Correlation between the coronary computed tomography angiography-derived pericoronary fat attenuation index and coronary artery lesions in Kawasaki disease

Introduction

Kawasaki disease (KD) is a type of acute systemic vasculitis that predominantly afflicts young children and is a leading cause of acquired heart disease in this population (1). The primary serious complication of KD is the development of coronary artery lesions (CALs), including dilation, aneurysms, stenosis, and thrombosis (2). These lesions can lead to myocardial ischemia, infarction, and even sudden cardiac death, imposing a significant long-term burden on survivors (3).

The accurate detection and monitoring of CALs are therefore critical for risk stratification and long-term management. Traditionally, transthoracic echocardiography has been the primary screening tool in this setting by virtue of its noninvasive nature and wide availability. However, it has limited ability to visualize the distal coronary segments and to assess older, often more obese, children. Invasive coronary angiography, while serving as the gold standard for luminal assessment, is unsuitable for routine follow-up due to its inherent risks and procedural complexity (4).

Coronary computed tomography angiography (CCTA) has emerged as a robust, noninvasive alternative for the comprehensive evaluation of the coronary artery anatomy in patients with KD. It offers excellent spatial resolution, allowing for precise delineation of luminal irregularities, aneurysm dimensions, and the presence of calcification or thrombosis. Furthermore, CCTA allows for the assessment of coronary stenosis and its hemodynamic significance, providing a “one-stop shop” for anatomical and functional evaluation (5). Beyond luminal assessment, CCTA also facilitates the quantitative evaluation of perivascular tissue. In addition, pericoronary adipose tissue (PCAT) is anatomically adjacent to coronary arteries, and its inflammatory state may directly affect the vessel wall through paracrine mechanisms, leading to the formation of coronary aneurysmal lesions (6). The pericoronary fat attenuation index (FAI) is a novel radiological biomarker derived from CCTA data that quantifies the radiodensity of adipose tissue surrounding the coronary arteries. In the past, fat attenuation was considered a fixed entity; however, it is now recognized that inflammation within the vessel wall alters the composition of the perivascular fat, reducing its lipid content and increasing its water content, which in turn elevates its computed tomography (CT) attenuation value. Thus, a higher FAI is a sensitive indicator of active coronary inflammation (6).

Although the FAI has been extensively validated in the context of adult coronary artery disease for stratifying plaque vulnerability and predicting future cardiac events, its application in the pediatric population, particularly in inflammatory conditions such as KD, remains largely unexplored. Given that the pathogenesis of CALs in KD is driven by intense vasculitis and subsequent chronic inflammation, the FAI may serve as a novel, quantitative biomarker for detecting the subclinical perivascular inflammation associated with both acute coronary arteritis and chronic vascular remodeling. An analysis of the correlation between FAI and the presence, severity, and characteristics of CALs in patients with KD could provide valuable insights into the ongoing inflammatory activity and improve risk prediction beyond standard anatomical assessment alone. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2749/rc).

Methods

Study population and data collection

This retrospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Sun Yat-sen Memorial Hospital Institutional Review Board (approval No. SYSKY-2025-1052-01). The requirement for informed consent was waived due to the retrospective nature of the analysis. Patients diagnosed with KD who underwent CCTA between January 2010 and December 2023 at Sun Yat-sen Memorial Hospital were included. Diagnosis of KD was established according to the American Heart Association guidelines (1). Clinical data, including demographic information, laboratory findings, echocardiographic results, and details of acute-phase treatment, were collected from electronic medical records by three pediatric cardiologists (X.C., X.Z., and P.L.). Prior to initial intravenous immunoglobulin (IVIG) therapy, CCTA and echocardiography were conducted. Patients with incomplete clinical data, poor CCTA image quality, or a history of other cardiovascular diseases were excluded.

Patients with KD who had CALs were identified by the presence of coronary artery abnormalities on echocardiography imaging, coupled with a Z-score ≥2.5, or coronary artery diameter ≥2.5 mm for ages <3 years, ≥3.0 mm for ages 3–9 years, and ≥3.5 mm for ages >9 years. Conversely, KD patients without CALs were defined as those showing no coronary artery abnormalities on echocardiography imaging. The healthy control group included individuals who underwent CCTA for clinical suspicion of coronary artery disease but were found to have completely normal coronary arteries, with no luminal stenosis, atherosclerosis, or coronary anomalies. These control participants were matched for age and sex with patients in the KD groups to minimize demographic confounding factors. The flowchart of participant inclusion and exclusion is provided in Figure 1.

Figure 1 Flowchart of participant inclusion, including KD patients with or without CALs and healthy controls. CAL, coronary artery lesion; CCTA, coronary computed tomography angiography; KD, Kawasaki disease.

Echocardiography assessment

Echocardiography was used to measure the dimensions of coronary arteries of all patients with KD by a cardiac ultrasound physician (J.S.) and a pediatric cardiologist (X.C.). The diagnostic criteria for CALs (7) included a Z-score ≥2.5 or coronary artery diameter ≥2.5 mm for ages <3 years, ≥3.0 mm for ages 3–9 years, and ≥3.5 mm for ages >9 years. The Z-scores of the most severe coronary artery were obtained with an online Z-score calculator (https://kwsd.info/zsp_form.cgi).

Coronary CTA acquisition and evaluation

All CCTA examinations were performed with a 128-slice multidetector CT scanner (Discovery CT750 HD, GE HealthCare, Chicago, IL, USA). A standard coronary angiography protocol was applied, which included prospective electrocardiogram triggering and administration of intravenous iodinated contrast agent (iohexol; 350 mgI/mL). Images were reconstructed with a slice thickness of 0.9 mm and an increment of 0.45 mm.

Coronary artery segments were defined according to the modified American Heart Association 17-segment model (8). Lesions were classified by two cardiovascular radiologists (Y.L. and Z.B.) based on the Z-score system, with a Z-score ≥2.5 indicating coronary artery aneurysm formation (9). Stenosis was quantified as a reduction of ≥50% in luminal diameter.

Measurement of pericoronary FAI

The FAI was measured automatically with dedicated cardiac image analysis software (uAI-CoronaryCTA, United Imaging, Shanghai, China). When the automatic measurement area was inaccurate, it was manually corrected by cardiovascular radiologists (Y.L. and Z.W.). Pericoronary FAI was recorded as the average CT attenuation within a radial distance equal to the diameter of the coronary arteries, with thresholds of −190 to −30 Hounsfield units (HU) used to identify the adipose tissue surrounding a segment extending 5 mm radially from the outer vessel wall. To measure inflammation in the coronary artery as a whole, pericoronary FAI was measured in the proximal 40-mm segments of the left anterior descending coronary artery (LAD) and left circumflex artery (LCX), as well as in the proximal 10- to 50-mm segment of the right coronary artery (RCA). For patient-by-patient analysis, the FAI of the three branches was averaged as the global FAI (Figure 2) (10). A random subset of 20 patients and 10 healthy controls was reanalyzed by two independent cardiovascular radiologists. The interclass correlation coefficient (ICC) was calculated.

Figure 2 A 5-year-old boy with KD complicated by CALs, including a large aneurysm (short arrows) and stenosis (long arrows) involving three branches. (A,C,D) The process by which the FAI is derived from CCTA imaging. (B) The image of the coronary artery obtained by the volume rendering technique shows aneurysms in the LAD, LCX, and RCA. CAL, coronary artery lesion; CCTA, coronary computed tomography angiography; FAI, fat attenuation index; HU, Hounsfield units; KD, Kawasaki disease; LAD, left anterior descending coronary artery; LCX, left circumflex artery; RCA, right coronary artery.

Statistical analysis

Statistical analyses were performed with SPSS software version 25 (IBM Corp., Armonk, NY, USA) and R version 4.2.2 (The R Foundation for Statistical Computing, Vienna, Austria). Continuous variables are presented as the mean ± standard deviation or as the median and interquartile range, as appropriate. Categorical variables are expressed as frequencies and percentages. The correlation between FAI and the presence and severity of CALs was assessed via Pearson or Spearman correlation coefficients. A P value <0.05 was considered statistically significant. We developed univariate and multivariate logistic regression models to determine the independent risk factors for CALs in patients with KD, reporting the findings as odds ratios (ORs) with 95% confidence intervals (CIs). The ability of FAI to predict CALs in patients with KD was evaluated via receiver operating characteristic (ROC) curve analysis.

Results

Patient characteristics

The study included 71 patients with KD (mean age 8.60±2.72 years; 44 males and 27 females) and 31 healthy controls matched for age and body mass index (mean age 8.99±2.52 years; 18 males and 13 females) (Table 1). The pericoronary FAI was significantly higher in the KD group (−72.1±6.9 HU) than in the healthy control group (−77.6±7.5 HU, P<0.001).

The baseline characteristics and clinical manifestations of the KD population are presented in Table 2. Patients with CALs (n=40) were significantly older than those without CALs (n=31) (9.50±2.69 vs. 7.44±2.33 years, P<0.001) and had a longer disease duration before IVIG treatment (4.85±3.00 vs. 3.69±1.43 days, P=0.036). Significant differences were observed in IVIG resistance, with the CAL group, as compared to the non-CAL group, exhibiting higher rates of resistance (47.5% vs. 3.2%, P<0.001), fever duration ≥7 days (50.0% vs. 0.0%, P<0.001), leukocyte count ≥30×10⁹/L (35.0% vs. 6.5%, P=0.004), platelet count ≥500×10⁹/L (67.5% vs. 38.7%, P=0.016), hypoalbuminemia <30 g/L (55.0% vs. 19.4%, P=0.002), myocardial enzyme abnormalities (25.0% vs. 3.2%, P=0.018), elevated erythrocyte sedimentation rate (ESR) >100 mm/min (70.0% vs. 38.7%, P=0.008), procalcitonin levels ≥0.5 ng/mL (40.0% vs. 6.5%, P=0.001), and coronary wall thickening (65.0% vs. 6.5%, P<0.001). Additionally, the FAI was significantly higher in the CAL group than in the non-CAL group (−69.2±5.0 vs. −76.0±7.2, P<0.001). No statistically significant differences were found in gender distribution, BMI, heart rate, incomplete KD presentation, hemoglobin levels, alanine aminotransferase abnormalities, pericardial effusion, C-reactive protein levels, thrombosis, calcification, or stenosis between the two groups.

Analysis of pericoronary FAI

The results of FAI showed good reproducibility (interobserver ICC =0.91; 95% CI: 0.85–0.95). The pericoronary FAI was significantly lower in the control group (−77.6±7.5 HU) than in the KD group (−72.1±6.9 HU, P<0.001).

Among the KD groups, the mean pericoronary FAI values for all three major coronary arteries were significantly higher in the CAL group than in the non-CAL group (LAD: −68.5±6.7 vs. −75.2±5.1 HU; LCX: −69.8±7.2 vs. −76.9±5.8 HU; RCA: −70.1±6.9 vs. −77.5±5.3 HU; all P values <0.001) (Table 2). Additionally, the global pericoronary FAI was significantly higher in the CAL group than in the non-CAL group (−69.2±5.0 vs. −76.0±7.2, P<0.001) (Figure 3).

Figure 3 The global FAI value in different subgroups and its association with the ESR, maximum size, and Z-score of CALs in patients with KD. (A) The global FAI in the different subgroups. The plot shows that patients with KD with CALs had a significantly different global FAI as compared to patients with KD but without CALs and healthy controls (*, both P values <0.001). (B-D) The global FAI in the KD with CAL group and its association with ESR (mm/h), maximum size (mm), and the Z-score of severe CALs. CAL, coronary artery lesion; ESR, erythrocyte sedimentation rate; FAI, fat attenuation index; HU, Hounsfield units; KD, Kawasaki disease.

Correlation analysis

Pearson correlation analysis revealed a positive correlation between the global FAI value (average of the LAD, LCX, and RCA values) and the maximum size of the coronary artery (r=0.31; P<0.05) and Z-score (r=0.34; P<0.05). Furthermore, significant positive correlations were observed between global FAI and the marker of acute-phase inflammation, peak ESR (r=0.39; P<0.001) (Figure 3).

Multivariate logistic regression analysis of coronary lesions in patients with KD

Univariable logistic regression analysis (Table 3) revealed that age, IVIG resistance, white blood cell count ≥30×10⁹/L, platelet ≥500×10⁹/L, albumin <30 g/L, ESR >100 mm/h, procalcitonin ≥0.5 ng/mL, and pericoronary FAI were independent predictors of CALs.

Least absolute shrinkage and selection operator and 10-fold cross-validation were used to select the factors for inclusion in the multiple logistic regression analysis. Multivariate logistic regression analysis identified that the independent predictors of CALs were age (OR =1.55; 95% CI: 1.07–2.25; P=0.022), platelet count ≥500×10⁹/L (OR =13.81; 95% CI: 1.78–107.22; P=0.012), ESR >100 mm/h (OR =24.26; 95% CI: 3.03–194.19; P=0.003), albumin <30 g/L (OR =8.74; 95% CI: 1.46–52.47; P=0.018), and the pericoronary FAI (OR =1.36; 95% CI: 1.14–1.63; P<0.001), with the pericoronary FAI being the most statistically significant (P<0.001) (Table 3).

Predictive performance of pericoronary FAI and clinical parameters

According to the ROC analysis, the FAI combined with clinical parameters (pericoronary FAI + age + platelet count ≥500×10⁹/L + albumin <30 g/L + ESR >100 mm/h) had the best performance for predicting CALs in patients with KD disease [area under the curve (AUC) =0.935; 95% CI: 0.885–0.986], followed by clinical parameters (AUC =0.858; 95% CI: 0.766–0.950) and the FAI (AUC =0.783; 95% CI: 0.664–0.901) (Figure 4). A global FAI cutoff value of >−72.8 HU yielded a sensitivity of 86.2% and a specificity of 87.8% in identifying the presence of CALs.

Figure 4 ROC curve analysis of the ability of the global FAI and clinical parameters to discriminate between patients with KD with and without CALs. The AUCs of FAI, clinical parameters, and the FAI combined with clinical parameters were 0.783 (95% CI: 0.664–0.901), 0.858 (95% CI: 0.766–0.950), and 0.935 (95% CI: 0.885–0.986), respectively. AUC, area under the curve; CAL, coronary artery lesion; CI, confidence interval; ESR, erythrocyte sedimentation rate; FAI, fat attenuation index; KD, Kawasaki disease; ROC, receiver operating characteristic.

Discussion

This study generated compelling evidence that the CCTA-derived pericoronary FAI can serve as a robust quantitative biomarker for assessing coronary inflammation and predicting CALs in patients with KD. The FAI was significantly elevated in patients with KD compared to healthy controls (−72.1±6.9 vs. −77.6±7.5 HU, P<0.001), with greater increases observed in those with CALs (−69.2±5.0 vs. −76.0±7.2 HU, P<0.001). The strong positive correlations between FAI and established inflammatory markers such as peak ESR (r=0.39; P<0.001), as well as with anatomical indices of disease severity, including maximal coronary size (r=0.34; P<0.05) and Z-score (r=0.31; P<0.05), underscore FAI’s potential as an integrated measure of vascular inflammatory activity. Furthermore, multivariate logistic regression analysis showed that independent predictors of the occurrence of CALs in KD patients were the pericoronary FAI (OR =1.36; P<0.001), platelet count ≥500×10⁹/L (OR =13.81; P=0.012), ESR >100 mm/h (OR =24.26; P=0.003), albumin <30 g/L (OR =8.74; P=0.018), and age (OR =1.55; P=0.022). Importantly, the integration of FAI with clinical parameters yielded an exceptionally high performance for identifying CALs, as evidenced by an AUC of 0.935, suggesting substantial incremental value for risk stratification in clinical practice.

The inflammatory state of the PCAT can be quantitatively assessed via the pericoronary FAI, and in this study, it was used for the first time to predict CALs in patients with KD. The concept of utilizing PCAT composition as an indicator of coronary vascular inflammation is supported by a growing body of literature across various cardiovascular conditions. Inflammation within the vascular wall leads to changes in the functional properties of surrounding adipose tissue, including altered adipokine secretion and increased lipid turnover, which in turn elevate its CT attenuation values (11-13). Our observation of a heightened FAI in patients with KD aligns with studies in adults with coronary artery disease, with elevated FAI being consistently associated with increased pericoronary inflammation and a higher risk of acute coronary events (11-14). Specifically, Biradar et al. demonstrated that an FAI value greater than −77.3 HU around the RCA is a powerful predictor of future acute coronary events in patients with nonobstructive coronary artery disease, highlighting the prognostic relevance of this metric beyond anatomical stenosis (11). Similarly, research on other inflammatory vasculitides, such as that observed in patients with psoriasis, has shown that effective anti-inflammatory therapy can reduce FAI, further supporting its role as a dynamic marker of vascular inflammation (15).

When contextualized within the specific realm of KD, our findings contribute to a nascent but promising field in need of reliable objective measures that can complement echocardiographic assessment. Coronary artery Z-scores from echocardiography, despite being relied upon historically, have limited sensitivity for detecting early wall inflammation before anatomical dilation occurs and are insufficient for quantifying diffuse perivascular changes. The nomogram developed by Hu et al., which incorporated laboratory parameters such as sodium, hemoglobin, D-dimer, and cystatin C levels, along with platelet count, achieved a respectable AUC of 0.844 for predicting CALs (16). Our model, which includes the FAI, demonstrates superior discriminatory power (AUC =0.935), suggesting that direct imaging-based assessment of perivascular inflammation adds significant value to the use of serum biomarkers alone. This is further supported by the emerging findings from studies on radiomics approaches. Zhu et al. and Ye et al. both reported that radiomic models analyzing PCAT on CCTA outperformed simple FAI measurements for tasks such as identifying vulnerable plaques and predicting major adverse cardiovascular events (17-19). These studies, along with ours, point toward a future where sophisticated image analysis can provide a more holistic and sensitive evaluation of coronary involvement in inflammatory conditions.

The pathophysiological basis for FAI elevation in KD is rooted in the intense panvasculitis that characterizes the disease. The inflammatory cascade in KD involves the widespread activation of the immune system, which has been linked to IVIG non-responsiveness, with cytokines such as interleukin (IL)-1, IL-6, and notably, IL-17A, being particularly prominent in this process (20). This systemic inflammation directly affects the coronary arteries and their surrounding adipose tissue. The significant correlation we observed between FAI and peak ESR (r=0.39; P<0.001) suggests a direct clinical link between systemic inflammation and localized coronary changes. The involvement of specific immune pathways is an area of active investigation. Research by Freeman et al. indicated that T-cell activation phenotypes, particularly programmed cell death protein 1 (PD-1) expression on CD8⁺ central memory cells, were associated with worsened pericoronary inflammation as measured by the FAI in individuals with and without human immunodeficiency virus (HIV) (12). Although our study did not profile T-cell subsets, it is plausible that similar mechanisms of adaptive immune activation drive the inflammatory changes in the pericoronary fat in patients with KD. Furthermore, the study by Chen et al. on leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) suggests complex immunoregulatory mechanisms are at play in the pathogenesis of KD and the formation of CALs (21), which may also be reflected in FAI alterations.

A critical strength of our study lies in its demonstration of FAI’s utility for both discrimination and risk prediction. In multivariate analysis, the FAI emerged as an independent risk factor for CALs, with an OR of 1.36 per unit increase. This positions the AI alongside other strong predictors identified in large cohorts, such as delayed IVIG treatment and the presence of coronary artery abnormalities on initial echocardiography, as highlighted by Takaki et al. nationwide Japanese study (22). The ability of the FAI to provide incremental predictive value when combined with clinical parameters is a key finding with direct clinical implications. It suggests that CCTA-derived FAI could be particularly valuable in assessing patients with incomplete or atypical KD presentations, a population in which diagnosis is often challenging and delayed and thus associated with higher rates of complications (23,24). For instance, Giryes et al. reported that the presence of anterior uveitis, a sometimes-overlooked sign, was associated with earlier diagnosis and a significantly lower risk of CALs in patients with incomplete KD (23). The FAI may serve as an objective imaging biomarker to aid in the diagnosis and risk stratification of such complex cases. Azhe et al. reported the presence of coronary artery aneurysm (β=7.20; P<0.001) to be independently associated with mean PCAT attenuation on CT (19).

Despite these promising results, our study has several limitations that must be acknowledged. First, its retrospective design introduces the potential for selection bias. Patients undergoing CCTA may represent a subset with particularly concerning clinical features or equivocal echocardiograms, potentially limiting the generalizability of our findings to all patients with KD. Second, the measurement of FAI is not without technical challenges. As conclusively demonstrated by Lisi et al., FAI values can vary significantly depending on CT reconstruction parameters, including the kernel and the level of iterative reconstruction used (25). This lack of standardization across platforms and institutions poses a major hurdle to the widespread clinical adoption of the FAI and underscores the need for strict protocol harmonization in future multicenter studies. Third, while we excluded patients with known obstructive coronary artery disease, the potential confounding influence of other factors that might affect pericoronary fat density, such as overall adiposity or concurrent systemic inflammatory conditions, cannot be entirely ruled out. Finally, the cross-sectional nature of our correlation analyses limits our ability to establish a definitive causal relationship between FAI elevation and CAL development, and thus longitudinal studies tracking FAI changes from the acute phase through convalescence are warranted.

The clinical implications of our research are substantial. The high AUC of 0.935 for the model combining FAI with clinical parameters suggests that this approach could significantly improve the early identification of patients with KD at the highest risk for developing CALs. This would allow for the earlier implementation of more personalized and aggressive treatment strategies. This could potentially include the administration of primary adjunctive corticosteroid therapy or other biologics in high-risk individuals, an approach that has been shown to reduce IVIG retreatment rates and improve outcomes in some studies (26,27). Echocardiography facilitates the routine assessment of coronary artery luminal dimensions and wall brightness, but it has limitations in objectively quantifying PCAT inflammation, especially in patients with suboptimal acoustic windows or nondilated coronary segments. However, the FAI should not replace echocardiography but rather serve as an adjunctive tool when CCTA is clinically indicated (e.g., for coronary aneurysm evaluation or stenosis assessment). The incremental value lies in its ability to detect pericoronary inflammation even before luminal changes become apparent, thus providing an earlier or more sensitive inflammatory marker. In our study, all CCTA examinations were performed in accordance with the “as low as reasonably achievable” principle, and a low-dose scanning protocol was selected to minimize radiation exposure. Moreover, the potential benefit of identifying high-risk inflammatory phenotypes may justify the low radiation exposure in selected patients. This is particularly relevant for the long-term follow-up of patients with regressed aneurysms, who may still harbor residual vascular inflammation and an increased lifetime risk of cardiovascular events, as suggested by long-term outcome studies (28).

Future research directions should be multifaceted. Prospectively designed, multicenter studies are urgently needed to validate our findings in a larger, more diverse KD population and to establish standardized CT acquisition and reconstruction protocols for reliable FAI measurement (25). The evolution of imaging analysis from simple attenuation measurement to more complex radiomic phenotyping of PCAT holds considerable promise (27-29). Investigating the dynamic changes in the FAI during the acute, subacute, and convalescent phases of KD, and in response to different therapeutic interventions, will be crucial for understanding its natural history and utility as a treatment monitoring biomarker. The integration of FAI with other emerging diagnostic modalities, such as targeted metabolomics (29) or cell-free RNA profiling (30), could lead to the development of powerful multiomics prediction models. Finally, exploring the potential of the FAI to guide long-term management decisions, such as the intensity of antithrombotic therapy or the use of anti-inflammatory agents such as statins or angiotensin-converting enzyme inhibitors in patients with persistent aneurysms, represents a critical avenue for clinical research that could directly improve patient outcomes (31,32).

Conclusions

Our study establishes the pericoronary FAI derived from CCTA as a novel, reliable, and quantitative imaging biomarker for assessing coronary inflammation and predicting the risk of CALs in patients with KD. Its strong correlations with inflammatory markers and disease severity, its independent predictive value, and its significant incremental utility when combined with clinical parameters position the FAI as a potent tool for enhancing risk stratification. This has the potential to facilitate earlier, more targeted interventions for high-risk patients, with the ultimate aim being the mitigation of long-term cardiovascular sequelae of this pediatric form of vasculitis. Although technical challenges in standardization remain, the continued refinement of imaging protocols and analytical techniques promises to further solidify the role of FAI in the comprehensive evaluation and management of patients with KD.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2749/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2749/dss

Funding: This work was supported by the Science and Technology Bureau of Shanwei City (No. 2025C009).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2749/coif). The 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. This retrospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Sun Yat-sen Memorial Hospital Institutional Review Board (No. SYSKY-2025-1052-01), and the requirement for informed consent was waived owing to the retrospective nature of the study.

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/.

References

1. McCrindle BW, Rowley AH, Newburger JW, Burns JC, Bolger AF, Gewitz M, Baker AL, Jackson MA, Takahashi M, Shah PB, Kobayashi T, Wu MH, Saji TT, Pahl EAmerican Heart Association Rheumatic Fever, Endocarditis, and Kawasaki Disease Committee of the Council on Cardiovascular Disease in the Young. Council on Cardiovascular and Stroke Nursing; Council on Cardiovascular Surgery and Anesthesia; and Council on Epidemiology and Prevention. Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association. Circulation 2017;135:e927-99. Erratum in: Circulation 2019;140:e181-4.
2. Jia C, Zhuge Y, Zhang S, Ni C, Wang L, Wu R, Niu C, Wen Z, Rong X, Qiu H, Chu M. IL-37b alleviates endothelial cell apoptosis and inflammation in Kawasaki disease through IL-1R8 pathway. Cell Death Dis 2021;12:575. [Crossref] [PubMed]
3. Kato T, Miura M, Kobayashi T, Kaneko T, Fukushima N, Suda K, Maeda J, Shimoyama S, Shiono J, Hirono K, Ikeda K, Sato S, Numano F, Mitani Y, Waki K, Ayusawa M, Fukazawa R, Fuse S. Z‐Score Project 2nd Stage Study Group*. Analysis of Coronary Arterial Aneurysm Regression in Patients With Kawasaki Disease by Aneurysm Severity: Factors Associated With Regression. J Am Heart Assoc 2023;12:e022417. Erratum in: J Am Heart Assoc 2023;12:e027722.
4. van Stijn D, Planken N, Kuipers I, Kuijpers T. CT Angiography or Cardiac MRI for Detection of Coronary Artery Aneurysms in Kawasaki Disease. Front Pediatr 2021;9:630462. [Crossref] [PubMed]
5. Hecht HS, Villines TC. Coronary computed tomographic angiography and invasive coronary angiography: A reevaluation. J Cardiovasc Comput Tomogr 2020;14:374-6. [Crossref] [PubMed]
6. Antonopoulos AS, Sanna F, Sabharwal N, Thomas S, Oikonomou EK, Herdman L, et al. Detecting human coronary inflammation by imaging perivascular fat. Sci Transl Med 2017;9:eaal2658. [Crossref] [PubMed]
7. Subspecialty Group of Cardiology. the Society of Pediatrics, Chinese Medical Association; Editorial Board, Chinese Journal of Pediatrics. Recommendations for clinical management of Kawasaki disease with coronary artery lesions (2020 revision). Zhonghua Er Ke Za Zhi 2020;58:718-24.
8. Austen WG, Edwards JE, Frye RL, Gensini GG, Gott VL, Griffith LS, McGoon DC, Murphy ML, Roe BB. A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation 1975;51:5-40.
9. de Zorzi A, Colan SD, Gauvreau K, Baker AL, Sundel RP, Newburger JW. Coronary artery dimensions may be misclassified as normal in Kawasaki disease. J Pediatr 1998;133:254-8. [Crossref] [PubMed]
10. Oikonomou EK, Marwan M, Desai MY, Mancio J, Alashi A, Hutt Centeno E, et al. Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data. Lancet 2018;392:929-39. [Crossref] [PubMed]
11. Biradar B, Valakkada J, Ayappan A, Kannath S, Sasidharan B, Alex A. Right coronary artery pericoronary fat attenuation index as a future predictor for acute coronary events in nonobstructive coronary artery disease - a prospective single centre study. Clin Radiol 2025;82:106774. [Crossref] [PubMed]
12. Freeman ML, Hossain MB, Burrowes SAB, Jeudy J, Diaz-Mendez F, Mitchell SE, Prabhu SD, Lederman MM, Bagchi S. Association of T-Cell Phenotypes With Peri-Coronary Inflammation in People With and Without HIV and Without Cardiovascular Disease. Circ Cardiovasc Imaging 2025;18:e017033. [Crossref] [PubMed]
13. Choi YJ, Yang S, West H, Tomlins P, Hoshino M, Murai T, Hwang D, Shin ES, Doh JH, Nam CW, Wang J, Matsuo H, Kakuta T, Antoniades C, Koo BK. Association of coronary inflammation with plaque vulnerability and fractional flow reserve in coronary artery disease. J Cardiovasc Comput Tomogr 2025;19:32-9. [Crossref] [PubMed]
14. Sagris M, Antonopoulos AS, Simantiris S, Oikonomou E, Siasos G, Tsioufis K, Tousoulis D. Pericoronary fat attenuation index-a new imaging biomarker and its diagnostic and prognostic utility: a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging 2022;23:e526-36. [Crossref] [PubMed]
15. Ji L, Ravi S, Wright L, Nguyen V, Wiley J, Vukelic M, Kim S. Psoriasis treatments in the stabilization of atherosclerosis: a systematic review. Arch Dermatol Res 2024;317:159. [Crossref] [PubMed]
16. Hu C, Yan X, Song H, Dong Q, Yi C, Li J, Lv X. Establishment and validation of a nomogram for coronary artery lesions in children with Kawasaki disease. Front Cardiovasc Med 2024;11:1522473. [Crossref] [PubMed]
17. Zhu J, Zhu X, Lv S, Guo D, Li H, Zhao Z. Incremental Value of Pericoronary Adipose Tissue Radiomics Models in Identifying Vulnerable Plaques. J Comput Assist Tomogr 2025;49:422-30. [Crossref] [PubMed]
18. Ye K, Zhang L, Zhou H, Mo X, Shi C. Machine learning-based radiomic features of perivascular adipose tissue in coronary computed tomography angiography predicting inflammation status around atherosclerotic plaque: a retrospective cohort study. Ann Med 2025;57:2431606. [Crossref] [PubMed]
19. Azhe S, Hu L, Zhou Z, Huang S, Chen X, Li X, Fu C, Peng S, Wang C, Zhou K, Guo Y, Wen L. Pericoronary Adipose Tissue CT Attenuation in Kawasaki Disease and Association with Coronary Artery Aneurysms, Myocardial Perfusion, and Coronary Events. Radiol Cardiothorac Imaging 2025;7:e240303. [Crossref] [PubMed]
20. Lu Y, Hu FQ. Elevated Serum IL-17A in Kawasaki Disease Patients Predicts Responsiveness to Intravenous Immunoglobulin Therapy. Int Arch Allergy Immunol 2025;186:159-65. [Crossref] [PubMed]
21. Chen Z, Zeng A, Yang P, Zhang J, Liu D, Li M, Jing F, Yi Q. Role of leukocyte-associated Ig-like receptor-1 in the pathogenesis of Kawasaki disease and coronary artery aneurysms. Immunol Lett 2025;271:106948. [Crossref] [PubMed]
22. Takaki S, Kobayashi T, Kuwabara M, Kato N, Kosami K, Ae R. Coronary artery complications in patients with Kawasaki disease who successfully responded to the standard initial IVIG treatment. Arch Dis Child 2024;109:1029-34. [Crossref] [PubMed]
23. Giryes S, McGonagle D. Immune and non-immune mechanisms that determine vasculitis and coronary artery aneurysm topography in Kawasaki disease and MIS-C. Autoimmun Rev 2023;22:103240. [Crossref] [PubMed]
24. Ishikawa T, Iwashima S. Endothelial dysfunction in children within 5 years after onset of Kawasaki disease. J Pediatr 2013;163:1117-21. [Crossref] [PubMed]
25. Lisi C, Klambauer K, Moser LJ, Mergen V, Manka R, Flohr T, Eberhard M, Alkadhi H. The pericoronary adipose tissue attenuation in CT strongly depends on kernels and iterative reconstructions. Eur Radiol 2025;35:2866-76. [Crossref] [PubMed]
26. Wang AP, Khan H, Dong S, Kim KA, Jone PN, Lee S, Shulman S, Innocentini N, Zielinski T, Rowley AH. Primary Adjunctive Corticosteroids in the Acute Management of High-Risk Kawasaki Disease in a North American Cohort. J Pediatric Infect Dis Soc 2024;13:626-32. [Crossref] [PubMed]
27. Wang X, Shi X, Guo X, Chen S, Lin X, Yang F. Effectiveness of Initial Corticosteroid Treatment in Kawasaki Disease Children Suspected to be IVIG Resistant. Pediatr Cardiol 2025;46:2315-21. [Crossref] [PubMed]
28. Tsuda E, Yoneda S, Asaumi Y, Suzuki A. Cardiac events in Patients in their forties with Kawasaki disease and regression of coronary artery aneurysms. Cardiol Young 2020;30:1821-5. [Crossref] [PubMed]
29. Luo X, Tian J, Li Q, Jin Z, Fan X, Zhang H, Lv H, Ju Y. Development of a liquid chromatography-mass spectrometry based targeted metabolomics method for discovering diagnostic biomarkers in Kawasaki disease. J Chromatogr A 2025;1741:465619. [Crossref] [PubMed]
30. Loy CJ, Servellita V, Sotomayor-Gonzalez A, Bliss A, Lenz JS, Belcher E, et al. Plasma cell-free RNA signatures of inflammatory syndromes in children. Proc Natl Acad Sci U S A 2024;121:e2403897121. [Crossref] [PubMed]
31. Li L, Xu X, Guo Y, Yan Y, Li M, Zhao H, Wang M, Kong Q, Zhao C. C-reactive protein to high density lipoprotein cholesterol ratio for predicting coronary artery lesions, and intravenous immunoglobulin resistance in Kawasaki disease. Pediatr Rheumatol Online J 2025;23:108. [Crossref] [PubMed]
32. Suganuma E, Miura M, Koyama Y, Kobayashi T, Kaneko T, Hokosaki T, Numano F, Furuno K, Shiono J, Fuse S, Fukazawa R, Mitani Y. Regression effect of renin-angiotensin-aldosterone system inhibitors on Kawasaki disease patients with coronary artery aneurysm: a prospective, observational study. Eur J Pediatr 2024;183:4817-25. [Crossref] [PubMed]