Is there an association between coronary artery inflammation and coronary atherosclerotic burden?

Introduction

Cardiovascular diseases continue to be the leading cause of morbidity and mortality worldwide, accounting for a significant proportion of global deaths (1). Among these conditions, coronary artery disease (CAD) remains a significant concern, with acute myocardial infarctions often being overlooked in patients without a history of chest pain (2). Early identification of individuals at risk of myocardial infarction is critical for timely prevention, personalized treatment, and improved survival rates for CAD patients.

Previous studies have highlighted the importance of detection of coronary inflammation and coronary atherosclerotic burden in assessing the risk of adverse cardiac events (3-5). However, noninvasive detection of these factors remains challenging (6). Cardiac ultrasound and magnetic resonance imaging face limitations in accurately detecting coronary inflammation. While ¹⁸F-sodium fluoride positron emission tomography-computed tomography (¹⁸F-NaF PET-CT) has shown promising performance in detecting coronary artery inflammation, its higher cost and radiation dose impede widespread clinical application (7).

Coronary computed tomography angiography (CCTA) is a well-established noninvasive imaging technique widely used for qualitative and quantitative assessment of coronary plaque, atherosclerotic burden and inflammatory changes (8,9). By measuring coronary artery calcium (CAC) through CCTA, clinicians can evaluate the burden of coronary atherosclerosis. CAC score has been demonstrated as an independent predictor of mortality and a reliable method to assess the risk of future cardiovascular events, particularly in asymptomatic patients (10-12). Recent studies have also identified the attenuation of pericoronary adipose tissue (PCAT) in proximity to the right coronary artery (RCA) as a potential biomarker for coronary vascular inflammation (13-15). This PCAT attenuation, assessed through CCTA measurements, has shown promising performance in predicting future cardiac events in CAD patients (13-15).

Despite the significance of coronary inflammation and coronary atherosclerotic burden in assessing the risk of adverse cardiac events, it remains unclear whether a direct correlation exists among those factors. Therefore, the objective of this study is to investigate the potential association between coronary inflammation and coronary atherosclerotic burden by analyzing CCTA measurements of CAC scores and RCA proximal PCAT attenuation.

Methods

Patients

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Ethics Board of Lanzhou University Second Hospital, China (No. 2021A-165) and individual consent for this retrospective analysis was waived. The patients who underwent CCTA scans in our hospital from April 2021 to November 2021 were retrospectively collected and screened strictly according to the following inclusion and exclusion criteria. The inclusion criteria were as follows: (I) excellent image quality, (II) CAC and PCAT attenuation can be calculated, (III) patients older than 18 years old, and (IV) complete clinical and imaging data. The exclusion criteria were as follows: (I) previous coronary artery bypass surgery or stent placement; (II) clinical instability or atrial fibrillation; (III) with coronary artery malformation, prosthetic valve, and pacemaker; and (IV) concurrent or previous myocarditis or vasculitis within 6 months. Finally, a total of 346 patients were included, with 215 males and 131 females, with an average age of 56.60±10.82 years old. Figure 1 shows the flow diagram of patient selection.

Figure 1 Flow diagram of patient selection. CCTA, coronary computed tomography angiography; CAC, coronary artery calcium; PCAT, pericoronary adipose tissue.

CCTA acquisition

The examinations were performed with the dual source computed tomography (DSCT) scanner (SOMATOM Force, Siemens Healthcare, Forchheim, Germany), which scanned all layers from 1 cm below tracheal bifurcation to the bottom of the heart. For CT image scanning, all the CCTA data were acquired in retrospective electrocardiographic gating and craniocaudal direction with a slice of 0.75 mm, an acquisition of 192 mm × 0.6 mm, a pitch of 0.19, a rotation time of 0.25 s, and the tube voltage and tube current were automatically modulated using the CARE KV and CARE Dose 4D. Subsequently, the soft reconstruction kernel (Bv40) and advanced modeled iterative reconstruction (ADMIRE) were used to perform the axial reconstruction of CCTA images with an increment of 0.5 mm and a field of view of 188 mm × 188 mm. For enhanced scanning, the contrast agent ioprolamine (370 mgI/mL) was injected through the elbow vein with an Ulrich high-pressure syringe (Ulrich Medical, Ulm, Germany) at a flow rate of 5.0 mL/s and followed by 40 mL of normal saline at the same rate for irrigation. The CAC parameters were as follows: tube voltage, 120 kV; tube current, 80 mAs; rotation time, 0.25 s; pitch, 0.24; and slice thickness, 3.0 mm.

Measurement of pericoronary CT fat attenuation index and CAC

After the scan was completed, the system can automatically push the CCTA scan image of each patient to ‘CoronaryDoc’ software (Shukun Technology, China), and the CCTA image reconstruction and coronary plaque analysis were automatically completed in about 3 min. The software has been approved by the National Medical Products Administration (NMPA) (Class III) for coronary artery reconstruction and stenosis diagnosis of CCTA. After that, the results of each patient’s software analysis were ignored, and the CCTA images of each patient were diagnosed by 2 radiologists with more than 5 years of cardiovascular diagnosis experience respectively. By the visual analysis of the 2 radiologists, the criteria for CAD were defined according to whether the coronary artery was stenosed on the patient’s CCTA image, and the plaques for CAD were classified as noncalcified plaque (NCP), calcified plaque (CP), and mixed plaque (MP) (16). If there was a discrepancy between the 2 radiologists or with the analysis of Shukun coronary analysis software, the final diagnosis was made by another cardiovascular radiologist with more experience.

Using the Shukun PCAT analysis software, the system can automatically calculate the RCA PCAT attenuation of a patient in about 30–40 s. According to the method proposed by Oikonomou (3), we extracted the PCAT along the center line of the RCA starting from 1 cm downstream of roots at the aorta with a length span of 4 cm. The transverse area was set to 3 times the diameter of the vessel lumen. In this area, tissues with a CT value of −190 to −30 HU were considered as the PCAT. Furthermore, we measured the total CAC score using the Shukun CAC score software to reflect the patient’s overall coronary atherosclerotic burden. The CAC score was calculated by using the Agatston method, which is based on a weighted sum of lesions with a density greater than 130 HU (17). Figures 2,3 show fully automated measurements of CAC and CT attenuation values of PCAT, respectively.

Figure 2 Schematic diagram of coronary artery calcium measurement.

Figure 3 Schematic diagram of attenuation value measurement of pericoronary adipose tissue. (A) Axis position. (B) Curved planar reconstruction. (C) Cross-section multiplanar reconstruction. (D) Straightened curved planar reconstruction.

Patients grouping

According to the radiologists’ diagnosis and CAC score, the patients were classified as follows to compare differences in their PCAT attenuation:

• A. CAC score >0 vs. B. CAC score =0 and no CAD vs. C. CAC score =0 and with CAD;
• A₁. CAC score >10 vs. A₁^’. 0< CAC score ≤10 vs. C. CAC score =0 and with CAD;
• A₂. CAC score >100 vs. A₂^’. 0< CAC score ≤100 vs. C. CAC score =0 and with CAD; and
• A₃. CAC score >400 vs. A₃^’. 0< CAC score ≤400 vs. C. CAC score =0 and with CAD.

Statistical analysis

All the data were statistically analyzed by SPSS 23.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism 8.0.2 (GraphPad Software Inc., San Diego, CA, USA). The categorical variables were represented as frequency (percentage) and analyzed using the Chi-square test. The continuous variables were expressed as mean ± standard deviation or medians (interquartile range), and they were compared among the three groups using one-way ANOVA test or Kruskal-Wallis H test. The independent risk factors were screened using multiple logistic regressions.

Results

Patients’ baseline characteristics

In this study, there were 117 patients with CAC score >0, 161 patients with no CAD with CAC score =0, and 68 patients with CAD with CAC score =0. There were significant differences in age, body mass index (BMI), hypertension, hyperlipidemia, hyperglycemia, and smoking among the three groups (P<0.05). On the other hand, there were no statistically significant differences in gender and tube voltage among the three groups (P>0.05, Table 1).

Comparison of PCAT attenuation values within each group

• In this study, patients with CAD had significantly higher PCAT attenuation than patients without CAD (−87.54±9.39 vs. −93.45±7.42 HU, P=0.000). Taking the CAC score =0 as the boundary, it was found that the PCAT attenuation of patients with CAD with CAC score =0 was significantly higher than that of patients with CAC score >0 and patients with no CAD with CAC score =0 (−82.63±8.70 vs. −90.38±8.59 vs. −93.45±7.42 HU, P=0.000). In addition, patients with CAC score >0 also had significantly higher PCAT attenuation than patients with no CAD with CAC score =0 (Figure 4).
  

  Figure 4 Comparison of PCAT attenuation values between groups. *, P<0.05, compared with CAC =0 & CAD; ^#, P<0.05, compared with CAC =0 & No CAD. PCAT, pericoronary adipose tissue; CAD, coronary artery heart disease; CAC, coronary artery calcium.
• The CAC scores of 10, 100, and 400 were taken as the cutoff values. It was found that the PCAT attenuation was significantly higher in patients with CAD with a CAC score =0 (−82.63±8.70 HU) than that of patients with CAC score >10 (−90.70±8.27 HU, P=0.000), 0< CAC score ≤10 (−89.09±9.87 HU, P=0.000); CAC score >100 (−90.12±7.72 HU, P=0.000), 0< CAC score ≤100 (−90.59±9.26 HU, P=0.000); and CAC score >400 (−89.69±6.04 HU, P=0.000), 0< CAC score ≤400 (−90.50±8.94 HU, P=0.000). In contrast, there was no significant difference in the PCAT attenuation between patients with CAC score >10, 0< CAC score ≤10; CAC score >100, 0< CAC score ≤100; and CAC score >400, 0< CAC score ≤400 (Figure 4).

The results of multiple logistic regressions

In the multiple logistic regression analysis, the study set patients with no CAD with CAC score =0 as the reference group, the independent risk factors of patients with CAC score >0 were age [odds ratio (OR): 1.076, 95% CI: 1.045–1.108, P=0.000], BMI (OR: 1.153, 95% CI: 1.056–1.259, P=0.001), hyperlipidemia (OR: 0.327, 95% CI: 0.180–0.597, P=0.000), hypertension (OR: 0.355, 95% CI: 0.195–0.645, P=0.001), smoking (OR: 0.248, 95% CI: 0.156–0.518, P=0.000) and PCAT attenuation (OR: 1.041, 95% CI: 1.002–1.081, P=0.040); the independent risk factors of patients with CAD with CAC score =0 were BMI (OR: 1.186, 95% CI: 1.067–1.319, P=0.002), hyperlipidemia (OR: 0.416, 95% CI: 0.198–0.874, P=0.021), hypertension (OR: 0.385, 95% CI: 0.185–0.798, P=0.010), and PCAT attenuation (OR: 1.175, 95% CI: 1.120–1.232, P=0.000; Table 2, Figure 5).

Figure 5 The forest plots show the results of the multiple logistic regression. (A) No CAD patients with CAC score =0 vs. patients with CAC score >0. (B) No CAD patients with CAC score =0 vs. CAD patients with CAC score =0. CAD, coronary artery heart disease; CAC, coronary artery calcium; BMI, body mass index; PCAT, pericoronary adipose tissue; OR, odds ratio; CI, confidence interval.

Discussion

This study explored the potential association between coronary inflammation and coronary atherosclerotic burden based on the RCA proximal PCAT attenuation value and total CAC scores measured by the CCTA. The results showed that PCAT attenuation value was not necessarily associated with CT calcification but rather with the presence of CAD, especially in patients with NCP (patients with CAD with CAC score =0). In addition, BMI, hyperlipidemia, hypertension, and PCAT attenuation were independent risk factors for patients with CAD with CAC score =0 and patients with CAC score >0, when patients with no CAD with CAC score =0 were taken as the reference group.

The CAC score is a valid surrogate for the burden of coronary atherosclerosis, and its presence and magnitude are related to the increased risk of cardiovascular events; whereas, patients with a CAC score of 0 have always been considered to have a lower cardiovascular risk in the future (12,18). However, CAD patients with NCP were overlooked by the concept of a CAC score of 0 which could be caught by the CCTA but proven to be dangerous by research (19-21). We, therefore, further subdivided patients with CAC score of 0 into patients with no CAD with CAC score =0 and CAD patients with CAC score =0 to better explore the potential association between PCTA attenuation and CAC score. Clinically, the age, BMI, hypertension, hyperlipidemia, hyperglycemia, and smoking are found to be significantly different among patients with CAD with CAC score =0, CAC score >0, and patients with no CAD with CAC score =0. Moreover, our results were similar to previous studies, which found BMI, hyperlipidemia, and hypertension were independent risk factors for patients with CAD with CAC score =0 and patients with CAC score >0 (22-24). Therefore, patients with hyperlipidemia, hypertension, and high BMI should be prompted for lipid, blood pressure and weight control, and regular CAC and CCTA examinations to prevent adverse cardiac events.

The attenuation value of PCAT is considered as a noninvasive biomarker of coronary inflammation (3,25). The mechanism is that inflammatory signals released from the inflamed vessels can diffuse directly to PCAT, inducing its breakdown and inhibiting its formation, while promoting pericoronary edema (26). When patients undergo a CCTA, the CT attenuation value of PCAT increases because of the lower lipid content and higher water content around the inflamed coronary artery (3). In patients, higher PCAT attenuation values suggest a higher danger of adverse cardiac events (27,28). In this study, compared to patients with no CAD, we found higher PCAT attenuation in patients with CAD, which is consistent with Antonopoulos et al. (26), who suggested that coronary artery inflammation plays an important part in the development and progression of atherosclerosis (29,30). In addition, we also found that the PCAT attenuation of patients with CAD with CAC score =0 was significantly higher than those with CAC score >0. This may be due to the fact that the calcium presence makes the plaque relatively stable, with only minimal inflammatory components and coronary inflammation may be more pronounced in the NCP (31,32).

Higher Agatston CAC scores indicate greater coronary atherosclerotic burden and higher cardiovascular risk, which however is inconsistent with the pathophysiological progression of coronary atherosclerotic plaques from unstable to stable stages (33). To further explore the relationship, our study, using the boundaries of the CAC scores of 10, 100, and 400, delved into finding the correlation between CAC scores and PCAT attenuation values. In this study, no significant differences in PCAT attenuation values between CAC scores were noted, which is in agreement with studies by Ma et al. (16) and Goeller et al. (34), which showed that the inflammatory information captured by PCAT attenuation is not associated with coronary artery calcification. Furthermore, this is to be anticipated because CPs are composed mainly of hydroxyapatite and do not comprise the main inflammatory element of atherosclerotic plaques (35). Moreover, patients with CAD with CAC score =0, also known as NCP, had higher PCAT attenuation values compared to all other groups with CAC scores. This is consistent with the hypothesis that NCP is an early stage of atherosclerosis, and plaque calcification is a late manifestation of atherosclerosis; whereas, inflammation can be comparatively reduced as plaques become more stable and calcified (36).

We observed that in addition to BMI, hyperlipidemia, and hypertension (23,37), which are often reported as risk factors, increased PCAT attenuation was also an independent risk factor for patients with CAD with CAC score =0 and patients with CAC score >0, which indicated that both PCAT attenuation and patient clinical information have important added value for the cardiovascular disease risk assessment. Furthermore, Sugiyama et al. (38) found that the RCA Agatston CAC score was a determinant of the PCAT attenuation value proximal to the RCA in male patients. Therefore, for patients with clinical risk factors, it is necessary to undergo a follow-up CCTA even if their CAC score is 0. It is not only to avoid missing NCPs, but also to obtain additional information about coronary inflammation, which is considered to be more important.

Limitations

There are several limitations of this study. Firstly, the present study was a retrospective single-center study; therefore, a larger multicenter study is needed to further validate our findings prospectively. Secondly, although the difference in tube voltage was not statistically significant among the three groups of patients, the CT values of fat varied with the tube voltage. Thirdly, patients with CAD were not followed up for subsequent major adverse cardiovascular events in this study, and we will follow up with patients in this study in the future to further reveal the relationship between coronary atherosclerotic burden and vascular inflammation. Finally, only the PCAT attenuation of the proximal RCA was analyzed, and the correlation between coronary inflammation around the plaque and coronary atherosclerotic burden still needs to be further explored in the future.

Conclusions

Although PCAT attenuation values were not different among CAC scores, it was highest in patients with CAD with CAC score =0 and was also an independent risk factor for patients with CAD with CAC score =0 and CAC score >0. These suggest that direct relationship between coronary inflammation and coronary atherosclerotic burden is not evident, however, patients with CAD with CAC score =0 should not be ignored.

Acknowledgments

The abstract of this manuscript has been accepted for presentation as EPOS Radiologist (scientific) at the European Congress of Radiology 2023 (Number: #13213).

Funding: This work was supported by the National Natural Science Foundation of China (No. 82071872), and the Medical Innovation and Development Project of Lanzhou University (No. lzuyxcx-2022-139).

Footnote

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-147/coif). JZ reports that this work was supported by the National Natural Science Foundation of China (No. 82071872), and Medical Innovation and Development Project of Lanzhou University (No. lzuyxcx-2022-139). XZ was an employee of Siemens Healthineers Company, and ZX is an employee of Shukun Technology Company. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional ethics board of Lanzhou University Second Hospital (No. 2021A-165) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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