Journal of cardiovascular computed tomography最新文献

Background: Air pollution is associated with mortality and major adverse cardiovascular events (MACE) in the general population. However, little is known about the relationship between air pollution and coronary artery disease (CAD) and how this relates to MACE.

Methods: This study utilized data from the computed tomography (CT) arm of the PROMISE trial investigating symptomatic individuals with suspected CAD. We linked levels of air pollutants (PM_2·5, PM₁₀, NO₂, and ozone) at U.S. zip codes of residence CT-derived CAD and adjudicated MACE (all-cause death, myocardial infarction, and hospitalization for unstable angina). Multivariable analyses were adjusted for the ASCVD risk score and socioeconomic determinants of health. Mediation analyses were used to test putative pathways.

Results: In 4343 individuals (48 ​% males; age: 61 ​± ​8 years), elevated exposures to PM_2.5 (≥9.4 ​μg/m³) and NO₂ (≥5.3 ​ppb) were independently associated with obstructive CAD (aOR ​= ​1.23, 95%CI: 1.03-1.48, p ​= ​0.024; aOR ​= ​1.56, 95%CI: 1.02-2.40, p ​= ​0.042), while there were no significant associations with PM₁₀ (≥15 ​μg/m³) or ozone (≥51 ​ppb). Increased PM_2.5, PM₁₀ and ozone were independently associated with MACE (aHR ​= ​1.56, 95%CI: 1.12-2.18, p ​= ​0.008; aHR ​= ​2.09, 95%CI: 1.18-3.70, p ​= ​0.011, aHR ​= ​1.96, 95%CI: 1.20-3.21, p ​= ​0.008). In the mediation analysis, obstructive CAD accounted for 9 ​% of the total effect (p ​= ​0.012) between PM_2.5 and MACE.

Conclusion: Exposure to air pollution, particularly PM_2.5, was independently associated with obstructive CAD and MACE, with obstructive CAD mediating a small but significant portion of the association between air pollution and MACE.

Background: Conduction abnormalities (CA) after TAVI remain problematic. Membranous septum (MS) depth correlates inversely with new CA though within-patient variability exists.

Objectives: To determine the association of CT-derived MS area with new CA after TAVI.

Methods: MS depth was measured along its width (20 ​% intervals) to calculate MS area in 140 patients without CA. The primary outcome was PPI or new persistent LBBB at discharge.

Results: New CA occurred in 49 (35 ​%) patients of whom 10 (7.1 ​%) required PPI and 39 (27.9 ​%) developed persisting LBBB. MS area was significantly smaller in those with new CA (20.1 [8.6] vs. 41.2 [18.0] mm2; p ​< ​0.01). By multivariable regression, a model including MS area and TAVI contact (MS width∗implant depth): MS area ratio showed better discrimination for new CA compared with a model including MS depth and MS depth - implant depth (AUC 0.89 [95 ​% CI 0.83-0.94] vs. 0.84 [95 ​% CI 0.76-0.90]; p ​= ​0.05, respectively). Optimal cut off point for correct classification of new CA for MS depth was 3.9 ​mm (sensitivity 73 ​%, specificity 76 ​%, PPV 58 ​% and NPV 84 ​%), 28.0 ​mm² for MS area (sensitivity 88 ​%, specificity 78 ​%, PPV 68 ​% and NPV 92 ​%) and 1.88 (sensitivity 63 ​%, specificity 81, PPV 77 ​% and NPV 68 ​%) for TAVI contact: MS area ratio. To minimize new CA, maximal valve implant depth should ≤ (1.88 ∗ MS area)/MS width.

Conclusions: Pre-procedural assessment of the MS area offers additional predictive value for development of new conduction abnormalities after TAVI when compared with MS depth and can guide implant depth.

Despite the promising results, the clinical implications of the CCT-FFR is already debated. This metanalysis aimed to determine the potential benefits of incorporating FFRCT into stable CAD management. After searching for studies comparing outcomes of patients with suspected stable CAD who underwent CCT-FFR as a first strategy versus non-urgent cardiovascular testing after a clinical judgment, we calculated odds ratios (ORs) and 95 ​% confidence intervals (CIs) using a random-effects or fixed-effects meta-analysis model depending on heterogeneity significance. 5 studies (3 RCTs and 2 observational studies) globally encompassing 5282 patients (CCT-FFR ​= ​2604 patients, Control Group ​= ​2678 patients) were included in the quantitative analysis. The rates of ICA overall (OR 1.57, 95%CI 1.36-1.81, p value ​< ​0.001) and those without obstructive CAD (OR 6.63, 95%CI 4.79-9.16, p value ​< ​0.001) were reduced in the CCTAFFR group, as compared to the control group. Moreover, CCT-FFR patients underwent coronary revascularization more frequently than patients in the control arm (OR 0.48,CI 0.38-0.62, p value ​< ​0.001). There was no significance difference between the two strategies in terms of 1 year MACE (OR 1.11,CI 0.86-1.44, p value 0.42), nonfatal MI (OR 0.73, CI 0.41-1.33, p value 0.31), all-cause mortality (OR 1.29,CI 0.47-3.54, p value 0.63) and unplanned revascularization for angina (OR 0.99, 95%CI 0.65-1.49, p value 0.95). In conclusion, in the management of stable CAD, the use of CCT-FFR was associated with lower overall rates of ICA but higher rates of coronary revascularization with comparable 1-year clinical impact.

Background: As a new noninvasive diagnostic technique, computed tomography-derived fraction flow reserve (FFRCT) has been used to identify hemodynamically significant coronary artery stenosis. FFRCT can be calculated using computational fluid dynamics (CFD) or machine learning (ML) approaches. It was hypothesized that ML-based FFRCT (FFRCT_ML) has comparable diagnostic performance with CFD-based FFRCT (FFRCT_CFD). We used invasive FFR as the reference test to evaluate the diagnostic performance of FFRCT_ML vs. FFRCT_CFD.

Methods: We searched PubMed, Cochrane Library, EMBASE, WOS, and Scopus for articles published until March 2024. We analyzed the synthesized sensitivity, specificity, and diagnostic odds ratio (DOR) of FFRCT_ML vs FFRCT_CFD at both the patient and vessel levels. We generated summary receiver operating characteristic curves (SROC) and then calculated the area under the curve (AUC).

Results: This meta-analysis included 23 studies reporting FFRCT_CFD diagnostic performance and 18 studies reporting FFRCT_ML diagnostic performance. In the FFRCT_CFD group, 2501 patients and 3764 vessels or lesions were analyzed. In the FFRCT_ML group, 1323 patients and 4194 vessels or lesions were analyzed. Our results showed that at the per-patient level, FFRCT_CFD and FFRCT_ML had comparable pooled specificity (Z ​= ​-0.59, P ​= ​0.55) and AUC (P ​= ​0.5). At the per-vessel level, FFRCTCFD and FFRCTML also showed comparable specificity (Z ​= ​0.94, P ​= ​0.34), DOR (Z ​= ​0.7, P ​= ​0.48), and AUC (P ​= ​0.74). However, the sensitivity of FFRCT_ML was significantly lower compared to FFRCT_CFD at both patient (Z ​= ​-3.85, P ​= ​0.0001) and vessel (Z ​= ​-2.05, P ​= ​0.04) levels.

Conclusion: The FFRCT_ML technique was comparable to standard CFD approaches in terms of AUC and specificity. However, it did not achieve the same level of sensitivity as FFRCT_CFD.