The changes of coagulation profiles in Kawasaki disease and its associations with clinical classification, intravenous immunoglobulin responsiveness and coronary artery involvement.

Coagulation disorders are common in Kawasaki disease (KD). The main objectives of the present study were to probe the associations of coagulation profiles with clinical classification, IVIG responsiveness, coronary artery abnormalities (CAAs) in the acute episode of KD. A total of 313 KD children were recruited and divided into six subgroups, including complete KD (n = 217), incomplete KD (n = 96), IVIG-responsive KD (n = 293), IVIG-nonresponsive KD (n = 20), coronary artery noninvolvement KD (n = 284) and coronary artery involvement KD (n = 29). Blood samples were collected within 24-h pre-IVIG therapy and 48-h post-IVIG therapy. Coagulation profiles, conventional inflammatory mediators and blood cell counts were detected. Echocardiography was performed during the period from 2- to 14-day post-IVIG infusion. In addition, 315 sex- and age-matched healthy children were enrolled as the controls. (1) Before IVIG therapy, coagulation disorders were more prone to appear in KD patients than in healthy controls, and could be overcome by IVIG therapy. FIB and DD significantly increased in the acute phase of KD, whereas reduced to normal levels after IVIG therapy. (2) PT and APTT were significantly longer in patients with complete KD when compared with their incomplete counterparts after IVIG therapy. (3) The larger δDD, δFDP and the smaller δPT, δINR predicted IVIG nonresponsiveness. (4) The higher δDD and δFDP correlated with a higher risk for CAAs (DD: r = -0.72, FDP: r = -0.54). Coagulation disorders are correlated with complete phenotype, IVIG nonresponsiveness and CAA occurrence in the acute episode of KD, and can be rectified by synergistic effects of IVIG and aspirin.

Association of remnant cholesterol with coronary artery ectasia: a cross-sectional study.

OBJECTIVE: Coronary artery ectasia (CAE) is a condition characterized by the localized or widespread dilation of one or more coronary arteries. The majority of CAE patients do not present with clinical symptoms, and the exact cause of CAE remains unclear. Therefore, a retrospective analysis was conducted to explore the potential causes of CAE. METHODS: This study was a retrospective analysis of patients who underwent coronary angiography at Guangdong Provincial People's Hospital between January 2017 and July 2022, of whom 679 patients were ultimately enrolled in the study. Among them, 260 patients were diagnosed with CAE, whereas 419 patients with normal coronary results composed the control group. Remnant cholesterol (RC) was calculated as total cholesterol (TC) minus high-density lipoprotein cholesterol (HDL-C) minus low-density lipoprotein cholesterol (LDL-C). The association between RC levels and the risk of CAE was assessed via multivariable logistic models. RESULTS: Out of the 679 patients who participated in this study, with an average age of 59.9 years, 38.3% were diagnosed with CAE. Patients with CAE had higher RC levels than did those without CAE (P = 0.001). A significant positive association was observed between RC levels and the risk of CAE, with a multivariable adjusted odds ratio (OR) of 1.950 (95% confidence interval [CI]: 1.163-3.270). There was a significant positive association between RC levels and the risk of CAE in both single-vessel and multivessel dilation cases, as well as in isolated CAE and dilation secondary to coronary atherosclerosis. According to the subgroup analyses, RC levels were positively associated with the risk of CAE in participants with hypertension (OR, 1.065; 95% CI, 1.034-1.098). CONCLUSION: RC levels are positively correlated with CAE, implying that a focus on RC could be beneficial in CAE research.

Effective descriptor extraction strategies for correspondence matching in coronary angiography images.

The importance of 3D reconstruction of coronary arteries using multiple coronary angiography (CAG) images has been increasingly recognized in the field of cardiovascular disease management. This process relies on the camera matrix's optimization, needing correspondence info for identical point positions across two images. Therefore, an automatic method for determining correspondence between two CAG images is highly desirable. Despite this need, there is a paucity of research focusing on image matching in the CAG images. Additionally, standard deep learning image matching techniques often degrade due to unique features and noise in CAG images. This study aims to fill this gap by applying a deep learning-based image matching method specifically tailored for the CAG images. We have improved the structure of our point detector and redesigned loss function to better handle sparse labeling and indistinct local features specific to CAG images. Our method include changes to training loss and introduction of a multi-head descriptor structure leading to an approximate 6% improvement. We anticipate that our work will provide valuable insights into adapting techniques from general domains to more specialized ones like medical imaging and serve as an improved benchmark for future endeavors in X-ray image-based correspondence matching.

Anomalous Right Coronary Artery From Pulmonary Artery Presenting as Inferior Wall Ischemia: A Case Report.

We illustrate the case of a 62-year-old man with a symptomatic anomalous right coronary artery from pulmonary artery (ARCAPA). Our patient had presented with dyspnea on exertion with electrocardiogram showing pronounced inferior Q waves and marked inferolateral ST-T wave changes. The patient had a nuclear stress test which showed inferior wall ischemia. Subsequently, the patient underwent coronary angiography which showed an ARCAPA. The patient underwent surgical repair with reimplantation of the right coronary artery to the ascending aorta which was tolerated well. Our case illustrates ARCAPA presenting late in adulthood with ischemic symptoms that was treated with corrective surgery.

Ultrasound enhancing agents in cardiovascular imaging: expanding horizons beyond coronary arteries.

From its inception as a two-dimensional snapshot of the beating heart, echocardiography has become an indelible part of cardiovascular diagnostics. The integration of ultrasound enhancing agents (UEAs) marks a pivotal transition, enhancing its diagnostic acumen beyond myocardial perfusion. These agents have refined echocardiography's capacity to visualize complex cardiac anatomy and pathology with unprecedented clarity, especially in non-coronary artery disease contexts. UEAs aid in detailed assessments of myocardial viability, endocardial border delineation in left ventricular opacification, and identification of intracardiac masses. Recent innovations in UEAs, accompanied by advancements in echocardiographic technology, offer clinicians a more nuanced view of cardiac function and blood flow dynamics. This review explores recent developments in these applications and future contemplated studies.

Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.

BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disease risk stratification and predictive modeling. HYPOTHESIS: ML models based on optical coherence tomography (OCT) imaging, laboratory tests, and clinical characteristics can predict the occurrence of SM. METHODS: We studied 337 patients from the Affiliated Hospital of Zunyi Medical University, China, who had PCI and coronary OCT from May to October 2023. We employed nested cross-validation to partition patients into training and test sets. We developed five ML models: XGBoost, LR, RF, SVM, and NB based on calcification features. Performance was assessed using ROC curves. Lasso regression selected features from 46 clinical and 21 OCT imaging features, which were optimized with the five ML algorithms. RESULTS: In the prediction model based on calcification features, the XGBoost model and SVM model exhibited higher AUC values. Lasso regression identified five key features from clinical and imaging data. After incorporating selected features into the model for optimization, the AUC values of all algorithmic models showed significant improvements. The XGBoost model demonstrated the highest calibration accuracy. SHAP values revealed that the top five ranked features influencing the XGBoost model were calcification length, age, coronary dissection, lipid angle, and troponin. CONCLUSION: ML models developed using plaque imaging features and clinical characteristics can predict the occurrence of SM. ML models based on clinical and imaging features exhibited better performance.

Impact of morphofunctional assessment with quantitative flow ratio and optical coherence tomography in patients with acute coronary syndromes.

BACKGROUND: Combining morphological and physiological evaluations might improve the risk stratification of patients who undergo percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS) culprit lesions. AIMS: We aimed to investigate the clinical utility of morphofunctional evaluation after PCI for identifying ACS patients with increased risk of subsequent clinical events. METHODS: We retrospectively studied 298 consecutive ACS patients who had undergone optical coherence tomography (OCT)-guided PCI. We performed OCT-based morphological analysis and quantitative flow ratio (QFR)-based physiological assessment immediately after PCI. The non-culprit segment (NCS) was defined as the most stenotic untreated segment in the culprit vessel. The primary outcome was target vessel failure (TVF), a composite of cardiac death, target vessel-related myocardial infarction, and ischaemia-driven target vessel revascularisation. RESULTS: During a median follow-up period of 990 days, 42 patients experienced TVF. Cox regression analysis revealed that the presence of thin-cap fibroatheroma (TCFA) in the NCS and a low post-PCI QFR, or the presence of TCFA in the NCS and a high ΔQFR in the NCS (QFRNCS), were independently associated with TVF. The subgroup with TCFA in the NCS and a low post-PCI QFR had a significantly higher incidence of TVF (75%) than the other subgroups, and those with TCFA in the NCS and a high ΔQFRNCS had a significantly higher incidence of TVF (86%) than the other subgroups. The integration of TCFA in NCS, post-PCI QFR, and ΔQFRNCS with traditional risk factors significantly enhanced the identification of subsequent TVF cases. CONCLUSIONS: Combining post-PCI OCT and QFR evaluation may enhance risk stratification for ACS patients after successful PCI, particularly in predicting subsequent TVF.

Prevalence, Clinical Features, Treatment, and Outcomes in Patients With Myocardial Infarction With Non-Obstructive Coronary Arteries.

AIM: To study clinical and demographic characteristics, treatment options, and clinical outcomes in patients with myocardial infarction with non-obstructive coronary arteries (MINOCA) compared with patients with myocardial infarction with obstructive coronary arteries (MIOCA). MATERIAL AND METHODS: This single-center prospective observational study included 712 successive patients diagnosed with acute myocardial infarction (MI), who routinely underwent direct coronary angiography. Based on the presence of stenosing coronary atherosclerosis, the patients were divided into two groups: MIOCA (coronary stenosis ≥50%) and MINOCA (coronary stenosis <50% without other, alternative causes). Clinical outcomes included in-hospital and long-term overall mortality, and cardiovascular rehospitalization. The median follow-up was 1.5 years. RESULTS: MINOCA was diagnosed in 73 (10.3%) patients, 37 (50%) of whom were women. The median age of patients with MINOCA was 61 years and in the MIOCA group 65 years. No significant differences in cardiovascular risk factors were found between patients with MINOCA and MIOCA. In 53.4% of cases, the cause of MINOCA was a discrepancy between the myocardial oxygen demand and supply, and in 35.6% of cases, the cause was hypertensive crisis and pulmonary edema. The factors associated with MINOCA included an age ≤58 years, female gender, absence of the ST-segment elevation, absence of areas of impaired local contractility, and presence of aortic stenosis and bronchopulmonary infection. Patients with MINOCA were less likely to be prescribed acetylsalicylic acid, P2Y12 inhibitors, dual antiplatelet therapy, beta-blockers, and statins (p<0.05). Data on long-term outcomes were available for 87.5% of patients (n=623). The prognosis of patients with MIOCA was comparable for in-hospital mortality (1.5% vs. 6.2%; p=0.161) and long-term overall mortality (6.1% vs. 14.7%; p=0.059). Cardiovascular rehospitalizations were more frequent in the MINOCA group (33.3% vs. 21.5%; p=0.042). CONCLUSION: The prevalence of MINOCA in our study was 10.3% among all patients with acute MI. MINOCA patients had comparable generally recognized cardiovascular risk factors with MIOCA patients. MINOCA patients had a comparable prognosis for in-hospital and long-term mortality and more often required cardiovascular rehospitalization.

Improving cardiovascular risk prediction with machine learning: a focus on perivascular adipose tissue characteristics.

BACKGROUND: Timely prevention of major adverse cardiovascular events (MACEs) is imperative for reducing cardiovascular diseases-related mortality. Perivascular adipose tissue (PVAT), the adipose tissue surrounding coronary arteries, has attracted increased amounts of attention. Developing a model for predicting the incidence of MACE utilizing machine learning (ML) integrating clinical and PVAT features may facilitate targeted preventive interventions and improve patient outcomes. METHODS: From January 2017 to December 2019, we analyzed a cohort of 1077 individuals who underwent coronary CT scanning at our facility. Clinical features were collected alongside imaging features, such as coronary artery calcium (CAC) scores and perivascular adipose tissue (PVAT) characteristics. Logistic regression (LR), Framingham Risk Score, and ML algorithms were employed for MACE prediction. RESULTS: We screened seven critical features to improve the practicability of the model. MACE patients tended to be older, smokers, and hypertensive. Imaging biomarkers such as CAC scores and PVAT characteristics differed significantly between patients with and without a 3-year MACE risk in a population that did not exhibit disparities in laboratory results. The ensemble model, which leverages multiple ML algorithms, demonstrated superior predictive performance compared with the other models. Finally, the ensemble model was used for risk stratification prediction to explore its clinical application value. CONCLUSIONS: The developed ensemble model effectively predicted MACE incidence based on clinical and imaging features, highlighting the potential of ML algorithms in cardiovascular risk prediction and personalized medicine. Early identification of high-risk patients may facilitate targeted preventive interventions and improve patient outcomes.

Smoking paradox in coronary function and structure of acute ST-segment elevation myocardial infarction patients treated with primary percutaneous coronary intervention.

BACKGROUND: The Smoking paradox has generated inconsistent findings concerning the clinical prognosis of acute ST-segment elevation myocardial infarction (STEMI) patients, while providing limited insights into coronary anatomy and function which are crucial prognostic factors. Therefore, this study aimed to further investigate the existence of smoking paradox in coronary anatomy and function. METHODS: This study divided STEMI patients into smokers and non-smokers. Quantitative coronary angiography, angiography­derived microcirculatory resistance (AMR) and quantitative flow ratio (QFR) were utilized to analyze coronary anatomy and function. These parameters were compared using multivariable analysis and propensity score matching. The clinical outcomes were evaluated using Kaplan-Meier curve and Cox regression. RESULTS: The study included 1258 patients, with 730 in non-smoker group and 528 in smoker group. Smokers were significantly younger, predominantly male, and had fewer comorbidities. Without adjusting for confounders, smokers exhibited larger lumen diameter [2.03(1.45-2.57) vs. 1.90(1.37-2.49), P = 0.033] and lower AMR [244(212-288) vs. 260(218-301), P = 0.006]. After matching and multivariate adjustment, smokers exhibited inversely smaller lumen diameter [1.97(1.38-2.50) vs. 2.15(1.63-2.60), P = 0.002] and higher incidence of coronary microvascular dysfunction [233(53.9%) vs. 190(43.6%), P = 0.002], but showed similar AMR and clinical outcomes compared to non-smokers. There was no difference in QFR between two groups. CONCLUSION: Smoking among STEMI patients undergoing pPCI was associated with smaller lumen diameter and higher occurrence of coronary microvascular dysfunction, although it had no further impact on clinical prognosis. The smoking paradox observed in coronary anatomy or function may be explained by younger age, gender, and lower prevalence of comorbidities.

Coronary Plaque Characterization with T1-weighted MRI and Near-Infrared Spectroscopy to Predict Periprocedural Myocardial Injury.

Purpose To clarify the predominant causative plaque constituent for periprocedural myocardial injury (PMI) following percutaneous coronary intervention: (a) erythrocyte-derived materials, indicated by a high plaque-to-myocardium signal intensity ratio (PMR) at coronary atherosclerosis T1-weighted characterization (CATCH) MRI, or (b) lipids, represented by a high maximum 4-mm lipid core burden index (maxLCBI4 mm) at near-infrared spectroscopy intravascular US (NIRS-IVUS). Materials and Methods This retrospective study included consecutive patients who underwent CATCH MRI before elective NIRS-IVUS-guided percutaneous coronary intervention at two facilities. PMI was defined as post-percutaneous coronary intervention troponin T values greater than five times the upper reference limit. Multivariable analysis was performed to identify predictors of PMI. Finally, the predictive capabilities of MRI, NIRS-IVUS, and their combination were compared. Results A total of 103 lesions from 103 patients (median age, 72 years [IQR, 64-78]; 78 male patients) were included. PMI occurred in 36 lesions. In multivariable analysis, PMR emerged as the strongest predictor (P = .001), whereas maxLCBI4 mm was not a significant predictor (P = .07). When PMR was excluded from the analysis, maxLCBI4 mm emerged as the sole independent predictor (P = .02). The combination of MRI and NIRS-IVUS yielded the largest area under the receiver operating curve (0.86 [95% CI: 0.64, 0.83]), surpassing that of NIRS-IVUS alone (0.75 [95% CI: 0.64, 0.83]; P = .02) or MRI alone (0.80 [95% CI: 0.68, 0.88]; P = .30). Conclusion Erythrocyte-derived materials in plaques, represented by a high PMR at CATCH MRI, were strongly associated with PMI independent of lipids. MRI may play a crucial role in predicting PMI by offering unique pathologic insights into plaques, distinct from those provided by NIRS. Keywords: Coronary Plaque, Periprocedural Myocardial Injury, MRI, Near-Infrared Spectroscopy Intravascular US Supplemental material is available for this article. © RSNA, 2024.

Coronary Angiography During Ex-Situ Heart Perfusion in a Porcine Model.

Heart transplantation is the gold standard treatment for advanced heart failure. The procurement of extended criteria donors (ECD) increases due to the current organ shortage. Coronary angiography is recommended in ECD at risk for coronary artery disease but is not systematically performed. These hearts are, therefore, either declined for transplant or procured without screening for coronary artery disease. Coronary angiography during normothermic ex-situ heart perfusion (NESP) could be an interesting approach to enhance the rate of ECD procurement and to reduce the risk of primary graft failure in the absence of coronary angiography in ECD. The present protocol aims to provide material details along with optimal imaging views for coronary angiography during NESP. Reproducible angiographic views were observed, including one dedicated to the right coronary artery, two for the left anterior descending artery, two for the circumflex artery, and a spider view. Continuous lactate extraction was observed in all procedures with a final median concentration of 1.10 mmol/L (0.61-1.75 mmol/L) two hours after coronary angiography, consistent with myocardial viability. The median contrast agent volume used for ex-situ imaging of the isolated perfused heart was 48 mL (38-108 mL). This protocol was reproducible for coronary artery imaging and did not impair myocardial viability during NESP.

Hyperpolarized Water for Coronary Artery Angiography and Whole-Heart Myocardial Perfusion Quantification.

Purpose: Water freely diffuses across cell membranes, making it suitable for measuring absolute tissue perfusion. In this study, we introduce an imaging method for conducting coronary artery angiography and quantifying myocardial perfusion across the entire heart using hyperpolarized water. Methods:1H was hyperpolarized using dissolution dynamic nuclear polarization (dDNP) with UV-generated radicals. Submillimeter resolution coronary artery images were acquired as 2D projections using a spoiled GRE (SPGRE) sequence gated on diastole. Dynamic perfusion images were obtained with a multi-slice SPGRE with diastole gating, covering the entire heart. Perfusion values were analyzed through histograms, and the most frequent estimated perfusion value (the mode of the distribution), was compared with the average values for 15O water PET from the literature. Results: A liquid state polarization of 10% at the time of the injection and a 30 s T1 in D2O TRIS buffer were measured. Both coronary artery and dynamic perfusion images exhibited good quality. The main and small coronary artery branches were well resolved. The most frequent estimated perfusion value is around 0.6 mL/g/min, which is lower than the average values obtained from the literature for 15O-water PET (around 1.1 and 1.5 mL/g/min). Conclusions: The study successfully demonstrated the feasibility of achieving high-resolution, motion-free coronary artery angiography and 3D whole-heart quantitative myocardial perfusion using hyperpolarized water.

Non-invasive fractional flow reserve estimation in coronary arteries using angiographic images.

Coronary artery disease is the leading global cause of mortality and Fractional Flow Reserve (FFR) is widely regarded as the gold standard for assessing coronary artery stenosis severity. However, due to the limitations of invasive FFR measurements, there is a pressing need for a highly accurate virtual FFR calculation framework. Additionally, it's essential to consider local haemodynamic factors such as time-averaged wall shear stress (TAWSS), which play a critical role in advancement of atherosclerosis. This study introduces an innovative FFR computation method that involves creating five patient-specific geometries from two-dimensional coronary angiography images and conducting numerical simulations using computational fluid dynamics with a three-element Windkessel model boundary condition at the outlet to predict haemodynamic distribution. Furthermore, four distinct boundary condition methodologies are applied to each geometry for comprehensive analysis. Several haemodynamic features, including velocity, pressure, TAWSS, and oscillatory shear index are investigated and compared for each case. Results show that models with average boundary conditions can predict FFR values accurately and observed errors between invasive FFR and virtual FFR are found to be less than 5%.

Longitudinal assessment of coronary plaque regression related to sodium-glucose cotransporter-2 inhibitor using coronary computed tomography angiography.

BACKGROUND: Sodium-Glucose Cotransporter-2 Inhibitor (SGLT2i) is a novel oral drug for treating type 2 diabetes mellitus (T2DM) with demonstrated cardiovascular benefits. Previous studies in apolipoprotein E knockout mice have shown that SGLT2i is associated with attenuated progression of atherosclerosis. However, whether this effect extends to T2DM patients with coronary atherosclerosis in real-world settings remains unknown. METHODS: In this longitudinal cohort study using coronary computed tomography angiography (CCTA), T2DM patients who underwent ≥ 2 CCTA examinations at our center between 2019 and 2022 were screened. Eligible patients had multiple study plaques, defined as non-obstructive stenosis at baseline and not intervened during serial CCTAs. Exclusion criteria included a CCTA time interval < 12 months, prior SGLT2i treatment, or initiation/discontinuation of SGLT2i during serial CCTAs. Plaque volume (PV) and percent atheroma volume (PAV) were measured for each study plaque using CCTA plaque analysis software. Patients and plaques were categorized based on SGLT2i therapy and compared using a 1:1 propensity score matching (PSM) analysis. RESULTS: The study included 236 patients (mean age 60.5 ± 9.5 years; 69.1% male) with 435 study plaques (diameter stenosis ≥ 50%, 31.7%). Following SGLT2i treatment for a median duration of 14.6 (interquartile range: 13.0, 20.0) months, overall, non-calcified, and low-attenuation PV and PAV were significantly decreased, while calcified PV and PAV were increased (all p < 0.001). Meanwhile, reductions in overall PV, non-calcified PV, overall PAV, and non-calcified PAV were significantly greater in SGLT2i-treated compared to non-SGLT2i-treated plaques (all p < 0.001). PSM analysis showed that SGLT2i treatment was associated with higher reductions in overall PV (- 11.77 mm3 vs. 4.33 mm3, p = 0.005), non-calcified PV (- 16.96 mm3 vs. - 1.81 mm3, p = 0.017), overall PAV (- 2.83% vs. 3.36%, p < 0.001), and non-calcified PAV (- 4.60% vs. 0.70%, p = 0.003). These findings remained consistent when assessing annual changes in overall and compositional PV and PAV. Multivariate regression models demonstrated that SGLT2i therapy was associated with attenuated progression of overall or non-calcified PV or PAV, even after adjusting for cardiovascular risk factors, medications, and baseline overall or non-calcified PV or PAV, respectively (all p < 0.05). The effect of SGLT2i on attenuating non-calcified plaque progression was consistent across subgroups (all p for interaction > 0.05). CONCLUSIONS: In this longitudinal CCTA cohort of T2DM patients, SGLT2i therapy markedly regressed coronary overall PV and PAV, mainly result from a significant reduction in non-calcified plaque.

Ponytail Left Anterior Descending Artery: A Case Report.

Division of the anterior descending branch into many small arteries is a rare coronary anomaly. We report the case of a 64-year-old female with severe stenosis (>75%) in the proximal region of the anterior descending branch as indicated by coronary computed tomography angiography (CCTA). In addition, coronary angiography showed that the anterior descending branch of the coronary artery split into numerous small arteries, an anomaly that can confound clinical examination.