Lack of Incremental Prognostic Value of Pericoronary Adipose Tissue Computed Tomography Attenuation Beyond Coronary Artery Disease Reporting and Data System for Major Adverse Cardiovascular Events in Patients With Acute Chest Pain
Pericoronary adipose tissue (PCAT) and Coronary Artery Disease Reporting and Data System (CAD-RADS) category had prognostic values for major adverse cardiovascular events (MACEs). However, little is known about the difference between CAD-RADS and PCAT computed tomography (CT) attenuation for predicting MACEs. This study was to compare the prognostic value of PCAT and CAD-RADS for MACEs in patients with acute chest pain.
Between January 2010 and December 2021, all consecutive emergency patients with acute chest pain referred for coronary computed tomography angiography were enrolled in this retrospective study. MACEs included unstable angina requiring hospitalization, coronary revascularization, nonfatal myocardial infarction, and all-cause death. Patients’ clinical characteristics, CAD-RADS, and PCAT CT attenuation were used to evaluate risk factors of MACEs using multivariable Cox regression analysis.
A total of 1313 patients were evaluated (mean age, 57.13±12.57 years; 782 men). During a median follow-up of 38 months, 142 of the 1313 patients (10.81%) experienced MACEs. Multivariable Cox regression analysis showed that CAD-RADS categories 2, 3, 4, 5 (hazard ratio range, 2.286–8.325; all P<0.005) and right coronary artery PCAT CT attenuation (hazard ratio, 1.033; P=0.006) were independent predictors of MACEs after adjusting for clinical risk factors. The C statistics revealed that CAD-RADS improved risk stratification compared with PCAT CT alone (C-index, 0.760 versus 0.712; P=0.036). However, the benefit of right coronary artery PCAT CT attenuation combined with CAD-RADS was not significant compared with CAD-RADS alone (0.777 versus 0.760; P=0.129).
Right coronary artery PCAT CT attenuation and CAD-RADS were independent predictors of MACEs. However, no incremental prognostic value of right coronary artery PCAT CT attenuation beyond CAD-RADS was detected for MACEs in patients with acute chest pain.
Coronary Artery Disease Reporting and Data System (CAD-RADS) has incremental prognostic values for major adverse cardiovascular events beyond atherosclerotic cardiovascular disease risk score and coronary artery calcium score in patients suspected coronary artery disease. CAD-RADS, however, does not consider the biological features, such as coronary inflammation. Pericoronary adipose tissue (PCAT) computed tomography (CT) can be noninvasively measured at coronary computed tomography angiography imaging, indicating the presence of coronary inflammation. Thus, adding PCAT CT attenuation to CAD-RADS maybe improves risk stratification of patients. The prognostic value of CAD-RADS was compared with PCAT CT attenuation, and the incremental value of PCAT CT attenuation beyond CAD-RADS was also investigated. In this retrospective study, 142 of 1313 patients (10.81%) had major adverse cardiovascular events after a median follow-up of 38 months (interquartile range, 20–65 months). CAD-RADS categories 2, 3, 4, 5 (hazard ratio range, 2.286–8.325; all P<0.005) and right coronary artery PCAT CT attenuation (hazard ratio, 1.033; P=0.006) were independent predictors of major adverse cardiovascular events after adjusting for clinical risk factors. The C statistics revealed that CAD-RADS improved risk stratification compared with PCAT CT attenuation (C-index, 0.760 versus 0.712; P=0.036). However, the benefit of right coronary artery PCAT CT attenuation combined with CAD-RADS was not significant compared with CAD-RADS alone (0.777 versus 0.760; P=0.129).
Coronary computed tomography angiography (CCTA) is now a noninvasive, first-line examination for the assessment of coronary artery disease.1 The Coronary Artery Disease Reporting and Data System (CAD-RADS), which adds categories for left main coronary artery and multivessel disease and considers high-risk plaque features, was established in 2016 to standardize the reporting of coronary artery disease on CCTA.2 A published report from PROMISE trial (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) suggested that CAD-RADS has incremental prognostic values for major adverse cardiovascular events (MACEs) beyond atherosclerotic cardiovascular disease risk score and coronary artery calcium score (CACS) in patients with stable chest pain and suspected coronary artery disease.3 Furthermore, a recent research study also demonstrated that CAD-RADS has an incremental prognostic value over CACS in the prediction of MACEs in emergency patients with acute chest pain.4 CAD-RADS, however, limited to quantifying the extent of coronary atherosclerotic disease, does not consider the biological features, such as coronary inflammation.5
Inflammation is one of the primary mechanisms responsible for the development and progression of coronary atherosclerosis.6 In particularly, inflammation plays a crucial role in both atherosclerotic plaque formation and destabilization, as such accurate assessment of coronary inflammatory might improve risk stratification of coronary artery disease patients and allow tailoring anti-inflammatory treatment.7,8 It has been established that inflammation surrounding coronary arteries can be detected by measuring pericoronary adipose tissue (PCAT) computed tomography (CT) attenuation at CCTA imaging.9 Series studies have indicated that PCAT CT attenuation was associated with plaque vulnerability,10 culprit lesions in patients with acute coronary syndrome,11 and the hemodynamic status of coronary stenosis.12,13 Furthermore, the CRISP-CT study (Cardiovascular Risk Prediction Using Computed Tomography) has indicated that PCAT CT attenuation of the right coronary artery (RCA) was of prognostic importance for MACEs over traditional risk factors and CCTA metrics, including the stenosis severity of CAD, CACS, and presence of high-risk plaque features.14
However, little is known about the difference between CAD-RADS and PCAT CT attenuation for predicting MACEs. Therefore, the aim of the present study was to determine the prognostic value of PCAT CT attenuation and CAD-RADS for MACEs, and further assess the incremental prognostic value of PCAT CT attenuation beyond CAD-RADS in patients with acute chest pain.
The data that support the findings of this study are available from the corresponding author upon reasonable request.
The study complied with the Declaration of Helsinki. The institutional review committee approved the study protocol and waived the need for written informed consent. Between January 2010 and December 2021, all patients who admitted to our emergency department for acute chest pain were retrospectively enrolled in the study. The inclusion criteria were low to intermediate pretest probability of CAD, aged 18 years or older, and underwent CCTA. Exclusion criteria were (1) history of percutaneous coronary intervention or coronary artery bypass grafting; (2) history of myocardial infarction; (3) incomplete medical records for risk factors or blood tests; (4) nonevaluable CCTA images quality; (5) missing CCTA data; (6) MACEs occurred within 30 days. The clinical data were reviewed and recorded from their medical records.
Image Acquisition and Analysis
All CCTA scans were performed on a second generation 128-slice dual source CT (Somatom Definition Flash, Siemens Healthineers) with retrospectively ECG-triggered spiral acquisition. Two board-certified radiologists (R.J.X. and J.X.) with >10 years of experience in cardiac CT imaging blindly reviewed all CCTA images. Any discrepancies were resolved in consensus with another cardiovascular radiologist with 28 years of experience (M.W.Z.). CACS were calculated using the Agatston score and classified into CACS=0, 0< CACS <100, 100≤ CACS <400, and CACS ≥400.15 The CAD-RADS category was divided into 6 categories CAD-RADS 0 (0% stenosis: documented absence of CAD), CAD-RADS 1 (1%–24% stenosis: minimal nonobstructive CAD), CAD-RADS 2 (25%–49% stenosis: mild nonobstructive CAD), CAD-RADS 3 (50%–69% stenosis: moderate stenosis), CAD-RADS 4A (70%–99% stenosis: severe stenosis), and CAD-RADS 4B (>50% stenosis in left main coronary artery or ≥70% stenosis in 3 vessel), and CAD-RADS 5 (100% stenosis: total occlusion).2 CAD-RADS categories 4A and 4B were combined and considered as a single group because of the small patient numbers of CAD-RADS 4B.
PCAT Measurement and Analysis
PCAT measurement and analysis was performed using a dedicated workstation (Perivascular Fat Analysis Tool, Shukun Technology Co, Beijing, China). The proximal 40 mm segments of the left anterior descending (LAD) coronary artery and left circumflex coronary artery (LCX) and the proximal 10 to 50 mm segment of the RCA were traced as previously described.14 Within the preidentified segment of interest, the lumen as well as the inner and outer vessel wall border were tracked in an automated manner with additional manual optimization. PCAT was defined as the adipose tissue located within a radial distance from the outer vessel wall equal to the diameter of the coronary vessel.9,14 Voxel histograms of CT attenuation were plotted and the mean CT attenuation of all voxels between −190 and −30 HU (thresholds used for the definition of adipose tissue) within the PCAT volume was calculated. The PCAT CT attenuation was defined as the mean CT attenuation of PCAT of the traced 40 mm segment by the crude analysis.
Follow-up information was gathered through a review of hospital medical records or telephone interviews by a dedicated physician (Z.L.R.) through to the end of June 2022. MACEs consisted of unstable angina requiring hospitalization, late coronary revascularization, nonfatal myocardial infarction, and all-cause death. Coronary revascularization included percutaneous coronary intervention and coronary artery bypass grafting. The 30-day point after the index CCTA was used as a cutoff between early and late coronary revascularization. Only late coronary revascularizations were considered MACEs.
All statistical analyses were performed using SPSS software package (version 26.0, SPSS, Chicago, IL) and Medcalc (version 13.0.2, Medcalc Software, Mariakerke, Belgium). Normally distributed variables are presented as mean±SD and compared between groups using independent sample Student t tests. Non-normally distributed variables are presented as median with interquartile range and compared by using a Mann-Whitney U test. Categorical variables are presented as frequencies with percentages and compared by using χ2 test, or Fisher exact test. The influence of clinical characteristics, CAD-RADS category, and PCAT CT attenuation on MACEs was determined using Cox regression analysis, and the results were reported as hazard ratios (HRs) with 95% CIs. Univariable analysis of baseline clinical characteristics, CAD-RADS category, and PCAT CT attenuation was performed to identify potential predictors. To determine independent predictors of MACEs, multivariable analysis was performed by independently and collectively adding CACS, CAD-RADS, and PCAT attenuations to other significant univariable predictors. Only variables with P<0.05 in univariable analyses were added to the final multivariable models to prevent model overfitting. The Harrell C-index was used to compare the predictive performance of different models by using nonparametric test. Cumulative event rates of MACEs were estimated by using the Kaplan-Meier curves and compared by using the log-rank test. Receiver-operating characteristic curves were built for PCAT CT attenuation based on a logistic regression model. The Delong test was used to compare the areas under the curve. A 2-sided P value of 0.05 was considered statistically significant.
Of 2111 patients admitted to emergency department due to acute chest pain, 798 patients with the following reasons were excluded (1) history of percutaneous coronary intervention and coronary artery bypass grafting (n=148), (2) history of myocardial infarction (n=20), (3) incomplete medical records for risk factors or blood tests (n=98), (4) nonevaluable CCTA image quality (n=5), (5) missing CCTA data (n=259), and (6) MACEs occurred within 30 days (n=268; Figure 1). Finally, a total of 1313 patients (mean age 57.13±12.57 years) were included for analysis. Of the study cohorts, 59.56% (782 of 1313) were men with a mean age of 55.69 years. After a median follow-up of 38 months (interquartile range, 20–65 months), 142 patients (10.81%) had MACEs, in which the overall incidence of all-cause death, nonfatal myocardial infarctions, late coronary revascularizations, and unstable angina hospitalizations were 2.21% (29/1313), 0.53% (7/1313), 2.89% (38/1313), and 5.18% (68/1313), respectively.
The baseline characteristics and imaging results of the patients were summarized according to the occurrence of MACEs in Table 1. Patients with MACEs were older (P<0.001), had higher prevalence of diabetes (P<0.001), hypertension (P=0.022), and family history of coronary artery disease (P=0.012). Furthermore, CACS was present in 470 (35.80%) subjects at baseline. In patients with CACS, the median CACS was 71.60 (interquartile range, 18.38–267.09). CACS in patients with MACEs were significantly higher than those without MACEs (103.70 versus 69.74; P<0.001).
|Age, y||57.13±12.57||56.56±12.39||61.79±13.04||< 0.001|
|Male, n (%)||782 (59.56%)||698 (59.60%)||84 (59.15%)||0.998|
|Diabetes, n (%)||110 (8.38%)||82 (7.00%)||28 (19.72%)||< 0.001|
|Hypertension, n (%)||425 (32.37%)||367 (31.34%)||58 (40.85%)||0.022|
|Smoking, n (%)||469 (35.72%)||418 (35.70%)||51 (35.92%)||0.959|
|Dyslipidemia, n (%)||60 (4.57%)||49 (4.18%)||11 (7.75%)||0.055|
|Family history of CAD, n (%)||78 (5.94%)||76 (6.49%)||2 (1.41%)||0.012|
|TG||1.55 (1.08–2.52)||1.48 (1.05–2.48)||1.81 (1.27–3.39)||0.860|
|hs-CRP, mg/L||3.48 (0.81–33.90)||2.66 (0.81–44.66)||4.45 (0.81–24.45)||0.017|
|White cell count, ×109/L||6.54 (4.55–9.60)||6.51 (4.58–9.47)||7.02 (4.52–10.35)||0.644|
|CACS||71.60 (18.38–267.09)||69.74 (18.75−246.09)||103.70 (17.80–416.13)||< 0.001|
|CACS grade, n (%)||< 0.001|
|0||843 (64.28%)||783 (66.87%)||60 (42.25%)|
|0< CACS <100||267 (20.34%)||227 (19.39%)||40 (28.17%)|
|100≤ CACS <400||117 (8.91%)||96 (8.20%)||21 (14.79%)|
|≥400||86 (6.55%)||65 (5.56%)||21 (14.79%)|
|CAD-RADS category, n (%)||< 0.001|
|0||480 (36.56%)||460 (39.28%)||20 (14.08%)|
|1||197 (15.00%)||180 (15.37%)||17 (11.97%)|
|2||382 (29.09%)||344 (29.38%)||38 (26.76%)|
|3||130 (9.90%)||101 (8.63%)||29 (20.42%)|
|4||107 (8.15%)||76 (6.49%)||31 (21.83%)|
|5||17 (1.29%)||10 (0.85%)||7 (4.93%)|
|PCAT CT attenuation (HU)|
Among the 1313 patients, 36.56% (480/1313) were classified as CAD-RADS 0, 15.00% (197/1313) as CAD-RADS 1, 29.09% (382/1313) as CAD-RADS 2, 9.90% (130/1313) as CAD-RADS 3, 8.15% (107/1313) as CAD-RADS 4 (86 of CAD-RADS 4A, and 21 of CAD-RADS 4B), and 1.29% (17/1313) as CAD-RADS 5. CAD-RADS 3 to 5 were more frequent in MACEs group, while CAD-RADS 0-2 were more frequent in no MACEs group. The baseline and imaging characteristics of the patients were also summarized according to PCAT CT attenuation of each coronary artery in Table S1.
CAD-RADS With MACEs
Of 142 patients with MACEs, 14.08% (20 patients) had a CAD-RADS of 0, 11.97% (17 patients) had a CAD-RADS of 1, 26.76% (38 patients) had a CAD-RADS of 2, 20.42% (29 patients) had a CAD-RADS of 3, 21.83% (31 patients) had a CAD-RADS of 4, and 4.93% of (7 patients) had a CAD-RADS of 5. As determined with the log-rank test in Kaplan-Meier estimates, CAD-RADS groups showed significant associated with the time to the event, with an increased risk for MACEs with the next higher category (log-rank P<0.001; Figure 2).
PCAT CT Attenuation With MACEs
RCA PACT CT attenuation (−75.77±11.02 versus −78.38±9.74; P=0.003) was higher in patients who experienced MACEs as compared with those who did not, whereas, LAD (−73.67±9.21 versus −75.13±8.53; P=0.057) and LCX (−70.25±8.37 versus −71.34±8.09; P=0.131) PCAT CT attenuation did not differ between patients with and without MACEs (Table 1).
From Youden index analysis, the prognostic threshold of PCAT CT attenuation was >−81.00 HU for RCA, >−70.00 HU for LAD and >−71.00 HU for LCX, respectively. The baseline characteristics and imaging results of the patients were summarized according to RCA, LAD, and LCX PCAT CT attenuation in the Supplemental Material. The Kaplan-Meier survival curves for subjects stratified by higher PCAT CT attenuation in different coronary arteries were also demonstrated that PCAT CT attenuation was associated with an increased rate of MACEs (log-rank P=0.002 for RCA, P=0.001 for LAD, and P=0.028 for LCX; Figure 3).
Univariable and Multivariable Analyses
Univariable Cox regression analysis for MACEs showed that age (P<0.001), diabetes (P<0.001), hypertension (P=0.004), dyslipidemia (P=0.036), family of coronary artery disease (P=0.002), CACS (P<0.001), and PCAT CT attenuation in each coronary artery (RCA: P<0.001, LAD: P=0.010, LCX: P=0.016) were associated with MACEs. Compared with CACS, 0, 0< CACS <100 (HR, 2.432 [95% CI, 1.629–3.632]; P<0.001), 100≤ CACS <400 (HR, 3.389 [95% CI, 2.057–5.584]; P<0.001), and CACS ≥400 (HR, 4.876 [95% CI, 2.958–8.039]; P<0.001) were all associated with MACEs. Also, CAD-RADS 2 (HR, 2.880 [95% CI, 1.675–4.953]; P<0.001), CAD-RADS 3 (HR, 6.024 [95% CI, 3.407–10.651]; P<0.001), CAD-RADS 4 (HR, 8.242 [95% CI, 4.697–14.464]; P<0.001), and CAD-RADS 5 (HR, 12.832 [95% CI, 5.417–30.398]; P<0.001) were associated with MACEs (Table 2).
|Variable||HR (95% CI)||P value|
|Family of CAD||0.105 (0.026–0.428)||0.002|
|hs-CRP, mg/L||0.993 (0.976–1.010)||0.434|
|White cell count, ×109/L||1.000 (0.999–1.001)||0.922|
|0< CACS <100||2.432 (1.629–3.632)||<0.001|
|100≤ CACS <400||3.389 (2.057–5.584)||<0.001|
|PCAT CT attenuation (HU)|
In multivariable Cox regression analysis adjusted for clinical risk factors (age, diabetes, hypertension, dyslipidemia, and family of CAD), CAD-RADS 2 to 5 were associated with MACEs in model 2. The HRs for MACEs within the CAD-RADS 2 to 5 were 2.299 (P=0.008), 4.738 (P<0.001), 5.548 (P<0.001), and 8.967 (P<0.001), respectively. Only RCA PCAT CT attenuation was independently associated with MACEs after adjusting for clinical risk factors in model 3. The HR for MACEs were higher in patients with lower RCA PCAT CT attenuation (HR, 1.035 [95% CI, 1.011–1.059]; P=0.003). Even when adjusted for CAD-RADS in the model 4, RCA PCAT CT attenuation remained an independent and significant predictor of MACEs (HR, 1.033 [95% CI, 1.010–1.057]; P=0.006; Table 3).
|Variable||Model 1||Model 2||Model 3||Model 4|
|HR (95% CI)||P value||HR (95% CI)||P value||HR (95% CI)||P value||HR (95% CI)||P value|
|Age||1.034 (1.020–1.049)||<0.001||1.014 (0.998–1.030)||0.079||1.033 (1.018–1.048)||<0.001||1.013 (0.997–1.029)||0.106|
|Diabetes||2.489 (1.569–3.949)||<0.001||2.041 (1.287–3.236)||0.002||2.674 (1.671–4.277)||<0.001||2.162 (1.357–3.445)||0.001|
|Hypertension||1.088 (0.758–1.562)||0.648||1.011 (0.702–1.454)||0.995||1.095 (0.762–1.574)||0.623||1.011 (0.703–1.453)||0.954|
|Dyslipidemia||1.046 (0.539–2.029)||0.895||1.419 (0.731–2.755)||0.301||1.005 (0.513–1.968)||0.989||1.401(0.715–2.743)||0.325|
|Family of CAD||0.114 (0.028–0.469)||0.003||0.093 (0.023–0.384)||0.001||0.123 (0.030–0.505)||0.004||0.097(0.023–0.400)||0.001|
|CACS||1.000 (1.000–1.000)||0.648||1.000 (1.000–1.000)||0.725|
|0< CACS <100||1.109 (0.694–1.772)||0.665||1.084 (0.676–1.739)||0.738|
|10≤ CACS <400||1.271 (0.706–2.286)||0.424||1.287 (0.713–2.324)||0.402|
|≥400||1.483 (0.707–3.109)||0.297||1.586 (0.755–3.329)||0.223|
|1||1.619 (0.839–3.121)||0.151||1.593 (0.826–3.073)||0.165|
|2||2.299 (1.242–4.257)||0.008||2.286 (1.238–4.222)||0.008|
|3||4.738 (2.499–8.985)||<0.001||4.594 (2.408–8.763)||<0.001|
|4||5.548 (2.834–10.862)||<0.001||5.144 (2.588–10.224)||<0.001|
|5||8.967 (3.418–23.524)||<0.001||8.325 (3.149–22.009)||<0.001|
|PCAT CT attenuation (HU)|
|RCA||1.035 (1.011–1.059)||0.003||1.033 (1.010–1.057)||0.006|
|LAD||1.006 (0.976–1.036)||0.715||1.006 (0.975–1.037)||0.713|
|LCX||0.986 (0.954–1.019)||0.411||0.976 (0.945–1.009)||0.152|
To assess the incremental prognostic value of PCAT CT attenuation, the C statistics index of different models were calculated. The addition of PCAT CT attenuation to CAD-RADS category (C-index, 0.760) slightly but not significantly increased the C statistics index (0.770; P=0.129).
To our knowledge, this is the first study to compare the prognostic value of CAD-RADS and PCAT CT attenuation at CCTA for MACEs in patients with acute chest pain. Our results demonstrated that CAD-RADS ≥2 and RCA PCAT CT attenuation ≤−81 HU were independent predictors of MACEs. However, adding RCA PCAT CT attenuation to CAD-RADS did not increase the prognostic potential for MACEs in patients with acute chest pain.
CAD-RADS With MACEs
CAD-RADS category, a standardized method for describing a wide range of CCTA data related to the occurrence, severity, and composition of coronary atherosclerosis, can be used to stratify patients with stable or acute chest pain.16 To date, several studies have demonstrated that CAD-RADS had significantly prognostic value for MACEs and diagnostic performance for coronary artery disease.3,4,17 Bittner et al3 reported that traditional coronary stenosis severity (HR, 3.82–9.62; all P<0.001), high-risk plaque (HR, 2.61; P<0.001), and CAD-RADS 1-5 (HR, 2.43–21.84; all P<0.05) were all associated with MACEs for patients with stable chest pain. Recently, a multicenter retrospective observational cohort study also suggested that CAD-RADS category 3 (HR, 8.2 P<0.001) and CAD-RADS categories 4 or 5 (HR, 20.2; P<0.001) were associated with MACEs in patients with acute chest pain.4 Similar to the 2 previous studies, we found that CAD-RADS 2 to 5 (HR range, 2.299–8.967, all P<0.01) were associated with MACEs after adjusting for clinical risk and CACS in patients with acute chest pain.
All these study results suggested that CAD-RADS had superior prognostic value for MACEs over the clinical risk score, CACS, coronary stenosis severity, quantitative and qualitative plaque characteristics in patients with either stable chest pain or acute chest pain. This may be attributed to the properties of CAD-RADS that has comprehensive evaluation ability involving coronary stenosis severity, high-risk plaque features, and multivessel lesions. The comprehensive evaluation of CAD-RADS may better reflect the extend of coronary atherosclerosis, and thus are more association with MACEs.
PCAT CT Attenuation and MACEs
PCAT CT attenuation has emerged as a novel CCTA-based biomarker for predicting adverse outcomes by capturing coronary inflammation. There were several data on the prognostic value of PCAT CT attenuation.14,18,19 The CRISP-CT study showed that PCAT CT attenuation of the RCA (HR, 1.49–2.15; P<0.01) and LAD (HR, 1.77–2.61; P<0.001) were associated with all-cause mortality and cardiac mortality, and PCAT CT attenuation ≥−70.1 HU was an independent predictor of all-cause and cardiac mortality beyond clinical characteristics, epicardial adipose tissue volume, number of high-risk plaque features, and Duke index for extent of coronary artery disease.14 However, another study by Bengs et al19 indicated that RCA (P=0.049), but not LAD (P=0.426) and LCX (P=0.370), PCAT CT attenuation was associated with MACEs. Our results also demonstrated that only RCA PCAT CT attenuation (HR, 1.033; P=0.006) was independently associated with MACEs in patients with acute chest pain when adjusted for clinical traditional risk and CAD-RADS category. A reasonable explanation for this contrary result may be because that PCAT is richer and less hindering nonfatty structures around the proximity RCA as compared with the LAD and LCX, and thus the PCAT CT attenuation is ease to measure.9,20
As it is widely recognized, inflammation has an important role in atherosclerotic plaque vulnerability leading to adverse outcomes. PCAT CT attenuation, a novel noninvasive biomarker quantified at CCTA, which is considered to reflect the coronary inflammation. Previous studies have suggested that increased PCAT CT attenuation was associated with the presence of high-risk plaque features that are correlated with future clinical events.6,10 Our results further demonstrated the results.
Furthermore, we found that adding RCA PCAT CT attenuation to CAD-RADS did not significantly improve the prognostic value of CAD-RADS for MACEs in patients with acute chest pain. PCAT CT attenuation was associated with the coronary inflammation and the plaque vulnerability,9,14,20 while CAD-RADS comprehensively involves the coronary stenosis severity, high-risk plaque features, and multivessel lesions, which were directly associated with MACEs. Therefore, it was reasonable to believe that PCAT CT attenuation was less sensitive than CAD-RADS for the prediction of MACEs, and thus did not present incremental prognostic value.
Limitations of this study should be considered. First, this study was a single-center retrospective analysis conducted in a cohort with high family of coronary artery disease and comorbidities, which limited its generalizability. Second, we could not investigate the prognostic value of the CAD-RADS S (stent) or G (graft) category modifiers as well as CAD-RADS N. Third, PCAT CT attenuation was defined as the average attenuation of PCAT, which might result in an underestimation of coronary inflammation in obese individuals as attenuation will be lower given the larger adipocytes; vice versa, this can lead to an overestimation in lean patients. Lastly, our study used a composite end point of all-cause death and nonfatal myocardial infarction but does not provide information on cause of death as this was unavailable.
Both RCA PACT CT attenuation and CAD-RADS were independent predictors of MACEs. However, no incremental prognostic value of RCA PCAT CT attenuation beyond CAD-RADS was detected for MACEs in acute chest pain patients.
Sources of Funding
This study has received funding by the National Natural Science Foundation of China (grant number 82071917, 82202149), and the Key Research and Development Plan of Shaanxi Province (grant numbers 2020ZDLSF01-01).
coronary artery calcium score
Coronary Artery Disease Reporting and Data System
coronary computed tomography angiography
Cardiovascular Risk Prediction Using Computed Tomography
left anterior descending
major adverse cardiovascular events
pericoronary adipose tissue
Prospective Multicenter Imaging Study for Evaluation of Chest Pain
right coronary artery
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