The predictive value of lesion-specific pericoronary fat attenuation index for major adverse cardiovascular events in patients with type 2 diabetes.

BACKGROUND: The purpose of this study was to explore the prognostic significance of the lesion-specific pericoronary fat attenuation index (FAI) in forecasting major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM). METHODS: This study conducted a retrospective analysis of 304 patients diagnosed with T2DM who underwent coronary computed tomography angiography (CCTA) in our hospital from December 2011 to October 2021. All participants were followed for a period exceeding three years. Detailed clinical data and CCTA imaging features were carefully recorded, encompassing lesion-specific pericoronary FAI, FAI of the three prime coronary arteries, features of high-risk plaques, and the coronary artery calcium score (CACS). The MACE included in the study comprised cardiac death, acute coronary syndrome (which encompasses unstable angina pectoris and myocardial infarction), late-phase coronary revascularization procedures, and hospital admissions prompted by heart failure. RESULTS: Within the three-year follow-up, 76 patients with T2DM suffered from MACE. The lesion-specific pericoronary FAI in patients who experienced MACE was notably higher compared to those without MACE (-84.87 ± 11.36 Hounsfield Units (HU) vs. -88.65 ± 11.89 HU, p = 0.016). Multivariate Cox regression analysis revealed that CACS ≥ 100 (hazard ratio [HR] = 4.071, 95% confidence interval [CI] 2.157-7.683, p < 0.001) and lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.400, 95% CI 1.399-4.120, p = 0.001) were independently associated with heightened risk of MACE in patients with T2DM over a three-year period. Kaplan-Meier analysis showed that patients with higher lesion-specific pericoronary FAI were more likely to develop MACE (p = 0.0023). Additionally, lesions characterized by higher lesion-specific pericoronary FAI values were found to have a greater proportion of high-risk plaques (p = 0.015). Subgroup analysis indicated that lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.017, 95% CI 1.143-3.559, p = 0.015) was independently correlated with MACE in patients with T2DM who have moderate to severe coronary calcification. Moreover, the combination of CACS ≥ 100 and lesion-specific pericoronary FAI>-83.5 HU significantly enhanced the predictive value of MACE in patients with T2DM within 3 years. CONCLUSIONS: The elevated lesion-specific pericoronary FAI emerged as an independent prognostic factor for MACE in patients with T2DM, inclusive of those with moderate to severe coronary artery calcification. Incorporating lesion-specific pericoronary FAI with the CACS provided incremental predictive power for MACE in patients with T2DM.

LncRNA PGM5-AS1 inhibits non-small cell lung cancer progression by targeting miRNA-423-5p/SLIT2 axis.

Non-small cell lung cancer (NSCLC) is a common and aggressive primary malignancy worldwide. Dysregulation of long non-coding RNAs (lncRNAs) has been shown to play an essential regulatory role in multiple cancers. However, the role of PGM5-AS1 in NSCLC remains unclear. Here, we found that PGM5-AS1 was down-regulated in NSCLC tissues and cells. Furthermore, reduced PGM5-AS1 expression levels were associated with larger tumor size, positive lymph node metastasis, advanced TNM stage and worse prognosis. We found that overexpression of PGM5-AS1 inhibited cell proliferation and metastasis, and induced apoptosis and G0/G1 cell cycle arrest in NSCLC cell lines. Using dual luciferase gene reporter and RNA immunoprecipitation assays, we confirmed that miR-423-5p interacted with PGM5-AS1, and that their expression levels were negatively correlated in NSCLC tissues. miR-423-5p was also found to reverse PGM5-AS1-induced malignant biological behavior. Moreover, we identified slit guidance ligand 2 (SLIT2) as a target gene of miR-423-5p. Using a dual luciferase gene reporter assay, we confirmed the regulatory relationship between SLIT2 and miR-423-5p and demonstrated that their expression levels were negatively correlated. Our rescue experiments showed that SLIT2 knockdown reversed miR-423-5p-mediated effects. Overall, this study identifies PGM5-AS1 as a potential prognostic biomarker for NSCLC and shows that PGM5-AS1 suppresses NSCLC development by regulating the miR-423-5p/SLIT2 axis.

A new predictor of coronary artery disease in acute ischemic stroke or transient ischemic attack patients: pericarotid fat density.

OBJECTIVES: The study aims to evaluate the incremental predictive value of pericarotid fat density (PFD) on head and neck computed tomography angiography (CTA) for the obstructive coronary artery disease (CAD) (≥ 50% stenosis) relative to a clinical risk model (Framingham risk score (FRS)) and the degree of carotid artery stenosis and plaque type in acute ischemic stroke (AIS) or transient ischemic attack (TIA) patients without a known history of CAD. METHODS: In a cohort of 134 consecutive stable patients diagnosed with AIS or TIA undergoing head and neck CTA between January 2010 and December 2021, pericarotid adipose tissue density (PFD) was quantified using a dedicated software. We collected demographic and clinical data, assessed the risk of CAD using the FRS, and analyzed coronary and carotid artery CTA images. Univariate and multivariate logistic regression analyses were performed to assess associations between FRS, PFD, CTA variables, and obstructive CAD risk. Four prediction models were established to evaluate the incremental predictive value of PFD relative to FRS, stenosis degree, and plaque types. Receiver operating characteristic (ROC) curves were generated, and the areas under the curves (AUC) were compared. RESULTS: Increasing FRS, stenosis degree, and PFD values were positively correlated with obstructive CAD (all p < 0.05). In the predictive models for obstructive CAD, the model incorporating carotid stenosis exhibited superior predictive performance compared to FRS alone (p < 0.05). Moreover, the predictive model integrating PFD demonstrated enhanced performance and yielded the highest AUC of the receiver operator characteristic curve (AUC = 0.783), with sensitivity and specificity values of 86.89% and 65.75%, respectively. CONCLUSION: CTA-derived PFD measurements offer supplementary predictive value for obstructive CAD beyond FRS and stenosis, thereby facilitating improved risk stratification of TIA or stroke patients without a history of CAD history. CLINICAL RELEVANCE STATEMENT: CTA-derived PFD provides incremental predictive value for obstructive coronary artery disease in acute ischemic stroke or transient ischemic attack patients without CAD history, beyond Framingham risk score and carotid artery stenosis degree, improving risk stratification. KEY POINTS: • Pericarotid fat density is associated with obstructive coronary artery disease in acute ischemic stroke or transient ischemic attack patients. • Higher pericarotid fat density corresponds to an increased risk of obstructive coronary artery disease. • Estimation of pericarotid fat density using computed tomography angiography imparts additional predictive value for obstructive CAD in risk stratification of acute ischemic stroke or transient ischemic attack patients.

Incremental diagnostic value of radiomics signature of pericoronary adipose tissue for detecting functional myocardial ischemia: a multicenter study.

OBJECTIVES: To determine the incremental diagnostic value of radiomics signature of pericoronary adipose tissue (PCAT) in addition to the coronary artery stenosis and plaque characters for detecting hemodynamic significant coronary artery disease (CAD) based on coronary computed tomography angiography (CCTA). METHODS: In a multicenter trial of 262 patients, CCTA and invasive coronary angiography were performed, with fractional flow reserve (FFR) in 306 vessels. A total of 13 conventional quantitative characteristics including plaque characteristics (N = 10) and epicardial adipose tissue characteristics (N = 3) were obtained. A total of 106 radiomics features depicting the phenotype of the PCAT surrounding the lesion were calculated. All data were randomly split into a training dataset (75%) and a testing dataset (25%). Then three models (including the conventional model, the PCAT radiomics model, and the combined model) were established in the training dataset using multivariate logistic regression algorithm based on the conventional quantitative features and the PCAT radiomics features after dimension reduction. RESULTS: A total of 124/306 vessels showed functional ischemia (FFR ≤ 0.80). The radiomics model performed better in discriminating ischemia from non-ischemia than the conventional model in both training (area under the receiver operating characteristic (ROC) curve (AUC): 0.770 vs 0.732, p < 0.05) and testing datasets (AUC: 0.740 vs 0.696, p < 0.05). The combined model showed significantly better discrimination than the conventional model in both training (AUC: 0.810 vs 0.732, p < 0.05) and testing datasets (AUC: 0.809 vs 0.696, p < 0.05). CONCLUSIONS: The PCAT radiomics model showed good performance in predicting myocardial ischemia. Addition of PCAT radiomics to lesion quantitative characteristics improves the predictive power of functionally relevant CAD. KEY POINTS: • Based on the plaque characteristics and EAT characteristics, the conventional model showed poor performance in predicting myocardial ischemia. • The PCAT radiomics model showed good prospect in predicting myocardial ischemia. • When combining the radiomics signature with the conventional quantitative features (including plaque features and EAT features), it showed significantly better performance in predicting myocardial ischemia.

Prediction of acute coronary syndrome within 3 years using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography.

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.

The prognostic value of late gadolinium enhancement in heart diseases: an umbrella review of meta-analyses of observational studies.

OBJECTIVES: Cardiac magnetic resonance imaging (CMR) has proven itself as an accurate and robust diagnostic approach and has been widely used in the detection of various heart diseases. An increasing number of studies focusing more on the prognostic aspect of LGE-CMR arose in recent years, contributing to the redundant systematic reviews and meta-analyses in this field. By providing a bird's eye view and performing scrupulous evidence rating, this umbrella review aims to help clinical practitioners and policy-makers interpret the results of the meta-analyses on the prognostic role of late gadolinium enhancement (LGE) in patients with heart diseases. METHODS: An umbrella review of meta-analyses of observational studies. RESULTS: The 11 included systematic reviews comprise 33 meta-analyses covering 11 types of heart diseases, 19 different outcomes, 23,058 subjects, and 5393 events. Thirty-one of 33 meta-analyses were found supported by weak pieces of evidence and the remaining were deemed not suggestive. The meta-analysis with a p value of 9.21 × 10-15 and 991 events was updated by strictly re-conducting the meta-analysis by Becker et al. The updated meta-analysis on the prognostic role of LGE in subjects with non-ischemic dilated cardiomyopathy (DCM) in terms of major adverse cardiovascular events (MACE) included 1131 events and was rated as highly suggestive evidence. CONCLUSIONS: The prognostic role of LGE in DCM patients in terms of MACE is supported by highly suggestive evidence, which may facilitate the optimization of the timing of prophylactic implantable or wearable implantable cardioverter-defibrillators (ICD) considering the high risk of MACE and lower expectation of recovery. KEY POINTS: • Cardiac magnetic resonance imaging (CMR) has been widely used in the detection of various heart diseases. Numerous studies focusing on the prognostic aspect of LGE arose in recent years. • The meta-analysis on the prognostic role of LGE in dilated cardiomyopathy (DCM) patients in terms of major adverse cardiovascular events (MACE) by Becker et al was updated and was deemed to be supported by highly suggestive evidence. • The credibility of the meta-analysis supported by highly suggestive evidence may facilitate the optimization of the timing of prophylactic implantable or wearable implantable cardioverter defibrillators (ICD) considering the high risk of MACE and lower expectation of recovery.

Evolutionary Dynamics Optimal Research-Oriented Tumor Immunity Architecture.

The article is devoted to evolutionary dynamics optimal control-oriented tumor immune differential game system. First, the mathematical model covering immune cells and tumor cells considering the effects of chemotherapy drugs and immune agents. Second, the bounded optimal control problem covering is transformed into solving Hamilton-Jacobi-Bellman (HJB) equation considering the actual constraints and infinite-horizon performance index based on minimizing the amount of medication administered. Finally, approximate optimal control strategy is acquired through iterative-dual heuristic dynamic programming (I-DHP) algorithm avoiding dimensional disaster effectively and providing optimal treatment scheme for clinical applications.

Associations between the serum triglyceride-glucose index and pericoronary adipose tissue attenuation and plaque features using dual-layer spectral detector computed tomography: a cross-sectional study.

Background and aims: The triglyceride-glucose (TyG) index is a reliable alternative marker for insulin resistance (IR). Pericoronary adipose tissue (PCAT) can indirectly reflect coronary inflammation. IR and coronary inflammation play a key role in the development and progression of coronary atherosclerosis. Therefore, this study investigated the relationships between the TyG index, PCAT and atherosclerotic plaque characteristics to explore whether IR might lead to coronary artery atherosclerosis progression by inducing coronary inflammation. Methods: We retrospectively collected data on patients with chest pain who underwent coronary computed tomography angiography using spectral detector computed tomography at our institution from June to December 2021. The patients were grouped based on their TyG index levels: T1 (low), T2 (medium), and T3 (high). Each patient was assessed for total plaque volume, plaque load, maximum stenosis, the plaque component volume proportion, high-risk plaques(HRPs), and plaque characteristics (including low attenuation plaques, positive remodeling, a napkin ring sign, and spot calcification). PCAT quantification was performed on the proximal right coronary artery using the fat attenuation index (FAI) measured from a conventional multicolor computed tomography image (FAI120kVp), a spectral virtual single-energy image (FAI40keV), and the slope of the spectral HU curve (λHU). Results: We enrolled 201 patients. The proportion of patients with maximum plaque stenosis, positive remodeling, low-density plaques, and HRPs increased as the TyG index level increased. Moreover, the FAI40keV and λHU significantly differed among the three groups, and we identified good positive correlations between FAI40keV and λHU and the TyG index (r = 0.319, P <0.01 and r = 0.325, P <0.01, respectively). FAI120kVp did not significantly differ among the groups. FAI40keV had the highest area under the curve, with an optimal cutoff value of -130.5 HU for predicting a TyG index value of ≥9.13. The multivariate linear regression analysis demonstrated that FAI40keV and λHU were independently positively related to a high TyG index level (standardized regression coefficients: 0.117 [P <0.001] and 0.134 [P <0.001], respectively). Conclusions: Patients with chest pain and a higher TyG index level were more likely to have severe stenosis and HRPs. Moreover, FAI40keV and λHU had good correlations with the serum TyG index, which may noninvasively reflect PCAT inflammation under insulin resistance. These results could help explain the mechanism of plaque progression and instability in patients with insulin resistance might be related to IR-induced coronary inflammation.

Incremental Prognostic Value of Pericoronary Adipose Tissue Thickness Measured Using Cardiac Magnetic Resonance Imaging After Revascularization in Patients With ST-Elevation Myocardial Infarction.

Background and Aim: Pericoronary adipose tissue (PCAT) reflects pericoronary inflammation and is associated with coronary artery disease. We aimed to identify the association between local PCTA thickness using cardiac magnetic resonance (CMR) and prognosis of patients with ST-elevation myocardial infarction (STEMI), and to investigate the incremental prognostic value of PCAT thickness in STEMI after reperfusion. Methods: A total of 245 patients with STEMI (mean age, 55.61 ± 10.52 years) who underwent CMR imaging within 1 week of percutaneous coronary intervention therapy and 35 matched controls (mean age, 53.89 ± 9.45 years) were enrolled. PCAT thickness indexed to body surface area at five locations, ventricular volume and function, infarct-related parameters, and global strain indices were evaluated using CMR. Associations between PCAT thickness index and 1-year major adverse cardiovascular events (MACE) after STEMI were calculated. The prognostic value of the standard model based on features of clinical and CMR and updated model including PACT thickness index were further assessed. Results: Patients with MACE had a more significant increase in PCAT thickness index at superior interventricular groove (SIVGi) than patients without MACE. The SIVGi was significantly associated with left ventricular ejection fraction (LVEF), infarct size, and global deformation. SIVGi > 4.98 mm/m2 was an independent predictor of MACE (hazard ratio, 3.2; 95% CI: 1.6-6.38; p < 0.001). The updated model significantly improved the power of prediction and had better discrimination ability than that of the standard model for predicting 1-year MACE (areas under the ROC curve [AUC] = 0.8 [95% CI: 0.74-0.87] vs. AUC = 0.76 [95% CI: 0.68-0.83], p < 0.05; category-free net reclassification index [cfNRI] = 0.38 [95% CI: 0.1-0.53, p = 0.01]; integrated discrimination improvement [IDI] = 0.09 [95% CI: 0.01-0.18, p = 0.02]). Conclusions: This study demonstrated SIVGi as an independent predictor conferred incremental value over standard model based on clinical and CMR factors in 1-year MACE predictions for STEMI.

Association of Pericoronary Adipose Tissue Quality Determined by Dual-Layer Spectral Detector CT With Severity of Coronary Artery Disease: A Preliminary Study.

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 < 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.

Pericoronary adipose tissue attenuation assessed by dual-layer spectral detector computed tomography is a sensitive imaging marker of high-risk plaques.

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 (CTpoly), virtual mono-energetic images at 40 keV (CT40 keV), the slope of spectral attenuation curve (λHU), and the effective atomic number (Zeff). 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 non-high-risk plaques, especially CT40 keV [-153.76±24.97 (non-high-risk plaque) vs. -119.87±22.74 (high-risk plaque), P<0.001]. CT40 keV was a predictive factor of high-risk plaques, and high CT40 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 CT40 keV may provide a novel imaging marker of plaque vulnerability.

Evaluation of Altered Glutamatergic Activity in a Piglet Model of Hypoxic-Ischemic Brain Damage Using 1H-MRS.

METHODS: Twenty-five newborn piglets were selected and then randomly assigned to the control group (n = 5) and the model group (n = 20) subjected to HI. HI was induced by blocking bilateral carotid blood flow under simultaneous inhalation of a 6% oxygen mixture. 1H-MRS data were acquired from the basal ganglia at the following time points after HI: 6, 12, 24, and 72 h. Changes in protein levels of EAAT2 and GluR2 were determined by immunohistochemical analysis. Correlations among metabolite concentrations, metabolite ratios, and the protein levels of EAAT2 and GluR2 were investigated. RESULTS: The Glu level sharply increased after HI, reached a transient low level of depletion that approached the normal level in the control group, and subsequently increased again. Negative correlations were found between concentrations of Glu and EAAT2 protein levels (R s = -0.662, P < 0.001) and between the Glu/creatine (Cr) ratio and EAAT2 protein level (R s = -0.664, P < 0.001). Moreover, changes in GluR2 protein level were significantly and negatively correlated with those in Glu level (the absolute Glu concentration, R s = -0.797, P < 0.001; Glu/Cr, R s = -0.567, P = 0.003). CONCLUSIONS: Changes in Glu level measured by 1H-MRS were inversely correlated with those in EAAT2 and GluR2 protein levels following HI, and the results demonstrated that 1H-MRS can reflect the early changes of glutamatergic activity in vivo.

Early Changes in Glutamate Metabolism and Perfusion in Basal Ganglia following Hypoxia-Ischemia in Neonatal Piglets: A Multi-Sequence 3.0T MR Study.

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.