Intravascular Ultrasound Tissue Characterization Research Articles

Multislice computerized tomography coronary angiography can be a comparable tool to intravascular ultrasound in evaluating "true" coronary artery bifurcations.

Coronary bifurcation atherosclerosis depends on its angles, flow, and extensive branching. We investigate the ability of CT coronary angiography (CTCA) to determine atherosclerotic plaque characteristics of "true" bifurcation compared with intravascular ultrasound (IVUS) and the influence on side branch (SB) fate after percutaneous coronary intervention (PCI). The study included 70 patients with 72 "true" bifurcations. Most of the bifurcations were in the left anterior descending-diagonal (Dg) territory [50 out of 72 (69.4%)]. Longitudinal plaque evaluation at the polygon of confluence [carina and 5 mm proximal and distal in the main branch (MB)] showed that carina side MB and SB plaque had occurred with the lowest incidence with fibro-lipid structure (115 ± 63 HU and 89 ± 73 HU, p < 0.001 for all). Bland-Altman analysis showed a discrepancy in measuring mainly the lumen area between CTCA and IVUS in proximal MB [lumen 5.10, 95% CI (95% confidence interval, 4.53-5.68) mm2, p < 0.001; vessel -1.42, 95% CI (-2.63 to -0.21) mm2, p = 0.023], carina MB [lumen 3.74, 95% CI (3.37-4.10) mm2, p < 0.001; vessel -0.48, 95% CI (-1.45 to 0.48) mm2, p = 0.322], and distal MB [lumen 4.72, 95% CI (4.27-5.18) mm2, p < 0.001; vessel 0.62, 95% CI (-0.53 to 1.77) mm2, p = 0.283]. A significant correlation existed between average plaque density on CTCA with a percentage of calcified plaque on IVUS tissue characterization (proximal r = 0.307/p = 0.024, carina 0.469/0.008, distal 0.339/0.024, minimal lumen diameter 0.318/0.020). Circumferential plaque in the proximal MB segment remained an independent predictor of SB compromise [OR 3.962 (95% CI 1.170-13.418)]. Detection and characterization of atherosclerotic plaque by CTCA in non-left main "true" coronary bifurcations can provide useful information about bifurcation anatomy and plaque distribution that can predict outcomes after provisional stenting, thus guiding the interventional strategy to bifurcation PCI.

IVUS Tissue Characterization of Coronary Plaque by Classification Restricted Boltzmann Machine

The tissue characterization of coronary plaque is an important task to assess the atherosclerotic process and the potential risks of their ruptures on patient. Thanks to intravascular ultrasound (IVUS) medical imaging technique, the reflected ultrasound signals from tissues are acquired, then be used to visualize inside the artery by the computer-assisted equipment. Often, the characterization of tissues is based on the analysis of their responding echo intensity. However, the domination of various factors and the data robustness are the realistic challenges of IVUS classification problems. The quality of the visualization totally depends on the proposed classifier of descriptive features along with its algorithm. In this study, our objective is to characterize IVUS tissues by using classification restricted Boltzmann machine (ClassRBM). We propose to binarize feature patterns extracted from time domain signals for the input of ClassRBM. The results show a better evaluation compared to the conventional integrated backscatter IVUS method (IB-IVUS) for the same task.

Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization.

In this paper, we propose a supervised domain adaptation (DA) framework for adapting decision forests in the presence of distribution shift between training (source) and testing (target) domains, given few labeled examples. We introduce a novel method for DA through an error-correcting hierarchical transfer relaxation scheme with domain alignment, feature normalization, and leaf posterior reweighting to correct for the distribution shift between the domains. For the first time we apply DA to the challenging problem of extending in vitro trained forests (source domain) for in vivo applications (target domain). The proof-of-concept is provided for in vivo characterization of atherosclerotic tissues using intravascular ultrasound signals, where presence of flowing blood is a source of distribution shift between the two domains. This potentially leads to misclassification upon direct deployment of in vitro trained classifier, thus motivating the need for DA as obtaining reliable in vivo training labels is often challenging if not infeasible. Exhaustive validations and parameter sensitivity analysis substantiate the reliability of the proposed DA framework and demonstrates improved tissue characterization performance for scenarios where adaptation is conducted in presence of only a few examples. The proposed method can thus be leveraged to reduce annotation costs and improve computational efficiency over conventional retraining approaches.

Plaque and blood vulnerability in ST segment elevation myocardial infarction patients

The purpose of the study was to evaluate associations between iMap intravascular ultrasound tissue characterization of culprit and nonculprit lesions in infarct-related artery and plasma biomarkers during ST segment elevation myocardial infarction (STEMI) and at 10-month follow-up. Sixty-three STEMI patients at the time of index hospitalization and 10-month follow-up underwent coronary angiography and intravascular ultrasound with iMap tissue characterization of the culprit artery. Proximal and culprit segments were analyzed. A higher percentage of necrotic tissue in the nonculprit segment was found in patients in the top soluble intercellular adhesion molecule 1 (sICAM-1) quartile compared with the other three quartiles (34.3±10.9 vs. 26.3±11.6%, P=0.041) in the acute setting. At 10-month follow-up the top quartile of sICAM-1 in both the acute and stable setting was associated with a lower percentage of fibrotic tissue, but a higher percentage of lipidic and necrotic tissue in the nonculprit segment. In the top quartile of plasminogen activator inhibitor 1 during STEMI, a lower percentage of fibrotic tissue (53.0±13.9 vs. 63.0±13.3%, P=0.014), higher percentage of lipidic tissue (11.7±3.1 vs. 9.4±2.4%, P=0.004), and higher percentage of necrotic tissue (33.4±11.6 vs. 25.7±11.3%, P=0.025) were found in the nonculprit segment. Nonculprit plaque vulnerability characteristics were associated with elevated plasma biomarkers for sICAM-1 and plasminogen activator inhibitor 1.

TCT-670 Impact of Intravascular Ultrasound Tissue Characterization, in Addition to Plaque Burden and Local Endothelial Shear Stress, on the Prediction of New Adverse Cardiac Events in Humans

intravascular ultrasound (IVUS) sub-study enrolled 2064 pts. Methods: Pre-PCI grayscale and VH-IVUS images from 916 culprit lesions in 773 pts were assessed to determine the underlying morphology. Lesions were compared between males (n1⁄4582) vs females (n1⁄4191) in two age groups (< 65 years and 65 years) and included plaque rupture, attenuated plaque, and VH-IVUS thin cap fibroatheroma (TCFA). Results: Culprit lesion plaque ruptures were more common in males than in females overall [254/699 (36.3%) in males vs 50/217 (23.0%) in females, p<0.001] and in younger pts [159/379 (42.0%) in males vs 15/79 (19.0%) in females, p1⁄40.0007], but not in older pts (Table). A similar pattern was seen in VH-TCFAs both overall [373/699 (53.4%) in males vs 97/217 (44.7%) in females, p1⁄40.026] and in younger pts [204/379 (54.0%) in males vs 31/79 (39.0%) in females, p1⁄40.04], but again not in older pts. Multivariate analysis showed that male gender was an independent predictor for plaque rupture [OR:1.85 (1.26, 2.71), p1⁄40.0017] in addition to pre-PCI diameter stenosis [OR: 1.87 (1.57, 2.23) per 10%, p<0.0001], body mass index [OR: 1.05 (1.01, 1.08), 0.005], ST-elevation myocardial infarction [OR: 1.45 (0.99, 2.13), p1⁄40.06], and current smoking [OR: 1.37 (0.99, 1.90), p1⁄40.06]. Conclusions: There was a difference in the frequency of unstable plaque morphology in culprit lesions between male and female pts in young pts; younger male pts had more unstable plaques (plaque ruptures and VH-TCFAs) than younger female pts. However, this difference was not seen in older pts.

A comparison between 40 MHz intravascular ultrasound iMap imaging system and integrated backscatter intravascular ultrasound

BackgroundiMap is a newly developed intravascular ultrasound (IVUS) tissue characterization system based on pattern recognition of the radio frequency (RF) signals. PurposeThe purpose of this study was to compare tissue characterization between iMap and another previously validated tissue characterization system, integrated backscatter (IB)-IVUS in vivo and to clarify similarities and differences between these two methods. MethodsA total of 31 lesions from 16 patients with ischemic heart disease were studied. IVUS imaging was performed using 40MHz IVUS catheter. RF signals from each lesion were then exported to analyze tissue characterization using both iMap and IB-IVUS. By iMap, coronary plaque was classified into four categories, fibrotic, lipidic, necrotic, or calcified. By IB-IVUS, coronary plaque was classified into four categories, fibrosis, lipid pool, dense fibrosis, or calcification. After the images were acquired, IB-IVUS and iMap images were compared at exactly the same cross-sections. Because severe calcification is a perfect reflector, dense calcification lesions (>20%) were excluded. ResultsBoth fibrotic and calcified by iMap correlated well with fibrosis and calcification by IB-IVUS (fibrotic vs. fibrosis: r2=0.522, p<0.001, calcified vs. calcification: r2=0.560, p<0.001). Although lipidic by iMap did not correlate with lipid pool by IB-IVUS, necrotic by iMap correlated well with lipid pool by IB-IVUS (r2=0.480, p<0.001). ConclusionAlthough tissue types classified by iMap correlated well with corresponding tissue type by IB-IVUS, some discrepancy presented between the two systems. These results may call for careful interpretation of the tissue types obtained by the different IVUS tissue characterization systems.

Morphology of coronary artery lesions assessed by virtual histology intravascular ultrasound tissue characterization and fractional flow reserve

Fractional flow reserve (FFR) is an index of the physiological significance of a coronary stenosis. Patients who have lesions with a FFR of >0.80, even optimally treated with medication, have however a MACE rate ranging from 8 to 21%. Coronary plaques at high risk of rupture and clinical events can be also identified by virtual histology intravascular ultrasound (IVUS-VH) as plaques with high amount of necrotic core (NC) abutting the lumen. Aim of this exploratory study was to investigate whether the geometry and composition of lesions with FFR≤0.80 were different from their counterparts. Fifty-five consecutive patients in whom FFR was clinically indicated on a moderate angiographic lesion, received also an imaging investigation on the same lesion with IVUS-VH. Data on plaque geometry and composition was analyzed. Patients were subdivided in two groups according to the value of FFR (> or ≤0.80). Lesions with a FFR≤0.80 (n=17) showed a slightly larger plaque burden than those with FFR>0.80 (n=38) (54.6±0.7% vs. 51.7±0.7% P=0.1). In addition, they tend to have less content of necrotic core than their counterparts (14.2±8% vs. 19.2±10.2%, P=0.08). No difference was found in the distribution of NC-rich plaques (fibroatheroma and thin-capped fibroatheroma) between groups (82% in FFR≤0.80 vs. 79% in FFR>0.80, P=0.5). Although FFR≤0.80 lesions have larger plaque size, they do not differ in composition from the ones with FFR>0.80. Further exploration in a large prospective study is needed to study whether the lesions with FFR>0.80 that are NC rich are the ones associated with the presence of clinical events at follow-up.

The Dynamic Nature of Coronary Artery Lesion Morphology Assessed by Serial Virtual Histology Intravascular Ultrasound Tissue Characterization

We used virtual histology intravascular ultrasound (VH-IVUS) to investigate the natural history of coronary artery lesion morphology. Plaque stability is related to its histological composition. We performed serial (baseline and 12-month follow-up) VH-IVUS studies and examined 216 nonculprit lesions (plaque burden >or=40%) in 99 patients. Lesions were classified into pathological intimal thickening (PIT), VH-IVUS-derived thin-capped fibroatheroma (VH-TCFA), thick-capped fibroatheroma (ThCFA), fibrotic plaque, and fibrocalcific plaque. At baseline, 20 lesions were VH-TCFAs; during follow-up, 15 (75%) VH-TCFAs "healed," 13 became ThCFAs, 2 became fibrotic plaque, and 5 (25%) VH-TCFAs remained unchanged. Compared with VH-TCFAs that healed, VH-TCFAs that remained VH-TCFAs located more proximally (values are median [interquartile range]) (16 mm [15 to 18 mm] vs. 31 mm [22 to 47 mm], p = 0.013) and had larger lumen (9.1 mm(2) [8.2 to 10.7 mm(2)] vs. 6.9 mm(2) [6.0 to 8.2 mm(2)], p = 0.021), vessel (18.7 mm(2) [17.3 to 28.6 mm(2)] vs. 15.5 mm(2) [13.3 to 16.6 mm(2)]; p = 0.010), and plaque (9.7 mm(2) [9.6 to 15.7 mm(2)] vs. 8.4 mm(2) [7 to 9.7 mm(2)], p = 0.027) areas; however, baseline VH-IVUS plaque composition did not differ between VH-TCFAs that healed and VH-TCFAs that remained VH-TCFAs. Conversely, 12 new VH-TCFAs developed; 6 late-developing VH-TCFAs were PITs, and 6 were ThCFAs at baseline. In addition, plaque area at minimum lumen sites increased significantly in PITs (7.8 mm(2) [6.2 to 10.0 mm(2)] to 9.0 mm(2) [6.5 to 12.0 mm(2)], p < 0.001), VH-TCFAs (8.6 mm(2) [7.3 to 9.9 mm(2)] to 9.5 mm(2) [7.8 to 10.8 mm(2)], p = 0.024), and ThCFAs (8.6 mm(2) [6.8 to 10.2 mm(2)] to 8.8 mm(2) [7.1 to 11.4 mm(2)], p < 0.001) with a corresponding decrease lumen areas, but not in fibrous or fibrocalcific plaque. Most VH-TCFAs healed during 12-month follow-up, whereas new VH-TCFAs also developed. PITs, VH-TCFAs, and ThCFAs showed significant plaque progression compared with fibrous and fibrocalcific plaque.

Biomarker Release After Percutaneous Coronary Intervention

Cardiac biomarkers of necrosis provide clinicians with important “messages” from the heart. They are released into the interstitium of the myocardium after loss of the integrity of cardiac myocyte membranes. The pattern of the rise and fall of an individual biomarker (ie, its release kinetics) depends on its intracellular location in the myocyte, molecular weight, and clearance from the interstitium of the myocardium and ultimately the circulation.1 Cardiac biomarkers play an integral role in the clinical diagnosis of myocardial infarction (MI). Referring to the spontaneous occurrence of MI in patients, the World Health Organization required that at least 2 of the following be present to fulfill the criteria for MI: a history of ischemia-type chest discomfort, evolutionary changes on serially obtained ECG tracings, and a rise and fall in serum cardiac markers.2 Article see p 10 See Editorial Circulation . 2008;118:609–611 See Article Circulation . 2008;118:632–638 Several dramatic advances have occurred in the biomarker component of the diagnosis of MI. Analytes with greater specificity for the myocardium were introduced into clinical medicine, with creatine kinase-MB replacing total creatine kinase and subsequently cardiac-specific troponins replacing creatine kinase-MB as the biomarker of choice for diagnosing MI.3 Assay technology improved as clinical chemists moved from enzymatic activity assays for CK to highly specific immunoassays that can detect progressively smaller concentrations of cardiac troponins in the peripheral circulation.4 Although ST-elevation MI (STEMI) is easily identified on the 12-lead ECG, we now recognize that many patients previously diagnosed with unstable angina are more properly diagnosed as having non–ST-elevation MI (NSTEMI) on the basis of the detection of elevated levels of cardiac troponins in their blood.5 Cardiac biomarkers are used as a rough guide to the extent of myocardial necrosis. The higher the peak biomarker level after STEMI, the larger the …

Intravascular ultrasound tissue characterization. I like the rainbow but... what's behind the colours?

Intravascular ultrasound (IVUS) remains the gold standard for, precise, high-quality visualization of atherosclerotic plaque on the vessel wall.1 Conventional grey-scale IVUS provides unique insights into the underlying substrate of atherosclerotic disease, and classical studies have demonstrated that plaque echogenicity correlated with its histological composition. However, despite its ability to provide direct insight on plaque composition, grey-scale IVUS has been unable to identify vulnerable plaques.2 The reason for this appears to be multifaceted. First, the current resolution of the technique is unable to define some subtle characteristics of these plaques, including the thickness of the fibrous cap. Secondly, ‘thrombotic-prone’ plaques have several pathological substrates apart from the classical ‘vulnerable plaque’ (i.e. thin cap fibroateroma) and, phenotypically, constitute a moving target. Thirdly, further accuracy to identify better the distinct histological components of atherosclerotic plaques with IVUS is clearly required. Some technological developments have attempted to overcome the limitations of conventional IVUS to elucidate plaque components.2–6 All of them rely on sophisticated mathematical analyses of the raw radiofrequency signal, aim to obtain real-time clinically meaningful tissue characterization, and provide a “ rainbow ” of appealing colours encoding different plaque components.2–6 Direct use of radiofrequency data avoids signal alterations induced by automated processing and gain adjustments. Integrated backscatter IVUS (IB-IVUS) uses the fast Fourier transformation to analyse frequencies within the signal and provides colour-coded tissue maps of plaque components (lipid, fibrous, and calcified) enabling tissue characterization with a good correlation with histological and angioscopic findings.3 Some provocative preliminary studies have even suggested that IB-IVUS may allow the detection of changes in plaque characteristics induced by lipid-lowering drugs and could also help to predict future coronary events.2,4 Alternative modalities of tissue characterization, namely wavelet analysis of radiofrequency signals, have also been validated to … *Corresponding author. Email: falf{at}hotmail.com

Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes

Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.

Fractal dimension of 40 MHz intravascular ultrasound radio frequency signals

Objective Fully automatic tissue characterization in intravascular ultrasound systems is still a challenge for the researchers. The present work aims to evaluate the feasibility of using the Higuchi fractal dimension of intravascular ultrasound radio frequency signals as a feature for tissue characterization. Methods Fractal dimension images are generated based on the radio frequency signals obtained using mechanically rotating 40 MHz intravascular ultrasound catheter (Atlantis SR Plus, Boston Scientific, USA) and compared with the corresponding correlation images. Conclusion An inverse relation between the fractal dimension images and the correlation images was revealed indicating that the hard or slow moving tissues in the correlation image usually have low fractal dimension and vice-versa. Thus, the present study suggests that fractal dimension images may be used as a feature for intravascular ultrasound tissue characterization and present better resolution then the correlation images.

Feasibility of in vivo intravascular ultrasound tissue characterization in the detection of early vascular transplant rejection.

Unprocessed ultrasound radiofrequency (RF) signal analysis has been shown to distinguish different tissue structures more reliably than gray-scale interpretation of conventional ultrasound images. The objective of this study was to test the feasibility of in vivo intravascular ultrasound (IVUS) RF signal analysis in an animal model of allograft rejection. Six cynomolgus monkeys underwent transplantation of 3-cm aortic allograft segments distal to the renal arteries from immunologically mismatched donors. IVUS imaging with a 30-MHz system was performed 84 to 105 days after the operation. RF signals were acquired from cross sections of the recipient and the allograft aortas in real time with a digitizer at 500 MHz with 8-bit resolution. Sixty-five cross sections and 68 regions of interest (31 in host aorta and 37 in allograft) were analyzed in the adventitial layer with a total number of 8568 vectors processed. For each region of interest, a weighted-average attenuation was calculated on the basis of the attenuation and length for each individual vector. Histological examination was performed at every cross section imaged by IVUS. When the gray-scale images of conventional IVUS scored by an independent observer were compared, no distinction between adventitia of the native aorta and allograft was possible. Analysis of the average RF backscatter power also showed no significant difference (70.32+/-3.55 versus 70.72+/-3.38 dB). However, the average attenuation of allografts was significantly lower than that of the host aortas (2.64+/-1.38 versus 4.02+/-1.16 dB/mm, P<0.001). Histology demonstrated a marked adventitial inflammatory response in all allografts, with no inflammation observed in the host aortas. In vivo IVUS tissue characterization can be performed during routine imaging. In this model of transplant vasculopathy, RF attenuation measurements were more sensitive than visual or quantitative gray-scale analysis.

Distinction between soft plaque and thrombus by intravascular ultrasound tissue characterization

Distinction between soft plaque and thrombus by intravascular ultrasound tissue characterization