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European Heart Journal Advance Access originally published online on January 13, 2006
European Heart Journal 2006 27(6):655-663; doi:10.1093/eurheartj/ehi716
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© The European Society of Cardiology 2006. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Distance from the ostium as an independent determinant of coronary plaque composition in vivo: an intravascular ultrasound study based radiofrequency data analysis in humans

Marco Valgimigli, Gastón A. Rodriguez-Granillo, Héctor M. Garcia-Garcia, Patrizia Malagutti, Evelyn Regar, Peter de Jaegere, Pim de Feyter and Patrick W. Serruys*

Erasmus Medical Center, Thoraxcenter Bd-406, Dr Molewaterplein 40, 3015-GD Rotterdam, The Netherlands

Received 15 June 2005; revised 3 November 2005; accepted 15 December 2005; online publish-ahead-of-print 13 January 2006.

* Corresponding author. Tel: +31 10 4635260; fax: +31 10 4369154. E-mail address: p.w.j.c.serruys{at}erasmusmc.nl


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 Limitations of the study
 Conclusion
 References
 
Aims Relative plaque composition, more than its morphology alone, is thought to play a pivotal role in determining propensity to vulnerability. Thus, we investigated in vivo whether the distance from coronary ostium to plaque location independently affects plaque composition in humans. This may help explaining the recently reported non-uniform distribution of culprit lesions along the vessel in acute coronary syndromes.

Methods and results In 51 consecutive patients (45 men), aged 38–76 years (mean age: 58±10), a non-culprit vessel was investigated through spectral analysis of IVUS radiofrequency data (IVUS-Virtual HistologyTM). The study vessel was the left anterior descending artery in 23 (45%) patients; the circumflex artery in nine (18%), and right coronary artery in 19 (37%). The overall length of the region of interest, subsequently divided into 10 mm segments, was 41.5±13 mm long (range: 30.2–78.4). No significant change was observed in terms of relative plaque composition along the vessel with respect to fibrous, fibrolipidic, and calcified tissue, whereas the percentage of lipid core resulted to be increased in the first (median: 8.75%; IQR: 5.7–18) vs. the third (median: 6.1%; IQR: 3.2–12) (P=0.036) and fourth (median: 4.5%; IQR: 2.4–7.9) (P=0.006) segment. At multivariable regression analysis, distance from the ostium resulted to be an independent predictor of relative lipid content [ß=–0.28 (95%CI: –0.15, –0.41)], together with older age, unstable presentation, no use of statin, and presence of diabetes mellitus.

Conclusion Plaque distance from the coronary ostium, as an independent determinant of relative lipid content, is potentially associated to plaque vulnerability in humans.

Key Words: Plaque • Lipid core • Imaging • Vulnerable plaque • Virtual histology

Coronary plaque rupture or erosion, by triggering local thrombosis is thought to play a pivotal role in the genesis of acute coronary syndromes (ACS) and sudden death.1,2

A series of landmark angiographic studies in the mid-1980s demonstrated that nearly two-thirds of all myocardial infarction originate from non-flow limiting atherosclerotic lesions and prior angiographic studies focusing on plaque morphology alone failed to identify quiescent plaques prone to rapidly progress or rupture.3–7

Consequently, the mechanical and biological properties of coronary plaques, which overall reflect plaque composition, along with systemic inflammation has mainly been targeted for the diagnosis and treatment of plaque instability.8

Epidemiological studies in patients with ST-segment elevation myocardial infarction (STEMI) report that sites of occlusion are not uniformly distributed throughout each of the major epicardial coronary arteries but tended to cluster within the proximal third of each of the vessels.9,10 Accordingly, despite the recognition that several factors involved in the pathogenesis of plaque vulnerability are widespread,11–14 local trigger(s) should be also targeted to explain the presence of high-risk coronary spots.15

Plaque composition, favouring propensity to vulnerability, might also be non-uniformly distributed along each coronary vessel. This might explain the higher likelihood for plaque erosion or rupture to occur proximally in the coronary tree.

To investigate this hypothesis, the non-culprit, non-treated vessel containing angiographically non-obstructive (<50%) lesions was systematically investigated to assess plaque composition through spectral analysis of IVUS radiofrequency data [IVUS-Virtual HistologyTM (IVUS-VH)] in consecutive patients referred to our institution for percutaneous coronary intervention (PCI).

Our findings support for the first time to the best of our knowledge in vivo the hypothesis that plaque composition in humans may differ in relation to plaque localization along the coronary tree.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 Limitations of the study
 Conclusion
 References
 
Study protocol and patients enrolment
This was a single-center, investigators-driven, observational prospective study aimed to evaluate the distribution of plaque composition along the coronary vessel in consecutive patients referred to our institution for elective or urgent PCI, in whom the non-culprit, non-treated vessel was judged suitable for a safe IVUS 30 mm-pullback or more, based on angiographic (absence of the following: >50% stenotic disease, extensive calcification, severe vessel tortuosity) and clinical (haemodynamic stability) findings. According to the protocol, not more than one vessel-per patient could be evaluated and the region of interest (ROI), subsequently divided into 10 mm segments, had to start from the coronary ostium. Thus, an analysable interrogated vessel length of at least 30 mm, starting from coronary ostium, was the main selection criterion, once the patient was included in the study.

In the group of patients presenting with an ACS, the culprit lesion has been categorized as complex or non-complex, based on angiographic findings as previously described.12

This protocol was approved by the Hospital Ethics Committee and is in accordance with the declaration of Helsinki. Written informed consent was obtained from every patient.

IVUS-VH acquisition and analysis
Details regarding the validation of the technique, on explanted human coronary segments, have previously been reported.16 Briefly, IVUS-VH uses spectral analysis of IVUS radiofrequency data to construct tissue maps that classify plaque into four major components. In preliminary in vitro studies, four histological plaque components (fibrous, fibro-lipid, lipid core, and calcium) were correlated with a specific spectrum of the radiofrequency signal.16 These different plaque components were assigned colour codes. Calcified, fibrous, fibrolipidic, and lipid-necrotic regions were labelled white, green, greenish-yellow, and red, respectively.17

IVUS-VH data was acquired after intracoronary administration of nitrates using a continuous pullback (0.5 mm/s) with a commercially available mechanical sector scanner (UltracrossTM 2.9F 30 MHz catheter, Boston Scientific, Santa Clara, CA), by a dedicated IVUS-VH console (Volcano Therapeutics, Rancho Cordova, CA). The IVUS-VH data were stored on a CD-ROM and sent to the imaging core lab for offline analysis. IVUS B-mode images were reconstructed from the RF data by customized software (IVUSLab, Volcano Therapeutics, Rancho Cordova, CA).17 Manual contour detection of both the lumen and the media-adventitia interface was performed and the RF data was normalized using a technique known as ‘Blind Deconvolution’, an iterative algorithm that deconvolves the catheter transfer function from the backscatter, thus accounting for catheter-to-catheter variability.18,19

Statistical analysis
The sample size was calculated on the assumption that plaques located in the proximal segment of the coronary artery, defined as the first 10 mm coronary segment, would display a mean lipid content of around 40%, with a sigma of around 35% based on previous findings,20 with a lipid content of 10% in the distal plaques, defined as those located beyond the first 20 mm from the coronary ostium. To detect this effect size with 80% power and a type-I error (alpha) of 0.05, 48 patients were required. Four main models were constructed based on the number of 10 mm segments that were included.

  • Model 1 comprised three 10 mm segments available in all patients included.
  • Model 2 comprised four 10 mm segments available in 43 patients.
  • Models 3 and 4, composed of five and six 10 mm segments in 20 and 11 patients, respectively, were considered as exploratory analysis because of limited sample size.

Values are expressed as mean±SD and median and inter-quartile range (IQR) as appropriate.

As all cross-sectional areas (CSA) provided by IVUS analysis, were shown to have a non-normal distribution at Kolmogorov–Smirnov goodness-of-fit test, they were log-transformed before analysis. Similarly, to all percentages relative to stenosis rate and plaque composition were applied an arcsin transformation.21 Comparisons between the two groups were performed with the Student's t-test. Fisher's exact test was used for categorical variables. Comparisons among 10 mm segments were accomplished through a general linear mixed model with a compound symmetry correlation structure and the intercept as only random effect. Maximum likelihood method was adopted to estimate parameters in the models. Linear contrasts were applied to evaluate effects of distance, analysed as dummy variable, on the studied parameters. Post hoc comparisons were systematically performed by Turkey honest significance difference test.22

Because of limited statistical power in models 3 and 4, the multivariable analysis regarding both clinical presentation and plaque location along the vessel, along with the interaction between the two was restricted to models 1 and 2.

In order to establish the determinants of lipid relative content in the plaques in our model and confirm distance from the coronary ostium as an independent predictor of relative lipid content, a univariate (including age, sex, history of hypertension, hypercholesterolaemia, cardiovascular disorders in the family, diabetes mellitus, levels of LDL, HDL, and triglycerides, use of statin, coronary vessel analysed, clinical presentation, and distance for the ostium stratified into 10 mm segments) and multivariable (with all variables showing a P-value of ≤0.1 at univariate analysis) linear mixed model using percentage of lipid content in all 10 mm segments, analysed as outcome variable, was also applied.

All statistical tests were two-tailed. Probability was significant at a level of <0.05. Statistical analysis was performed using Statistica 6.1 Software (Statsoft Inc.) and R-language (R Foundation).


   Results
Top
 Abstract
 Methods
 Results
Discussion
 Limitations of the study
 Conclusion
 References
 
From 16 April 2003 to 10 September 2004, 67 patients were prospectively included in the protocol. Sixteen patients were subsequently excluded from the final analysis because of short (<30 mm) IVUS pullback in 10, poor IVUS quality in two and lack of coronary plaque at IVUS investigation in four patients. Thus, 51 patients (45 men), aged 38–76 years (mean age: 58±10) constituted the final patient population. Their baseline characteristics are provided in Table 1. Overall, 33 patients were affected by stable angina (SA), whereas the remaining 18 patients were admitted to hospital because of a non-ST-elevation ACS. In the SA group, the mean Cardiovascular Canadian Score was 2±1, whereas the TIMI risk score, the percentage of patients with troponin T above upper limit of normal (0.02 µg/L) and the delay from symptoms onset to PCI were 4±2, 56% and 4±3 days in the ACS group, respectively. In the ACS group, the culprit lesion was located in the proximal coronary segments in 13 (72%) patients, including 6 (33%) in the left anterior descending artery (LAD), four (22%) in the circumflex artery (CFX), and three (17%) in the right coronary artery (RCA), while in the remaining five (28%) patients the culprit lesion was located in the mid or distal segment of the coronary vessels. Overall, 11 out of 18 identified culprit lesions in the ACS group satisfied the criteria for complex lesions based on angiographic findings. The study vessel was the LAD artery in 23 (45%) patients, the CFX in nine (18%), and RCA in 19 (37%). The overall length of the ROI was 41.5±13 mm long [(range: 30.2–78.4) (41±13 in SA group vs. 42±13 in ACS group, P=0.6)]. The results regarding quantitative coronary IVUS analysis in the whole population, stratified into 10 mm vessel length (paired-segment analysis), are reported in Table 2. Lumen CSA significantly decreased every 10 mm in model 1, whereas this happened starting from the third segment, as compared with first coronary tract, in model 2.


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  		Table 1 Study population
 

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  		Table 2 Quantitative vessel analysis at IVUS
 
As compared with ostial 10 mm segment, vessel CSA resulted to be decreased in the third and fourth segment in models 1 and 2, respectively, whereas plaque CSA reduction reached statistical significance only in the fourth segment of model 2. Distance from the coronary ostium did not affect the percentage of stenosis. The third and fourth models, restricted to a progressively lower number of patients but based on a longer vessel length, mainly confirmed the trends observed in the first two models.

Change in plaque composition along the study vessel
The results regarding quantitative coronary plaque composition analysis are reported in Table 3.


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  		Table 3 Plaque composition stratified into 10 mm segments
 
Fibrous tissue was the most prevalent component of plaque composition in each 10 mm segment throughout the four models considered, followed by fibrolipidic tissue, lipidic core, and calcium.

No significant change was observed in terms of relative plaque composition passing from the most proximal to those progressively more distally located segments along the vessel with respect to fibrous, fibrolipidic, and calcified tissue. Conversely, the percentage of lipid core resulted to be increased in the first [(mean: 13%; 95%CI: 10, 16), (median: 8.75%; IQR: 5.7, 18)] with respect to the third segment [(mean: 8.7%; 95%CI: 6.5, 11), (median: 6.2%; IQR: 2.6, 12.1)] in model 1 (P<0.05; primary endpoint) and to third [(mean: 8.4%; 95%CI: 6, 11), (median: 6.1%; IQR: 3.2–12)] (P<0.05) and fourth [(mean: 6.8%; 95%CI: 4, 9.6), (median: 4.5%; IQR: 2.4–7.9)] (P<0.01) segment in model 2 (Figure 3). A similar shift in relative plaque composition along the vessel was observed in models 3 and 4. Interestingly, ACS patients presenting with the culprit lesion located in the proximal segment of the coronary artery did not differ in terms of relative plaque distribution along the vessel with respect to those with culprit lesion sited in the mid of distal tract.


Figure 7163
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  		Figure 3 IVUS-VH CSA along a coronary vessel. IVUS-VH cross-sectional areas in a representative patient showing the change in plaque composition (calcium: white; fibrous: green; fibrolipidic: greenish-yellow; and lipid core: red) along the longitudinal axis of the vessel. LM, left main coronary artery; CFX, circumflex artery; LAD, left anterior descending artery. The distance between the cross-sectional area and the ostium of the vessel is reported in millimetres (mm).

 
Clinical presentation and change in plaque composition along the study vessel
No significant change in calcium content with respect to clinical presentation (stable vs. unstable) was observed (data not shown). In model 1, fibrous plaque content was overall significantly increased in stable (68%) [95%CI: 65%, 71%] vs. unstable (63%) [95%CI: 59%, 64.7%] group, whereas a decrease in stable (17%) [95%CI: 16%, 19%] vs. unstable (22%) [95%CI: 20%, 24%] patients was observed for fibrolipid content when all 227 segments were pooled together (P=0.03 and P=0.006, respectively). However, when distance from the ostium, stratified into 10 mm segments, was also inserted into the model, only trends towards increase in fibrous and decrease in fibrolipidic content in stable vs. unstable patients were observed, which did not reach statistical significance. This was confirmed in model 2. In contrary, even when analysed simultaneously, both plaque location along the vessel (P=0.044 and P=0.002 for models 1 and 2, respectively) and clinical presentation (stable vs. unstable) (P=0.01 and P=0.004 for models 1 and 2, respectively) resulted to be independent predictors of lipid content (Figures 1B and 2B) after adjustment for age, sex, diabetic status, type of coronary artery analysed, and use of statin. Finally, in order to evaluate whether the shift in lipid content along the vessel was influenced by clinical presentation, the interplay between these two main determinants of lipid content was investigated, but no statistical interaction emerged between plaque location and lipid core content (P=0.8 and P=0.49 for models 1 and 2, respectively).


Figure 7161
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  		Figure 1 Relative change in plaque composition with respect to segment 1. Starting from segment 3, relative lipid content showed a progressive decrease with respect to ostial segment (segment 1) taken as a reference. Relative changes in segments 2 and 3 were calculated using model 1, whereas for the relative change in segments 4, 5, and 6, models 2, 3, and 4 were employed, respectively. All relative changes are expressed as mean value and standard deviation.

 

Figure 7162
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  		Figure 2 Per-segment distribution of relative lipid content in the study population. Per-segment distribution of relative lipid contents both in the whole population and stable vs. unstable patients in model 1 (A) and 2 (B). Bars indicate median values in the whole population. As shown in Table 3, relative lipid content significantly decreased in the whole population in segment 3 in model 1 and in segments 3 and 4 in model 2 with respect to segment 1 at post hoc analysis.

 
Distance from the ostium as an independent predictor of lipid content
In Table 4 the variables found to be associated to the relative lipid content along the vessel are shown. The lipid core in the most distally located coronary segment (segment 3) in model 1 was significantly lower compared with segment 1, taken as a reference, independently from all other identified predictors. When all 227 segments were included in the model, distance from the ostium, stratified into 10 mm segments, resulted to be an independent predictor of relative lipid content along vessel wall, together with older age, unstable presentation, no use of statin, and the presence of diabetes mellitus. In keeping with the results obtained at the post hoc analysis, after adjusting for clinical presentation, relative lipid content in segment 1 did not differ from segment 2 [ß –0.08 (95%CI: –0.28, 0.116)], while it did so starting from segment 3 [ß –0.22 (95%CI: ß 0.39, ß 0.05)], with a progressively lower ß-value for segment 4 [ß –0.34 (95%CI: –0.39, –0.05)] and 5 [ß –0.38 (95%CI: –0.55, –0.21)].


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  		Table 4 Predictors of plaque lipid content at uni- and multi-variate analysis in model 1
 

   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
Limitations of the study
 Conclusion
 References
 
Several lines of research in the last decades have clearly pointed out how factors involved in pathogenesis and progression of atherosclerotic lesions are widespread throughout the circulatory bed.8,11,12,14,23,24

As a corollary to this, evidence that a single pharmacological or mechanical treatment, when applied locally, is able to affect progression of coronary atherosclerosis is weak and not conclusive.25 On the other hand, systemic therapy, such as an intensive lipid-lowering treatment, has been convincingly shown to be able to stop atherosclerotic disease progression and even induce coronary lesions regression in some studies.26–30 The same paradigm is thought to be true for factors involved in atherosclerotic lesions vulnerability, albeit probably in a more elusive way.25

These findings should be combined, however, with the evidence provided by recent epidemiological studies, which corroborate the hypothesis according to which sites of occlusions are not uniformly distributed throughout the coronary tree, rather they show a tendency to cluster in partially predictable hot spots located within the proximal third of each coronary vessels.9,10

Thus, the interplay among systemic and local factors able to promote progression and vulnerability of atherosclerotic coronary lesions should be probably both targeted in the attempt to control the chronic and acute consequences of coronary atherosclerosis.15

Among local factors known to affect genesis and progression of coronary atherosclerotic lesions, shear stress (SS) has been extensively investigated.

Fluid SS, acting on genes ‘sensitive’ to local haemodynamic forces, is known to elicit a large number of humoural, metabolic, and structural responses in endothelial cells (EC).31 Low SS on ECs partially explains the local arterial susceptibility to atherosclerosis, as low SS enhances the oxidation of lipids and their accumulation in the intima.31,32

Moreover, fluid turbulence in itself is able to directly activate platelets, thus possibly playing a pivotal role in thrombogenesis as well.33

It is tempting to speculate that other local factors could play additional roles in modulating progression and instability of atherosclerotic lesions in coronary arteries. Among them, pathological studies have suggested that the distribution of thin-cap atheromas, which are lipid rich core plaques known to be at particularly high-risk for rupture, are not uniformly distributed along the coronary vessels in post-mortem examinations.34 Rather, they cluster in the proximal segments of the three main coronary arteries, which is in keeping with the longitudinal distribution of both ruptured and healed plaques.34

This non-uniform distribution of vulnerable plaques in humans could partially explain the clustering of occlusive culprit lesion in the proximal or middle tract of coronary arteries. In this regard, we hypothesized that plaque composition was also not uniformly distributed in vivo in humans in patients with symptomatic coronary disease. Thanks to a recently developed technology based on spectral analysis of IVUS radiofrequency data (IVUS-VH),16,17 we prospectively evaluated whether plaque composition is independently affected by the distance from coronary ostium in a consecutive series of patients. Our findings support the concept that coronary plaques located in the proximal tract ({approx}20 mm) of coronary vessels are relatively richer in lipid content with respect to those more distally located, independently from clinical presentation. In this regard, the magnitude of lipid content appeared to be relatively higher in patients presenting with clinical instability but no interaction emerged in our model between clinical presentation and lipid content, suggesting that the relative change in plaque composition along the vessel is a well-preserved phenotype in both groups of patients. Moreover, distance from the coronary ostium resulted to be an independent predictor of relative lipid content along the vessel wall in our regression model, together with age, unstable presentation, presence of diabetes mellitus, and no use of statin.

Our current findings should be regarded as an attempt to extend the pathophysiological knowledge on plaque vulnerability, mainly because of the well-known linkage between plaque composition and risk of plaque rupture or erosion.34–36 Thus, this might contribute to explain the higher likelihood for plaque erosion or rupture to occur proximally in the coronary tree. Moreover, the finding that coronary plaques show a relatively higher lipid content if proximally located along the longitudinal axis of the vessel with respect to those more distally located might elicit new methodological issues in future investigations. In particular, hypothesizing that plaque progression/regression studies accomplished through aggressive lipid-lowering regimen would mainly affect the lipid content in the plaque, it seems reasonable to believe that the relative effect of the tested medication observed at IVUS investigation in terms of overall plaque CSA, could differ in relation to the localization of ROI with respect to the coronary ostium. This could bear special hazard particularly in those studies having limited ROI length.37

An interesting finding of our study was that the percentage of stenosis did not differ in relation to the distance from the ostium, whereas plaque area was progressively smaller moving form proximal to distal segments. This might be explained by the interplay between the physiological proximal–distal tapering of the coronary vessel and the higher propensity of the proximal segments to undergo positive remodelling with respect to those located more distally. This seems to be in keeping with our recent findings that positive remodelling is indeed more pronounced in lipid-rich coronary segments.38


   Limitations of the study
Top
 Abstract
 Methods
 Results
 Discussion
 Limitations of the study
Conclusion
 References
 
As exploratory-pilot investigation, our current findings should be regarded as provisional. In particular, to assess relatively minor changes in plaque composition along longitudinal vessel axis, such as that observed for fibrous tissue, or for highly dispersed data such as for relative calcium content, a bigger, properly powered, sample size is clearly needed. Similarly, the observed insignificant trends for fibrous tissue to be increased and fibrolipidic content to be decreased in stable vs. unstable patients may reflect a type-II error. Our results mainly apply to the first 40 mm of the three main coronary arteries, whereas the longitudinal pattern of shift in coronary plaque composition in coronary segments more distally located or in left main coronary artery should be evaluated in studies specifically designed for such an aim. In particular, in keeping with our primary endpoint, the only comparison for which this study was properly powered for is the one between the first and the third segment in model 1. All other analyses, including the tests for four models and all post hoc comparisons should be regarded as exploratory. Despite careful examination of all angiograms, we cannot completely rule out the possibility that patients with a higher number of IVUS interrogated 10 mm segments had a more favourable coronary anatomy as compared with those in whom a long pull-back could not been obtained.

Relevant to this point, it is the fact that: (i) plaque composition in the first three coronary segments did not differ in patients with 30 mm pull back length as compared with those in whom a longer IVUS pull back was obtained; and (ii) the change in plaque composition along the study vessel was remarkably consistent in all the four models analysed.

We failed to find sex-related differences in the proximal–distal pattern of plaque composition. However, the great majority (88%) of patients enrolled were males, which calls for future studies with more balanced sex-distribution to properly address this gender issue.

Finally, it should not undergo unnoticed that the proportion of lipid core content predicted by our multivariable regression model, despite highly significant, was far from being optimal. This means that future investigations should probably aim to increase the capability to predict relative lipid content in coronary plaques taking a broader set of possible independent predictors into account.


   Conclusion
Top
 Abstract
 Methods
 Results
 Discussion
 Limitations of the study
 Conclusion
References
 
Our study provides proof of concept for a non-uniform longitudinal distribution of plaque composition mainly in terms of lipid core content along the main coronary arteries in vivo in humans. The clinical and pathophysiological meaning of this observation and whether it could help explaining the non-uniform distribution of vulnerable plaques along the coronary vessel remains unclear. Future studies are needed to extend and possibly confirm our current findings.

Conflict of interest: none declared.


   References
Top
 Abstract
 Methods
 Results
 Discussion
 Limitations of the study
 Conclusion
 References
 

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