Numerical simulations of carotid MRI quantify the accuracy in measuring atherosclerotic plaque components in vivo

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.

The effects of plaque morphology and material properties on peak cap stress in human coronary arteries

Heart attacks are often caused by rupture of caps of atherosclerotic plaques in coronary arteries. Cap rupture occurs when cap stress exceeds cap strength. We investigated the effects of plaque morphology and material properties on cap stress. Histological data from 77 coronary lesions were obtained and segmented. In these patient-specific cross sections, peak cap stresses were computed by using finite element analyses. The finite element analyses were 2D, assumed isotropic material behavior, and ignored residual stresses. To represent the wide spread in material properties, we applied soft and stiff material models for the intima. Measures of geometric plaque features for all lesions were determined and their relations to peak cap stress were examined using regression analyses. Patient-specific geometrical plaque features greatly influence peak cap stresses. Especially, local irregularities in lumen and necrotic core shape as well as a thin intima layer near the shoulder of the plaque induce local stress maxima. For stiff models, cap stress increased with decreasing cap thickness and increasing lumen radius (R = 0.79). For soft models, this relationship changed: increasing lumen radius and increasing lumen curvature were associated with increased cap stress (R = 0.66). The results of this study imply that not only accurate assessment of plaque geometry, but also of intima properties is essential for cap stress analyses in atherosclerotic plaques in human coronary arteries.

Carotid plaque elasticity estimation using ultrasound elastography, MRI, and inverse FEA - A numerical feasibility study

The material properties of atherosclerotic plaques govern the biomechanical environment, which is associated with rupture-risk. We investigated the feasibility of noninvasively estimating carotid plaque component material properties through simulating ultrasound (US) elastography and in vivo magnetic resonance imaging (MRI), and solving the inverse problem with finite element analysis. 2D plaque models were derived from endarterectomy specimens of nine patients. Nonlinear neo-Hookean models (tissue elasticity C1) were assigned to fibrous intima, wall (i.e., media/adventitia), and lipid-rich necrotic core. Finite element analysis was used to simulate clinical cross-sectional US strain imaging. Computer-simulated, single-slice in vivo MR images were segmented by two MR readers. We investigated multiple scenarios for plaque model elasticity, and consistently found clear separations between estimated tissue elasticity values. The intima C1 (160 kPa scenario) was estimated as 125.8 ± 19.4 kPa (reader 1) and 128.9 ± 24.8 kPa (reader 2). The lipid-rich necrotic core C1 (5 kPa) was estimated as 5.6 ± 2.0 kPa (reader 1) and 8.5 ± 4.5 kPa (reader 2). A scenario with a stiffer wall yielded similar results, while realistic US strain noise and rotating the models had little influence, thus demonstrating robustness of the procedure. The promising findings of this computer-simulation study stimulate applying the proposed methodology in a clinical setting.

Carotid Plaque Morphological Classification Compared With Biomechanical Cap Stress: Implications for a Magnetic Resonance Imaging-Based Assessment

BACKGROUND AND PURPOSE

Two approaches to target plaque vulnerability-a histopathologic classification scheme and a biomechanical analysis-were compared and the implications for noninvasive risk stratification of carotid plaques using magnetic resonance imaging were assessed.

METHODS

Seventy-five histological plaque cross sections were obtained from carotid endarterectomy specimens from 34 patients (>70% stenosis) and subjected to both a Virmani histopathologic classification (thin fibrous cap atheroma with <0.2-mm cap thickness, presumed vulnerable) and a peak cap stress computation (<140 kPa: presumed stable; >300 kPa: presumed vulnerable). To demonstrate the implications for noninvasive plaque assessment, numeric simulations of a typical carotid magnetic resonance imaging protocol were performed (0.62×0.62 mm(2) in-plane acquired voxel size) and used to obtain the magnetic resonance imaging-based peak cap stress.

RESULTS

Peak cap stress was generally associated with histological classification. However, only 16 of 25 plaque cross sections could be labeled as high-risk (peak cap stress>300 kPa and classified as a thin fibrous cap atheroma). Twenty-eight of 50 plaque cross sections could be labeled as low-risk (a peak cap stress<140 kPa and not a thin fibrous cap atheroma), leading to a κ=0.39. 31 plaques (41%) had a disagreement between both classifications. Because of the limited magnetic resonance imaging voxel size with regard to cap thickness, a noninvasive identification of only a group of low-risk, thick-cap plaques was reliable.

CONCLUSIONS

Instead of trying to target only vulnerable plaques, a more reliable noninvasive identification of a select group of stable plaques with a thick cap and low stress might be a more fruitful approach to start reducing surgical interventions on carotid plaques.

Three-dimensional coronary dark-blood interleaved with gray-blood (cDIG) magnetic resonance imaging at 3 tesla

PURPOSE

Three-dimensional (3D) dark-blood MRI has shown great potential in coronary artery plaque evaluation. However, substantial variability in quantification could result from superficial calcification because of its low signal. To address this issue, a 3D coronary dark-blood interleaved with gray-blood (cDIG) technique was developed.

METHODS

cDIG is based on a balanced steady-state free precession readout combined with a local re-inversion-based double-inversion-recovery (LocReInv-DIR) preparation. The LocReInv-DIR is applied every two RR intervals. Dark-blood and gray-blood contrasts are collected in the first and second RR interval, respectively. To improve the respiratory gating efficiency, two independent navigators were developed to separately gate the respiratory motion for the two interleaved acquisitions. In vivo experiments in eight healthy subjects and one patient were conducted to validate the technique.

RESULTS

cDIG provided dual-contrasts without compromise in scan time. The dark-blood images with cDIG demonstrated excellent wall and lumen signal performances and morphological measurements. Advantageously, cDIG yielded a second contrast that was shown to help identify the superficial calcification in the coronary plaque of a patient.

CONCLUSION

A novel technique was developed for obtaining 3D coronary vessel wall and gray lumen images. The additional contrast may aid in identifying calcified nodules and thus potentially improve the evaluation of coronary plaque burden.

A computer-simulation study on the effects of MRI voxel dimensions on carotid plaque lipid-core and fibrous cap segmentation and stress modeling

Background

The benefits of a decreased slice thickness and/or in-plane voxel size in carotid MRI for atherosclerotic plaque component quantification accuracy and biomechanical peak cap stress analysis have not yet been investigated in detail because of practical limitations.

Methods

In order to provide a methodology that allows such an investigation in detail, numerical simulations of a T1-weighted, contrast-enhanced, 2D MRI sequence were employed. Both the slice thickness (2 mm, 1 mm, and 0.5 mm) and the in plane acquired voxel size (0.62x0.62 mm² and 0.31x0.31 mm²) were varied. This virtual MRI approach was applied to 8 histology-based 3D patient carotid atherosclerotic plaque models.

Results

A decreased slice thickness did not result in major improvements in lumen, vessel wall, and lipid-rich necrotic core size measurements. At 0.62x0.62 mm² in-plane, only a 0.5 mm slice thickness resulted in improved minimum fibrous cap thickness measurements (a 2–3 fold reduction in measurement error) and only marginally improved peak cap stress computations. Acquiring voxels of 0.31x0.31 mm² in-plane, however, led to either similar or significantly larger improvements in plaque component quantification and computed peak cap stress.

Conclusions

This study provides evidence that for currently-used 2D carotid MRI protocols, a decreased slice thickness might not be more beneficial for plaque measurement accuracy than a decreased in-plane voxel size. The MRI simulations performed indicate that not a reduced slice thickness (i.e. more isotropic imaging), but the acquisition of anisotropic voxels with a relatively smaller in-plane voxel size could improve carotid plaque quantification and computed peak cap stress accuracy.

Atherosclerotic plaque fibrous cap assessment under an oblique scan plane orientation in carotid MRI

Carotid magnetic resonance imaging (MRI) is used to noninvasively assess atherosclerotic plaque fibrous cap (FC) status, which is closely related to ischemic stroke. Acquiring anisotropic voxels improves in-plane visualization, however, an oblique scan plane orientation could then obscure a FC (i.e., contrast below the noise level) and thus impair a reliable status assessment. To quantify this, we performed single-slice numerical simulations of a clinical 3.0T, 2D T1-weighted, black-blood, contrast-enhanced pulse sequence with various voxel dimensions: in-plane voxel size of 0.62 mm × 0.62 mm and 0.31 mm × 0.31 mm, slice thickness of 1, 2, and 3 mm. Idealized plaque models (FC thickness of 0.5, 1, and 1.5 mm) were imaged at various scan plane angles (0°-40° in steps of 10°), and the FC contrast was quantified. We found that when imaging thin FCs with anisotropic voxels, the FC contrast decreased when the scan plane orientation angle increased. However, a reduced in-plane voxel size at the cost of an increased slice thickness often led to enhanced FC contrast even in the presence of scan plane orientation angles of up to 40°. It can be concluded that while isotropic-voxel imaging eliminates the issue of scan plane obliqueness, it comes at the cost of reduced FC contrast, thus likely decreasing the reliability of FC status assessment in carotid MRI. If scan plane orientation obliquity at the slice of interest is moderate (<40°) or otherwise diminished through careful scan planning, voxel anisotropy could increase FC contrast and, in effect, increase the reliability of FC status assessment.

Atherosclerotic plaque component segmentation in combined carotid MRI and CTA data incorporating class label uncertainty

Atherosclerotic plaque composition can indicate plaque vulnerability. We segment atherosclerotic plaque components from the carotid artery on a combination of in vivo MRI and CT-angiography (CTA) data using supervised voxelwise classification. In contrast to previous studies the ground truth for training is directly obtained from 3D registration with histology for fibrous and lipid-rich necrotic tissue, and with μCT for calcification. This registration does, however, not provide accurate voxelwise correspondence. We therefore evaluate three approaches that incorporate uncertainty in the ground truth used for training: I) soft labels are created by Gaussian blurring of the original binary histology segmentations to reduce weights at the boundaries between components, and are weighted by the estimated registration accuracy of the histology and in vivo imaging data (measured by overlap), II) samples are weighted by the local contour distance of the lumen and outer wall between histology and in vivo data, and III) 10% of each class is rejected by Gaussian outlier rejection. Classification was evaluated on the relative volumes (% of tissue type in the vessel wall) for calcified, fibrous and lipid-rich necrotic tissue, using linear discriminant (LDC) and support vector machine (SVM) classification. In addition, the combination of MRI and CTA data was compared to using only one imaging modality. Best results were obtained by LDC and outlier rejection: the volume error per vessel was 0.9±1.0% for calcification, 12.7±7.6% for fibrous and 12.1±8.1% for necrotic tissue, with Spearman rank correlation coefficients of 0.91 (calcification), 0.80 (fibrous) and 0.81 (necrotic). While segmentation using only MRI features yielded low accuracy for calcification, and segmentation using only CTA features yielded low accuracy for necrotic tissue, the combination of features from MRI and CTA gave good results for all studied components.