Computed tomography-based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment

CT-derived Epicardial Adipose Tissue Inflammation Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement

PURPOSE

Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR).

MATERIALS AND METHODS

Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed. The amount and density of EAT and PAT were quantified from single-slice CT images at the level of the aortic valve. Using established risk scores and known independent risk factors, a clinical benchmark model (BMI, Chronic kidney disease stage, EuroSCORE 2, STS Prom, year of intervention) for outcome prediction (2-year mortality) after TAVR was established. Subsequently, we tested whether the additional inclusion of area and density values of EAT and PAT in the clinical benchmark model improved prediction. For this purpose, the cohort was divided into a training (n=798) and a test cohort (n=399).

RESULTS

Within the 2-year follow-up, 264 patients died. In the training cohort, particularly the addition of EAT density to the clinical benchmark model showed a significant association with outcome (hazard ratio 1.04, 95% CI: 1.01-1.07; P =0.013). In the test cohort, the outcome prediction of the clinical benchmark model was also significantly improved with the inclusion of EAT density (c-statistic: 0.589 vs. 0.628; P =0.026).

CONCLUSIONS

EAT density as a surrogate marker of EAT inflammation was associated with 2-year mortality after TAVR and may improve outcome prediction independent of established risk parameters.

Coronary Artery Disease Assessment via On-Site CT Fractional Flow Reserve in Patients Undergoing Transcatheter Aortic Valve Replacement

Purpose To examine the clinical feasibility of workstation-based CT fractional flow reserve (CT-FFR) for coronary artery disease (CAD) evaluation during preprocedural planning in patients undergoing transcatheter aortic valve replacement (TAVR). Materials and Methods In this retrospective single-center study, 434 patients scheduled for TAVR between 2018 and 2020 were screened for study inclusion; a relevant proportion of patients (35.0% [152 of 434]) was not suitable for evaluation due to insufficient imaging properties. A total of 112 patients (mean age, 82.1 years ± 6.7 [SD]; 58 [52%] men) were included in the study. Invasive angiography findings, coronary CT angiography results, and Agatston score were acquired and compared with on-site CT-FFR computation for evaluation of CAD and prediction of major adverse cardiovascular events (MACE) within a 24-month follow-up. Results Hemodynamic relevant CAD, as suggested by CT-FFR of 0.80 or less, was found in 41 of 70 (59%) patients with stenosis of 50% or more. MACE occurred in 23 of 112 (20.5%) patients, from which 14 of 23 had stenoses with CT-FFR of 0.80 or less (hazard ratio [HR], 3.33; 95% CI: 1.56, 7.10; P = .002). CT-FFR remained a significant predictor of MACE after inclusion in a multivariable model with relevant covariables (HR, 2.89; 95% CI: 1.22, 6.86; P = .02). An Agatston score of 1000 Agatston units or more (HR, 2.25; 95% CI: 0.98, 5.21; P = .06) and stenoses of 50% or more determined via invasive angiography (HR, 0.94; 95% CI: 0.41, 2.17; P = .88) were not significant predictors of MACE. Conclusion Compared with conventional CAD markers, CT-FFR better predicted adverse outcomes after TAVR. A relevant portion of the screened cohort, however, was not suitable for CT-based CAD evaluation. Keywords: CT, Transcatheter Aortic Valve Implantation/Replacement (TAVI/TAVR), Cardiac, Coronary Arteries, Outcomes Analysis © RSNA, 2024 See also the commentary by Weir-McCall and Pugliese in this issue.