Background: The pericoronary fat attenuation index (FAI) derived from conventional polychromatic computed tomography (CT) can capture the presence of coronary inflammation. However, conventional polychromatic CT has limitations in material component differentiation, and spectral CT could have a better ability to discriminate tissue characteristics. Hence, this study sought to assess pericoronary adipose tissue (PCAT) attenuation using spectral CT and explore its association with atherosclerotic plaque characteristics.Methods: We enrolled 104 patients with coronary atherosclerosis who met the inclusion criteria and underwent coronary CT angiography with dual-layer spectral detector computed tomography (SDCT).Plaque anatomical characteristics were measured, and the PCAT attenuation was assessed by polychromatic images (CT poly ), virtual mono-energetic images at 40 keV (CT 40 keV ), the slope of spectral attenuation curve (λ HU ), and the effective atomic number (Z eff ). The association of PCAT attenuation indicators with the presence of high-risk plaques was analyzed, along with the indicators' ability to identify high-risk plaques.Results: PCAT attenuation indicators around high-risk plaques were higher than those around nonhigh-risk plaques, especially CT 40 keV [−153.76±24.97 (non-high-risk plaque) vs. −119.87±22.74 (high-risk plaque), P<0.001]. CT 40 keV was a predictive factor of high-risk plaques, and high CT 40 keV (≥−120.60 HU) could assist in the identification of high-risk plaques, with an area under the curve of 0.883 (95% CI: 0.83-0.94, P<0.05).Conclusions: PCAT surrounding high-risk plaques showed higher attenuation; a finding that has been associated with coronary artery inflammation. The metrics derived from SDCT, especially CT40 keV , showed higher discriminatory power for detecting changes in PCAT attenuation than polychromatic CT. PCAT attenuation assessed by CT 40 keV may provide a novel imaging marker of plaque vulnerability.

Objectives To evaluate whether radiomics signature of pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could improve the prediction of future acute coronary syndrome (ACS) within 3 years. Methods We designed a retrospective case-control study that patients with ACS (n = 90) were well matched to patients with no cardiac events (n = 1496) during 3 years follow-up, then which were randomly divided into training and test datasets with a ratio of 3:1. A total of 107 radiomics features were extracted from PCAT surrounding lesions and 14 conventional plaque characteristics were analyzed. Radiomics score, plaque score, and integrated score were respectively calculated via a linear combination of the selected features, and their performance was evaluated with discrimination, calibration, and clinical application. Results Radiomics score achieved superior performance in identifying patients with future ACS within 3 years in both training and test datasets (AUC = 0.826, 0.811) compared with plaque score (AUC = 0.699, 0.640), with a significant difference of AUC between two scores in the training dataset (p = 0.009); while the improvement of integrated score discriminating capability (AUC = 0.838, 0.826) was non-significant. The calibration curves of three predictive models demonstrated a good fitness respectively (all p > 0.05). Decision curve analysis suggested that integrated score added more clinical benefit than plaque score. Stratified analysis revealed that the performance of three predictive models was not affected by tube voltage, CT version, different sites of hospital. Conclusion CCTA-based radiomics signature of PCAT could have the potential to predict the occurrence of subsequent ACS. Radiomics-based integrated score significantly outperformed plaque score in identifying future ACS within 3 years. Key Points • Plaque score based on conventional plaque characteristics had certain limitations in the prediction of ACS. • Radiomics signature of PCAT surrounding plaques could have the potential to improve the predictive ability of subsequent ACS. • Radiomics-based integrated score significantly outperformed plaque score in the identification of future ACS within 3 years.

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Background: Pericoronary adipose tissue (PCAT) is considered as a source of inflammatory mediators, leading to the development of coronary atherosclerosis. The study aimed to investigate the correlation between PCAT quality derived from dual-layer spectral detector CT (SDCT) and the severity of coronary artery disease (CAD), and whether PCAT parameters were independently associated with the presence of CAD.Materials and Methods: A total of 403 patients with symptoms of chest pain who underwent SDCT were included. PCAT quality including fat attenuation index (FAI) measured from conventional polychromatic CT images (FAI120kvp) and spectral virtual mono-energetic images at 40 keV (FAI40keV), slope of spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured around the lesions representing the maximal degree of vascular stenosis in each patient. Meanwhile, overall epicardial adipose tissue (EAT) attenuation was acquired in the conventional polychromatic energy imaging.Results: FAI40keV, λHU, Eff-Z, and FAI120kvp increased along with the degree of CAD in general and were superior to the overall EAT attenuation for detecting the presence of CAD. Multivariate logistic regression analysis indicated that FAI40keV was the most powerful independent indicator (odds ratio 1.058, 95% CI 1.044–1.073; p &lt; 0.001) of CAD among these parameters. Using an optimal cut-off (−131.8 HU), FAI40keV showed higher diagnostic accuracy of 80.6% compared with the other parameters.Conclusions: These preliminary findings suggest that FAI40keV on SDCT may be an appealing surrogate maker to allow monitoring of PCAT changes in the development of CAD.

The excitotoxicity of glutamate metabolism as well as hemodynamic disorders of the brain are both risk factors for neonatal hypoxic–ischemic brain damage (HIBD). In the present study, changes in glutamate metabolism in the basal ganglia were detected by proton magnetic resonance spectroscopy (1H-MRS) at 0–6, 8–12, 24–30, and 48–60 h after the induction of hypoxia-ischemia (HI) in newborn piglets. Meanwhile, correlation analysis was performed by combining the microcirculatory perfusion informations acquired by intravoxel incoherent motion (IVIM) scan to explore their possible interaction mechanism. The results suggested that Glu level in the basal ganglia underwent a “two-phase” change after HI; perfusion fraction f, an IVIM-derived perfusion parameter, was clearly decreased in the early stage after HI, then demonstrated a transient and slight recovery process, and thereafter continued to decrease. The changes in f and Glu level were in a significant negative correlation (r = −0.643, P = 0.001). Our study results revealed that Glu level is closely associated with the microcirculatory perfusion changes in the acute stage of HIBD.