Peri-stent FAI was independently associated with an increased risk of in-stent restenosis (OR 1.403) and was significantly higher in patients with ISR compared to those without.
Observational (n=117)
Blinded image analysis
No
Does the perivascular adipose tissue CT fat attenuation index (FAI) predict the prevalence and severity of coronary in-stent restenosis in patients with previous coronary stenting?
Peri-stent fat attenuation index (FAI) derived from CCTA can serve as a non-invasive imaging biomarker to independently predict the risk and severity of coronary in-stent restenosis.
Effect estimate: OR 1.403 (95% CI 1.211-1.625)
Absolute Event Rate: -78.1% vs -87.2%
p-value: p=<0.001
Objectives To investigate the association between the perivascular adipose tissue (PVAT) fat attenuation index (FAI) derived from coronary computed tomography angiography (CCTA) and the prevalence of in-stent restenosis (ISR) in patients with coronary stent implantation. Methods A total of 117 patients with previous coronary stenting referred for invasive coronary angiography (ICA) were enrolled in this retrospective observational analysis. All patients underwent CCTA between July 2016 and November 2021. The deep learning-based (DL-based) method was used to analyze and measure the peri-stent FAI value. Additionally, the relationship between hematological and biochemical parameters collected from all the patients was also explored. The least absolute shrinkage and selection operator (LASSO) method was applied to the most useful feature selection, and binary logistic regression was used to test the association between the selected features and ISR. The predictive performance for ISR of the identified subgroups was evaluated by calculating the area under the curve (AUC) of receiver operator curves plotted for each model. The Pearson correlation coefficient was used to assess the correlation of peri-stent FAI values with degrees of ISR. Results The peri-stent FAI values in the ISR group were significantly higher than those in the non-ISR group (−78.1 ± 6.2 HU vs. −87.2 ± 7.3 HU, p 0.001). The predictive ISR features based on the LASSO analysis were peri-stent FAI, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), and high-sensitivity c-reactive protein (hs-CRP), with an AUC of 0.849, 0.632, 0.620, and 0.569, respectively. Binary logistic regression analysis determined that peri-stent FAI was uniquely and independently associated with ISR after adjusting for other risk factors (odds ratio OR 1.403; 95% CI: 1.211 to 1.625; p 0.001). In the subgroup analysis, the AUCs of the left anterior descending coronary artery (LAD), left circumflex coronary artery (LCx), and right coronary artery (RCA) stents groups were 0.80, 0.87, and 0.96, respectively. The Pearson's correlation coefficient indicated a term moderately correlation between ISR severity and peri-stent FAI values ( r = 0.579, P 0.001). Conclusions The peri-stent FAI can be used as an independently non-invasive biomarker to predict ISR risk and severity after stent implantation.
Qin et al. (Tue,) conducted a observational in Coronary in-stent restenosis (n=117). Peri-stent Fat Attenuation Index (FAI) vs. Non-ISR was evaluated on In-stent restenosis (ISR) (OR 1.403, 95% CI 1.211-1.625, p=<0.001). Peri-stent FAI was independently associated with an increased risk of in-stent restenosis (OR 1.403) and was significantly higher in patients with ISR compared to those without.