Academic radiology · 2026
Coronary Plaque Burden, Distribution, and Perivascular Fat Characteristics in Patients with Diabetes Mellitus: A Coronary CT Angiography Study.
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Xu Xiaoyu, Song Peng, Wei Xiaoxuan, Li Hongpeng, Hu Jing, Tian Xin
Аннотация
BACKGROUND: Comparing coronary plaque distribution, plaque characteristics, and perivascular inflammation between patients with diabetes mellitus (DM) and those without metabolic disease, and further exploring these features across different metabolic phenotypes of DM. In addition, evaluating the performance of fat attenuation index (FAI) measured at different spatial scales in capturing diabetes-related perivascular inflammatory changes.
METHODS: 324 Patients undergoing CCTA were retrospectively enrolled and classified into a DM group and a non-metabolic disease (non-metabolic syndrome) group. The DM group further stratified into four subgroups based on hypertension and hyperlipidemia. We assessed coronary plaque characteristics, CT-derived fractional flow reserve (CT-FFR), and perivascular fat parameters at periplaque, 1 mm, and 2 mm distances. Multivariable logistic regression was used to identify factors independently associated with DM. Generalized estimating equation (GEE) models evaluated plaque distribution across coronary branches, and the interaction between DM and plaque characteristics.
RESULTS: Compared to the non-metabolic syndrome group, patients with DM had higher BMI, hs-CRP, TG, and glucose levels, lower HDL-C and CT-FFR, and higher FAI-2mm distal (all p < 0.05). The association between FAI-2mm distal and DM remained significant after adjustment for systemic inflammatory and metabolic factors. At the patient level, mean and maximum FAI differed between groups at specific distal periplaque regions, whereas FAI of the most-stenotic and highest-risk plaques did not. Among DM phenotypes, periplaque FAI differed significantly, with higher values observed in the isolated-DM and DM-HL-HTN groups than in selected single-comorbidity groups. GEE analysis accounting for patient-level clustering showed that DM was associated with the presence of coronary plaque (p < 0.001), but did not significantly modify its distribution across coronary locations. CT-FFR was significantly associated with FAI values (p<0.05), whereas diabetes status did not significantly modify this association (p>0.05). Napkin-ring sign was associated with higher FAI and showed a significant interaction with diabetes status (p < 0.001).
CONCLUSION: FAI analysis reveals distinct inflammatory patterns and heterogeneity among diabetic phenotypes. Higher perivascular FAI in the coronary segment located 2 mm distal to the plaque was showed in DM patients, while the biological significance of this spatial pattern remains uncertain. Diabetes increased overall coronary plaque burden without altering vessel-specific distribution patterns. Napkin-ring sign was associated with higher FAI and showed a significant interaction with diabetes status.
METHODS: 324 Patients undergoing CCTA were retrospectively enrolled and classified into a DM group and a non-metabolic disease (non-metabolic syndrome) group. The DM group further stratified into four subgroups based on hypertension and hyperlipidemia. We assessed coronary plaque characteristics, CT-derived fractional flow reserve (CT-FFR), and perivascular fat parameters at periplaque, 1 mm, and 2 mm distances. Multivariable logistic regression was used to identify factors independently associated with DM. Generalized estimating equation (GEE) models evaluated plaque distribution across coronary branches, and the interaction between DM and plaque characteristics.
RESULTS: Compared to the non-metabolic syndrome group, patients with DM had higher BMI, hs-CRP, TG, and glucose levels, lower HDL-C and CT-FFR, and higher FAI-2mm distal (all p < 0.05). The association between FAI-2mm distal and DM remained significant after adjustment for systemic inflammatory and metabolic factors. At the patient level, mean and maximum FAI differed between groups at specific distal periplaque regions, whereas FAI of the most-stenotic and highest-risk plaques did not. Among DM phenotypes, periplaque FAI differed significantly, with higher values observed in the isolated-DM and DM-HL-HTN groups than in selected single-comorbidity groups. GEE analysis accounting for patient-level clustering showed that DM was associated with the presence of coronary plaque (p < 0.001), but did not significantly modify its distribution across coronary locations. CT-FFR was significantly associated with FAI values (p<0.05), whereas diabetes status did not significantly modify this association (p>0.05). Napkin-ring sign was associated with higher FAI and showed a significant interaction with diabetes status (p < 0.001).
CONCLUSION: FAI analysis reveals distinct inflammatory patterns and heterogeneity among diabetic phenotypes. Higher perivascular FAI in the coronary segment located 2 mm distal to the plaque was showed in DM patients, while the biological significance of this spatial pattern remains uncertain. Diabetes increased overall coronary plaque burden without altering vessel-specific distribution patterns. Napkin-ring sign was associated with higher FAI and showed a significant interaction with diabetes status.