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J Am Coll Cardiol, 2006; 48:81-88, doi:10.1016/j.jacc.2006.02.062 (Published online 7 June 2006).
© 2006 by the American College of Cardiology Foundation
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CLINICAL RESEARCH: CORONARY ARTERY DISEASE

Diagnostic Accuracy of Optical Coherence Tomography and Integrated Backscatter Intravascular Ultrasound Images for Tissue Characterization of Human Coronary Plaques

Masanori Kawasaki, MD, PhD*,*, Brett E. Bouma, PhD*, Jason Bressner, PhD*, Stuart L. Houser, MD{dagger}, Seemantini K. Nadkarni, PhD*, Briain D. MacNeill, MD{ddagger}, Ik-Kyung Jang, MD, PhD{ddagger}, Hisayoshi Fujiwara, MD, PhD§ and Guillermo J. Tearney, MD, PhD*

* Wellman Laboratories of Photomedicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
{dagger} Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
{ddagger} Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
§ Regeneration and Advanced Medical Science, Gifu University Graduate School of Medicine, Gifu, Japan.

Manuscript received January 4, 2006; revised manuscript received February 21, 2006, accepted February 27, 2006.

* Reprint requests and correspondence: Dr. Masanori Kawasaki, Wellman Laboratories of Photomedicine, Massachusetts General Hospital and Harvard Medical School, 40 Blossom Street, Boston, Massachusetts 02114. (Email: masanori{at}ya2.so-net.ne.jp).


   Abstract
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 Abstract
Methods
 Results
 Discussion
 References
 
OBJECTIVES: The purpose of the present study was to validate the diagnostic accuracy of optical coherence tomography (OCT), integrated backscatter intravascular ultrasound (IB-IVUS), and conventional intravascular ultrasound (C-IVUS) for tissue characterization of coronary plaques and to evaluate the advantages and limitations of each of these modalities.

BACKGROUND: The diagnostic accuracy of OCT for characterizing tissue types is well established. However, comparisons among OCT, C-IVUS, and IB-IVUS have not been done.

METHODS: We examined 128 coronary arterial sites (42 coronary arteries) from 17 cadavers; IVUS and OCT images were acquired on the same slice as histology. Ultrasound signals were obtained using an IVUS system with a 40-MHz catheter and digitized at 1 GHz with 8-bit resolution. The IB values of the ultrasound signals were calculated with a fast Fourier transform.

RESULTS: Using histological images as a gold standard, the sensitivity of OCT for characterizing calcification, fibrosis, and lipid pool was 100%, 98%, and 95%, respectively. The specificity of OCT was 100%, 94%, and 98%, respectively (Cohen’s {kappa} = 0.92). The sensitivity of IB-IVUS was 100%, 94%, and 84%, respectively. The specificity of IB-IVUS was 99%, 84%, and 97%, respectively (Cohen’s {kappa} = 0.80). The sensitivity of C-IVUS was 100%, 93%, and 67%, respectively. The specificity of C-IVUS was 99%, 61%, and 95%, respectively (Cohen’s {kappa} = 0.59).

CONCLUSIONS: Within the penetration depth of OCT, OCT has a best potential for tissue characterization of coronary plaques. Integrated backscatter IVUS has a better potential for characterizing fibrous lesions and lipid pools than C-IVUS.

Abbreviations and Acronyms
  C-IVUS = conventional intravascular ultrasound
  CI = confidence interval
  IB = integrated backscatter
  IVUS = intravascular ultrasound
  OCT = optical coherence tomography
  ROI = region of interest

According to postmortem and angioscopic studies, acute coronary syndromes are thought to be caused by the disruption or erosion of lipid-rich plaques (consisting of a large lipid core with thin fibrous cap) that can lead to subsequent thromboses (1–3). Therefore, it is important to develop methods for the evaluation of tissue characteristics of coronary plaques.

There are several clinical approaches for determining the tissue characterization of plaques. Many techniques for the tissue characterization of plaques have been developed using mathematical analyses of ultrasound signals (4–6). Nair et al. (7) reported the intravascular ultrasound (IVUS) system for tissue characterization using an autoregressive classification scheme rather than depending on the classic Fourier method. In this study, not only integrated backscatter (IB) values but also other parameters such as frequencies at maximum and minimum power and slope of regression line of ultrasound backscattered signals were taken into account for the analysis. We also developed a method of analyzing IB values that uses computer-generated color-coded maps of tissue characteristics and reported the feasibility of this system (8–10).

Recently developed, intravascular optical coherence tomography (OCT) provides high-resolution, cross sectional images of tissue in situ and has an axial resolution of 10 µm and a lateral resolution of 20 µm (11–13). The OCT images of human coronary atherosclerotic plaques obtained in vivo provide additional, more detailed structural information than IVUS (14–17). Characterizing different types of atherosclerotic plaques on the basis of sensitivity and specificity compared with histological findings to determine plaque vulnerability was established in a previous study (18). According to this study, the sensitivity and specificity of the classification of the plaque components were sufficient for tissue characterization in clinical settings. However, comparisons among OCT, conventional intravascular ultrasound (C-IVUS), and IB-IVUS in the same histological image have not been done.

The purpose of the present study was to compare OCT, C-IVUS, and IB-IVUS images of coronary arterial plaques with histological images, and to evaluate the advantages and limitations of each of these modalities.


   Methods
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 Abstract
 Methods
Results
 Discussion
 References
 
Specimens.   We examined 128 grossly diseased coronary arterial sites for the comparison between OCT images and IVUS images (42 coronary arteries from 17 cadavers). Ten of these patients had symptomatic cardiovascular disease (59%). The coronary arteries were dissected at autopsy within 8 h after death. The harvested coronary arteries were stored immediately in phosphate-buffered saline at 4°C. The time between death and OCT and IVUS imaging did not exceed 48 h. The experimental protocol was approved by the Institutional Review Board at Massachusetts General Hospital.

OCT imaging.   The OCT system used in the present study has been described previously (11,14). Optical coherence tomography images were acquired at 4 frames/s (500 angular pixels x 250 radial pixels), displayed with a gray-scale lookup table, and digitally archived. The optical source used in this experiment had a center wavelength of 1,310 nm and a bandwidth of 65 nm, providing an axial resolution of 10 µm in tissue. Before OCT and IVUS imaging, arteries were warmed to 37°C in saline. Coronary arteries were imaged with 3.2-F OCT catheters. The position of the interrogating beam on the tissue was monitored by a visible light beam (laser diode, 635 nm) that was coincident with the infrared beam. We set a total of 128 regions of interest (ROI 0.2 x 0.2 mm) on the OCT images and classified tissue characteristics in the ROIs according to the definitions described in Table 1 (14). All OCT diagnoses were performed by two skilled readers (B.E.B. and G.J.T.) blinded to the diagnoses based on IVUS and histology. For the comparison with diagnoses based on histology, we used ROIs from the OCT images in which the diagnoses made by the two OCT readers were identical.


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  		Table 1. Definitions of Tissue Types of Each ROI
 
IB-IVUS system presets and imaging.   The C-IVUS images and IB signals were acquired using an IVUS system (Clear View, Boston Scientific, Natick, Massachusetts) and a 40-MHz intravascular catheter. In addition, we used an analog-digital converter (Wavepro 960, LeCroy, Chestnut Ridge, New York), which enabled acquisition, storage, and retrieval of signals that were digitized at 1 GHz with 8-bit resolution. The stored ultrasound signals we retrieved from memory and analyzed offline. Integrated backscatter values were calculated as the average power, measured in decibels, of the ultrasound signal backscattered from a small volume of tissue using a fast Fourier transform. The tissue characteristics were classified into calcification, fibrosis, lipid pool, and intimal hyperplasia according to the signal level and color-code by commercially available software (Noesys, Fortner Research LLC, Sterling, Virginia). Our definition of IB values for each histological category was determined by comparing the histological images as reported in a previous study (8). We set ROIs on the corresponding sites of the IVUS images to the OCT image. To clarify the rotational and cross sectional position of the included segment, several surgical needles were carefully inserted in the coronary arteries, and the sites where the needles were inserted were marked by ink before OCT and IVUS imaging to serve as a reference point for comparison with histology. Then, the catheter was advanced in the coronary arteries and pulled back at 0.5 mm/s by activating an auto-pullback device. The time interval between the segments imaged by OCT and IVUS and the segments where surgical needles were inserted was used to determine the precise location of the imaged segments. After images were acquired, the segments marked by ink were used as a reference site for determining the corresponding segments to be used for histology.

All IB-IVUS diagnoses were performed by two skilled readers (K.S. and M.O.) blinded to the histological diagnoses. For the comparison with diagnoses based on histology, we used ROIs from the IB-IVUS images in which the diagnoses made by the two IB-IVUS readers were identical.

Conventional IVUS imaging.   All C-IVUS images were digitized on a square frame (512 pixels x 512 pixels) with an 8-bit gray-scale with 256 grades (1 = white, 256 = black), imported into a personal computer and saved for subsequent review and analysis. The IVUS gain settings were held constant during the study. We set ROIs on the corresponding sites of the IVUS images to the OCT images. Definitions of each tissue component were described in Table 1. These determinations were performed according to the recommendations of the clinical expert consensus document of the American College of Cardiology (19). For the comparison with diagnoses based on histology, we used ROIs from the C-IVUS images in which the diagnoses made by the two C-IVUS readers were identical.

Histological study.   Each coronary arterial ROI was examined for comparing among OCT, IB-IVUS, C-IVUS, and histological diagnoses. Subsequently, two days after fixation with 10% buffered formalin, ring-like arterial specimens obtained at a same level as the imaging study were decalcified for 5 h and then embedded with paraffin and cut in 4-µm transverse sections perpendicular to the longitudinal axis of the artery. They were stained with hematoxylin-eosin and Masson’s trichrome. According to the definition of atherosclerotic lesions by the American Heart Association Council on Atherosclerosis, pathologic subsets were identified in each ROI corresponding to the imaging study (20). These histological classifications were based on the evaluation of a single specialist (S.L.H.) who was blinded to the imaging results.

Statistical analyses.   Numerical data were expressed as the mean ± SD. The degree of agreement between OCT images and IVUS images and interobserver variability were quantified by the Cohen’s {kappa} test for concordance (21). A {kappa} value of 0.61 to 0.80 indicates good agreement, and 0.81 to 1.0 indicates excellent agreement (22). For estimation of predictive ability, the sensitivity, specificity, positive predictive value, and negative predictive value of the different imaging modalities were calculated for each tissue component.


   Results
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Discussion
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Reliability of each imaging modality.   Intravascular ultrasound gray scale levels of calcification, echo-lucent, and intermediate echogenicity using properly adjusted gain settings with 256 grades (1 = white, 256 = black) were 39 ± 17, 217 ± 39 and 91 ± 26, respectively. Of a total of 128 ROIs that were selected from the OCT, IB-IVUS, and C-IVUS images, the two readers made identical diagnoses at 121, 114, and 108 ROIs, respectively. Only the ROIs in which the diagnoses were identical between two readers were used for comparison with histology. The overall agreement between two OCT reader’s diagnoses was high (Cohen’s {kappa} = 0.88 [95% confidence interval (CI) 0.79 to 0.97]). The overall agreement between two IB-IVUS readers’ diagnoses and between two C-IVUS readers’ diagnoses were 0.78 (95% CI 0.67 to 0.88) and 0.62 (95% CI 0.47 to 0.77), respectively (Table 2).


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  		Table 2. Interobserver Variability of Each Imaging Diagnosis
 
Comparison between imaging diagnoses and histological criteria.   Table 3 shows the diagnostic accuracies of each imaging. The sensitivity of OCT for characterizing calcification, fibrosis, lipid pool, and intimal hyperplasia considering histology as a standard was 100%, 98%, 95%, and 86%, respectively. The specificity of OCT was 100%, 94%, 98%, and 100%, respectively. The sensitivity of IB-IVUS for characterizing calcification, fibrosis, lipid pool, and intimal hyperplasia considering histology as a standard was 100%, 94%, 84%, and 67%, respectively. The specificity of IB-IVUS was 99%, 84%, 97%, and 99%, respectively. The sensitivity of C-IVUS for characterizing calcification, fibrosis, and lipid pool was 100%, 93%, and 67%. The specificity of C-IVUS was 99%, 61%, and 95%, respectively. The overall agreement between the OCT and the histological diagnoses was excellent (Cohen’s {kappa} = 0.92, 95% CI 0.85 to 1.00). The overall agreement between the IB-IVUS and histological diagnoses was 0.80 (95% CI 0.69 to 0.92). The overall agreement of between the C-IVUS and histological diagnoses was 0.59 (95% CI 0.42 to 0.77) (Table 4). Representative corresponding cross sections of each imaging modality are shown in Figures 1 and 2.Go The overall agreement between the OCT and the IB-IVUS diagnoses was 0.77 (95% CI 0.65 to 0.90). The overall agreement between the OCT and C-IVUS diagnoses was 0.62 (95% CI 0.44 to 0.79) (Table 5). False-positive diagnoses of IB-IVUS and C-IVUS for lipid pool often contained histological evidence of small amounts of lipid accumulation within a predominantly fibrous lesion. These lesions that included a clinically irrelevant amount of lipid pool were identified as lipid pool by IB-IVUS (n = 3) and echo-lucent by C-IVUS (n = 5), and reduced the negative predictive values for fibrosis (84% and 74%).


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  		Table 3. Assessment of IB-IVUS and Conventional IVUS for Plaque Characterization
 

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  		Table 4. Comparison Between Imaging Diagnosis and Histological Diagnosis
 

Figure 1
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  		Figure 1 Corresponding cross section of each imaging modality. Regions of interest (0.2 mm x 0.2 mm) were randomly set on each image (red squares). (A) Histological image (Masson’s trichrome staining). (B) Optical coherence tomography image. (C) Conventional intravascular ultrasound image. (D) Integrated backscatter intravascular ultrasound image. The lipid pool was detected by histology (arrowhead in A). The same lipid pool was detected by optical coherence tomography as a homogenous, diffusely bordered, signal-poor region (arrowhead in B) and detected by integrated backscatter intravascular ultrasound as the blue area (arrowhead in D). The lipid pool could not be clearly discriminated by conventional intravascular ultrasound. CL = calcification. Bar = 1 mm.

 

Figure 2
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  		Figure 2 Example of a discrepancy between the optical coherence tomography and integrated backscatter intravascular ultrasound diagnosis. (A) Histological image (Masson’s trichrome staining). (B) Optical coherence tomography image. (C) Conventional intravascular ultrasound image. (D) Integrated backscatter intravascular ultrasound image. A fibrous lesion was detected by optical coherence tomography as a homogeneous, highly backscattering (signal-rich) region (arrowhead in B). However, the fibrous lesion was misclassified as intimal hyperplasia by the integrated backscatter intravascular ultrasound image (arrowhead in D) because the fibrous lesion consisted of fibrosis with minimal collagen fiber. CL = calcification. Bar = 1 mm.

 

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  		Table 5. Comparison Between IVUS Diagnosis and OCT Diagnosis
 

   Discussion
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 Abstract
 Methods
 Results
 Discussion
References
 
Comparison between OCT and histological diagnoses.   Optical coherence tomography diagnoses, in which two OCT readers diagnoses were identical, were in excellent agreement with the histological diagnoses in the present study. In our previous study, false negative and false positive diagnoses for lipid-rich plaque were seen comparing the OCT images and histological findings (18). However, in the present study, false negative diagnoses for lipid-rich plaque, which could be attributed to the limited penetration depth of OCT (1.25 to 2.00 mm), were not seen because all ROIs were set within the penetration depth of OCT. In addition, false positive diagnoses for lipid-rich plaque, which could be attributed to difficulty of differentiating clinically relevant large lipid pools and insignificant lipid accumulation, were not seen because of the small ROIs (0.2 mm x 0.2 mm).

Comparison of calcified lesions.   Because of its ease of identification, calcium is one of the most frequently studied tissue components with conventional IVUS imaging. Although C-IVUS and IB-IVUS depict calcified lesions with high sensitivity and specificity, a relationship between the bright signal with shadowing on IVUS and the calcification detected by histology was mainly inferred because it was necessary to decalcify the tissue for sectioning and staining (23). Thus, it was not possible to see the precise location of calcification in the tissue sample. Moreover, subsequent microtome cuts frequently produce artificial tears, which make it difficult to correlate histology with IVUS images for quantitative analysis. Therefore, an absolute gold standard for judging the accuracy of IVUS images for locating site of tissue calcifications has been missing. However, OCT shows the entire calcified lesion and adjacent tissue because of the lack of saturation and acoustic shadowing in the OCT images. Optical coherence tomography imaging, which presents an "optical biopsy," enabled us to precisely compare the IVUS images to the histological features and, thus, locate the calcified lesions.

Discrimination of intimal hyperplasia.   Basically, intimal hyperplasia cannot be discriminated by conventional IVUS. Detecting intimal hyperplasia by conventional IVUS is possible only in the study of restenosis after stent implantation because the major reason for restenosis is intimal hyperplasia, which is a gradual progressive condition (24–26). On the other hand, OCT can detect intimal hyperplasia as a signal-rich layer adjacent to the vessel lumen (14). In a previous IB-IVUS study, although intimal hyperplasia and fibrosis had significantly different IB values, intimal hyperplasia and lipid pool had similar IB values (8). Therefore, discrimination between intimal hyperplasia and lipid pool was based only on the anatomical location of the ROI. Although lipid core are located under fibrous caps, intimal hyperplasia is generally located on the surface of the vessel lumen and is not covered by fibrous cap. Thus, ROIs on the surface of the vessel lumen with IB values indicative of lipid pool were classified as intimal hyperplasia rather than lipid pool. In the present study, the sensitivity and positive predictive value of IB-IVUS for characterizing intimal hyperplasia were not sufficient (67% and 80%). False negative diagnoses for intimal hyperplasia were seen, which could be attributed to similar IB values for the vessel lumen and intimal hyperplasia consisting of loose smooth muscle cells (Fig. 2).

Discrepancy between histological findings and IVUS findings.   The spotty location of the signals indicating lipid pool in fibrous lesions was diagnosed as a clinically irrelevant amount of lipid pool. It was reported that inflammatory cells were observed in 46% of fibrous caps and in 32% of the shoulder of fibrous caps (27). Integrated backscatter values of fibrosis, which abound in inflammatory cells and fibroblasts, tended to be similar to the IB values of intimal hyperplasia and lipid pool. Therefore, false positive diagnoses for lipid pool were seen in the IB-IVUS images. The same tendency was recognized in the diagnoses based on the C-IVUS images.

According to a previous report, very dense fibrous plaques may produce sufficient reflectivity and attenuation or acoustic shadowing to be misclassified as calcified (19). In the present study, there were ROIs that were misclassified as calcification by IB-IVUS (n = 1) and C-IVUS (n = 1) due to this phenomenon.

Diagnostic accuracy of C-IVUS and IB-IVUS.   As reported previously, IVUS has a high capability for the diagnosis of calcification (28–30). Although the diagnostic accuracy of IB-IVUS for discriminating between lipid pool and fibrosis was high, a crossover of IB values or echo-intensity between lipid pool and fibrosis caused a reduction in the diagnostic accuracy of IB-IVUS. In addition, the specificity and negative predictive value for fibrosis were less than expected because intimal hyperplasia was misdiagnosed as fibrosis, and very dense fibrosis was misdiagnosed as calcification (19). Hiro et al. (28) reported that the reasons for discordance between echogenicity and tissue composition were interobserver variability of image interpretation and various types of tissue, which could produce acoustic impedance mismatch in the plaques. In previous studies, the IVUS images used to assess the predictive values for the different tissue components were obtained with a 30-MHz transducer. As described in one study, intimal lesions were easier to detect with a 40-MHz than a 30-MHz transducer (29). In the present study, the predictive accuracy of C-IVUS was generally better than expected compared with the predictive accuracy described in the previous reports (28–30). This was because we used a 40-MHz transducer and ROIs in which the diagnoses made by the two readers were identical, which minimized interobserver variability in characterizing the tissue components. Recent IVUS study has shown that assessment of lipid pools with a 40-MHz transducer was achieved with acceptable accuracy (sensitivity 65%, specificity 95%) (31). The present study supports this previous data.

Study limitations.   There were several limitations in the present study. First, comparison of the images could only be performed relatively close to the surface of the vessel wall because the limited depth of penetration of OCT and ROIs were set within the depth of penetration of OCT. This may increase the accuracy of OCT but decrease the accuracy of the two IVUS modalities. Visualization by OCT is possible only by displacing blood with saline in the clinical setting, whereas imaging in the present study was performed in saline. In addition, arterial specimens used in the present study were not distended by physiological pressure. Therefore, the findings of the present study may not be applicable to the clinical setting. Second, the present study focused on a comparison between OCT imaging and IVUS imaging achieved by conventional and IB methods. It is possible that OCT may not outperform some of the other mathematical models for radiofrequency signal analysis, such as wavelet analysis, autoregressive analysis, and attenuation slope mapping with regard to assessment of the entire arterial wall. Third, atherosclerotic plaque generally contains overlap of the various tissue components and may be heterogeneous. Therefore, evaluation of the diagnostic accuracy of tissue classification by an imaging modality is affected by the size of the ROI. We used relatively small ROIs for comparison. A diagnosis based on a small ROI is not applicable to an entire cross section of an arterial segment. Furthermore, the statistical power to assess diagnostic accuracy was limited by the small number of specimens and ROIs with calcification and intimal hyperplasia and by the inclusion of cases in which the arterial segments used for the analyses were close to each other.

Conclusions.   We reported, in detail, the comparison among OCT, IB-IVUS, and C-IVUS in the same histological images. Optical coherence tomography has the best potential for tissue characterization of coronary plaques. Integrated backscatter IVUS has a better potential for characterizing fibrous lesions and lipid pools than C-IVUS.


   Acknowledgments
 
The authors acknowledge the help of Dr. Keiji Sano and Dr. Munenori Okubo for the support of IVUS diagnosis and Mr. Toshiyuki Nishimura for the support of the experimental equipment.


   Footnotes
 
This study was supported by the Banyu Fellowship Awards in Cardiovascular Medicine, which are sponsored by Banyu Pharmaceutical Co. Ltd. and The Merck Company Foundation.


   References
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 Abstract
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 References
 

  1. Mizuno K, Satomura K, Miyamoto A, et al. Angioscopic evaluation of coronary artery thrombi in acute coronary syndromes N Engl J Med 1992;326:287-291.[Abstract]
  2. Davis MJ. Anatomic feature in victims of sudden coronary deathcoronary artery pathology. Circulation 1992;85:119-124.
  3. Horie T, Sekiguchi M, Hirosawa K. Coronary thrombosis in pathogenesis of acute myocardial infarction. Histopathological study of coronary arteries in 108 necropsied cases using serial section Br Heart J 1978;40:153-161.[Abstract/Free Full Text]
  4. Komiyama N, Berry G, Kolz M, et al. Tissue characterization of atherosclerotic plaques by intravascular ultrasound radio frequency signal analyses. An in vitro study of human coronary arteries Am Heart J 2000;140:565-574.[CrossRef][ISI][Medline]
  5. Murashige A, Hiro T, Fujii T, et al. Detection of lipid-laden atherosclerotic plaque by wavelet analysis of radiofrequency intravascular ultrasound signals. In vitro validation and preliminary in vivo application J Am Coll Cardiol 2005;45:1954-1960.[Abstract/Free Full Text]
  6. Schaar AJ, de Korte CL, Mastik F, et al. Characterizing vulnerable plaque features with intravascular elastography Circulation 2003;108:2636-2641.[Abstract/Free Full Text]
  7. Nair A, Kuban BD, Tuzcu EM, et al. Coronary plaque classification with intravascular ultrasound radiofrequency data analysis Circulation 2002;106:2200-2206.[Abstract/Free Full Text]
  8. Kawasaki M, Takatsu H, Noda T, et al. In vivo quantitative tissue characterization of human coronary arterial plaques by use of integrated backscatter intravascular ultrasound and comparison with angioscopic findings Circulation 2002;105:2487-2492.[Abstract/Free Full Text]
  9. Kawasaki M, Sano K, Okubo M, et al. Volumetric quantitative analysis of tissue characteristics of coronary plaques after statin therapy using three dimensional integrated backscatter intravascular ultrasound J Am Coll Cardiol 2005;45:1946-1953.[Abstract/Free Full Text]
  10. Sano K, Kawasaki M, Ishihara Y, et al. Assessment of vulnerable plaques causing acute coronary syndrome using integrated backscatter intravascular ultrasound J Am Coll Cardiol 2006;47:734-741.[Abstract/Free Full Text]
  11. Tearney GJ, Brezinski ME, Bouma BE, et al. In vivo endoscopic optical biopsy with optical coherence tomography Science 1997;276:2037-2039.[Abstract/Free Full Text]
  12. Brezinski ME, Tearney GJ, Bouma BE, et al. Imaging of coronary artery microstructure (in vitro) with optical coherence tomography Am J Cardiol 1996;77:92-93.[CrossRef][ISI][Medline]
  13. Brezinski ME, Tearney GJ, Bouma BE, et al. Optical coherence tomography for optical biopsyproperties and demonstration of vascular pathology. Circulation 1996;93:1206-1213.[Abstract/Free Full Text]
  14. 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]
  15. Jang IK, Tearney GJ, MacNeill B, et al. In vivo characterization of coronary atherosclerotic plaque by use of optical coherence tomography Circulation 2005;111:1551-1555.[Abstract/Free Full Text]
  16. Brezinski ME, Tearney GJ, Weissman NJ, et al. Assessing atherosclerotic plaque morphologycomparison of optical coherence tomography and high frequency intravascular ultrasound. Heart 1997;77:397-403.[Abstract/Free Full Text]
  17. Kume T, Akasaka T, Kawamoto T, et al. Assessment of coronary intima-media thickness by optical coherence tomographycomparison with intravascular ultrasound. Circ J 2005;69:903-907.[CrossRef][ISI][Medline]
  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. Mintz GS, Nissen SE, Anderson WD, et al. American College of Cardiology clinical expert consensus document on standards for acquisition, measurement and reporting of intravascular ultrasound studies (IVUS). A report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents developed in collaboration with the European Society of Cardiology endorsed by the Society of Cardiac Angiography and Interventions J Am Coll Cardiol 2001;37:1478-1492.[Free Full Text]
  20. Stary HC, Chandler B, Dinsmore RE, et al. American Heart Association 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 atherosclerosis Circulation 1995;92:1355-1374.[Abstract/Free Full Text]
  21. Cohen J. A coefficient of agreement for nominal scales Educ Psychol Meas 1960;20:37-46.[CrossRef][ISI]
  22. Fleiss JL. Statistical Methods for Rates and Proportions. 2nd edition. New York, NY: John Wiley & Son; 1981.
  23. Friedrich GJ, Moes NY, Muhlberger VA, et al. Detection of intralesional calcium by intracoronary ultrasound depends on the histologic pattern Am Heart J 1994;128:435-441.[CrossRef][ISI][Medline]
  24. Mintz GS, Tinana A, Hong MK, et al. Impact of preinterventional arterial remodeling on neointimal hyperplasia after implantation of (non-polymer-encapsulated) paclitaxel-coated stents Circulation 2003;108:1295-1298.[Abstract/Free Full Text]
  25. Murata T, Hiro T, Fujii T, et al. Impact of the cross-sectional geometry of the post-deployment coronary stent on in-stent neointimal hyperplasiaan intravascular ultrasound study. Circ J 2002;66:489-493.[CrossRef][ISI][Medline]
  26. Mehran R, Mintz GS, Hong MK, et al. Validation of the in vivo intravascular ultrasound measurement of in-stent neointimal hyperplasia volumes J Am Coll Cardiol 1998;32:794-799.[Abstract/Free Full Text]
  27. Pasterkamp G, Schoneveld A, van der Wal AC, et al. Relation of arterial geometry to luminal narrowing and histologic markers for plaque vulnerabilitythe remodeling paradox. J Am Coll Cardiol 1998;32:655-662.[Abstract/Free Full Text]
  28. Hiro T, Leung CY, De Guzman S, et al. Are soft echoes really soft? Intravascular ultrasound assessment of mechanical properties in human atherosclerotic tissue Am Heart J 1997;133:1-7.[CrossRef][ISI][Medline]
  29. Di Mario C, The SH, Madretsma S, et al. Detection and characterization of vascular lesions by intravascular ultrasoundan in vitro study correlated with histology. J Am Soc Echocardiogr 1992;5:135-146.[Medline]
  30. Peters RJ, Kok WE, Havenith MG, et al. Histopathologic validation of intracoronary ultrasound imaging J Am Soc Echocardiogr 1994;7:230-241.[Medline]
  31. Prati F, Arbustini E, Labellarte A, et al. Correlation between high frequency intravascular ultrasound and histomorohology in human coronary arteries Heart 2001;85:567-570.[Abstract/Free Full Text]



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