ACUTE MYOCARDIAL ISCHEMIA/INFARCTION
Focal and multi-focal plaque macrophage distributions in patients with acute and stable presentations of coronary artery disease
Briain D. MacNeill, MB, MSC*, ,
Ik-Kyung Jang, MD, PHD*,
Brett E. Bouma, PHD,
Nicusor Iftimia, PHD,
Masamichi Takano, MD, PHD*,,
Hiroshi Yabushita, MD, PHD*,,||,
Milen Shishkov, PHD,
Christopher R. Kauffman, BS,
Stuart L. Houser, MD, ,
H.Thomas Aretz, MD,
Denise DeJoseph, ACNP*,
Elkan F. Halpern, PHD and
Guillermo J. Tearney, MD, PHD,,*
* Cardiology Division
Wellman Center for Photomedicine
Department of Pathology
Department of Radiology, Harvard Medical School, Boston, MassachusettsUSA
|| Department of Cardiology, Kinki University School of Medicine, Kinki, Japan
Manuscript received October 23, 2003;
accepted May 31, 2004.
* Reprint requests and correspondence: Dr. Guillermo J. Tearney, Wellman Center for Photomedicine, Massachusetts General Hospital, BAR 703, Boston, Massachusetts 02114 (Email: gtearney{at}partners.org).
 |
Abstract
|
|---|
OBJECTIVES: This study was designed to utilize optical coherence tomography (OCT) images of coronary atherosclerotic plaque macrophages to investigate the relationship between macrophage distributions and clinical syndrome.
BACKGROUND: The relative significance of focal macrophage infiltration and generalized coronary inflammation for predicting acute coronary events is a currently a source of considerable controversy in cardiology. Lack of a high-resolution cross-sectional imaging modality has limited macrophage evaluation in vivo.
METHODS: Intracoronary OCT imaging was performed at culprit and non-culprit plaques in patients presenting with stable angina pectoris, unstable angina pectoris,and ST-segment elevation myocardial infarction. Macrophage densities were quantified from these images and analyzed with respect to the clinical presentations of the patients under investigation.
RESULTS: A significantly greater macrophage density was found in unstable patients, both for fibrous and lipid-rich plaques (p = 0.025 and p = 0.002, respectively). Within each patient, the macrophage densities at culprit and non-culprit lesions correlated significantly (r = 0.66, y = 0.88x + 0.43, p = 0.01). Sites of plaque rupture demonstrated a greater macrophage density than non-ruptured sites (6.95 ± 1.60%, 5.29 ± 1.17%; p = 0.002). Surface macrophage infiltration was a stronger predictor of unstable clinical presentation than subsurface infiltration for culprit lesions (p = 0.035) but not for remote lesions (p = 0.80).
CONCLUSIONS: Our results demonstrate that increases in both multi-focal and focal macrophage densities are highly correlated with symptom severity. By providing a means of detecting increases in plaque macrophage content before an acute event, this technique may aid in determining prognosis and guiding preventive therapy.
|
Abbreviations and Acronyms
| | ACS = acute coronary syndrome | | AUC = area under the curve | | NSD = normalized standard deviation | | OCT = optical coherence tomography | | ROC = receiver operator characteristic | | SAP = stable angina pectoris | | STEMI = ST-segment elevation myocardial infarction |
|
Our understanding of the pathophysiology of atherosclerosis and its thrombotic complications continues to evolve (1). It is now accepted that plaque instability is more closely related to biologic activity and cellular composition than to angiographic appearance (2). Post-mortem studies have shown that most acute coronary events occur at the site of a ruptured, macrophage-rich, thin-capped fibroatheroma; a minority (<25%) occur as a result of endothelial erosion (3–5). This finding has resulted in extensive efforts to determine if focal features of individual so-called "vulnerable" plaques can predict subsequent instability. It remains unknown if features of plaque vulnerability are concentrated at a single site or are more broadly distributed, as suggested by findings of multi-focal inflammation (6,7) and reports of multiple simultaneous plaque rupture in patients with acute coronary syndromes (8–11). An alternative hypothesis proposes that increased systemic or multi-focal arterial inflammation is an independent risk for acute coronary events, expanding the vulnerable plaque concept into a broader conceptual framework of the "vulnerable patient" (12–14).
An important goal of research in coronary atherosclerosis is to elucidate the degree of risk imparted by individual or focal plaque features versus multi-focal coronary inflammation. Measurement of macrophage densities within high-resolution cross-sectional images of plaques from patients with different clinical syndromes could shed light on this issue. Intravascular optical coherence tomography (OCT) is an optical analog of ultrasound that provides high-resolution ( 10 µm) cross-sectional images of the arterial wall (15–17). Optical coherence tomography is a reliable and reproducible modality for plaque characterization (17,18). Recently, we demonstrated the ability of OCT to accurately quantify macrophage infiltration within atherosclerotic plaque ex vivo by establishing a high degree of correlation between OCT signal variance and the presence of CD68-positive cells (19). Extension of this method enables transformation of the conventional OCT image into a two-dimensional representation of macrophage content (Fig. 1a). The purpose of the present study was to utilize this novel technique to evaluate the distribution of coronary macrophages in living patients with ST-segment elevation myocardial infarction (STEMI), acute coronary syndromes (ACS), and stable angina pectoris (SAP).
|
Methods
|
|---|
Patient population.
We enrolled patients (n = 49) undergoing single-vessel percutaneous coronary intervention for de novo coronary artery disease over an 18-month period between July 2001 and December 2002. Exclusion criteria included renal insufficiency (creatinine  1.8 mg/dl), coronary artery bypass graft intervention, and emergent procedures including primary angioplasty. The study was approved by the Partners Institutional Review Board, and all patients gave informed consent before participation.
Clinical presentation.
Using standard definitions, clinical presentation was defined as STEMI, ACS constituting non-STEMI and unstable angina pectoris, and SAP (20). The culprit lesion was determined using coronary angiography in conjunction with the patient's electrocardiogram and ventriculogram (21).
OCT imaging.
The technique of intracoronary OCT imaging has previously been described (17). Briefly, before percutaneous coronary intervention, a 3.0-F OCT catheter was passed over a 0.014-inch angioplasty wire through a standard 7-F guide catheter. Under angiographic guidance, the OCT catheter was advanced to the culprit lesion. Images were acquired at 4 frames/s during intermittent saline injection (8 to 10 ml) and digitally recorded. We acquired images at the center of the culprit plaque and at its proximal and distal segments. Thus, up to three angiographically distinct images of the culprit plaque were obtained per patient. In addition, within the same vessel, we imaged angiographically mild or moderate lesions (30% to 70% stenosis) that were remote from the culprit site. Each OCT image was analyzed independently. Using previously established criteria, images of lipid-rich or fibrous plaques were selected for analysis by two observers who were blinded to the clinical presentation (18). Images with significant signal attenuation that precluded satisfactory evaluation of plaque morphology were excluded from the analysis.
Fibroatheroma cap segmentation.
After the selection of images of lipid-rich plaques, the caps were outlined using automatic bimodal histogram segmentation (22,23). The threshold was set at the nadir of the bimodal histogram distribution computed from the pixel values within the plaque (22). The lateral boundaries of the cap were marked at the interface between the lipid pool and the adjacent fibrous tissue (Fig. 1c). For rupture sites, the interior boundary was marked 250 µm from the lateral-most portion of the intimal disruption. For each image, the fibrous cap was further segmented by morphologically eroding the cap with a 50 µm2 kernel into the most superficial 50 µm, which we defined as "surface," and the remainder of the cap, which we defined as "subsurface." This image processing provided two distinct cap segments, which allowed comparison between the surface (<50 µm from the lumen) and subsurface (>50 µm from the lumen) macrophage densities of the fibrous cap. Portions of the cap that were obscured by: 1) overlying thrombus, 2) intraluminal blood, 3) guide wire, or 4) arterial wall compression by the catheter sheath were excluded from analysis.
Quantitative macrophage analysis.
We performed measurement of macrophage content on raw OCT data within the region of interest using a technique previously validated in an ex vivo study (19). Median filtering was performed with a 3 x 3 square kernel to remove speckle noise (IPLab Spectrum 3.1, Scanalytics, Fairfax, Virginia) (23,24). We then measured the normalized standard deviation (NSD) for each pixel within each cap using a 125 µm2 window centered at the pixel location (Fig. 1d):
 | (1) |
where NSD(x,y) was the normalized standard deviation of the OCT signal at pixel location (x,y), Smax was the maximum OCT image value, and Smin was the minimum OCT image value. Pixels within the (125 x 125) µm2 window that did not overlap with the segmented cap were excluded. For each image, we assessed macrophage density by obtaining the average of the NSD values within the segmented cap (mean NSD). Macrophage densities within rupture sites, surface, and subsurface caps were calculated in the same manner. Because the segmentation of the caps and the computation of the NSD were conducted in an automated fashion, the determination of macrophage density was objective and not likely subject to investigator bias.
Statistical analysis.
Results are expressed as means ± SD unless otherwise stated. The NSD measurements between the groups were compared using analysis of variance. Significant variance was further analyzed using the least squares mean t test, which does not control for multiple comparisons. Correlation between continuous variables was estimated using Pearson's correlation coefficient. Comparison between the acute presentations (ACS + STEMI) and the stable presentations (SAP) were performed using the Student t test. Receiver operating characteristic (ROC) curves were constructed comparing the true positive rate (sensitivity) to the false positive rate of surface and subsurface macrophage densities for predicting patients with an acute coronary event. Results for ROC analysis are expressed as area ± standard error. Pairwise comparisons of the area under the ROC curve (AUC) were conducted using MedCalc (MedCalc Software, Mariakerke, Belgium) and the method described by Hanley and McNeil (25,26). All other analyses were performed using SAS software (SAS Institute Inc., Cary, North Carolina). A p value of  0.05 was considered statistically significant.
|
Results
|
|---|
A total of 166 images of lipid-rich and 59 images of fibrous plaques were obtained from 49 patients. The baseline characteristics of the patient population are presented in Table 1. From this group, 47 lipid-rich and 18 fibrous plaques were excluded because of poor image quality. The remaining 119 lipid-rich plaques (76 culprit sites, 43 remote sites) and 41 fibrous plaques were analyzed. Culprit images were obtained in 74% and remote images were obtained in 55% of the patients studied. The median time to OCT imaging was 2 days (range 1 to 13 days) for the STEMI group, 4 days (range 1 to 30 days) for the ACS group, and 41 days (range 2 to 60 days) for the stable group.
Lipid-rich plaques.
To establish the relationship between macrophage infiltration and clinical syndrome, we compared the macrophage densities of lipid-rich plaques in patients presenting with STEMI, ACS, or SAP. We found that the macrophage densities varied significantly among the three clinical groups (p < 0.001). Specifically, we demonstrated a significantly greater macrophage density in both the STEMI (5.54 ± 1.48%) and the ACS (5.86 ± 2.01%) groups than in the SAP group (4.14 ± 1.81%) (p = 0.002 and p < 0.001, respectively) (Fig. 2a). No significant difference was seen in macrophage density between the STEMI and the ACS groups (p = 0.38). The results are summarized in Table 2.
View larger version (21K):
[in this window]
[in a new window]
|
Figure 2 Multi-focal macrophage density results. (a) Bar graph showing macrophage density at culprit and remote sites for each clinical syndrome. Standard error bars are represented. Within each clinical syndrome no significant difference was found between the macrophage content at culprit and remote lesions. (b) Scatter plot of macrophage density in culprit lesions relative to that at remote sites within the same patient. Linear regression equation, Pearson's correlation coefficient (r), and p value are depicted in the insert. ACS = acute coronary syndrome; SAP = stable angina pectoris; STEMI = ST-segment elevation myocardial infarction.
|
|
Fibrous plaques.
We also investigated whether macrophage content in fibrous plaques was also related to clinical presentation. When the STEMI and ACS syndromes were combined into a broader but clinically relevant category representing all unstable patients (STEMI + ACS), we found a significantly higher macrophage density in fibrous plaques of the unstable group (5.41 ± 1.10%) than in plaques of the stable group (4.43 ± 1.46%) (p = 0.025).
Multi-focal macrophage infiltration.
In order to determine if macrophage content was increased in multiple locations in unstable patients, we further analyzed macrophage densities within lipid-rich plaques at both culprit and remote sites within the same vessel. For culprit lesions, the macrophage density was significantly higher in STEMI (5.66 ± 1.44%) and ACS (5.91 ± 2.06%) groups than in the SAP (4.21 ± 1.74%) group (p = 0.013 and p = 0.003, respectively). At remote sites, a significantly greater macrophage density was found in the unstable (STEMI + ACS) group than in the stable group (5.53 ± 1.71% vs. 4.02 ± 2.02%; p = 0.03). Moreover, when we compared culprit and remote macrophage densities within each clinical syndrome, we found that no significant difference existed between culprit and remote sites for each clinical group (STEMI: p = 0.52; ACS: p = 0.81; SAP: p = 0.82) (Fig. 2a). Furthermore, within the same patients (n = 15), macrophage density at remote sites correlated significantly with that of culprit sites (r = 0.67, y = 0.88x + 0.43, p = 0.006)(Fig. 2b).
Focal macrophage infiltration.
Having established that multi-focal macrophage content was elevated in patients with unstable coronary syndromes, we asked whether focal elevations in macrophage content were independently related to symptom severity. In order to address this question, we analyzed culprit lipid-rich plaques within the STEMI and ACS groups that demonstrated clear OCT evidence of plaque rupture (n = 6; 2 STEMI, 4 ACS). For each rupture site we analyzed a 250 µm segment at the point of disruption and compared the macrophage density of the rupture location to that of the remainder of the plaque (Fig. 3a). We found a significantly higher macrophage density at the rupture site than of the adjacent non-ruptured cap within the same image (6.95 ± 1.6%, 5.29 ± 1.17%; p = 0.002) (Fig. 3b). Furthermore, macrophage density at rupture sites was significantly greater than that of all non-ruptured culprit sites in the combined STEMI and ACS groups (6.95 ± 1.6%, 5.75 ± 1.8%; p = 0.04).
View larger version (77K):
[in this window]
[in a new window]
|
Figure 3 Focal macrophage density results. (a) Optical coherence tomography (OCT) image of a rupture site (outlined in red) overlying a lipid-rich plaque (LP). The * represents guide wire shadow. A 500 µm scale bar is seen in the top right-hand corner. (b) Bar graph representing mean macrophage density at sites of rupture, corresponding to outlined segment in panel a, compared with the rest of the plaque. Standard error bars are represented. (c and d) Receiver operating characteristic curves for surface and subsurface macrophage density for prediction of an acute coronary event at culprit sites (panel c) and remote sites (panel d). Areas under curve (AUC) for surface and subsurface macrophage density and the p value are noted in the insert.
|
|
Finally, we examined the spatial location of macrophages within the fibrous cap of lipid-rich plaques to determine if the proximity of macrophages to the endothelial surface was related to coronary syndrome. We divided the fibrous cap into a superficial layer (<50 microns from the luminal surface) and a subsurface layer (>50 microns from the luminal surface). For each layer we computed ROC curves for the prediction of an unstable coronary presentation. At culprit sites, the AUC for superficial macrophage density was significantly greater (0.79 ± 0.06) than the AUC of the subsurface macrophage density (0.69 ± 0.07; p = 0.035) (Fig. 3c). For remote sites, the difference between surface (0.73 ± 0.09) and subsurface (0.72 ± 0.09) AUCs was not significant (p = 0.80) (Fig. 3d).
|
Discussion
|
|---|
Macrophages have been implicated in every stage of coronary atherosclerosis from its initiation to its clinical presentation (27–29). Macrophages secrete matrix metalloproteinases that decrease plaque stability (30) and express tissue factor, a potent promoter of coagulation (31). Increased macrophage infiltration within culprit lesions has been demonstrated in autopsy studies of patients dying of acute coronary events and atherectomy studies of patients presenting with acute coronary syndromes (32,33). As such, macrophages are considered central to atherosclerosis and its thrombotic complications.
In this study, we have extended the results of previous investigations (32,33) by obtaining the first measurements of macrophage distributions within high-resolution cross-sectional images of human coronary plaques in vivo. In so doing we observed a link between the structural morphology and biologic activity of coronary plaques. The value of this biologic measurement is reflected in the significant differences in cap macrophage densities found in patients with stable and unstable coronary syndromes.
Our results demonstrate that increased multi-focal inflammation is present in patients with severe manifestations of coronary atherosclerosis. First, a high degree of correlation was found between the macrophage densities at remote and culprit sites within the same patient. Second, no significant difference in macrophage content was detected between the remote and culprit sites within each clinical group. Finally, within remote sites, a significantly greater macrophage density was found in the acute compared with the stable clinical syndromes. These findings support recent studies that demonstrate inflammatory cell activation not only within the culprit artery but also within non-culprit arteries (6,7). Our data therefore provide further proof of the multi-focal nature of inflammation in symptomatic coronary atherosclerosis and demonstrate in vivo that this inflammation is manifested, at least in part, by increased macrophage density in the fibrous caps of both culprit and non-culprit lesions.
By demonstrating a significantly greater macrophage density at sites of plaque rupture, our results indicate that focal increases in macrophage content within individual plaques also affect plaque stability. Focal macrophage activation is thought to cause plaque instability by reducing collagen synthesis, increasing collagen degradation, and inducing smooth muscle cell apoptosis (28). The significant role of focal inflammatory plaque features is further supported by our observation that surface macrophage content was more predictive of clinical syndrome in culprit plaques, but not in remote lesions. The increased significance of macrophages at the surface of culprit lesions alone indicates that the spatial distribution of macrophages is intrinsically different in culprit lesions from that in non-culprit lesions within the same patient, even in the setting of elevated generalized inflammation. This finding may be explained by the results of recent studies that have shown that macrophages present at plaque surfaces may promote instability through endothelial erosion and tissue factor expression (34–37). This predilection of macrophages for the surface of culprit lesions may provide us with a new parameter for assessing individual plaque vulnerability.
An added advantage of this method is the potential to assess macrophage distribution in the context of high-resolution cross-sectional images of plaque morphology (Fig. 1). Previous studies have demonstrated that OCT is capable of characterizing plaque type with high sensitivity and specificity (18). In this study, we demonstrated that in acute patients inflammation is increased not only within the fibroatheromas typically implicated in plaque rupture, but also in fibrous plaques. Although fibrous plaques have traditionally been considered more stable, erosion of the superficial endothelial layer overlying fibrous plaques is found in a significant number of patients with an acute coronary event (3,4).
Other methods for detecting arterial inflammation.
Atherosclerotic plaque temperature and thermal heterogeneity have previously been shown to correlate with plaque macrophage content (38). Clinical application of this technique demonstrated significantly greater intracoronary thermal heterogeneity in patients presenting with acute coronary events (39), findings that are consistent with our data. Similarly, magnetic resonance imaging of iron oxide-labeled macrophages has recently been shown to predict ruptured or rupture-prone carotid plaques in vivo (40). Both techniques are of great interest insofar as they provide a functional measure of macrophages within atherosclerotic plaque. Optical coherence tomography complements these modalities, as it detects macrophages in the context of other microstructural features of plaque instability, such as a thin fibrous cap, a lipid-rich core, or evidence of rupture.
Study limitations.
Because blood attenuates light, it must be removed from the field of view in order to obtain high quality optical images. In the current study, blood was purged during imaging by flushing the artery with saline. This procedure permitted clear cross-sectional imaging at discrete locations but precluded comprehensive evaluation of the entire vessel. It is likely, therefore, that some rupture sites within some culprit lesions were not visualized. Inadequate saline purging resulted in exclusion of some images from analysis because of poor OCT image quality. Exclusion of these images may have introduced an inadvertent selection bias and, as a result, our findings should be considered preliminary. Forthcoming enhancements to OCT technology, including improvements in saline delivery and faster acquisition rates, will enable comprehensive screening of long coronary segments. Unfortunately, thrombus rapidly attenuates the OCT signal, prohibiting accurate measurement of macrophage content arising from the vessel wall underlying the thrombus. This attenuation would affect the macrophage density measurement, independent of the actual macrophage content. Although in principle it is possible to correct for the attenuation of the overlying thrombus, this correction method has not yet been validated against a gold standard. As a result, we chose to eliminate lesions containing a thrombus from the data set. In doing so, we may have underestimated the effect of macrophages at sites of endothelial erosion and rupture. Despite this limitation, our results achieved a high level of significance.
Imaging was performed at a single time point following symptom onset. As a result, the degree to which inflammation was a cause or a consequence of the clinical presentation could not be examined. Several studies have demonstrated elevation of acute-phase reactants or inflammatory markers before clinical presentation, indicating that inflammation precedes plaque disruption (41,42). Upcoming clinical trials will address this question by investigating the evolution of macrophage distributions in patients with a variety of symptoms.
The use of HMG-CoA reductase inhibitors (statins) is currently thought to improve cardiac mortality by a variety of mechanisms, one of which includes the inflammatory modulation properties of statins (28). Unfortunately, in this study information on statin use was not adequately recorded, and we were therefore unable to evaluate the effect of statins on macrophage content. Larger clinical studies utilizing OCT are planned that will investigate the relationship between macrophage distributions and patient-specific factors including statin use, age, gender, diabetes, hyperlipidemia, homocysteinemia, smoking, and high sensitivity C-reactive protein.
Conclusions.
This study provides evidence supporting both the vulnerable plaque model and the hypothesis of multi-focal inflammatory risk, linked by the common thread of increased macrophage infiltration. Therefore, we hypothesize that elevated multi-focal coronary macrophage content, present in both culprit lesions and at remote sites, serves as a background for heightened risk. Superimposed on this inflammatory background, local increases in macrophage content, particularly at the cap surface and at areas at high risk for rupture, further promote the instability of individual lesions. Future studies will test these hypotheses by using this technology to evaluate the significance of both local and generalized macrophage content for predicting acute coronary events. As our understanding of coronary atherosclerosis advances, we anticipate that the relationship between these two hypotheses will become clearer and that optimal treatment strategies will combine pharmacologic therapy to control multi-focal intracoronary inflammation and directed local therapy to further diminish the likelihood of an acute coronary event.
|
Acknowledgments
|
|---|
We are grateful to Dr. James Muller for reviewing the manuscript.
|
Footnotes
|
|---|
This study was funded in part by the Center for Integration of Medicine and Innovative Technology (development of the imaging platform), Guidant Corporation, the National Institutes of Health (grant 5-R01-HL70039), and through a generous gift from Dr. and Mrs. J. S. Chen to the optical diagnostics program of the MGH Wellman Center for Photomedicine.
|
References
|
|---|
1. Fuster V, Fayad ZA, Badimon JJ. Acute coronary syndromesbiology. Lancet 1999;353:115-119.
2. Libby P. Current concepts of the pathogenesis of the acute coronary syndromes Circulation 2001;104:365-372.[Free Full Text]
3. Virmani R, Kolodgie FD, Burke AP, Farb A, Schwartz SM. Lessons from sudden coronary deatha comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler Thromb Vasc Biol 2000;20:1262-1275.[Free Full Text]
4. Farb A, Burke AP, Tang AL, et al. Coronary plaque erosion without rupture into a lipid core. A frequent cause of coronary thrombosis in sudden coronary death Circulation 1996;93:1354-1363.[Abstract/Free Full Text]
5. Arbustini E, Grasso M, Diegoli M, et al. Coronary atherosclerotic plaques with and without thrombus in ischemic heart syndromesa morphologic, immunohistochemical, and biochemical study. Am J Cardiol 1991;68:36B-50B.[CrossRef][Medline]
6. Mazzone A, De Servi S, Ricevuti G, et al. Increased expression of neutrophil and monocyte adhesion molecules in unstable coronary artery disease Circulation 1993;88:358-363.[Abstract/Free Full Text]
7. Buffon A, Biasucci LM, Liuzzo G, D'Onofrio G, Crea F, Maseri A. Widespread coronary inflammation in unstable angina N Engl J Med 2002;347:5-12.[CrossRef][Medline]
8. Asakura M, Ueda Y, Yamaguchi O, et al. Extensive development of vulnerable plaques as a pan-coronary process in patients with myocardial infarctionan angioscopic study. J Am Coll Cardiol 2001;37:1284-1288.[Abstract/Free Full Text]
9. Maehara A, Mintz GS, Bui AB, et al. Morphologic and angiographic features of coronary plaque rupture detected by intravascular ultrasound J Am Coll Cardiol 2002;40:904-910.[Abstract/Free Full Text]
10. Mann J, Davies MJ. Mechanisms of progression in native coronary artery diseaserole of healed plaque disruption. Heart 1999;82:265-268.[Abstract/Free Full Text]
11. Farb A, Malcom GT, Liang YH, Smialek J, Virmani R, Burke AP. Coronary risk factors and plaque morphology in men with coronary disease who died suddenly N Engl J Med 1997;336:1276-1282.[CrossRef][Medline]
12. Maseri A, Fuster V. Is there a vulnerable plaque? Circulation 2003;107:2068-2071.[Free Full Text]
13. Casscells W, Naghavi M, Willerson JT. Vulnerable atherosclerotic plaquea multifocal disease. Circulation 2003;107:2072-2075.[Free Full Text]
14. Naghavi M, Libby P, Falk E, et al. From vulnerable plaque to vulnerable patient. A call for new definitions and risk assessment strategiespart I. Circulation 2003:1664-1672.
15. Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography Science 1991;254:1178-1181.[Abstract/Free Full Text]
16. Brezinski ME, Tearney GJ, Bouma BE, et al. Optical coherence tomography for optical biopsy. Properties and demonstration of vascular pathology Circulation 1996;93:1206-1213.[Abstract/Free Full Text]
17. Jang IK, Bouma BE, Kang DH, et al. Visualization of coronary atherosclerotic plaques in patients using optical coherence tomographycomparison with intravascular ultrasound. J Am Coll Cardiol 2002;39:604-609.[Abstract/Free Full Text]
18. Yabushita H, Bouma BE, Houser SL, et al. Characterization of human atherosclerosis by optical coherence tomography Circulation 2002;106:1640-1645.[Abstract/Free Full Text]
19. Tearney GJ, Yabushita H, Houser SL, et al. Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography Circulation 2003;107:113-119.[Abstract/Free Full Text]
20. Cannon CP, Battler A, Brindis RG, et al. American College of Cardiology key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes. A report of the American College of Cardiology Task Force on Clinical Data Standards (Acute Coronary Syndromes Writing Committee) J Am Coll Cardiol 2001;38:2114-2130.[Free Full Text]
21. Ambrose JA, Winters SL, Arora RR, et al. Coronary angiographic morphology in myocardial infarctiona link between the pathogenesis of unstable angina and myocardial infarction. J Am Coll Cardiol 1985;6:1233-1238.[Abstract]
22. Gonzalez R, Wintz P. Digital Image Processing2nd edition. Reading, MA: Addison-Wesley Publishing Co; 1987.
23. Jahne B. Digital Image Processing: Concepts, Algorithms and Scientific ApplicationsBerlin: Springer-Verlag; 1991.
24. Pratt W. Digital Image Processing2nd edition. New York, NY: John Wiley and Sons; 1991.
25. Hanley J, McNeil B. A method of comparing the areas under receiver operating characteristic curves derived from the same cases Radiology 1983;148:839-843.[Abstract/Free Full Text]
26. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve Radiology 1982;143:29-36.[Abstract/Free Full Text]
27. Ross R. Atherosclerosisan inflammatory disease. N Engl J Med 1999;340:115-126.[CrossRef][Medline]
28. Libby P. Inflammation in atherosclerosis Nature 2002;420:868-874.[CrossRef][Medline]
29. van der Wal AC, Becker AE, van der Loos CM, Das PK. Site of intimal rupture or erosion of thrombosed coronary atherosclerotic plaques is characterized by an inflammatory process irrespective of the dominant plaque morphology Circulation 1994;89:36-44.[Abstract/Free Full Text]
30. Shah PK, Falk E, Badimon JJ, et al. Human monocyte-derived macrophages induce collagen breakdown in fibrous caps of atherosclerotic plaques. Potential role of matrix-degrading metalloproteinases and implications for plaque rupture Circulation 1995;92:1565-1569.[Medline]
31. Zaman AG, Helft G, Worthley SG, Badimon JJ. The role of plaque rupture and thrombosis in coronary artery disease Atherosclerosis 2000;149:251-266.[CrossRef][Medline]
32. Stary HC, Chandler AB, Dinsmore RE, et al. A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. A report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association Circulation 1995;92:1355-1374.[Abstract/Free Full Text]
33. Moreno PR, Falk E, Palacios IF, Newell JB, Fuster V, Fallon JT. Macrophage infiltration in acute coronary syndromes. Implications for plaque rupture Circulation 1994;90:775-778.[Abstract/Free Full Text]
34. Rajavashisth T, Qiao JH, Tripathi S, et al. Heterozygous osteopetrotic (op) mutation reduces atherosclerosis in LDL receptor-deficient mice J Clin Invest 1998;101:2702-2710.[Medline]
35. Colli S, Lalli M, Rise P, et al. Increased thrombogenic potential of human monocyte-derived macrophages spontaneously transformed into foam cells Thromb Haemost 1999;81:576-581.[Medline]
36. Lesnik P, Rouis M, Skarlatos S, Kruth HS, Chapman MJ. Uptake of exogenous free cholesterol induces upregulation of tissue factor expression in human monocyte-derived macrophages Proc Natl Acad Sci U S A 1992;89:10370-10374.[Abstract/Free Full Text]
37. Kolodgie F, Narula J, Burke A, et al. Localization of apoptotic macrophages at the site of plaque rupture in sudden coronary death. Am J Pathol 2000;1259–68..
38. Casscells W, Hathorn B, David M, et al. Thermal detection of cellular infiltrates in living atherosclerotic plaquespossible implications for plaque rupture and thrombosis. Lancet 1996;347:1447-1451.[CrossRef][Medline]
39. Stefanadis C, Diamantopoulos L, Vlachopoulos C, et al. Thermal heterogeneity within human atherosclerotic coronary arteries detected in vivoa new method of detection by application of a special thermography catheter. Circulation 1999;99:1965-1971.[Abstract/Free Full Text]
40. Kooi ME, Cappendijk VC, Cleutjens KB, et al. Accumulation of ultrasmall superparamagnetic particles of iron oxide in human atherosclerotic plaques can be detected by in vivo magnetic resonance imaging Circulation 2003;107:2453-2458.[Abstract/Free Full Text]
41. Liuzzo G, Biasucci LM, Gallimore JR, et al. The prognostic value of C-reactive protein and serum amyloid A protein in severe unstable angina N Engl J Med 1994;331:417-424.[CrossRef][Medline]
42. Ridker PM. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women N Engl J Med 2000;342:836-843.[CrossRef][Medline]
This article has been cited by other articles:
|
|
|
|
 
S. Uemura, K.-i. Ishigami, T. Soeda, S. Okayama, J. H. Sung, H. Nakagawa, S. Somekawa, Y. Takeda, H. Kawata, M. Horii, et al.
Thin-cap fibroatheroma and microchannel findings in optical coherence tomography correlate with subsequent progression of coronary atheromatous plaques
Eur. Heart J.,
January 1, 2012;
33(1):
78 - 85.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
H. C. Lowe, J. Narula, J. G. Fujimoto, and I.-K. Jang
Intracoronary Optical Diagnostics: Current Status, Limitations, and Potential
J. Am. Coll. Cardiol. Intv.,
December 1, 2011;
4(12):
1257 - 1270.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. J. Suter, S. K. Nadkarni, G. Weisz, A. Tanaka, F. A. Jaffer, B. E. Bouma, and G. J. Tearney
Intravascular Optical Imaging Technology for Investigating the Coronary Artery
J. Am. Coll. Cardiol. Img.,
September 1, 2011;
4(9):
1022 - 1039.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
D. Vancraeynest, A. Pasquet, V. Roelants, B. L. Gerber, and J.-L. J. Vanoverschelde
Imaging the Vulnerable Plaque
J. Am. Coll. Cardiol.,
May 17, 2011;
57(20):
1961 - 1979.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
H. G. Bezerra, M. A. Costa, G. Guagliumi, A. M. Rollins, and D. I. Simon
Intracoronary Optical Coherence Tomography: A Comprehensive Review: Clinical and Research Applications
J. Am. Coll. Cardiol. Intv.,
November 1, 2009;
2(11):
1035 - 1046.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
I. Laitinen, A. Saraste, E. Weidl, T. Poethko, A. W. Weber, S. G. Nekolla, P. Leppanen, S. Yla-Herttuala, G. Holzlwimmer, A. Walch, et al.
Evaluation of {alpha}v{beta}3 Integrin-Targeted Positron Emission Tomography Tracer 18F-Galacto-RGD for Imaging of Vascular Inflammation in Atherosclerotic Mice
Circ Cardiovasc Imaging,
July 1, 2009;
2(4):
331 - 338.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
G. J. Tearney, S. Waxman, M. Shishkov, B. J. Vakoc, M. J. Suter, M. I. Freilich, A. E. Desjardins, W.-Y. Oh, L. A. Bartlett, M. Rosenberg, et al.
Three-dimensional coronary artery microscopy by intracoronary optical frequency domain imaging.
J. Am. Coll. Cardiol. Img.,
November 1, 2008;
1(6):
752 - 761.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
J. Waldeck, F. Hager, C. Holtke, C. Lanckohr, A. von Wallbrunn, G. Torsello, W. Heindel, G. Theilmeier, M. Schafers, and C. Bremer
Fluorescence Reflectance Imaging of Macrophage-Rich Atherosclerotic Plaques Using an {alpha}v{beta}3 Integrin-Targeted Fluorochrome
J. Nucl. Med.,
November 1, 2008;
49(11):
1845 - 1851.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
O C Raffel, T Akasaka, and I-K Jang
Cardiac optical coherence tomography
Heart,
September 1, 2008;
94(9):
1200 - 1210.
[Full Text]
[PDF]
|
|
|
|
|
|
|
Y. Honda and P. J. Fitzgerald
Frontiers in Intravascular Imaging Technologies
Circulation,
April 15, 2008;
117(15):
2024 - 2037.
[Full Text]
[PDF]
|
|
|
|
|
|
|
C. Di Mario and P. Barlis
Optical Coherence Tomography: A New Tool to Detect Tissue Coverage in Drug-Eluting Stents
J. Am. Coll. Cardiol. Intv.,
April 1, 2008;
1(2):
174 - 175.
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. Gossl, L. O. Lerman, and A. Lerman
Frontiers in Nephrology: Early Atherosclerosis A View Beyond the Lumen
J. Am. Soc. Nephrol.,
November 1, 2007;
18(11):
2836 - 2842.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
T. Kubo, T. Imanishi, S. Takarada, A. Kuroi, S. Ueno, T. Yamano, T. Tanimoto, Y. Matsuo, T. Masho, H. Kitabata, et al.
Assessment of Culprit Lesion Morphology in Acute Myocardial Infarction: Ability of Optical Coherence Tomography Compared With Intravascular Ultrasound and Coronary Angioscopy
J. Am. Coll. Cardiol.,
September 4, 2007;
50(10):
933 - 939.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
P. W. Serruys, H. M. Garcia-Garcia, and E. Regar
From Postmortem Characterization to the In Vivo Detection of Thin-Capped Fibroatheromas: The Missing Link Toward Percutaneous Treatment: What If Diogenes Would Have Found What He Was Looking For?
J. Am. Coll. Cardiol.,
September 4, 2007;
50(10):
950 - 952.
[Full Text]
[PDF]
|
|
|
|
|
|
|
S. K. Nadkarni, M. C. Pierce, B. H. Park, J. F. de Boer, P. Whittaker, B. E. Bouma, J. E. Bressner, E. Halpern, S. L. Houser, and G. J. Tearney
Measurement of Collagen and Smooth Muscle Cell Content in Atherosclerotic Plaques Using Polarization-Sensitive Optical Coherence Tomography
J. Am. Coll. Cardiol.,
April 3, 2007;
49(13):
1474 - 1481.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
V. Amirbekian, M. J. Lipinski, K. C. Briley-Saebo, S. Amirbekian, J. G. S. Aguinaldo, D. B. Weinreb, E. Vucic, J. C. Frias, F. Hyafil, V. Mani, et al.
Detecting and assessing macrophages in vivo to evaluate atherosclerosis noninvasively using molecular MRI
PNAS,
January 16, 2007;
104(3):
961 - 966.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
S. Waxman, F. Ishibashi, and J. E. Muller
Detection and Treatment of Vulnerable Plaques and Vulnerable Patients: Novel Approaches to Prevention of Coronary Events
Circulation,
November 28, 2006;
114(22):
2390 - 2411.
[Full Text]
[PDF]
|
|
|
|
|
|
|
R. Hosokawa, N. Kambara, M. Ohba, T. Mukai, M. Ogawa, H. Motomura, N. Kume, H. Saji, T. Kita, and R. Nohara
A Catheter-Based Intravascular Radiation Detector of Vulnerable Plaques
J. Nucl. Med.,
May 1, 2006;
47(5):
863 - 867.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
D. Stamper, N. J. Weissman, and M. Brezinski
Plaque Characterization With Optical Coherence Tomography
J. Am. Coll. Cardiol.,
April 18, 2006;
47(8_Suppl_C):
C69 - C79.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. J. Sampson, M. S. Winterbone, J. C. Hughes, N. Dozio, and D. A. Hughes
Monocyte Telomere Shortening and Oxidative DNA Damage in Type 2 Diabetes
Diabetes Care,
February 1, 2006;
29(2):
283 - 289.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
K. Toutouzas, M. Drakopoulou, J. Mitropoulos, E. Tsiamis, S. Vaina, M. Vavuranakis, V. Markou, E. Bosinakou, and C. Stefanadis
Elevated Plaque Temperature in Non-Culprit De Novo Atheromatous Lesions of Patients With Acute Coronary Syndromes
J. Am. Coll. Cardiol.,
January 17, 2006;
47(2):
301 - 306.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
G. S. Ginsburg, M. P. Donahue, and L. K. Newby
Prospects for Personalized Cardiovascular Medicine: The Impact of Genomics
J. Am. Coll. Cardiol.,
November 1, 2005;
46(9):
1615 - 1627.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
S. K. Nadkarni, B. E. Bouma, T. Helg, R. Chan, E. Halpern, A. Chau, M. S. Minsky, J. T. Motz, S. L. Houser, and G. J. Tearney
Characterization of Atherosclerotic Plaques by Laser Speckle Imaging
Circulation,
August 9, 2005;
112(6):
885 - 892.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
M. P.S. Dunphy, A. Freiman, S. M. Larson, and H. W. Strauss
Association of Vascular 18F-FDG Uptake with Vascular Calcification
J. Nucl. Med.,
August 1, 2005;
46(8):
1278 - 1284.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
T. M. Muanza, A. P. Cotrim, M. McAuliffe, A. L. Sowers, B. J. Baum, J. A. Cook, F. Feldchtein, P. Amazeen, C. N. Coleman, and J. B. Mitchell
Evaluation of Radiation-Induced Oral Mucositis by Optical Coherence Tomography
Clin. Cancer Res.,
July 15, 2005;
11(14):
5121 - 5127.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
|
|
|
H.-J. Priebe
Perioperative myocardial infarction--aetiology and prevention
Br. J. Anaesth.,
July 1, 2005;
95(1):
3 - 19.
[Abstract]
[Full Text]
[PDF]
|
|
|
|
Top
Abstract
Methods
red) at a site of disruption (arrow) within a lipid-rich plaque (LP). The * represents guide wire shadow artifact. (b) Optical coherence tomography (OCT) image of an LP. The * represents guide wire shadow artifact. A 500 µm scale bar is shown in the top right-hand corner. (c) Outline (red) of the segmented fibrous cap of the OCT image depicted in panel b. (d) Normalized standard deviation image superimposed over a standard intensity image shows locations (blue