36 research outputs found

    Heterogeneous plaque-lumen geometry is associated with major adverse cardiovascular events.

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    AIMS Prospective studies show that only a minority of plaques with higher risk features develop future major adverse cardiovascular events (MACE), indicating the need for more predictive markers. Biomechanical estimates such as plaque structural stress (PSS) improve risk prediction but require expert analysis. In contrast, complex and asymmetric coronary geometry is associated with both unstable presentation and high PSS, and can be estimated quickly from imaging. We examined whether plaque-lumen geometric heterogeneity evaluated from intravascular ultrasound affects MACE and incorporating geometric parameters enhances plaque risk stratification. METHODS AND RESULTS We examined plaque-lumen curvature, irregularity, lumen aspect ratio (LAR), roughness, PSS, and their heterogeneity indices (HIs) in 44 non-culprit lesions (NCLs) associated with MACE and 84 propensity-matched no-MACE-NCLs from the PROSPECT study. Plaque geometry HI were increased in MACE-NCLs vs. no-MACE-NCLs across whole plaque and peri-minimal luminal area (MLA) segments (HI curvature: adjusted P = 0.024; HI irregularity: adjusted P = 0.002; HI LAR: adjusted P = 0.002; HI roughness: adjusted P = 0.004). Peri-MLA HI roughness was an independent predictor of MACE (hazard ratio: 3.21, P < 0.001). Inclusion of HI roughness significantly improved the identification of MACE-NCLs in thin-cap fibroatheromas (TCFA, P < 0.001), or with MLA ≀ 4 mm2 (P < 0.001), or plaque burden (PB) ≄ 70% (P < 0.001), and further improved the ability of PSS to identify MACE-NCLs in TCFA (P = 0.008), or with MLA ≀ 4 mm2 (P = 0.047), and PB ≄ 70% (P = 0.003) lesions. CONCLUSION Plaque-lumen geometric heterogeneity is increased in MACE vs. no-MACE-NCLs, and inclusion of geometric heterogeneity improves the ability of imaging to predict MACE. Assessment of geometric parameters may provide a simple method of plaque risk stratification

    VH-IVUS and OCT identification of TCFA

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    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 mm(2); P=0.01) and necrotic core areas (1.59±0.99 versus 1.03±0.85 mm(2); P=0.02) were increased in TCFA versus other fibroatheroma. On OCT, although minimal fibrous cap thickness was similar (71.8±44.1 ÎŒm versus 72.6±32.4; P=0.30), the number of continuous frames with fibrous cap thickness ≀85 ÎŒm 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 ÎŒm 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 ÎŒm over 3 continuous frames. Combined VH-IVUS/OCT imaging markedly improved TCFA identification.This study was funded by grants from the British Heart Foundation (FS/13/33/30168), Heart Research UK (RG2638/14/16), the Cambridge NIHR Biomedical Research Centre, and the BHF Cambridge Centre for Research Excellence.This is the final version of the article. It first appeared from American Heart Association via http://dx.doi.org/10.1161/CIRCIMAGING.115.00348
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