Sophie Z Gu, Yuan Huang, Charis Costopoulos, Benn Jessney, Christos Bourantas, Zhongzhao Teng, Sylvain Losdat, Akiko Maehara, Lorenz Räber, Gregg W Stone, Martin R Bennett
{"title":"斑块-管腔几何形状的异质性与重大不良心血管事件有关。","authors":"Sophie Z Gu, Yuan Huang, Charis Costopoulos, Benn Jessney, Christos Bourantas, Zhongzhao Teng, Sylvain Losdat, Akiko Maehara, Lorenz Räber, Gregg W Stone, Martin R Bennett","doi":"10.1093/ehjopen/oead038","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>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.</p><p><strong>Methods and results: </strong>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 <i>P</i> = 0.024; HI irregularity: adjusted <i>P</i> = 0.002; HI LAR: adjusted <i>P</i> = 0.002; HI roughness: adjusted <i>P</i> = 0.004). Peri-MLA HI roughness was an independent predictor of MACE (hazard ratio: 3.21, <i>P</i> < 0.001). Inclusion of HI roughness significantly improved the identification of MACE-NCLs in thin-cap fibroatheromas (TCFA, <i>P</i> < 0.001), or with MLA ≤ 4 mm<sup>2</sup> (<i>P</i> < 0.001), or plaque burden (PB) ≥ 70% (<i>P</i> < 0.001), and further improved the ability of PSS to identify MACE-NCLs in TCFA (<i>P</i> = 0.008), or with MLA ≤ 4 mm<sup>2</sup> (<i>P</i> = 0.047), and PB ≥ 70% (<i>P</i> = 0.003) lesions.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":11973,"journal":{"name":"European Heart Journal Open","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9b/b0/oead038.PMC10152392.pdf","citationCount":"0","resultStr":"{\"title\":\"Heterogeneous plaque-lumen geometry is associated with major adverse cardiovascular events.\",\"authors\":\"Sophie Z Gu, Yuan Huang, Charis Costopoulos, Benn Jessney, Christos Bourantas, Zhongzhao Teng, Sylvain Losdat, Akiko Maehara, Lorenz Räber, Gregg W Stone, Martin R Bennett\",\"doi\":\"10.1093/ehjopen/oead038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>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.</p><p><strong>Methods and results: </strong>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 <i>P</i> = 0.024; HI irregularity: adjusted <i>P</i> = 0.002; HI LAR: adjusted <i>P</i> = 0.002; HI roughness: adjusted <i>P</i> = 0.004). Peri-MLA HI roughness was an independent predictor of MACE (hazard ratio: 3.21, <i>P</i> < 0.001). Inclusion of HI roughness significantly improved the identification of MACE-NCLs in thin-cap fibroatheromas (TCFA, <i>P</i> < 0.001), or with MLA ≤ 4 mm<sup>2</sup> (<i>P</i> < 0.001), or plaque burden (PB) ≥ 70% (<i>P</i> < 0.001), and further improved the ability of PSS to identify MACE-NCLs in TCFA (<i>P</i> = 0.008), or with MLA ≤ 4 mm<sup>2</sup> (<i>P</i> = 0.047), and PB ≥ 70% (<i>P</i> = 0.003) lesions.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":11973,\"journal\":{\"name\":\"European Heart Journal Open\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9b/b0/oead038.PMC10152392.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Heart Journal Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/ehjopen/oead038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/5/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Heart Journal Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ehjopen/oead038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/5/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目的:前瞻性研究表明,只有少数具有较高风险特征的斑块会在未来发生重大不良心血管事件(MACE),这表明需要更多的预测标记物。斑块结构应力(PSS)等生物力学估计值可改善风险预测,但需要专家分析。相比之下,复杂和不对称的冠状动脉几何形状与不稳定表现和高 PSS 相关,并且可以通过成像快速估算。我们研究了血管内超声评估的斑块-管腔几何异质性是否会影响 MACE,以及纳入几何参数是否会增强斑块风险分层:我们检查了PROSPECT研究中44个与MACE相关的非病灶(NCL)和84个倾向匹配的无MACE-NCL的斑块-管腔弯曲度、不规则度、管腔纵横比(LAR)、粗糙度、PSS及其异质性指数(HIs)。在整个斑块和近端管腔区 (MLA) 区段中,MACE-NCLs 的斑块几何 HI 均比无 MACE-NCLs 高(HI 曲度:调整后 P = 0.024;HI 不规则度:调整后 P = 0.002;HI LAR:调整后 P = 0.002;HI 粗糙度:调整后 P = 0.004)。围 MLA HI 粗糙度是 MACE 的独立预测因子(危险比:3.21,P < 0.001)。纳入 HI 粗糙度可显著提高薄帽纤维瘤(TCFA,P < 0.001)、MLA ≤ 4 mm2(P < 0.001)或斑块负荷(PB)≥ 70% 的 MACE-NCLs 的识别率(P < 0.001),并进一步提高了PSS识别TCFA(P = 0.008)或MLA≤4 mm2(P = 0.047)、PB≥70%(P = 0.003)病变中MACE-NCLs的能力:结论:MACE 与无 MACE-NCL 相比,斑块-管腔几何异质性增加,纳入几何异质性可提高成像预测 MACE 的能力。几何参数评估可为斑块风险分层提供一种简单的方法。
Heterogeneous plaque-lumen geometry is associated with major adverse cardiovascular events.
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.