50 and IVUS180 data sets for model construction, respectively. 3D fluid-structure interaction (FSI) models based on IVUS + OCT, IVUS50, and IVUS180 data sets were constructed to investigate cap thickness impact on stress/strain calculations. Compared to IVUS + OCT, IVUS50 underestimated mean cap thickness (27 slices) by 34.5%, overestimated mean cap stress by 45.8%, (96.4 versus 66.1 kPa). IVUS50 maximum cap stress was 59.2% higher than that from IVUS + OCT model (564.2 versus 354.5 kPa). Differences between IVUS and IVUS + OCT models for cap strain and flow shear stress (FSS) were modest (cap strain <12%; FSS <6%). IVUS + OCT data and models could provide more accurate cap thickness and stress/strain calculations which will serve as basis for further plaque investigations.

MRI-based patient-specific human carotid atherosclerotic vessel material property variations in patients, vessel location and long-term follow up

Background

Image-based computational models are widely used to determine atherosclerotic plaque stress/strain conditions and investigate their association with plaque progression and rupture. However, patient-specific vessel material properties are in general lacking in those models, limiting the accuracy of their stress/strain measurements. A noninvasive approach of combining in vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) and computational modeling was introduced to quantify patient-specific carotid plaque material properties for potential plaque model improvements. Vessel material property variation in patients, along vessel segment, and between baseline and follow up were investigated.

Methods

In vivo 3D multi-contrast and Cine MRI carotid plaque data were acquired from 8 patients with follow-up (18 months) with written informed consent obtained. 3D thin-layer models and an established iterative procedure were used to determine parameter values of the Mooney-Rivlin models for the 81slices from 16 plaque samples. Effective Young’s Modulus (YM) values were calculated for comparison and analysis.

Results

Average Effective Young’s Modulus (YM) and circumferential shrinkage rate (C-Shrink) value of the 81 slices was 411kPa and 5.62%, respectively. Slice YM value varied from 70 kPa (softest) to 1284 kPa (stiffest), a 1734% difference. Average slice YM values by vessel varied from 109 kPa (softest) to 922 kPa (stiffest), a 746% difference. Location-wise, the maximum slice YM variation rate within a vessel was 311% (149 kPa vs. 613 kPa). The average slice YM variation rate for the 16 vessels was 134%. The average variation of YM values for all patients from baseline to follow up was 61.0%. The range of the variation of YM values was [-28.4%, 215%]. For plaque progression study, YM at follow-up showed negative correlation with plaque progression measured by wall thickness increase (WTI) (r = -0.7764, p = 0.0235). Wall thickness at baseline correlated with WTI negatively, with r = -0.5253 (p = 0.1813). Plaque burden at baseline correlated with YM change between baseline and follow-up, with r = 0.5939 (p = 0.1205).

Conclusion

In vivo carotid vessel material properties have large variations from patient to patient, along the diseased segment within a patient, and with time. The use of patient-specific, location specific and time-specific material properties in plaque models could potentially improve the accuracy of model stress/strain calculations.

Multiscale modeling methods in biomechanics

More and more frequently, computational biomechanics deals with problems where the portion of physical reality to be modeled spans over such a large range of spatial and temporal dimensions, that it is impossible to represent it as a single space-time continuum. We are forced to consider multiple space-time continua, each representing the phenomenon of interest at a characteristic space-time scale. Multiscale models describe a complex process across multiple scales, and account for how quantities transform as we move from one scale to another. This review offers a set of definitions for this emerging field, and provides a brief summary of the most recent developments on multiscale modeling in biomechanics. Of all possible perspectives, we chose that of the modeling intent, which vastly affect the nature and the structure of each research activity. To the purpose we organized all papers reviewed in three categories: 'causal confirmation,' where multiscale models are used as materializations of the causation theories; 'predictive accuracy,' where multiscale modeling is aimed to improve the predictive accuracy; and 'determination of effect,' where multiscale modeling is used to model how a change at one scale manifests in an effect at another radically different space-time scale. Consistent with how the volume of computational biomechanics research is distributed across application targets, we extensively reviewed papers targeting the musculoskeletal and the cardiovascular systems, and covered only a few exemplary papers targeting other organ systems. The review shows a research subdomain still in its infancy, where causal confirmation papers remain the most common. WIREs Syst Biol Med 2017, 9:e1375. doi: 10.1002/wsbm.1375 For further resources related to this article, please visit the WIREs website.

Cap inflammation leads to higher plaque cap strain and lower cap stress: An MRI-PET/CT-based FSI modeling approach

Plaque rupture may be triggered by extreme stress/strain conditions. Inflammation is also implicated and can be imaged using novel imaging techniques. The impact of cap inflammation on plaque stress/strain and flow shear stress were investigated. A patient-specific MRI-PET/CT-based modeling approach was used to develop 3D fluid-structure interaction models and investigate the impact of inflammation on plaque stress/strain conditions for better plaque assessment. 18FDG-PET/CT and MRI data were acquired from 4 male patients (average age: 66) to assess plaque characteristics and inflammation. Material stiffness for the fibrous cap was adjusted lower to reflect cap weakening causing by inflammation. Setting stiffness ratio (SR) to be 1.0 (fibrous tissue) for baseline, results for SR=0.5, 0.25, and 0.1 were obtained. Thin cap and hypertension were also considered. Combining results from the 4 patients, mean cap stress from 729 cap nodes was lowered by 25.2% as SR went from 1.0 to 0.1. Mean cap strain value for SR=0.1 was 0.313, 114% higher than that from SR=1.0 model. The thin cap SR=0.1 model had 40% mean cap stress decrease and 81% cap strain increase compared with SR=1.0 model. The hypertension SR=0.1 model had 19.5% cap stress decrease and 98.6% cap strain increase compared with SR=1.0 model. Differences of flow shear stress with 4 different SR values were limited (<10%). Cap inflammation may lead to large cap strain conditions when combined with thin cap and hypertension. Inflammation also led to lower cap stress. This shows the influence of inflammation on stress/strain calculations which are closely related to plaque assessment.

Quantify patient-specific coronary material property and its impact on stress/strain calculations using in vivo IVUS data and 3D FSI models: a pilot study

Computational models have been used to calculate plaque stress and strain for plaque progression and rupture investigations. An intravascular ultrasound (IVUS)-based modeling approach is proposed to quantify in vivo vessel material properties for more accurate stress/strain calculations. In vivo Cine IVUS and VH-IVUS coronary plaque data were acquired from one patient with informed consent obtained. Cine IVUS data and 3D thin-slice models with axial stretch were used to determine patient-specific vessel material properties. Twenty full 3D fluid-structure interaction models with ex vivo and in vivo material properties and various axial and circumferential shrink combinations were constructed to investigate the material stiffness impact on stress/strain calculations. The approximate circumferential Young's modulus over stretch ratio interval [1.0, 1.1] for an ex vivo human plaque sample and two slices (S6 and S18) from our IVUS data were 1631, 641, and 346 kPa, respectively. Average lumen stress/strain values from models using ex vivo, S6 and S18 materials with 5 % axial shrink and proper circumferential shrink were 72.76, 81.37, 101.84 kPa and 0.0668, 0.1046, and 0.1489, respectively. The average cap strain values from S18 material models were 150-180 % higher than those from the ex vivo material models. The corresponding percentages for the average cap stress values were 50-75 %. Dropping axial and circumferential shrink consideration led to stress and strain over-estimations. In vivo vessel material properties may be considerably softer than those from ex vivo data. Material stiffness variations may cause 50-75 % stress and 150-180 % strain variations.

Multiphysics simulation of the effect of leaflet thickness inhomogeneity and material anisotropy on the stress-strain distribution on the aortic valve

This study developed a realistic 3D FSI computational model of the aortic valve using the fixed-grid method, which was eventually employed to investigate the effect of the leaflet thickness inhomogeneity and leaflet mechanical nonlinearity and anisotropy on the simulation results. The leaflet anisotropy and thickness inhomogeneity were found to significantly affect the valve stress-strain distribution. However, their effect on valve dynamics and fluid flow through the valve were minor. Comparison of the simulation results against in-vivo and in-vitro data indicated good agreement between the computational models and experimental data. The study highlighted the importance of simulating multi-physics phenomena (such as fluid flow and structural deformation), regional leaflet thickness inhomogeneity and anisotropic nonlinear mechanical properties, to accurately predict the stress-strain distribution on the natural aortic valve.

Morphological and Stress Vulnerability Indices for Human Coronary Plaques and Their Correlations with Cap Thickness and Lipid Percent: An IVUS-Based Fluid-Structure Interaction Multi-patient Study

Plaque vulnerability, defined as the likelihood that a plaque would rupture, is difficult to quantify due to lack of in vivo plaque rupture data. Morphological and stress-based plaque vulnerability indices were introduced as alternatives to obtain quantitative vulnerability assessment. Correlations between these indices and key plaque features were investigated. In vivo intravascular ultrasound (IVUS) data were acquired from 14 patients and IVUS-based 3D fluid-structure interaction (FSI) coronary plaque models with cyclic bending were constructed to obtain plaque wall stress/strain and flow shear stress for analysis. For the 617 slices from the 14 patients, lipid percentage, min cap thickness, critical plaque wall stress (CPWS), strain (CPWSn) and flow shear stress (CFSS) were recorded, and cap index, lipid index and morphological index were assigned to each slice using methods consistent with American Heart Association (AHA) plaque classification schemes. A stress index was introduced based on CPWS. Linear Mixed-Effects (LME) models were used to analyze the correlations between the mechanical and morphological indices and key morphological factors associated with plaque rupture. Our results indicated that for all 617 slices, CPWS correlated with min cap thickness, cap index, morphological index with r = -0.6414, 0.7852, and 0.7411 respectively (p<0.0001). The correlation between CPWS and lipid percentage, lipid index were weaker (r = 0.2445, r = 0.2338, p<0.0001). Stress index correlated with cap index, lipid index, morphological index positively with r = 0.8185, 0.3067, and 0.7715, respectively, all with p<0.0001. For all 617 slices, the stress index has 66.77% agreement with morphological index. Morphological and stress indices may serve as quantitative plaque vulnerability assessment supported by their strong correlations with morphological features associated with plaque rupture. Differences between the two indices may lead to better plaque assessment schemes when both indices were jointly used with further validations from clinical studies.

Cardiovascular diseases are closely related to atherosclerotic plaque progression and rupture. Early detection of vulnerable plaques and prediction of potential plaque rupture and related clinical events are of vital importance. Plaque vulnerability, defined as the likelihood that a plaque would rupture, is difficult to measure due to lack of in vivo plaque rupture data. Morphological and stress-based plaque vulnerability indices were introduced in this paper as alternatives to obtain quantitative vulnerability assessment with potential improvement of patient screening tools. In vivo intravascular ultrasound data were acquired from patients and computational coronary plaque models were constructed to obtain data for analysis and index assignments. For the 617 slices from the 14 patients, morphological and stress indices were assigned to each slice using methods consistent with American Heart Association plaque classification schemes. Correlation analyses were performed for all the morphological and mechanical factors considered. The stress index has 66.77% agreement with morphological index. Morphological and stress indices may serve as quantitative plaque vulnerability assessment supported by their strong correlations with morphological features associated with plaque rupture. Differences between the two indices may lead to better plaque assessment schemes when the complementary indices were jointly used with further validations from clinical studies.

Hemodynamic Characterization of a Mouse Model for Investigating the Cellular and Molecular Mechanisms of Neotissue Formation in Tissue-Engineered Heart Valves

Decellularized allograft heart valves have been used as tissue-engineered heart valve (TEHV) scaffolds with promising results; however, little is known about the cellular mechanisms underlying TEHV neotissue formation. To better understand this phenomenon, we developed a murine model of decellularized pulmonary heart valve transplantation using a hemodynamically unloaded heart transplant model. Furthermore, because the hemodynamics of blood flow through a heart valve may influence morphology and subsequent function, we describe a modified loaded heterotopic heart transplant model that led to an increase in blood flow through the pulmonary valve. We report host cell infiltration and endothelialization of implanted decellularized pulmonary valves (dPV) and provide an experimental approach for the study of TEHVs using mouse models.

IVUS-based FSI models for human coronary plaque progression study: components, correlation and predictive analysis

Atherosclerotic plaque progression is believed to be associated with mechanical stress conditions. Patient follow-up in vivo intravascular ultrasound coronary plaque data were acquired to construct fluid-structure interaction (FSI) models with cyclic bending to obtain flow wall shear stress (WSS), plaque wall stress (PWS) and strain (PWSn) data and investigate correlations between plaque progression measured by wall thickness increase (WTI), cap thickness increase (CTI), lipid depth increase (LDI) and risk factors including wall thickness (WT), WSS, PWS, and PWSn. Quarter average values (n = 178-1016) of morphological and mechanical factors from all slices were obtained for analysis. A predictive method was introduced to assess prediction accuracy of risk factors and identify the optimal predictor(s) for plaque progression. A combination of WT and PWS was identified as the best predictor for plaque progression measured by WTI. Plaque WT had best overall correlation with WTI (r = -0.7363, p < 1E-10), cap thickness (r = 0.4541, p < 1E-10), CTI (r = -0.4217, p < 1E-8), LD (r = 0.4160, p < 1E-10), and LDI (r = -0.4491, p < 1E-10), followed by PWS (with WTI: (r = -0.3208, p < 1E-10); cap thickness: (r = 0.4541, p < 1E-10); CTI: (r = -0.1719, p = 0.0190); LD: (r = -0.2206, p < 1E-10); LDI: r = 0.1775, p < 0.0001). WSS had mixed correlation results.

Human coronary plaque wall thickness correlated positively with flow shear stress and negatively with plaque wall stress: an IVUS-based fluid-structure interaction multi-patient study

BACKGROUND

Atherosclerotic plaque progression and rupture are believed to be associated with mechanical stress conditions. In this paper, patient-specific in vivo intravascular ultrasound (IVUS) coronary plaque image data were used to construct computational models with fluid-structure interaction (FSI) and cyclic bending to investigate correlations between plaque wall thickness and both flow shear stress and plaque wall stress conditions.

METHODS

IVUS data were acquired from 10 patients after voluntary informed consent. The X-ray angiogram was obtained prior to the pullback of the IVUS catheter to determine the location of the coronary artery stenosis, vessel curvature and cardiac motion. Cyclic bending was specified in the model representing the effect by heart contraction. 3D anisotropic FSI models were constructed and solved to obtain flow shear stress (FSS) and plaque wall stress (PWS) values. FSS and PWS values were obtained for statistical analysis. Correlations with p < 0.05 were deemed significant.

RESULTS

Nine out of the 10 patients showed positive correlation between wall thickness and flow shear stress. The mean Pearson correlation r-value was 0.278 ± 0.181. Similarly, 9 out of the 10 patients showed negative correlation between wall thickness and plaque wall stress. The mean Pearson correlation r-value was -0.530 ± 0.210.

CONCLUSION

Our results showed that plaque vessel wall thickness correlated positively with FSS and negatively with PWS. The patient-specific IVUS-based modeling approach has the potential to be used to investigate and identify possible mechanisms governing plaque progression and rupture and assist in diagnosis and intervention procedures. This represents a new direction of research. Further investigations using more patient follow-up data are warranted.

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.

Reproduction of pressure field in ultrasonic-measurement-integrated simulation of blood flow

Ultrasonic-measurement-integrated (UMI) simulation of blood flow is used to analyze the velocity and pressure fields by applying feedback signals of artificial body forces based on differences of Doppler velocities between ultrasonic measurement and numerical simulation. Previous studies have revealed that UMI simulation accurately reproduces the velocity field of a target blood flow, but that the reproducibility of the pressure field is not necessarily satisfactory. In the present study, the reproduction of the pressure field by UMI simulation was investigated. The effect of feedback on the pressure field was first examined by theoretical analysis, and a pressure compensation method was devised. When the divergence of the feedback force vector was not zero, it influenced the pressure field in the UMI simulation while improving the computational accuracy of the velocity field. Hence, the correct pressure was estimated by adding pressure compensation to remove the deteriorating effect of the feedback. A numerical experiment was conducted dealing with the reproduction of a synthetic three-dimensional steady flow in a thoracic aneurysm to validate results of the theoretical analysis and the proposed pressure compensation method. The ability of the UMI simulation to reproduce the pressure field deteriorated with a large feedback gain. However, by properly compensating the effects of the feedback signals on the pressure, the error in the pressure field was reduced, exhibiting improvement of the computational accuracy. It is thus concluded that the UMI simulation with pressure compensation allows for the reproduction of both velocity and pressure fields of blood flow.

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.

Using in vivo Cine and 3D multi-contrast MRI to determine human atherosclerotic carotid artery material properties and circumferential shrinkage rate and their impact on stress/strain predictions

In vivo magnetic resonance image (MRI)-based computational models have been introduced to calculate atherosclerotic plaque stress and strain conditions for possible rupture predictions. However, patient-specific vessel material properties are lacking in those models, which affects the accuracy of their stress/strain predictions. A noninvasive approach of combining in vivo Cine MRI, multicontrast 3D MRI, and computational modeling was introduced to quantify patient-specific carotid artery material properties and the circumferential shrinkage rate between vessel in vivo and zero-pressure geometries. In vivo Cine and 3D multicontrast MRI carotid plaque data were acquired from 12 patients after informed consent. For each patient, one nearly-circular slice and an iterative procedure were used to quantify parameter values in the modified Mooney-Rivlin model for the vessel and the vessel circumferential shrinkage rate. A sample artery slice with and without a lipid core and three material parameter sets representing stiff, median, and soft materials from our patient data were used to demonstrate the effect of material stiffness and circumferential shrinkage process on stress/strain predictions. Parameter values of the Mooney-Rivlin models for the 12 patients were quantified. The effective Young's modulus (YM, unit: kPa) values varied from 137 (soft), 431 (median), to 1435 (stiff), and corresponding circumferential shrinkages were 32%, 12.6%, and 6%, respectively. Using the sample slice without the lipid core, the maximum plaque stress values (unit: kPa) from the soft and median materials were 153.3 and 96.2, which are 67.7% and 5% higher than that (91.4) from the stiff material, while the maximum plaque strain values from the soft and median materials were 0.71 and 0.293, which are about 700% and 230% higher than that (0.089) from the stiff material, respectively. Without circumferential shrinkages, the maximum plaque stress values (unit: kPa) from the soft, median, and stiff models were inflated to 330.7, 159.2, and 103.6, which were 116%, 65%, and 13% higher than those from models with proper shrinkage. The effective Young's modulus from the 12 human carotid arteries studied varied from 137 kPa to 1435 kPa. The vessel circumferential shrinkage to the zero-pressure condition varied from 6% to 32%. The inclusion of proper shrinkage in models based on in vivo geometry is necessary to avoid over-estimating the stresses and strains by up 100%. Material stiffness had a greater impact on strain (up to 700%) than on stress (up to 70%) predictions. Accurate patient-specific material properties and circumferential shrinkage could considerably improve the accuracy of in vivo MRI-based computational stress/strain predictions.

Spiral laminar flow prosthetic bypass graft: medium-term results from a first-in-man structured registry study

BACKGROUND

A number of surgical strategies and graft enhancements have been trialled to improve the performance of prosthetic grafts. Neointimal hyperplasia may, in part, be a normal cellular response to an abnormal (turbulent) flow environment. This first-in-many study assesses the safety and medium-term patency performance of a new graft designed to induce stable laminar flow through the distal anastomosis.

METHOD

Forty patients who required an infrainguinal bypass graft were recruited/registered from a number of centers in Belgium and The Netherlands. Thirty-nine received a Spiral Laminar Flow graft as part of a standard treatment protocol (23 above-the-knee and 16 below-the-knee bypasses). Kaplan-Meier analyses were used to calculate primary and secondary patency rates.

RESULTS

The 12-, 24-, and 30-month primary patency rates were 86%, 81%, and 81% for above-the-knee bypasses and 73%, 57%, and 57% for below-the-knee bypasses, respectively. In the case of secondary patency rates, numbers were unchanged for above-the-knee bypasses and were 86%, 64%, and 64%, respectively, for below-the-knee bypasses. There were no amputations in the study population.

CONCLUSION

This first-in-man series shows potential for the idea of spiral flow-enhanced prosthetic grafts. As always, randomized studies are required to explore the role of different enhanced prosthetic grafts.

In vivo serial MRI-based models and statistical methods to quantify sensitivity and specificity of mechanical predictors for carotid plaque rupture: location and beyond

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.