Author + information
- Received October 10, 2005
- Revision received January 27, 2006
- Accepted February 7, 2006
- Published online June 20, 2006.
- Kenya Nasu, MD⁎,⁎ (, )
- Etsuo Tsuchikane, MD, PhD⁎,
- Osamu Katoh, MD⁎,
- D. Geoffrey Vince, PhD†,
- Renu Virmani, MD‡,
- Jean-François Surmely, MD⁎,
- Akira Murata, MD⁎,
- Yoshihiro Takeda, MD⁎,
- Tatsuya Ito, MD⁎,
- Mariko Ehara, MD⁎,
- Tetsuo Matsubara, MD⁎,
- Mitsuyasu Terashima, MD⁎ and
- Takahiko Suzuki, MD, PhD⁎
- ↵⁎Reprint requests and correspondence:
Dr. Kenya Nasu, The Department of Cardiology, Toyohashi Heart Center, 21-1 Azagobutori, Ohyama-cho, Toyohashi-city, Aichi, 441-8530 Japan.
Objectives The goal of the present study was to compare the accuracy of in vivo tissue characterization obtained by intravascular ultrasound (IVUS) radiofrequency (RF) data analysis, known as Virtual Histology (VH), to the in vitro histopathology of coronary atherosclerotic plaques obtained by directional coronary atherectomy.
Background Vulnerable plaque leading to acute coronary syndrome (ACS) has been associated with specific plaque composition, and its characterization is an important clinical focus.
Methods Virtual histology IVUS images were performed before and after a single debulking cut using directional coronary atherectomy. Debulking region of in vivo histology image was predicted by comparing pre- and post-debulking VH images. Analysis of VH images with the corresponding tissue cross section was performed.
Results Fifteen stable angina pectoris (AP) and 15 ACS patients were enrolled. The results of IVUS RF data analysis correlated well with histopathologic examination (predictive accuracy from all patients data: 87.1% for fibrous, 87.1% for fibro-fatty, 88.3% for necrotic core, and 96.5% for dense calcium regions, respectively). In addition, the frequency of necrotic core was significantly higher in the ACS group than in the stable AP group (in vitro histopathology: 22.6% vs. 12.6%, p = 0.02; in vivo virtual histology: 24.5% vs. 10.4%, p = 0.002).
Conclusions Correlation of in vivo IVUS RF data analysis with histopathology shows a high accuracy. In vivo IVUS RF data analysis is a useful modality for the classification of different types of coronary components, and may play an important role in the detection of vulnerable plaque.
Atherosclerosis and its thrombotic complications are the leading cause of morbidity and mortality in industrialized countries. Rupture of vulnerable atherosclerotic plaques is the cause of most acute coronary syndrome (ACS). Atherosclerotic stability is related to its histologic composition, risk stratification, and treatment of high-risk lesions before rupture.
Gray scale intravascular ultrasound (IVUS) is a useful modality for characterizing the extent and distribution of atherosclerotic plaques in vivo as well as for the determination of the morphology of atherosclerotic plaques and the vessel wall (1–3). However, the region of low echogenicity, which is thought to represent the composition of lipid-containing and mixed plaque, remains relatively uncharacterized by gray scale IVUS (1,2).
Spectral analysis of the radiofrequency (RF) ultrasound backscatter signals known as Virtual Histology (VH) offers an in vivo opportunity to assess plaque morphology (4–7). Indeed, the VH IVUS technology (Volcano Therapeutics, Inc., Rancho Cordova, California) has been shown to have a 80% to 92% in vitro accuracy when used to identify the four different types of atherosclerotic plaques (e.g., fibrous, fibro-fatty, dense calcium, and necrotic core) (4). However, no quantitative in vivo histologic comparisons or validations exist. Therefore, the goal of the present study was to compare the accuracy of in vivo tissue characterization obtained by VH IVUS RF data analysis to the in vitro histopathology of coronary atherosclerotic plaques obtained by directional coronary atherectomy (DCA), and also to evaluate the differences in plaque compositions between stable angina pectoris (AP) and ACS.
The present study is a prospective single-center registry. The inclusion criteria consisted of patients older than 18 years of age with either symptomatic stable AP or ACS (Braunwald class IIIB, with positive serum markers) who were good candidates for percutaneous coronary revascularization. Angiographic inclusion criteria were: 1) target vessel reference diameter of >2.5 mm by visual estimation to allow the use of the FLEXI-CUT atherocatheter (Guidant Corp., Santa Clara, California; 2) one de-novo culprit lesion of >50% diameter stenosis, as determined by on-line quantitative coronary angiography; 3) mild-to-moderate vessel tortuosity; and 4) left ventricular ejection fraction >30%. Exclusion criteria were: 1) contraindications to IVUS examination; 2) severe peripheral vascular diseases that precluded the use of a 8-F arterial sheath; 3) other concomitant diseases or medical conditions that could impact patient/procedural outcomes, such as history of bleeding diathesis, stroke, or transient ischemic neurological attacks within the past year or hypersensitivity to heparin, aspirin, ticlopidine or X-ray contrast media; and 4) a positive pregnancy test.
The institutional review board of our institution approved the study, and all patients gave written, informed consent.
Procedure and data acquisition
The schema of procedure and data acquisition is illustrated in Figure 1.After baseline angiography, a 3.2-F, 30-MHz catheter (Boston Scientific Scimed Inc., Maple Grove, Minnesota) was placed distal to the target lesion. The catheter tip position was determined by infusion of contrast media, and was subsequently pulled back to the aortic ostium using a motorized pullback system set at 0.5 cm/s. During pullback, gray scale IVUS was recorded on super VHS videotape for off-line analysis, and raw RF data was captured at the top of the R-wave for reconstruction of the color-coded map by a VH data recorder (Volcano Therapeutics, Inc.). The captured RF data were written on optical discs and sent to the Cleveland Clinic Foundation (Cleveland, Ohio) for VH IVUS analysis.
Directional coronary atherectomy was performed at the region of the target lesion that corresponded to minimal luminal diameter on gray scale IVUS. Debulking was performed just one time with high pressure. The DCA procedure was performed and recorded in accordance with hospital standard of care. Angiography and IVUS with electrocardiogram-gated raw RF data acquisition were repeated after the atherectomy. The tissue sample was extracted from the atherocatheter and marked with a small clip or ink at the distal end.
During DCA, the tissue sample was assumed to be cut and pushed into the nosecone. However, it was not certain that the tissue sample was only pushed into the nosecone, but could possibly be curled into it, therefore misleading the marking of the proximal and distal end of the tissue sample. To address this issue, an in vitro experiment was performed as follows: 1) red ink was injected in a piece of porcine aorta; 2) an atherocatheter was positioned with the proximal end of the cutter window placed on the ink injected region; 3) the window was pressed on the aortic wall by finger, and the debulking procedure was performed; and 4) saline was injected from the tip of the nosecone, and the direction of the extracted tissue was evaluated. Over the 20 samples obtained with this method, the end of the tissue sample was reversed only one time.
Angiography was performed in at least two projections. Pre-debulking on-line quantitative coronary angiography was conducted utilizing the view revealing the highest degree of stenosis, and severity of coronary stenosis was measured using the Cardiovascular Measurement System (CMS-MEDIS Medical Imaging System, Leiden, the Netherlands). The lesion length, reference diameter, minimal luminal diameter, and diameter stenosis was calculated off-line by an independent operator. Analysis of cine frames was performed in end-diastole.
The length of tissue sample was measured immediately after extraction from the catheter. Tissue samples were immersion-fixed in 10% neutral-buffered formalin, processed for paraffin embedding, and sliced into 4-μm sections every 0.5 mm, starting proximally. After staining with hematoxylin and eosin, histology sections were forwarded to the Armed Forces Institute of Pathology (Washington, DC) and analyzed by an isolated operator who was blinded to the IVUS data acquisition. Four plaque components (fibrous tissue, fibro-fatty, necrotic core, and dense calcium) were defined (4,5) as follows: 1) fibrous tissue: areas of densely packed collagen; 2) fibro-fatty: fibrous tissue with significant lipid interspersed in collagen; 3) necrotic core: necrotic regions consisting of cholesterol clefts, foam cell, and microcalcifications; and 4) dense calcium: calcium depositing without adjacent necrosis. After analysis, the digitized histopathologic images and a description of the data were forwarded to the Cleveland Clinic Foundation for correlative analysis.
Gray scale IVUS analysis
From the pre-debulking IVUS data, the smallest lumen at the culprit lesion was identified from clockwise and longitudinal plaque distribution. Calculations were performed by an experienced operator. Vessel cross-sectional area and lumen cross-sectional area were calculated, and the difference between the two values was defined as plaque plus media cross-sectional area. Percent plaque plus media cross-sectional area was defined as plaque plus media cross-sectional area divided by vessel cross-sectional area.
VH IVUS analysis
Virtual histology analysis was performed at The Cleveland Clinic Foundation. Atherosclerotic coronary plaques were characterized by classification trees based on mathematical autoregressive spectral analysis of IVUS backscattered data (IVUSLab software, Volcano Therapeutics, Inc.), as described previously (8). The presence of fibrous, fibro-fatty, necrotic core, and dense calcium areas were assessed within the region of target lesion using pre- and post-debulking RF data collection scans. Fibrous areas were marked in green, fibro-fatty in yellow, dense calcium in white, and necrotic core in red. Finally, the predicted plaque composition was displayed as a color-coded tissue map. Virtual histology analysis was performed by an experienced analyst who was blinded to the in vitro histopathologic analysis.
VH IVUS-histopathology correlation analysis
Correlation analysis methodology is shown in Figure 2.
1. On the post-debulking gray scale IVUS, the proximal end of the debulking site was identified, and its distance from a proximal side branch (landmark) was accurately measured. In order to identify the proximal end of the debulking site on the pre-debulking IVUS images, this distance was measured from the same landmark.
2. Knowing the R-R interval (s) and the pullback speed of the IVUS catheter (0.5 mm/s), the distance between each VH images was calculated as follow: distance between two VH images (mm) = R-R interval × 0.5.
3. Knowing the interval (s) between the proximal end of debulking site and the nearest top of R-wave, its distance could be calculated as follows: distance 0 = interval × 0.5.
4. The distance between histology sections was calculated as 0.5 mm (= distance of cutting tissue) times the ratio of pre-fixed length of tissue sample (mm) to post-fixed length (mm) in order to correct for a 20% to 30% tissue sample shrinking during post-processing (8).
5. The VH image that was closest to each section was chosen as the corresponding color-coded map.
6. The debulked area on pre-debulking VH images was predicted by comparison of pre- with post-debulking VH images.
7. Histology sections and correlating VH images were assessed visually for the presence or absence of the four different components.
Continuous data are represented as mean values ± SD. Categoric data are expressed as frequencies of occurrence, and differences between groups were compared with chi-square tests. Comparison of continuous variables were performed by two-tailed unpaired Student ttest for normally distributed variables and by Mann-Whitney test for variables with skewed distribution. Statview version 5.0 (Abacus Concepts Inc., Berkeley, California) was used for data analysis. A probability value of <0.05 was considered to indicate statistical significance. The results from VH images were validated with the corresponding histopathology to determine predictive accuracy, sensitivity, and specificity from widely accepted equations in biomedical literature (9).
Baseline characteristics and procedural data
Between May 2004 and July 2005, 30 patients (15 patients with stable AP and 15 patients with ACS) met eligibility criteria for this study and were enrolled. Baseline demographic and clinical data are summarized in Table 1.There were no significant differences between the two groups. Baseline lesion characteristics and procedural data are summarized in Table 2.All lesion characteristics and debulking pressure were well matched between the two groups. No complications, including perforation, no-reflow, need for emergency bypass surgery or death, occurred during DCA.
Correlation of in vivo and in vitro histology
The predictive accuracy, sensitivity, and specificity for correlation analysis are shown in Table 3.The mean longitudinal gap between the VH image and the in vitro histology section was 0.11 ± 0.07 mm (range, 0 to 0.32 mm). Fibrous, fibro-fatty, necrotic core, and dense calcium regions were classified with high predictive accuracies of 87.1%, 87.1%, 88.3%, and 96.5%, respectively, using data from all patients. This trend was also observed in both subgroups.
Representative examples of color-coded tissue maps of VH were compared, and their comparison with the corresponding hematoxylin and eosin stained sections are shown in Figure 3.Gray scale IVUS could not differentiate necrotic core and fibro-fatty plaque (labeled as low-density area; cases 1a and 2a). In contrast, color-coded maps obtained by VH IVUS analysis could distinguish fibro-fatty plaque (labeled as yellow area; cases 1b and 2b) and necrotic core (as red area; cases 1b and 2b) with dense calcium as white. The predicted debulking area (within blue circle) showed a favorable correlation with in-vitro histopathology (cases 1d and 2d).
Tissue samples and in vitro histopathologic findings
The mean length of debulked tissue samples was 6.89 ± 1.69 mm, and there was no significant difference when comparing the two groups (stable AP, 6.27 ± 1.48 mm vs. 7.70 ± 1.72 mm, p = 0.12). Thrombi were observed more frequently in the ACS group than in the stable AP group (26.7% cases of stable AP and all cases of ACS patients). The frequency of each tissue component presence is illustrated in Table 4.A total of 307 sections were obtained (stable AP, n = 144; ACS, n = 163). The presence of necrotic core tissue was observed more frequently in the ACS group than in the stable AP group (22.6% vs. 12.5%, p = 0.02). In contrast, there were no significant differences in the frequency of the other plaque components when comparing the two groups.
In vivo VH images
The frequency of each plaque component at the predicted debulking area, identified from the comparison between pre- and post-debulking VH images, is illustrated in Table 4. The presence of necrotic core and dense calcium were observed more frequently in the ACS group than in the stable AP group (24.5% vs. 10.4%, p = 0.002; 11.1% vs. 4.1%, p = 0.03).
This is the first clinical study to assess the accuracy of in vivo histology for the diagnosis of plaque composition. Our single-center experience showed that in vivo tissue characterization by IVUS-based RF analysis favorably correlated with the results of in vitro histopathologic examination of tissue samples obtained by DCA. Thus, the use of VH IVUS for differentiating components of atherosclerotic tissue was achieved with high predictive accuracy.
Characterization of plaque components
Several characteristics inherent to IVUS imaging offer potential advantages in the evaluation of coronary disease. This tomographic orientation is able to visualize the full circumference of the vessel wall, examine arterial remodeling, and assess the thickness and echogenicity of atherosclerotic plaques (10–13). However, identification of atherosclerotic plaque components by densitometric category of gray scale IVUS is limited because of processing of the raw RF data (time-gain compensation, logarithmic compression, and envelope detection, and so on), and also interpretation must rely on simple visual inspection of acoustic reflections to determine plaque component. In previous in vivo or ex vivo studies, calcified and fibrous plaques were well identified by their hyperechoic appearance and homogeneous echocardiographic reflection (1–3,14–16). However, discrimination between lipid-containing and mixed (fibro-lipidic plaque), labeled as a region of low-density in gray scale IVUS remains difficult to achieve (1,2,17). Besides, analysis of tissue behind a calcification is difficult of signal attenuation.
In a previous study of the correlation of gray scale IVUS image with in vitro histopathology of an atherectomy sample, gray scale IVUS could not differentiate plaque compositions (18). However, previous ex vivo studies showed that characterization of different plaque component is feasible with the analysis of IVUS RF data (4–7). Further, this modality had potential clinical applications, as color-coding of plaque components allowed real-time evaluation during the procedure (Fig. 3). The present data from the in vivo IVUS RF analysis and the in vitro histopathologic images correlated well, indicating that VH IVUS is a useful modality for real-time characterization of clinically relevant plaque components.
However, although the frequency of dense calcium in the in vitro histology was not significantly different when comparing the two groups, in vivo VH images suggested an increase in dense calcium in the ACS group when compared with the stable AP group. Thus, although in vivo data correlated well with in vitro histology (predictive accuracy of 96.5%), the RF data analysis overestimated the frequency of calcifications. A previous report showed that the extent of calcium detected by electron-beam computed tomography was greater than would have been expected with regard to their age and gender (19). However, some post-mortem pathologic analyses of coronary arteries reported that calcium was a frequent feature of plaque rupture (20,21); others showed that ruptured plaques were less likely to be calcified in ACS patients (22,23). Thus, coronary calcium is not a marker for neither unstable nor stable plaques. Possible explanations for this overestimation may be as follows: 1) the IVUS beam is approximately 300 μm in longitudinal thickness, whereas the histology section is only 4-μm thick. A VH image therefore includes more tissue than a histology section; 2) the presence of calcium occurred with a very low frequency in this target lesion population; and 3) artifact is colored with white because the software for VH analysis is obliged to assign one of the four colors for each pixel.
Ability for detection of vulnerable plaques
The vulnerability of plaque to rupture is typically characterized by the presence of a necrotic core, which is a region of the fibroatheroma that is largely devoid of viable cells and consists of cellular debris and cholesterol clefts, a thin fibrous cap (<65 μm), and macrophage infiltration (24,25). Rupture of vulnerable plaques is defined as a necrotic core with a thin fibrous cap that is disrupted or ruptured (26–28) and their identification before rupture is an important clinical goal. In the present study, the presence of necrotic core was significantly higher in the ACS group than in the stable AP group, and these results correlated with between VH and histopathology data. The presence of necrotic core in debulking tissue, which is the part of atherosclerotic plaque situated at the lumen border, may possibly be the sign for a thin cap fibroatheroma.
The great advantage of VH IVUS is that it is based on a device that is practical for use in the clinical setting and that it generates a real-time assessment of plaque morphology. However, because this technology is based on IVUS with a maximum radial resolution of 100 μm, it cannot evaluate the presence or absence of a thin fibrous cap. Various invasive and noninvasive imaging techniques have been employed to detect vulnerable plaque (29–36), and the combination of these modalities may help in overcoming their individual limitations. For example, improved results may be obtained by combining the use of anatomic methods, including IVUS, VH IVUS, elastography, and optical coherence tomography, with functional imaging methods, such as thermography.
This study has several limitations. First, although 307 pairs of VH IVUS images and correlating histologic slices were obtained prospectively, only 30 patients from one center were involved. Study of larger patient populations from various centers is warranted to confirm these data.
Second, tissue samples obtained by DCA consisted of only the superficial part of the atherosclerotic plaque, which are smaller than artery samples obtained from autopsies, and yield smaller histologic section areas. However, the cross sectional location in the atherosclerotic plaque could be identified by comparing pre- and post-procedural VH IVUS images.
Third, it is possible that the extracted tissue reversed in the nosecone. Extrapolating the results from our in-vitro experiment described in the Methods section, this may have happened in one or two tissue samples of the current study. We calculated the sensitivity, specificity, and predictive accuracy that would have been obtained if a sample was reversed, and repeated it for each of the 30 samples. The results were, however, in a similar range.
Fourth, for the extracted tissue sample, there is a selection bias in the kind of lesion included in the present study by the fact that DCA is not an adequate method for calcified lesions. This may explain the fact that the presence of calcium occurred with a very low frequency in the present study population. Despite this fact, correlation analysis between predicted debulking area in the in vivo histology and in the in vitro histopathology showed favorable results and high predictive accuracy.
Fifth, although atherothrombi caused by plaque rupture, plaque erosion, and calcified nodules that protrude into the lumen occur in cases of ACS (37), the present version of VH IVUS technology is unable to differentiate thrombus. This algorithm relies on the placement of two borders, namely the luminal border and the media-adventitia border, so that small thrombus within these two borders might lead incorrect tissue characterization.
Sixth, the location of each VH image and histology section was identified as accurately as possible (Fig. 2). However, the pre- and post-procedural color-coded map may vary from the in-vitro histology section, because the RF data is captured at only the top of the R-wave, and the tissue sample may shrink during post-processing (8), leading to potential bias.
Finally, in this study we used a mechanical IVUS catheter for the recording of the RF data. The analysis software processing these data is almost identical to the one used with the phased-array IVUS catheter, which is commercially available. In this study, an IVUS pullback was performed with both systems in 10 patients with 85 sections. In these 85 sections, the predictive accuracies for the mechanical system were 86.8% for fibrous, 83.1% for fibro-fatty, 89.6% for necrotic core, and 96.9% for dense calcium, respectively. The predictive accuracies for the phased-array system were 87.8%, 79.7%, 91.1%, and 97.8%, respectively. The results obtained by both systems are similar. Consequently, the results of this study support as well the use of VH obtained with a phased-array system.
A color-coded mapping method using IVUS RF data analysis is useful to identify atherosclerotic plaque components of human coronary artery in vivo. This technique may play an important role in detecting vulnerable plaque.
This study was supported by a grant from Volcano Therapeutics, Inc., Rancho Cordova, California.
- Abbreviations and Acronyms
- acute coronary syndrome
- angina pectoris
- directional coronary atherectomy
- intravascular ultrasound
- Virtual Histology
- Received October 10, 2005.
- Revision received January 27, 2006.
- Accepted February 7, 2006.
- American College of Cardiology Foundation
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