Two softwares for ultrasound backscattering tissue characterization are currently available in clinical practice (Fig. 7.2). The first commercial available radiofrequency (RF) signal-based tissue composition analysis tool was the so-called virtual histology (VH-IVUS, Volcano Therapeutics, Rancho Cordova, CA, USA) software [12, 35, 36]. It uses in-depth analysis of the backscattered RF signal in order to provide a more detailed description of the atheromatous plaque composition and is performed with either a 20 MHz, 2.9 Fr phased array transducer catheter (Eagle Eye™ Gold, Volcano Therapeutics) or 45 MHz 3.2 Fr rotational catheter (Revolution, Volcano Therapeutics) that acquires IVUS data electrocardiogram gated [36]. The main principle of this technique is that it uses not only the envelope amplitude of the reflected RF signals (as grayscale IVUS does), but also the underlying frequency content to analyze the tissue components present in coronary plaques. This combined information is processed using autoregressive models and thereafter in a classification tree that determines four basic color-coded plaque tissue components [1, 35]: fibrous tissue (dark green) [2], fibrofatty tissue (light green) [3], necrotic core (red), and [4] dense calcium (white). The current software version assumes the presence of a media layer, which is artificially added, positioned just at the inside of the outer vessel contour. This technique has been compared in several studies against histology in humans and other species [12, 35, 37].

Recently, another RF-based processing method has become commercially available for coronary plaque tissue characterization and it is called iMAP-IVUS (Boston Scientific, Santa Clara, CA, USA) [38, 39]. In principle this software is comparable, from methodological point of view, to the IVUS-VH. However, by design, these two IVUS catheters have different capabilities for tissue characterization. Unlike VH, iMap uses a 40 MHz single rotational transducer on a drive shaft and can acquire radiofrequency data continuously, while VH uses similar catheter and additionally is also available in the electronic catheter (20 MHz). iMap and VH (40 MHz vs. 45/20 MHz) have relative advantages and disadvantages in displaying grayscale images. iMap has higher resolution, but displays specific artifacts such as nonuniform rotational distortion, because it is a rotational catheter. In addition, far-field imaging can be more problematic with high frequency catheters due to amplified attenuation and enhanced blood backscatter. Whereas VH feeds the spectra that are obtained from the radiofrequency data using autoregressive models into a classification tree that has reported diagnostic accuracies of over 90 % each plaque components as compared to histology [12], iMap uses a pattern recognition algorithm on the spectra that were obtained from a fast Fourier transformation and a histology-derived database [38]. The color code for tissue types is also different: iMap depicts fibrotic (light green), lipidic (yellow), necrotic (pink), and calcified tissue (blue), while VH depicts fibrous (green), fibrofatty (yellow green), necrotic core (red), and dense calcium (white), respectively. Taken together, it is possible that these distinctive features may lead to differences in the tissue characteristics of the images of coronary plaque obtained.

Shin et al. compared in vivo findings of this two IVUS-based tissue characterization system, showing a significant and systematic variability in plaque composition estimates [39]. iMap classified plaque as necrotic tissue in poor signal areas, such as guidewire artifact or acoustic shadowing, while VH displays fibrofatty. VH showed EEM as a gray medial stripe, while iMap always provided plaque composition results even for very thin plaques. VH tends to overestimate metallic stent struts, and iMap shows thinner stent thickness than VH. Also, in the VH there is peri-stent dense calcium with necrotic core halo, not seen in the iMap (Fig. 7.3).

Using IVUS-VH, the various stages of atherosclerosis can be defined (Fig. 7.4). The definition of an IVUS-derived TCFA, for example, is a lesion fulfilling the following criteria in at least three consecutive frames [1]: plaque burden ≥40 % [2]; confluent necrotic core ≥10 % in direct contact with the lumen (i.e., no visible overlying tissue) [40]. Using this definition of IVUS-derived TCFA, in patients with ACS who underwent IVUS of all three epicardial coronaries there were, on average, two IVUS-derived TCFAs per patient with half of them showing outward remodeling [40]. The potential value of these IVUS-VH-derived plaque types in the prediction of adverse coronary events was evaluated in an international multicentre prospective study, the Providing Regional Observations to Study Predictors of Events in the Coronary Tree study (PROSPECT study) [41]. The PROSPECT trial was a multicenter, natural history study of acute coronary syndrome patients: all patients underwent PCI in their culprit lesion at baseline, followed by an angiogram and IVUS virtual histology analyses of the three major coronary arteries. The longitudinal distribution of atherosclerotic plaque burden, virtual histology- IVUS characterized necrotic core content, and VH-TCFA was as follows: there was a gradient in plaque burden from the proximal (42.4 %) to mid (37.6 %) to distal (32.6 %) 30-mm-long segments (p < 0.0001). Overall, 67.4 % of proximal, 41.0 % of mid, and 29.7 % of distal 30-mm-long segments contained at least 1 lesion (plaque burden >40 %). Proportion of NC, however, was similar in the proximal and mid 30-mm-long segments of all arteries (10.3 % [interquartile range (IQR): 4.8–16.7 %] vs. 10.6 % [IQR: 5.0–18.1 %], p = 0.25), but less in the distal 30-mm-long segment (9.1 % [IQR: 3.7–17.8 %], p = 0.03 compared with the proximal segment and p = 0.003 compared with the mid segment). Overall, 17.3 % of proximal, 11.5 % of mid, and 9.1 % of distal 30-mm-long segments had at least one lesion that was classified as VH-TCFA (p < 0.0001). Comparing the LMCA with the combined cohort of proximal left anterior descending, left circumflex, and right coronary artery 30-mm-long segments: (1) plaque burden was less (35.4 % [IQR: 28.8–43.5 %] vs. 40.9 % [IQR: 33.3–48.0 %], p < 0.0001); (2) fewer LMCAs contained at least 1 lesion (17.5 %, p < 0.0001); (3) there was less NC (6.5 % [IQR: 2.9–12.2 %] vs. 9.3 % [IQR: 4.3–15.9 %], p < 0.0001); and (4) LMCAs rarely contained a VH-TCFA (1.8 %, p < 0.0001). Authors concluded that lesions that are responsible for acute coronary events (large, plaque burden-rich in NC) are somewhat more likely to be present in the proximal than the distal coronary tree, except for the LMCA [42].

A TCFA with a minimum lumen area of ≤4 mm² and a large plaque burden (≥70 %) had a 17.2 % likelihood of causing an event within 3 years. Interestingly, the anticipated high frequency of acute thrombotic cardiovascular events did not occur, with only a 1 % rate of myocardial infarction and no deaths directly attributable to non-culprit vessels over 3 years of follow-up. These results suggest that non-culprit, yet obstructive coronary plaques are most likely to be associated with increasing symptoms rather than thrombotic acute events, with 8.5 % of patients presenting with worsening angina and 3.3 % with unstable angina. The PROSPECT findings were recently confirmed by the VIVA study [43].

Although plaque characteristics (i.e., tissue characterization) do not yet influence current therapeutic guidelines, the available IVUS-based tissue characterization techniques have the ability to identify some of the pathological atheroma features described above and could help us to advance further our understanding on atherosclerosis.

IVUS-VH has been so far used in various studies in order to show serial changes of plaque composition in patients treated with various statin treatments (Table 7.1).

In one of them, patients with stable angina pectoris (n = 80) treated with fluvastatin for 1 year had significant regression of the plaque volume, and changes in the atherosclerotic plaque composition with a significant reduction of the fibrofatty volume (p < 0.0001). These changes in the fibrofatty volume had a significant correlation with changes in the LDL-cholesterol level (r = 0.703, p < 0.0001) and in the hs-C reactive protein level (r = 0.357, p = 0.006) [44]. Of note, the necrotic core did not change significantly.

In a second study, Hong et al. randomized 100 patients with stable angina and ACS to either rosuvastatin 10 mg or simvastatin 20 mg for 1 year. The overall necrotic core volume significantly decreased (p = 0.010) and the fibrofatty plaque volume increased (p = 0.006) after statin treatments. Particularly, there was a significant decrease in the necrotic core volume (p = 0.015) in the rosuvastatin-treated subgroup. By multiple stepwise logistic regression analysis, they showed that the only independent clinical predictor of decrease in the necrotic core volume was the baseline HDL-cholesterol level (p = 0.040, OR: 1.044, 95 % CI 1.002–1089) [45].

The IBIS 2 study compared the effects of 12 months of treatment with darapladib (oral Lp-PLA2 inhibitor, 160 mg daily) or placebo in 330 patients [46]. Endpoints included changes in necrotic core size (IVUS-VH) and atheroma size (IVUS-grayscale). Background therapy was comparable between groups, with no difference in LDL-cholesterol at 12 months (placebo: 88 ± 34 and darapladib: 84 ± 31 mg/dL, p = 0.37). In the placebo-treated group, however, necrotic core volume increased significantly, whereas darapladib halted this increase, resulting in a significant treatment difference of −5.2 mm³ (p = 0.012). These intraplaque compositional changes occurred without a significant treatment difference in total atheroma volume. Indeed, in a detailed report on the predictors of change either in percentage of necrotic core (PNC) or percentage of atheroma volume (PAV) were the variables associated with a decrease in PNC from baseline were darapladib, ACS, and a large content of NC at baseline, while variables associated with an increase in PNC were previous stroke and percentage diameter stenosis at baseline. Those variables associated with a decrease in PAV from baseline were waist circumference, statin use, CD40L, and baseline PAV, while the only variable associated with an increase in PAV was baseline diastolic blood pressure [47].