Cardiac computed tomography (CT) was initially developed as a non-invasive diagnostic tool to detect and quantify coronary stenosis. Thanks to the rapid technological development, cardiac CT has become a comprehensive imaging modality which offers anatomical and functional information to guide patient management. This is the second of two complementary documents endorsed by the European Association of Cardiovascular Imaging aiming to give updated indications on the appropriate use of cardiac CT in different clinical scenarios. In this article, emerging CT technologies and biomarkers, such as CT-derived fractional flow reserve, perfusion imaging, and pericoronary adipose tissue attenuation, are described. In addition, the role of cardiac CT in the evaluation of atherosclerotic plaque, cardiomyopathies, structural heart disease, and congenital heart disease is revised.

Cardiac computed tomography (CT) was introduced in the late 1990’s. Since then, an increasing body of evidence on its clinical applications has rapidly emerged. From an initial emphasis on its technical efficiency and diagnostic accuracy, research around cardiac CT has now evolved towards outcomes-based studies that provide information on prognosis, safety, and cost. Thanks to the strong and compelling data generated by large, randomized control trials, the scientific societies have endorsed cardiac CT as pivotal diagnostic test for the management of appropriately selected patients with acute and chronic coronary syndrome. This consensus document endorsed by the European Association of Cardiovascular Imaging is divided into two parts and aims to provide a summary of the current evidence and to give updated indications on the appropriate use of cardiac CT in different clinical scenarios. This first part focuses on the most established applications of cardiac CT from primary prevention in asymptomatic patients, to the evaluation of patients with chronic coronary syndrome, acute chest pain, and previous coronary revascularization.

Both the Assessing Diagnostic Value of Noninvasive FFRCT in Coronary Care (or ADVANCE) cohort and the clinical cohort of more than 10 000 patients showed relatively low rates for technically... Background Coronary artery fractional flow reserve (FFR) derived from CT angiography (FFTCT) enables functional assessment of coronary stenosis. Prior clinical trials showed 13%–33% of coronary CT ...

Atherosclerotic plaque characterization by coronary computed tomography angiography (CCTA) enables quantification of coronary artery disease (CAD) burden and type, which has been demonstrated as the strongest discriminant of future risk of major adverse cardiac events (MACE). To date, there are no clinically useful thresholds to assist with understanding a patient's disease burden and guide diagnosis and management, as there exists with coronary artery calcium (CAC) scoring. The purpose of this manuscript is to establish clinically relevant plaque stages and thresholds based on evidence from invasive angiographic stenosis (ICA) and fractional flow reserve (FFR) data. 303 patients underwent CCTA prior to ICA and FFR for an AHA/ACC clinical indication. Quantitative computed tomography (QCT) was performed for total plaque volume (TPV, mm³) and percent atheroma volume (PAV, %). We segmented atherosclerosis by composition for low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), and calcified plaque (CP). ICAs were evaluated by quantitative coronary angiography (QCA) for all coronary segments for % diameter stenosis. The relationship of atherosclerotic plaque burden and composition by QCT to ICA stenosis extent and severity by QCA and presence of ischemia by FFR was assessed to develop 4 distinct disease stages. The mean age of the patients was 64.4 ​± ​10.2 years; 71% male. At the 50% QCA stenosis threshold, QCT revealed a mean PAV of 9.7 (±8.2)% and TPV of 436 (±444.9)mm³ for those with non-obstructive CAD; PAV of 11.7 (±8.0)% and TPV of 549.3 (±408.3) mm³ for 1 vessel disease (1VD), PAV of 17.8 (±9.8)% and TPV of 838.9 (±550.7) mm³ for 2VD, and PAV of 19.2 (±8.2)% and TPV of 799.9 (±357.4) mm³ for 3VD/left main disease (LMD). Non-ischemic patients (FFR >0.8) had a mean PAV of 9.2 (±7.3) % and TPV of 422.9 (±387.9 ​mm³) while patients with at least one vessel ischemia (FFR ≤0.8) had a PAV of 15.2 (±9.5)% and TPV of 694.6 (±485.1). Definition of plaque stage thresholds of 0, 250, 750 ​mm³ and 0, 5, and 15% PAV resulted in 4 clinically distinct stages in which patients with no, nonobstructive, single VD and multi-vessel disease were optimally distributed. Atherosclerotic plaque burden by QCT is related to stenosis severity and extent as well as ischemia. We propose staging of CAD atherosclerotic plaque burden using the following definitions: Stage 0 (Normal, 0% PAV, 0 ​mm³ TPV), Stage 1 (Mild, >0-5% PAV or >0-250 ​mm³ TPV), Stage 2 (Moderate, >5-15% PAV or >250-750 ​mm³ TPV) and Stage 3 (Severe, >15% PAV or >750 mm3 TPV).

BACKGROUND: Multimodality imaging is currently suggested for the noninvasive diagnosis of cardiac masses. The identification of cardiac masses’ malignant nature is essential to guide proper treatment. We aimed to develop a cardiac magnetic resonance (CMR)-derived model including mass localization, morphology, and tissue characterization to predict malignancy (with histology as gold standard), to compare its accuracy versus the diagnostic echocardiographic mass score, and to evaluate its prognostic ability. METHODS: Observational cohort study of 167 consecutive patients undergoing comprehensive echocardiogram and CMR within 1-month time interval for suspected cardiac mass. A definitive diagnosis was achieved by histological examination or, in the case of cardiac thrombi, by histology or radiological resolution after adequate anticoagulation treatment. Logistic regression was performed to assess CMR-derived independent predictors of malignancy, which were included in a predictive model to derive the CMR mass score. Kaplan-Meier curves and Cox regression were used to investigate the prognostic ability of predictors. RESULTS: In CMR, mass morphological features (non-left localization, sessile, polylobate, inhomogeneity, infiltration, and pericardial effusion) and mass tissue characterization features (first-pass perfusion and heterogeneity enhancement) were independent predictors of malignancy. The CMR mass score (range, 0–8 and cutoff, ≥5), including sessile appearance, polylobate shape, infiltration, pericardial effusion, first-pass contrast perfusion, and heterogeneity enhancement, showed excellent accuracy in predicting malignancy (areas under the curve, 0.976 [95% CI, 0.96–0.99]), significantly higher than diagnostic echocardiographic mass score (areas under the curve, 0.932; P =0.040). The agreement between the diagnostic echocardiographic mass and CMR mass scores was good (κ=0.66). A CMR mass score of ≥5 predicted a higher risk of all-cause death ( P <0.001; hazard ratio, 5.70) at follow-up. CONCLUSIONS: A CMR-derived model, including mass morphology and tissue characterization, showed excellent accuracy, superior to echocardiography, in predicting cardiac masses malignancy, with prognostic implications.