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Combining morphological and biomechanical factors for optimal carotid plaque progression prediction: An MRI-based follow-up study using 3D thin-layer models.

ABSTRACT: Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis, prevention, and treatment. Magnetic resonance image (MRI) data of carotid atherosclerotic plaques were acquired from 20 patients with consent obtained. 3D thin-layer models were constructed to calculate plaque stress and strain. Data for ten morphological and biomechanical risk factors were extracted for analysis. Wall thickness increase (WTI), plaque burden increase (PBI) and plaque area increase (PAI) were chosen as three measures for plaque progression. Generalized linear mixed models (GLMM) with 5-fold cross-validation strategy were used to calculate prediction accuracy and identify optimal predictor. The optimal predictor for PBI was the combination of lumen area (LA), plaque area (PA), lipid percent (LP), wall thickness (WT), maximum plaque wall stress (MPWS) and maximum plaque wall strain (MPWSn) with prediction accuracy?=?1.4146 (area under the receiver operating characteristic curve (AUC) value is 0.7158), while PA, plaque burden (PB), WT, LP, minimum cap thickness, MPWS and MPWSn was the best for WTI (accuracy?=?1.3140, AUC?=?0.6552), and a combination of PA, PB, WT, MPWS, MPWSn and average plaque wall strain (APWSn) was the best for PAI with prediction accuracy?=?1.3025 (AUC?=?0.6657). The combinational predictors improved prediction accuracy by 9.95%, 4.01% and 1.96% over the best single predictors for PAI, PBI and WTI (AUC values improved by 9.78%, 9.45%, and 2.14%), respectively. This suggests that combining both morphological and biomechanical risk factors could lead to better patient screening strategies.

SUBMITTER: Wang Q

PROVIDER: S-EPMC6710108 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Combining morphological and biomechanical factors for optimal carotid plaque progression prediction: An MRI-based follow-up study using 3D thin-layer models.

Wang Qingyu Q Tang Dalin D Wang Liang L Canton Gador G Wu Zheyang Z Hatsukami Thomas S TS Billiar Kristen L KL Yuan Chun C

International journal of cardiology 20190704

Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis, prevention, and treatment. Magnetic resonance image (MRI) data of carotid atherosclerotic plaques were acquired from 20 patients with consent obtained. 3D thin-layer models were constructed to calculate plaque stress and strain. Data for ten morphological and biomechanical risk factors were extracted for analysis. Wall thickness increase (WTI), plaque burden increase (PBI) and plaque ar ...[more]

PMID: 31301863

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Project description:Background and purposeCarotid atherosclerotic plaques with a large lipid-rich necrotic core (LRNC), intraplaque hemorrhage (IPH), and a thin or ruptured fibrous cap are associated with increased stroke risk. Multi-sequence MRI can be used to quantify carotid atherosclerotic plaque composition. Yet, its clinical implementation is hampered by long scan times and image misregistration. Multi-contrast atherosclerosis characterization (MATCH) overcomes these limitations. This study aims to compare the quantification of plaque composition with MATCH and multi-sequence MRI.MethodsMATCH and multi-sequence MRI were used to image 54 carotid arteries of 27 symptomatic patients with ≥2 mm carotid plaque on a 3.0 T MRI scanner. The following sequence parameters for MATCH were used: repetition time/echo time (TR/TE), 10.1/4.35 ms; field of view, 160 mm × 160 mm × 2 mm; matrix size, 256 × 256; acquired in-plane resolution, 0.63 mm2× 0.63 mm2; number of slices, 18; and flip angles, 8°, 5°, and 10°. Multi-sequence MRI (black-blood pre- and post-contrast T1-weighted, time of flight, and magnetization prepared rapid acquisition gradient echo; acquired in-plane resolution: 0.63 mm2 × 0.63 mm2) was acquired according to consensus recommendations, and image quality was scored (5-point scale). The interobserver agreement in plaque composition quantification was assessed by the intraclass correlation coefficient (ICC). The sensitivity and specificity of MATCH in identifying plaque composition were calculated using multi-sequence MRI as a reference standard.ResultsA significantly lower image quality of MATCH compared to that of multi-sequence MRI was observed (p < 0.05). The scan time for MATCH was shorter (7 vs. 40 min). Interobserver agreement in quantifying plaque composition on MATCH images was good to excellent (ICC ≥ 0.77) except for the total volume of calcifications and fibrous tissue that showed moderate agreement (ICC ≥ 0.61). The sensitivity and specificity of detecting plaque components on MATCH were ≥89% and ≥91% for IPH, ≥81% and 85% for LRNC, and ≥71% and ≥32% for calcifications, respectively. Overall, good-to-excellent agreement (ICC ≥ 0.76) of quantifying plaque components on MATCH with multi-sequence MRI as the reference standard was observed except for calcifications (ICC = 0.37-0.38) and fibrous tissue (ICC = 0.59-0.70).Discussion and conclusionMATCH images can be used to quantify plaque components such as LRNC and IPH but not for calcifications. Although MATCH images showed a lower mean image quality score, short scan time and inherent co-registration are significant advantages.

Project description:BackgroundResearch has shown that carotid intima-media thickness (CIMT) could help to predict carotid plaque (CP) progression in patients with mild carotid stenosis. However, the debate continues as to the value of carotid intima thickness (CIT) in monitoring the development of CP in patients with severe carotid stenosis. This study sought to evaluate the relationships between CIT and the ultrasonic characteristics of CP and to analyze the value of CIT and the ultrasonic parameters of CP in assessing plaque vulnerability in advanced human carotid atherosclerosis.MethodsA total of 55 individuals who underwent carotid endarterectomy (CEA) were included in the study (mean age: 65±7 years; female: 9.1%). CIMT and CIT were examined at the common carotid artery (CCA). Plaque textural features, such as the gray-scale median (GSM), superb microvascular imaging (SMI) level, and total plaque area (TPA), were also identified. A Spearman correlation coefficient analysis was performed to examine the relationship between CIT and the ultrasonic parameters of CP. The CIT of various plaque types was compared. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic values of the ultrasound characteristics to evaluate CP vulnerability.ResultsThe mean CIT of all the participants was 0.382±0.095 mm, the mean CIT of the participants with stable plaques was 0.328±0.031 mm, and the mean CIT of participants with vulnerable plaques was 0.424±0.106 mm (P<0.001). CIT was associated with the SMI level (Spearman's correlation coefficient: r=0.392, P=0.005), TPA (Spearman's correlation coefficient: r=0.337, P=0.012). Patients with thicker CIT had larger lipid cores, higher levels of plaque vulnerability, and more intraplaque hemorrhages (IPHs). The areas under the ROCs (AUCs) with 95% confidence interval (CI) for CIMT, CIT, the SMI level, the GSM, the TPA, and the combined model for identifying vulnerable plaques were 0.673 (0.533-0.793), 0.849 (0.727-0.932), 0.771 (0.629-0.879), 0.669 (0.529-0.790), 0.858 (0.738-0.938), and 0.949 (0.854-0.990), respectively.ConclusionsCIT was associated with both the histology and ultrasonic features of CP. CIT may be helpful in the detection of severe CP development.

Dataset Information

Combining morphological and biomechanical factors for optimal carotid plaque progression prediction: An MRI-based follow-up study using 3D thin-layer models.

Publications

Combining morphological and biomechanical factors for optimal carotid plaque progression prediction: An MRI-based follow-up study using 3D thin-layer models.

Similar Datasets

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