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Background—Abdominal aortic aneurysm (AAA) wall inflammation and mechanical structural stress may influence AAA expansion and lead to rupture. We hypothesized a positive correlation between structural stress and fluorine-18-labeled 2-deoxy-2-fluoro-d-glucose (18F-FDG) positron emission tomography–defined inflammation. We also explored the influence of computed tomography–derived aneurysm morphology and composition, including intraluminal thrombus, on both variables.Methods and Results—Twenty-one patients (19 males) with AAAs below surgical threshold (AAA size was 4.10±0.54 cm) underwent 18F-FDG positron emission tomography and contrast-enhanced computed tomography imaging. Structural stresses were calculated using finite element analysis. The relationship between maximum aneurysm 18F-FDG standardized uptake value within aortic wall and wall structural stress, patient clinical characteristics, aneurysm morphology, and compositions was explored using a hierarchical linear mixed-effects model. On univariate analysis, local aneurysm diameter, thrombus burden, extent of calcification, and structural stress were all associated with 18F-FDG uptake (P<0.05). AAA structural stress correlated with 18F-FDG maximum standardized uptake value (slope estimate, 0.552; P<0.0001). Multivariate linear mixed-effects analysis revealed an important interaction between structural stress and intraluminal thrombus in relation to maximum standardized uptake value (fixed effect coefficient, 1.68 [SE, 0.10]; P<0.0001). Compared with other factors, structural stress was the best predictor of inflammation (receiver-operating characteristic curve area under the curve =0.59), with higher accuracy seen in regions with high thrombus burden (area under the curve =0.80). Regions with both high thrombus burden and high structural stress had higher 18F-FDG maximum standardized uptake value compared with regions with high thrombus burdens but low stress (median [interquartile range], 1.93 [1.60–2.14] versus 1.14 [0.90–1.53]; P<0.0001).Conclusions—Increased aortic wall inflammation, demonstrated by 18F-FDG positron emission tomography, was observed in AAA regions with thick intraluminal thrombus subjected to high mechanical stress, suggesting a potential mechanistic link underlying aneurysm inflammation. [ABSTRACT FROM AUTHOR]

Background--Although plaque rupture is responsible for most myocardial infarctions, few high-risk plaques identified by intracoronary imaging actually result in future major adverse cardiovascular events (MACE). Nonimaging markers of individual plaque behavior are therefore required. Rupture occurs when plaque structural stress (PSS) exceeds material strength. We therefore assessed whether PSS could predict future MACE in high-risk nonculprit lesions identified on virtual-histology intravascular ultrasound. Methods and Results--Baseline nonculprit lesion features associated with MACE during long-term follow-up (median: 1115 days) were determined in 170 patients undergoing 3-vessel virtual-histology intravascular ultrasound. MACE was associated with plaque burden ≥70% (hazard ratio: 8.6; 95% confidence interval, 2.5-30.6; P<0.001) and minimal luminal area ≤4 mm² (hazard ratio: 6.6; 95% confidence interval, 2.1-20.1; P=0.036), although absolute event rates for high-risk lesions remained <10%. PSS derived from virtual-histology intravascular ultrasound was subsequently estimated in nonculprit lesions responsible for MACE (n=22) versus matched control lesions (n=22). PSS showed marked heterogeneity across and between similar lesions but was significantly increased in MACE lesions at high-risk regions, including plaque burden ≥70% (13.9±11.5 versus 10.2±4.7; P<0.001) and thin-cap fibroatheroma (14.0±8.9 versus 11.6±4.5; P=0.02). Furthermore, PSS improved the ability of virtual-histology intravascular ultrasound to predict MACE in plaques with plaque burden ≥70% (adjusted log-rank, P=0.003) and minimal luminal area ≤4 mm² (P=0.002). Plaques responsible for MACE had larger superficial calcium inclusions, which acted to increase PSS (P<0.05). Conclusions--Baseline PSS is increased in plaques responsible for MACE and improves the ability of intracoronary imaging to predict events. Biomechanical modeling may complement plaque imaging for risk stratification of coronary nonculprit lesions. [ABSTRACT FROM AUTHOR]

Background--Although rupture of thin-cap fibroatheroma (TCFA) underlies most myocardial infarctions, reliable TCFA identification remains challenging. Virtual-histology intravascular ultrasound (VH-IVUS) and optical coherence tomography (OCT) can assess tissue composition and classify plaques. However, direct comparisons between VH-IVUS and OCT are lacking and it remains unknown whether combining these modalities improves TCFA identification. Methods and Results--Two hundred fifty-eight regions-of-interest were obtained from autopsied human hearts, with plaque composition and classification assessed by histology and compared with coregistered ex vivo VH-IVUS and OCT. Sixty-seven regions-of-interest were classified as fibroatheroma on histology, with 22 meeting criteria for TCFA. On VH-IVUS, plaque (10.91±4.82 versus 8.42±4.57 mm2; P=0.01) and necrotic core areas (1.59±0.99 versus 1.03±0.85 mm²; P=0.02) were increased in TCFA versus other fibroatheroma. On OCT, although minimal fibrous cap thickness was similar (71.8±44.1 |im versus 72.6±32.4; P=0.30), the number of continuous frames with fibrous cap thickness ≤ 85 µm was higher in TCFA (6.5 [1.75-11.0] versus 2.0 [0.0-7.0]; P=0.03). Maximum lipid arc on OCT was an excellent discriminator of fibroatheroma (area under the curve, 0.92; 95% confidence interval, 0.87-0.97) and TCFA (area under the curve, 0.86; 95% confidence interval, 0.81-0.92), with lipid arc ≥80° the optimal cut-off value. Using existing criteria, the sensitivity, specificity, and diagnostic accuracy for TCFA identification was 63.6%, 78.1%, and 76.5% for VH-IVUS and 72.7%, 79.8%, and 79.0% for OCT. Combining VH-defined fibroatheroma and fibrous cap thickness ≤85 µim over 3 continuous frames improved TCFA identification, with diagnostic accuracy of 89.0%. Conclusions--Both VH-IVUS and OCT can reliably identify TCFA, although OCT accuracy may be improved using lipid arc ≥80° and fibrous cap thickness ≤85 µm over 3 continuous frames. Combined VH-IVUS/OCT imaging markedly improved TCFA identification. [ABSTRACT FROM AUTHOR]