Insights in Cardiovascular Imaging: 2021

Background: Although epicardial adipose tissue (EAT) is associated with coronary artery disease (CAD), it is unclear whether EAT volume (EAV) can be used to diagnose high-risk coronary plaque burden associated with coronary events. This study aimed to investigate (1) the prognostic impact of low-attenuation non-calcified coronary plaque (LAP) burden on patient level analysis, and (2) the association of EAV with LAP volume in patients without known CAD undergoing coronary computed tomography angiography (CCTA).

Materials and Methods: This retrospective study consisted of 376 patients (male, 57%; mean age, 65.2 ± 13 years) without known CAD undergoing CCTA. Percent LAP volume (%LAP, <30 HU) was calculated as the LAP volume divided by the vessel volume. EAT was defined as adipose tissue with a CT attenuation value ranging from −250 to −30 HU within the pericardial sac. The primary endpoint was a composite event of death, non-fatal myocardial infarction, and unstable angina and worsening symptoms requiring unplanned coronary revascularization >3 months after CCTA. The determinants of %LAP (Q4) were analyzed using a multivariable logistic regression model.

Results: During the follow-up period (mean, 2.2 ± 0.9 years), the primary endpoint was observed in 17 patients (4.5%). The independent predictors of the primary endpoint were %LAP (Q4) (hazard ratio [HR], 3.05; 95% confidence interval [CI], 1.09–8.54; p = 0.033] in the Cox proportional hazard model adjusted by CAD-RADS category. Cox proportional hazard ratio analysis demonstrated that %LAP (Q4) was a predictor of the primary endpoint, independnet of CAD severity, Suita score, EAV, or CACS. The independent determinants of %LAP (Q4) were CACS ≥218.3 (p < 0.0001) and EAV ≥125.3 ml (p < 0.0001). The addition of EAV to CACS significantly improved the area under the curve (AUC) to identify %LAP (Q4) than CACS alone (AUC, EAV + CACS vs. CACS alone: 0.728 vs. 0.637; p = 0.013).

Conclusions: CCTA-based assessment of EAV, CACS, and LAP could help improve personalized cardiac risk management by administering patient-suited therapy.

Background: Cardiac CT (CCT) is well suited for a detailed analysis of heart structures due to its high spatial resolution, but in contrast to MRI and echocardiography, CCT does not allow an assessment of intracardiac flow. Computational fluid dynamics (CFD) can complement this shortcoming. It enables the computation of hemodynamics at a high spatio-temporal resolution based on medical images. The aim of this proposed study is to establish a CCT-based CFD methodology for the analysis of left ventricle (LV) hemodynamics and to assess the usability of the computational framework for clinical practice.

Materials and Methods: The methodology is demonstrated by means of four cases selected from a cohort of 125 multiphase CCT examinations of heart failure patients. These cases represent subcohorts of patients with and without LV aneurysm and with severe and no mitral regurgitation (MR). All selected LVs are dilated and characterized by a reduced ejection fraction (EF). End-diastolic and end-systolic image data was used to reconstruct LV geometries with 2D valves as well as the ventricular movement. The intraventricular hemodynamics were computed with a prescribed-motion CFD approach and evaluated in terms of large-scale flow patterns, energetic behavior, and intraventricular washout.

Results: In the MR patients, a disrupted E-wave jet, a fragmentary diastolic vortex formation and an increased specific energy dissipation in systole are observed. In all cases, regions with an impaired washout are visible. The results furthermore indicate that considering several cycles might provide a more detailed view of the washout process. The pre-processing times and computational expenses are in reach of clinical feasibility.

Conclusion: The proposed CCT-based CFD method allows to compute patient-specific intraventricular hemodynamics and thus complements the informative value of CCT. The method can be applied to any CCT data of common quality and represents a fair balance between model accuracy and overall expenses. With further model enhancements, the computational framework has the potential to be embedded in clinical routine workflows, to support clinical decision making and treatment planning.

Background: Cardiac magnetic resonance perfusion imaging during vasodilator stress is an established modality in patients with suspected and known coronary artery disease (CAD).

Aim: This study aimed to evaluate the performance of fast-Strain-Encoded-MRI (fast-SENC) for the diagnostic classification and risk stratification of patients with ischemic heart disease.

Methods: Perfusion and fast-SENC cardiac magnetic resonance (CMR) images were retrospectively analyzed in 111 patients who underwent stress CMR. The average myocardial perfusion score index, global and segmental longitudinal and circumferential strain (GLS and GCS and SLS and SCS, respectively), were measured at rest and during stress. The combination of SLS and SCS was referred to as segmental aggregate strain (SAS). Segments exhibiting perfusion defects or SAS impairment during stress were defined as “ischemic.” All-cause mortality, non-fatal infarction, and urgent revascularization were deemed as our combined clinical endpoint.

Results: During adenosine stress testing, 44 of 111 (39.6%) patients exhibited inducible perfusion abnormalities. During a mean follow-up of 1.94 ± 0.65 years, 25 (22.5%) patients reached the combined endpoint (death in n = 2, infarction in n = 3 and urgent revascularization in n = 20). Inducible perfusion defects were associated with higher number of segments with inducible SAS reduction ≥6.5% (χ² = 37.8, AUC = 0.79, 95% CI = 0.71–0.87, p < 0.001). In addition, patients with inducible perfusion defects or SAS impairment exhibited poorer outcomes (AUC_Perf = 0.81 vs. AUC_SAS = 0.74, p = NS vs. each other, and χ² = 30.8, HR = 10.3 and χ² = 9.5, HR = 3.5, respectively, p < 0.01 for both).

Conclusion: Purely quantitative strain analysis by fast-SENC during vasodilator stress was related to the diagnosis of ischemia by first-pass perfusion and is non-inferior for the risk stratification of patients with ischemic heart disease. This may bear clinical implications, especially in patients with contraindications for contrast agent administration.