Author + information
- Received March 18, 2015
- Revision received June 9, 2015
- Accepted June 14, 2015
- Published online October 1, 2015.
- Bo Zheng, MD∗,†,‡,
- Gary S. Mintz, MD†,
- John A. McPherson, MD§,
- Bernard De Bruyne, MD, PhD‖,
- Naim Z. Farhat, MD¶,
- Steven P. Marso, MD#,
- Patrick W. Serruys, MD, PhD∗∗,
- Gregg W. Stone, MD∗,† and
- Akiko Maehara, MD∗,†∗ ()
- ∗New York–Presbyterian/Columbia University Medical Center, New York, New York
- †Cardiovascular Research Foundation, New York, New York
- ‡Peking University First Hospital, Beijing, China
- §Vanderbilt University School of Medicine, Nashville, Tennessee
- ‖Cardiovascular Center Aalst, OLV-Clinic, Aalst, Belgium
- ¶North Ohio Heart Center/Elyria Memorial Hospital Regional Medical Center, Elyria, Ohio
- #University of Texas Southwestern Medical Center, Dallas, Texas
- ∗∗Erasmus Medical Center, Rotterdam, the Netherlands
- ↵∗Reprint requests and correspondence:
Dr. Akiko Maehara, Cardiovascular Research Foundation, 111 East 59th Street, 12th Floor, New York, New York 10022.
Objectives The study sought to examine the relative importance of lesion location versus vessel area and plaque burden in predicting plaque rupture within nonculprit fibroatheromas (FAs) in patients with acute coronary syndromes.
Background Previous studies have demonstrated that plaque rupture is associated with larger vessel area and greater plaque burden clustering in the proximal segments of coronary arteries.
Methods In the PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree) study 3-vessel grayscale and radiofrequency-intravascular ultrasound was performed after successful percutaneous coronary intervention in 697 patients with acute coronary syndromes. Untreated nonculprit lesion FAs were classified as proximal (<20 mm), mid (20 to 40 mm), and distal (>40 mm) according to the distance from the ostium to the maximum necrotic core site.
Results Overall, 74 ruptured FAs and 2,396 nonruptured FAs were identified in nonculprit vessels. The majority of FAs (73.6%) were located within 40 mm of the ostium, and the vessel area and plaque burden progressively decreased from proximal to distal FA location (both p < 0.001). In a multivariate logistic regression model, independent predictors for plaque rupture included the distance from the ostium to the maximum necrotic core site per millimeter (odds ratio [OR]: 0.86; 95% confidence interval [CI]: 0.76 to 0.98; p = 0.02), plaque burden per 10% (OR: 2.05; 95% CI: 1.63 to 2.58; p < 0.0001), vessel area per mm2 (OR: 1.14; 95% CI: 1.11 to 1.17; p < 0.0001), calcium (OR: 0.09; 95% CI: 0.05 to 0.18; p < 0.0001), and right coronary artery location (OR: 2.16; 95% CI: 1.25 to 3.27; p = 0.006). By receiver-operating characteristic analysis, vessel area correlated with plaque rupture stronger than either plaque burden (p < 0.001) or location (p < 0.001).
Conclusions Large vessel area, plaque burden, proximal location, right coronary artery location, and lack of calcium were associated with FA plaque rupture. The present study suggests that among these variables, vessel area may be the strongest predictor of plaque rupture among non–left main coronary arteries. (PROSPECT: An Imaging Study in Patients With Unstable Atherosclerotic Lesions [PROSPECT]; NCT00180466)
Previous pathologic studies have demonstrated that plaque rupture with thrombosis is the major mechanism leading to acute coronary syndromes (1–4). Lesions with high-risk characteristics, including thin-cap fibroatheromas (TCFAs) and plaque rupture, cluster predominantly in the proximal coronary segment of the left anterior descending artery (LAD) and more diffusely throughout the right coronary artery (RCA) (5–8). Vessel area, shear stress, and other anatomic features contribute to this pattern of longitudinal distribution (7–11); however, whether proximal location independently determines the risk of plaque rupture has remained unclear (7,8). The present study aims to investigate the predictors of plaque rupture among fibroatheromas within nonculprit lesions by using the 3-vessel grayscale and intravascular ultrasound (IVUS)-virtual histology (VH) data from the PROSPECT (Providing Regional Observations to Study Predictors of Events in the Coronary Tree) study.
Patient population and protocol
The enrollment criteria and the methodology of the PROSPECT study have been previously described in detail (12). In brief, 697 patients with acute coronary syndromes underwent grayscale and IVUS-VH examination of the proximal 6 to 8 cm of all the 3 coronary vessels after successful percutaneous coronary intervention of culprit lesions and other severe stenoses. The study was approved by the institutional review board or medical ethics committee at each participating center, and all patients signed written informed consent (12). Of 697 patients enrolled in the PROSPECT study, 454 patients with at least 1 fibroatheroma in a nonculprit vessel comprised the current study population.
Quantitative analysis of coronary angiography and IVUS
Imaging was performed using a synthetic aperture array, 20 MHz, 3.2-F catheter (Eagle Eye, Volcano Corporation, Rancho Cordova, California). During a motorized catheter pullback at 0.5 mm/s, grayscale IVUS was recorded, and radiofrequency data were captured gated to the R-wave (In-Vision Gold, Volcano Corporation). Qualitative and quantitative coronary angiographic assessment of the entire length of the coronary tree was performed at an independent core laboratory (Cardiovascular Research Foundation, New York, New York) using a proprietary methodology modified from standard Medis CMS software version 7.0 (Leiden, the Netherlands); this analysis included each major epicardial coronary artery and every side branch >1.5 mm in diameter. This 3-vessel angiographic analysis served as a roadmap to identify each lesion on the basis of longitudinal axis location (mm). Detailed angiographic, grayscale, and IVUS-VH methodology have been described previously (13). All IVUS images were also analyzed at an independent core laboratory (Cardiovascular Research Foundation). Off-line grayscale and IVUS-VH analyses were performed using: 1) QCU-CMS (Medis) for contouring; 2) pcVH 2.1 software (Volcano Corporation) for contouring and data output; and 3) proprietary qVH software for segmental qualitative assessment and quantitative data output.
A lesion was defined as a segment with ≥3 consecutive frames with ≥40% plaque burden. A fibroatheroma was defined as >10% confluent necrotic core (NC) and was subclassified as TCFA-VH, calcified thick-cap fibroatheroma (CaThCFA), and non-CaThCFA (13). A plaque rupture was defined as a cavity that communicated with the lumen with an overlying residual fibrous cap fragment.
One lesion could have multiple plaque ruptures (14). Rupture sites separated by ≥3 consecutive frames (approximately 1.5 mm) of artery containing smooth lumen contours and no cavity were considered to represent discrete and separate plaque ruptures.
One lesion could also contain more than 1 fibroatheroma. The main fibroatheroma groups (VH-TCFA, CaThCFA, and non-CaThCFA) required 3 consecutive slices demonstrating the same main fibroatheroma subtype. Fibroatheromas were considered multiple and distinct if they were separated by ≥3 consecutive image slices containing a different fibroatheroma subtype or nonfibroatheroma phenotype (13). The fibroatheroma subtype was assigned on the basis of the maximum NC slice. Plaque rupture was also mapped at the fibroatheroma level.
To evaluate the longitudinal distribution of IVUS-identified fibroatheromas, distances were measured from the ostium of the coronary artery to the slice with the greatest amount of NC within the fibroatheroma. Fibroatheromas were assigned to proximal (<20 mm), mid (20 to 40 mm), or distal segments (>40 mm) depending on the distance from the maximum NC site to the ostium of LAD, left circumflex artery (LCX), or RCA.
Categorical variables are presented using frequencies and percentages and compared using chi-square statistics, and continuous variables are presented as median (interquartile range) and compared using the Mann-Whitney U test. For fibroatheroma and lesion-level data, a model with a generalized estimating equation approach was used to compensate for potential cluster effects of multiple lesions and fibroatheromas in the same patient and presented as least squares means with 95% confidence intervals (CI). Multivariate logistic regression analysis was used to determine independent predictors of a plaque rupture. Since plaque rupture could influence IVUS-VH quantitative measures, the IVUS-VH parameters were not included in the analysis. Receiver-operating characteristic (ROC) analysis and calculation of sensitivity and specificity were performed to test the ability of location data and other grayscale parameters to differentiate ruptured fibroatheroma from nonruptured fibroatheroma. All statistical analyses were performed using SAS version 9.1.3 (SAS Institute Inc., Cary, North Carolina). When 2 or more ROC curves were statistically significant, these curves were compared by MedCalc Statistical Software version 13.0 (MedCalc Software, Ostend, Belgium). A p value of <0.05 was considered statistically significant.
Baseline characteristics of the 454 patients with at least 1 nonculprit vessel fibroatheroma who were included in this analysis are shown in Table 1. The median age of the patients was 58.6 years, 80.2% were men, and 17.9% had diabetes mellitus. The prevalence of statin, aspirin, and clopidogrel use at admission was 46.7%, 72.7%, and 62.3%, respectively.
Angiographic, grayscale, and IVUS-VH findings
Patient-level and lesion-level angiographic, grayscale IVUS, and IVUS-VH results are listed in Table 2. Briefly, the median number of lesions per patient identified by angiography and IVUS was 2.0 and 5.0, respectively. In addition, 67.3% of patients had at least 1 TCFA-VH. Among 2,383 analyzed lesions, there were 18.9% with a minimum lumen area <4 mm2 and 9.2% with a plaque burden ≥70%. In total, 74 ruptured fibroatheromas were identified, of which 90.5% (67 of 74) were located in a non–left main coronary location: 18.9% (14 of 74) were in the LAD, 17.6% (13 of 74) were in the LCX, and 54.1% (40 of 74) were in the RCA. The frequency of plaque rupture was 1.7% (14 of 823), 2.2% (13 of 579), and 4.5% (40 of 898) in the LAD, LCX, and RCA, respectively (p = 0.004).
Longitudinal distribution of fibroatheromas in nonculprit vessels
Figure 1 illustrates fibroatheroma distribution every 10 mm axial distance from each coronary ostium. The majority of nonruptured and ruptured fibroatheromas were located in the proximal (43.4%) and middle (30.2%) segments. Nevertheless, the gradient from proximal to distal was least in the RCA, in which fibroatheromas (including plaque rupture) were distributed more evenly compared with the LAD and LCX.
Dividing the fibroatheromas into 4 groups based on the mean external elastic membrane (EEM) area (<10 mm2, 10 to 15 mm2, 15 to 20 mm2, and >20 mm2), fibroatheromas were more likely to be observed in segments with large vessel areas. Fibroatheromas were preferably located in proximal segment with larger vessels in the LAD and LCX. By contrast, the vessel area of the RCA did not differ as dramatically as did the LAD and LCX from the proximal to the distal segments; in the RCA the majority of the segments had an EEM area that was >15 mm2. Therefore, fibroatheromas clustered in large proximal vessels in the LAD and LCX while they seemed to be distributed diffusely throughout the RCA (Figure 2). With respect to mean plaque burden, it was the smallest in the distal segment versus the proximal and middle segments in the LAD and RCA, but not in the LCX (Table 3).
Predictors of plaque rupture among nonculprit, non–left main fibroatheromas
The following potential predictors of plaque rupture in the LAD, LCX, or RCA were assessed in the multivariate logistic regression model: mean EEM area, mean plaque burden, distance from ostium to maximum NC slice, calcium identified by grayscale IVUS, and RCA location. Pooling all non–left main fibroatheromas together, all of these variables were independent predictors of plaque rupture (Table 4). The more proximal the location and the larger the EEM area and plaque burden, the more likely plaque rupture was to develop.
According to the ROC analysis for the predictors of plaque rupture (Figure 3), among fibroatheromas in the LAD, LCX, or RCA, EEM area (area under the curve [AUC]: 0.78, p < 0.001) and plaque burden (AUC: 0.65; p < 0.001), but not the distance from ostium to the maximum NC site (AUC: 0.56; p = 0.09), could discriminate ruptured from nonruptured fibroatheromas. A threshold of EEM area >16.3 mm2 and plaque burden >50% distinguished fibroatheromas with plaque ruptures from those without plaque rupture with a sensitivity of 88.1% and 83.6%, a specificity of 53.9% and 43.4%, a positive predictive value of 5.4% and 4.2%, a negative predictive value of 99.3% and 98.9%, and an accuracy of 54.7% and 44%, respectively. While comparing EEM area versus plaque burden versus longitudinal location, the distance from the ostium was the least predictive for plaque rupture (EEM vs. distance, p < 0.001; plaque burden vs. distance, p = 0.05) while the EEM area (compared with plaque burden) seemed to be a better predictor of plaque rupture (p < 0.001).
Fibroatheromas and ruptures in the left main coronary artery
In total, 7 ruptured fibroatheromas and 163 nonruptured fibroatheromas were identified in the left main coronary artery (frequency of 4.1%) with a spatial distribution that was different from the other 3 coronary arteries. Most of the fibroatheromas (82.8%) were localized in the distal 10 mm segment of the left main artery. Ruptured fibroatheromas had a larger plaque area (15.6 mm2 [95% CI: 12.7 to 16.8] vs. 11.4 mm2 [95% CI: 9.3 to 13.4], p = 0.006) and plaque burden (59.6% [95% CI: 52.2 to 61.5] vs. 46.0% [95% CI: 40.2 to 52.6], p = 0.002), but similar vessel area (27.6 mm2 [95% CI: 22.2 to 27.9] vs. 24.8 mm2 [95% CI: 21.4 to 27.5], p = 0.24) and lumen area (10.8 mm2 [95% CI: 9.8 to 15.0] vs. 13.1 mm2 [95% CI: 10.6 to 15.2], p = 0.24) compared with nonruptured fibroatheromas; however, plaque burden was the only significant predictor (AUC: 0.85; p < 0.001) by ROC analysis. A cut-off value of plaque burden >59.2% discriminated plaque rupture from nonrupture with a sensitivity of 71.4%, a specificity of 92.6%, a positive predictive value of 29.5%, a negative predictive value of 98.7%, and an accuracy of 91.8%.
In the current study we assessed the longitudinal distribution of grayscale and IVUS-VH parameters among fibroatheromas in nonculprit coronary arteries, as well as the impact of vessel area and plaque burden on plaque rupture. The main findings are as follows: 1) there was a gradient of high-risk plaques (fibroatheromas of all types and plaque ruptures) from proximal to distal coronary segments, mainly in the LAD and LCX and least in the RCA; and 2) although proximal location was an independent predictor for plaque rupture, vessel area and plaque burden were better discriminants of plaque rupture versus nonruptured fibroatheromas rather than the distance from the ostium to the maximum NC site.
Previous autopsy, angiographic, IVUS, and optical coherence tomography studies elucidated that the majority of high-risk plaques including ruptured plaques accumulated in proximal segments of the coronary tree (5–8,15–17). Cheruvu et al. (5), Farb et al. (18), and Davies (19) have reported that most histopathologic TCFAs and plaque ruptures clustered in the proximal third of coronary arteries, mainly in the LAD and LCX. This was confirmed by subsequent IVUS and optical coherence tomography studies of the left coronary arteries, but these studies suggested a more uniform distribution in the RCA that was also observed in the current study (6–8). In addition, high-risk left main coronary artery plaque was more likely to occur close to the distal left main coronary artery bifurcation (20), as also seen in the current study.
Kotani et al. (21) reported that culprit lesions with plaque rupture had a larger EEM area and plaque mass than nonculprit lesions among patients with ST-segment elevation myocardial infarction. In addition, by using IVUS across the entire coronary arteries, Wykrzykowska et al. (8) and Golinvaux et al. (7) found a significant gradient of both EEM area and plaque burden from proximal to distal in the LAD but not in the RCA. Furthermore, the plaque burden and EEM area were much larger in the distal RCA compared with distal LAD (8). Larger vessel area with greater plaque burden was more likely to coexist with positive remodeling that has also been considered as a morphologic feature of vulnerable coronary disease (22–24). In the current study, EEM area (>17.1 mm2) and plaque burden (>50%) were identified as independent risk factors of plaque rupture. Less anatomic tapering with potentially higher EEM volumes and plaque burden (both independent predictors for plaque burden in this analysis) may explain the more uniform distribution of high-risk fibroatheromas in the RCA. The power of the EEM area as a predictor of plaque rupture might be that it integrates vessel area, plaque burden, and positive remodeling, all of which may be important.
Disturbed coronary flow with low shear stress plays an important role in the pathogenesis of the atherosclerotic plaque that often develops near arterial bifurcations, branch ostia, and curvatures (25). Thus, the proximal segments of the LAD and LCX with major side branches promote the development of disturbed flow that could also occur near the distal left main coronary artery bifurcation. The absence of branches in the RCA may be another explanation for the diffuse distribution of high-risk plaques.
In the present study, there was a preponderance of FA plaque ruptures in the RCA. There are a number of possible explanations. One is that FA ruptures in the LAD or in a large LCX may more likely be immediately fatal. Another explanation is that the RCA is longer, larger, tapers less, has a larger plaque burden, and is typically diffusely diseased over a longer segment (i.e., ostium to distal bifurcation) compared to the LAD or LCX (26); therefore, there are more potential sites for the development of a rupture-prone FA.
First, in the current analysis, patients were enrolled after successful percutaneous coronary intervention treatment of the culprit lesion(s); culprit lesions were not included in the current analysis. Second, most of the analysis was performed at the fibroatheroma level; however, nonfibroatheromas are less likely to lead to cardiac events (27). Third, due to the fact that plaque rupture could affect the quantitative IVUS-VH data, the multivariate logistic regression model did not include IVUS-VH parameters. Finally, side branches were not studied.
The current analysis from the PROSPECT study demonstrated that plaque rupture was associated with larger vessel area, greater plaque burden, and proximal location within nonculprit coronary arteries; however, EEM area was the strongest predictor for plaque rupture in the LAD, LCX, and RCA, while plaque burden seemed to be the most important risk factor for plaque rupture in the left main coronary artery.
COMPETENCY IN MEDICAL KNOWLEDGE: Among nonculprit lesions of patients with acute coronary syndromes who were enrolled in the PROSPECT study, proximal lesion location, increasing vessel size, and plaque burden detected by grayscale IVUS were more likely to be associated with plaque rupture. In addition, larger vessel area (EEM >16.3 mm2) was the best marker for plaque rupture in non–left main lesions; and a greater plaque burden (>60%) was the best marker of ruptured plaque in left main lesions.
TRANSLATIONAL OUTLOOK: Further investigations are needed to validate these findings, especially the influence of vessel size on plaque rupture and the value of grayscale IVUS parameters in predicting plaque rupture and future cardiovascular events.
Dr. Zheng has received a research grant from Boston Scientific. Dr. Mintz is a consultant for Volcano Corporation, Boston Scientific, InfraReDx, and ACIST; has received fellowship/grant support from Volcano Corporation, Boston Scientific, and InfraReDx; and has received honoraria from Boston Scientific, InfraReDx, and ACIST. Dr. McPherson has received consultant fees from Cardiox, Inc., Healthwise, Inc., and Velomedix Inc. Dr. De Bruyne's institution receives grant support and consulting fees on his behalf from St. Jude Medical. Dr. Marso is a consultant for St. Jude Medical, Novo Nordisk, and The Medicines Company; and has received research grants from Bristol-Myers Squibb, Novo Nordisk, Terumo, The Medicines Company, and Volcano Corporation. Dr. Maehara has received grant support from Boston Scientific; is a consultant for ACIST and Boston Scientific; and has received speaker fees from St. Jude Medical. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. H. Vernon Anderson, MD, served as Guest Editor for this paper.
- Abbreviations and Acronyms
- area under the curve
- calcified thick-cap fibroatheroma
- external elastic membrane
- intravascular ultrasound
- left anterior descending artery
- left circumflex artery
- necrotic core
- right coronary artery
- receiver-operating characteristic
- thin-cap fibroatheroma
- virtual histology
- Received March 18, 2015.
- Revision received June 9, 2015.
- Accepted June 14, 2015.
- American College of Cardiology Foundation
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