Dataset Information

Non-invasive assessment of the haemodynamic significance of coronary stenosis using fusion of cardiac computed tomography and 3D echocardiography.

ABSTRACT:

Aims

Abnormal computed tomography coronary angiography (CTCA) often leads to stress testing to determine haemodynamic significance of stenosis. We hypothesized that instead, this could be achieved by fusion imaging of the coronary anatomy with 3D echocardiography (3DE)-derived resting myocardial deformation.

Methods and results

We developed fusion software that creates combined 3D displays of the coronary arteries with colour maps of longitudinal strain and tested it in 28 patients with chest pain, referred for CTCA (256 Philips scanner) who underwent 3DE (Philips iE33) and regadenoson stress CT. To obtain a reference for stenosis significance, coronaries were also fused with colour maps of stress myocardial perfusion. 3D displays were used to detect stress perfusion defect (SPD) and/or resting strain abnormality (RSA) in each territory. CTCA showed 56 normal arteries, stenosis <50% in 17, and >50% in 8 arteries. Of the 81 coronary territories, SPDs were noted in 20 and RSAs in 29. Of the 59 arteries with no stenosis >50% and no SPDs, considered as normal, 12 (20%) had RSAs. Conversely, with stenosis >50% and SPDs (haemodynamically significant), RSAs were considerably more frequent (5/6 = 83%). Overall, resting strain and stress perfusion findings were concordant in 64/81 arteries (79% agreement).

Conclusions

Fusion of CTCA and 3DE-derived data allows direct visualization of each coronary artery and strain in its territory. In this feasibility study, resting strain showed good agreement with stress perfusion, indicating that it may be potentially used to assess haemodynamic impact of coronary stenosis, as an alternative to stress testing that entails additional radiation exposure.

SUBMITTER: Maffessanti F

PROVIDER: S-EPMC6279096 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:In the last decades, significant advances have been made in the preventive approaches to cardiovascular disease. Even so, coronary artery disease remains one of the main causes of morbidity and mortality worldwide. Invasive imaging modalities, such as intravascular ultrasound or optical coherence tomography, have played a key role in the comprehension of the pathological processes underlying myocardial infarction and cerebrovascular disease. These imaging techniques have contributed greatly to the identification and phenotyping of the culprit lesion, the so-called vulnerable plaque. Coronary computed tomographic angiography (CCTA) has emerged in more recent years as the non-invasive modality of choice in the study of coronary atherosclerosis, showing in many studies a diagnostic yield comparable to invasive approaches. Moreover, being able to describe extra-luminal characteristics of the affected vessel, CCTA has greatly contributed towards shifting the attention of researchers from the mere quantification of luminal stenosis to the identification of adverse plaque features, which appear to have a stronger prognostic value. However, the identification of some of the hallmarks of vulnerable plaques is qualitative in nature and, therefore, subject to some degree of inter-reader variability. Moreover, CCTA is still unable to identify some fine markers of plaque vulnerability which can be detected by invasive techniques, such as neovascularization and plaque erosion, among others. Nonetheless, radiological images can be viewed as vast 3-D datasets which, via the use of recent technology, allow for the extraction of numerous quantitative features that may be used to accurately phenotype a given lesion. Radiomics is the process of extrapolating innumerable parameters from a given region of interest, with the goal of establishing correlations between quantitative variables and clinical data. These datasets can then be manipulated to create predictive models via the use of automated algorithms in a process called machine learning. As a result of these approaches, radiological images may offer information regarding the characterization of a plaque which can go much beyond the boundaries of what can be qualitatively asserted by the human eye, contributing to expanding the knowledge of the disease and ultimately assist clinical decisions. Thus far, radiomics has found its more consistent area of application in the field of oncology; to present date, the amount of clinical data regarding coronary artery disease is still relatively small, partly due to the technical difficulties associated with the implementation of such techniques to the study of a small and geometrically complex lesion such as the coronary plaque. The present review, after a summary of the imaging modalities most commonly used nowadays in the study of coronary plaques, will provide a perspective on the application of radiomic analysis to coronary artery disease.

Project description:BACKGROUND:Combined evaluation of coronary stenosis and the extent of ischemia is essential in patients with chest pain. Intermediate-grade stenosis on computed tomographic coronary angiography (CTCA) frequently triggers downstream nuclear stress testing. Alternative approaches without stress and/or radiation may have important implications. Myocardial strain measured from echocardiographic images can be used to detect subclinical dysfunction. The authors recently tested the feasibility of fusion of three-dimensional (3D) echocardiography-derived regional resting longitudinal strain with coronary arteries from CTCA to determine the hemodynamic significance of stenosis. The aim of the present study was to validate this approach against accepted reference techniques. METHODS:Seventy-eight patients with chest pain referred for CTCA who also underwent 3D echocardiography and regadenoson stress computed tomography were prospectively studied. Left ventricular longitudinal strain data (TomTec) were used to generate fused 3D displays and detect resting strain abnormalities (RSAs) in each coronary territory. Computed tomographic coronary angiographic images were interpreted for the presence and severity of stenosis. Fused 3D displays of subendocardial x-ray attenuation were created to detect stress perfusion defects (SPDs). In patients with stenosis >25% in at least one artery, fractional flow reserve was quantified (HeartFlow). RSA as a marker of significant stenosis was validated against two different combined references: stenosis >50% on CTCA and SPDs seen in the same territory (reference standard A) and fractional flow reserve < 0.80 and SPDs in the same territory (reference standard B). RESULTS:Of the 99 arteries with no stenosis >50% and no SPDs, considered as normal, 19 (19%) had RSAs. Conversely, with stenosis >50% and SPDs, RSAs were considerably more frequent (17 of 24 [71%]). The sensitivity, specificity, and accuracy of RSA were 0.71, 0.81, and 0.79, respectively, against reference standard A and 0.83, 0.81, and 0.82 against reference standard B. CONCLUSIONS:Fusion of CTCA and 3D echocardiography-derived resting myocardial strain provides combined displays, which may be useful in determination of the hemodynamic or functional impact of coronary abnormalities, without additional ionizing radiation or stress testing.