TY - JOUR AB - Background: Different ST-segment elevation myocardial infarction (STEMI) localizations go along with dissimilarities in the size of the affected myocardium, the causing coronary vessel occlusion, and the right ventricular participation. Therefore, this study aims to clarify if there is any difference in long-term survival between anterior- and non-anterior-wall STEMI. Methods: This study included 2,195 incident STEMI cases that occurred between 2009 and 2017, recorded by the population-based Augsburg Myocardial Infarction Registry, Germany. The study population comprised 1.570 men and 625 women aged 25–84 years at acute myocardial infarction. The patients were observed from the day of their first acute event with an average follow-up period of 4.3 years, (standard deviation: 3.0). Survival analyses and multivariable Cox regression analyses were performed to examine the association between infarction localizations and long-term all-cause mortality. Results: Of the 2,195 patients, 1,118 had an anterior (AWS)- and 1,077 a non-anterior-wall-STEMI (NAWS). No significant associations of the STEMI localization with long-term mortality were found. When comparing AWS with NAWS, a hazard ratio of 0.91 [95% confidence interval: 0.75–1.10] could be calculated after multivariable adjustment. In contrast to NAWS, AWS was associated with a greater <28 day mortality, less current or former smoking and higher creatine kinase-myocardial band levels (CK-MB) and went along with a higher frequency of impaired left ventricular ejection fraction (<30%). Conclusions: Despite pathophysiological differences between AWS and NAWS, and identified differences in multiple clinical characteristics, no significant differences in long-term mortality between both groups were observed. AU - Bauke, F.* AU - Schmitz, T.* AU - Harmel, E.* AU - Raake, P.* AU - Heier, M. AU - Linseisen, J.* AU - Peters, A. AU - Meisinger, C.* C1 - 69843 C2 - 55211 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Anterior-wall and non-anterior-wall STEMIs do not differ in long-term mortality: Results from the augsburg myocardial infarction registry. JO - Front. Cardiovasc. Med. VL - 10 PB - Frontiers Media Sa PY - 2024 SN - 2297-055X ER - TY - JOUR AB - Chronic kidney disease (CKD) significantly increases cardiovascular risk and mortality, and the accumulation of uremic toxins in the circulation upon kidney failure contributes to this increased risk. We thus performed a screening for potential novel mediators of reduced cardiovascular health starting from dialysate obtained after hemodialysis of patients with CKD. The dialysate was gradually fractionated to increased purity using orthogonal chromatography steps, with each fraction screened for a potential negative impact on the metabolic activity of cardiomyocytes using a high-throughput MTT-assay, until ultimately a highly purified fraction with strong effects on cardiomyocyte health was retained. Mass spectrometry and nuclear magnetic resonance identified the metabolite mycophenolic acid-β-glucuronide (MPA-G) as a responsible substance. MPA-G is the main metabolite from the immunosuppressive agent MPA that is supplied in the form of mycophenolate mofetil (MMF) to patients in preparation for and after transplantation or for treatment of autoimmune and non-transplant kidney diseases. The adverse effect of MPA-G on cardiomyocytes was confirmed in vitro, reducing the overall metabolic activity and cellular respiration while increasing mitochondrial reactive oxygen species production in cardiomyocytes at concentrations detected in MMF-treated patients with failing kidney function. This study draws attention to the potential adverse effects of long-term high MMF dosing, specifically in patients with severely reduced kidney function already displaying a highly increased cardiovascular risk. AU - Harlacher, E.* AU - Schulte, C.* AU - Vondenhoff, S.* AU - Schmitt-Kopplin, P. AU - Diederich, P.* AU - Hemmers, C.* AU - Moellmann, J.* AU - Wollenhaupt, J.* AU - Veltrop, R.* AU - Biessen, E.* AU - Lehrke, M.* AU - Peters, B.* AU - Schlieper, G.* AU - Kuppe, C.* AU - Floege, J.* AU - Jankowski, V.* AU - Marx, N.* AU - Jankowski, J.* AU - Noels, H.* C1 - 70306 C2 - 55499 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Increased levels of a mycophenolic acid metabolite in patients with kidney failure negatively affect cardiomyocyte health. JO - Front. Cardiovasc. Med. VL - 11 PB - Frontiers Media Sa PY - 2024 SN - 2297-055X ER - TY - JOUR AB - BACKGROUND: The objective of this study was to investigate the differences in presenting symptoms between patients with and without diabetes being diagnosed with an acute myocardial infarction (AMI). METHODS: A total of 5,900 patients with a first-time AMI were included into the analysis. All patients aged between 25 and 84 years were recorded by the population-based Myocardial Infarction Registry in Augsburg, Germany, between 2010 and 2017. The presence (yes/no) of 12 AMI typical symptoms during the acute event was assessed within the scope of a face-to-face interview. Multivariable adjusted logistic regression models were calculated to analyze the associations between presenting symptoms and diabetes mellitus in AMI patients. RESULTS: Patients with diabetes had significantly less frequent typical pain symptoms, including typical chest pain. Also, other symptoms like sweating, vomiting/nausea, dizziness/vertigo and fear of death/feeling of annihilation occurred significantly more likely in non-diabetic patients. The only exception was the symptom of shortness of breath, which was found significantly more often in patients with diabetes. In multivariable-adjusted regression models, however, the observed effects were attenuated. In patients younger than 55 years, the associations between diabetes and various symptoms were mainly missing. CONCLUSIONS: Type 2 diabetes mellitus is a risk factor not only for the development of AMI, but is also associated with an adverse outcome after AMI. Atypical clinical presentation additionally complicates the diagnostic process. It is therefore essential for physicians to be aware of the more often atypical symptoms that diabetic AMI patients report. AU - Schmitz, T.* AU - Wein, B.* AU - Raake, P.* AU - Heier, M. AU - Peters, A. AU - Linseisen, J.* AU - Meisinger, C.* C1 - 69902 C2 - 55206 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Do patients with diabetes with new onset acute myocardial infarction present with different symptoms than non-diabetic patients? JO - Front. Cardiovasc. Med. VL - 11 PB - Frontiers Media Sa PY - 2024 SN - 2297-055X ER - TY - JOUR AB - Atherosclerotic cardiovascular disease (ASCVD) is the most common cause of death globally. Increasing amounts of highly diverse ASCVD data are becoming available and artificial intelligence (AI) techniques now bear the promise of utilizing them to improve diagnosis, advance understanding of disease pathogenesis, enable outcome prediction, assist with clinical decision making and promote precision medicine approaches. Machine learning (ML) algorithms in particular, are already employed in cardiovascular imaging applications to facilitate automated disease detection and experts believe that ML will transform the field in the coming years. Current review first describes the key concepts of AI applications from a clinical standpoint. We then provide a focused overview of current AI applications in four main ASCVD domains: coronary artery disease (CAD), peripheral arterial disease (PAD), abdominal aortic aneurysm (AAA), and carotid artery disease. For each domain, applications are presented with refer to the primary imaging modality used [e.g., computed tomography (CT) or invasive angiography] and the key aim of the applied AI approaches, which include disease detection, phenotyping, outcome prediction, and assistance with clinical decision making. We conclude with the strengths and limitations of AI applications and provide future perspectives. AU - Kampaktsis, P.N.* AU - Emfietzoglou, M.* AU - Al Shehhi, A.* AU - Fasoula, N.-A. AU - Bakogiannis, C.* AU - Mouselimis, D.* AU - Tsarouchas, A.* AU - Vassilikos, V.P.* AU - Kallmayer, M.* AU - Eckstein, H.H.* AU - Hadjileontiadis, L.* AU - Karlas, A. C1 - 67404 C2 - 54157 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Artificial intelligence in atherosclerotic disease: Applications and trends. JO - Front. Cardiovasc. Med. VL - 9 PB - Frontiers Media Sa PY - 2023 SN - 2297-055X ER - TY - JOUR AU - Karlas, A. AU - Bariotakis, M. AU - Kallmayer, M.* AU - Hadjileontiadis, L.* AU - Wildgruber, M.* C1 - 67868 C2 - 54346 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Editorial: Research topic for frontiers in cardiovascular medicine: non-invasive sensing and imaging techniques for cardiometabolic diseases. JO - Front. Cardiovasc. Med. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2297-055X ER - TY - JOUR AB - Imaging plays a critical role in exploring the pathophysiology and enabling the diagnostics and therapy assessment in carotid artery disease. Ultrasonography, computed tomography, magnetic resonance imaging and nuclear medicine techniques have been used to extract of known characteristics of plaque vulnerability, such as inflammation, intraplaque hemorrhage and high lipid content. Despite the plethora of available techniques, there is still a need for new modalities to better characterize the plaque and provide novel biomarkers that might help to detect the vulnerable plaque early enough and before a stroke occurs. Optoacoustics, by providing a multiscale characterization of the morphology and pathophysiology of the plaque could offer such an option. By visualizing endogenous (e.g., hemoglobin, lipids) and exogenous (e.g., injected dyes) chromophores, optoacoustic technologies have shown great capability in imaging lipids, hemoglobin and inflammation in different applications and settings. Herein, we provide an overview of the main optoacoustic systems and scales of detail that enable imaging of carotid plaques in vitro, in small animals and humans. Finally, we discuss the limitations of this novel set of techniques while investigating their potential to enable a deeper understanding of carotid plaque pathophysiology and possibly improve the diagnostics in future patients with carotid artery disease. AU - Karlas, A. AU - Fasoula, N.-A. AU - Kallmayer, M.* AU - Schäffer, C.* AU - Angelis, G. AU - Katsouli, N. AU - Reidl, M. AU - Duelmer, F. AU - Al Adem, K. AU - Hadjileontiadis, L.J.* AU - Eckstein, H.H.* AU - Ntziachristos, V. C1 - 68865 C2 - 53683 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Optoacoustic biomarkers of lipids, hemorrhage and inflammation in carotid atherosclerosis. JO - Front. Cardiovasc. Med. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2297-055X ER - TY - JOUR AB - OBJECTIVE: Dyslipidemia is a key risk factor for coronary artery disease (CAD). This study aimed to investigate the correlation between the atherogenic index of plasma (AIP) and the severity of CAD. METHODS: 2,491 patients were enrolled in this study and analyzed retrospectively, including 665 non-CAD patients as the control group and 1,826 CAD patients. The CAD patients were classified into three subgroups according to tertiles of SYNTAX score (SS). Non-high-density lipoprotein cholesterol (Non-HDL-C) was defined as serum total cholesterol (TC) minus serum high-density lipoprotein cholesterol (Non-HDL-C), atherogenic index (AI) was defined as the ratio of non-HDL-C to HDL-C; AIP was defined as the logarithm of the ratio of the concentration of triglyceride (TG) to HDL-C; lipoprotein combine index (LCI) was defined as the ratio of TC∗TG∗ low-density lipoprotein cholesterol (LDL)to HDL-C; Castelli Risk Index I (CRI I) was defined as the ratio of TC to HDL-C; Castelli Risk Index II (CRI II) was defined as the ratio of LDL-C to HDL-C. RESULTS: The levels of AIP (P < 0.001), AI (P < 0.001), and LCI (P = 0.013) were higher in the CAD group compared with the non-CAD group. The Spearman correlation analysis showed that AIP (r = 0.075, P < 0.001), AI (r = 0.132, P < 0.001), and LCI (r = 0.072, P = 0.001) were positively correlated with SS. The multivariate logistic regression model showed CRI I (OR: 1.11, 95% CI: 1.03-1.19, P = 0.005), CRI II (OR: 1.26, 95% CI: 1.15-1.39, P < 0.001), AI (OR: 1.28, 95% CI: 1.17-1.40, P < 0.001), AIP (OR: 2.06, 95% CI: 1.38-3.07, P < 0.001), and LCI (OR: 1.01, 95% CI: 1.01-1.02, P < 0.001) were independent predictors of severity of CAD After adjusting various confounders. CONCLUSION: CRI I, CRI II, AIP, AI, and LCI were independent predictors of the severity of CAD, which could be used as a biomarker for the evaluation of the severity of CAD. AU - Li, Y.* AU - Feng, Y.* AU - Li, S.* AU - Ma, Y.* AU - Lin, J. AU - Wan, J.* AU - Zhao, M.* C1 - 68110 C2 - 54588 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - The atherogenic index of plasma (AIP) is a predictor for the severity of coronary artery disease. JO - Front. Cardiovasc. Med. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2297-055X ER - TY - JOUR AB - BACKGROUND: The aim of this study was to investigate the association between inflammatory plasma protein concentrations and long-term mortality in patients with ST-elevation myocardial infarction (STEMI). METHODS: For 343 STEMI patients recorded between 2009 and 2013 by the population-based Myocardial Infarction Registry Augsburg, 92 inflammatory plasma proteins were measured at the index event using the OLINK inflammation panel. In multivariable-adjusted Cox regression models, the association between each plasma protein and all-cause long-term mortality was investigated. Median follow-up time was 7.6 (IQR: 2.4) years. For plasma protein that showed a strong association with long-term mortality, a 5-year survival ROC analysis was performed. RESULTS: One plasma protein, namely Fibroblast Growth Factor 23 (FGF-23), was particularly well associated with long-term mortality in the multivariable-adjusted Cox model with an FDR-adjusted p-value of <0.001 and a Hazard Ratio (HR) of 1.57 [95% CI: 1.29-1.91]. In the 5-years ROC analysis, an AUC of 0.6903 [95% CI: 0.594-0.781] was estimated for FGF-23. All other plasma protein didńt show strong associations, each marker with FDR-adjusted p-values >0.05 in the multivariable-adjusted Cox models. CONCLUSIONS: FGF-23 is independently associated with long-term mortality after STEMI and might play an important role in the response to myocardial injury. The results suggest FGF-23 to be a useful marker in the long-term treatment of STEMI patients and a potential target for drug development. AU - Schmitz, T.* AU - Wein, B.* AU - Heier, M. AU - Peters, A. AU - Meisinger, C.* AU - Linseisen, J.* C1 - 67983 C2 - 54461 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Baseline fibroblast growth factor 23 is associated with long-term mortality in ST-elevation myocardial infarction-results from the augsburg myocardial infarction registry. JO - Front. Cardiovasc. Med. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2297-055X ER - TY - JOUR AB - BACKGROUND: Atherosclerosis is the underlying cause of many cardiovascular diseases, such as myocardial infarction or stroke. B cells, and their production of pro- and anti-atherogenic antibodies, play an important role in atherosclerosis. In B cells, TRAF2 and NCK-interacting Kinase (TNIK), a germinal center kinase, was shown to bind to TNF-receptor associated factor 6 (TRAF6), and to be involved in JNK and NF-κB signaling in human B cells, a pathway associated with antibody production. OBJECTIVE: We here investigate the role of TNIK-deficient B cells in atherosclerosis. RESULTS: ApoE-/-TNIKfl/fl (TNIKBWT) and ApoE-/-TNIKfl/flCD19-cre (TNIKBKO) mice received a high cholesterol diet for 10 weeks. Atherosclerotic plaque area did not differ between TNIKBKO and TNIKBWT mice, nor was there any difference in plaque necrotic core, macrophage, T cell, α-SMA and collagen content. B1 and B2 cell numbers did not change in TNIKBKO mice, and marginal zone, follicular or germinal center B cells were unaffected. Total IgM and IgG levels, as well as oxidation specific epitope (OSE) IgM and IgG levels, did not change in absence of B cell TNIK. In contrast, plasma IgA levels were decreased in TNIKBKO mice, whereas the number of IgA+ B cells in intestinal Peyer's patches increased. No effects could be detected on T cell or myeloid cell numbers or subsets. CONCLUSION: We here conclude that in hyperlipidemic ApoE-/- mice, B cell specific TNIK deficiency does not affect atherosclerosis. AU - van Os, B.W.* AU - Kusters, P.J.H.* AU - den Toom, M.* AU - Beckers, L.* AU - van Tiel, C.M.* AU - Vos, W.G.* AU - de Jong, E.* AU - Kieser, A. AU - van Roomen, C.* AU - Binder, C.J.* AU - Reiche, M.E.* AU - de Winther, M.P.* AU - Bosmans, L.A.* AU - Lutgens, E.* C1 - 67911 C2 - 54389 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Deficiency of germinal center kinase TRAF2 and NCK-interacting kinase (TNIK) in B cells does not affect atherosclerosis. JO - Front. Cardiovasc. Med. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2297-055X ER - TY - JOUR AB - Background: In this study we investigated the prevalence of undiagnosed impaired glucose tolerance and type-2-diabetes (T2D) among patients with acute myocardial infarction (AMI) and prospectively analyzed whether these patients have a higher long-term mortality. Methods: The analysis was based on 2,317 AMI patients aged 25-84 years from the population-based Myocardial Infarction Registry Augsburg, recruited between 2009 and 2014 and followed-up until 2019 (median follow-up time 6.5 years [IQR: 4.9-8.1]). AMI patients with a diagnosis of diabetes were divided into a high (>7.0%) and a low HbA1c group (≤7.0%) according to HbA1c values at admission. The remaining patients (without known diabetes) were grouped into normal (<5.7%), elevated (5.7-6.4%), and high (≥6.5%) HbA1c groups. In a multivariable-adjusted COX regression analysis, the association between HbA1c groups and long-term mortality was investigated. Linear regression models were used to identify AMI patients with elevated HbA1c values by means of personal characteristics. Results: At admission, 29.5% of all patients reported a diagnosis of diabetes. Of all patients without known diabetes, 5.4% had HbA1c values of ≥ 6.5 and 37.9% had HbA1c values between 5.7 and 6.4%. The fully adjusted Cox regression model showed a non-significant trend toward higher long-term mortality for AMI patients with increased HbA1c values (HbA1c 5.7-6.4% HR: 1.05 [0.79-1.38], HbA1c > 6.5% HR: 1.34 [0.77-2.31]). A linear regression model including the variables admission serum glucose, BMI, age, sex and type of infarction (STEMI, NSTEMI) showed only poor prediction of HbA1c values (R 2: 11.08%). Conclusion: A fairly high number of AMI patients without known diabetes have elevated HbA1c values. Though we could not prove a higher risk of premature mortality in these patients, early detection and adequate therapy might lead to reduced diabetes-associated complications and improve long-term outcomes. AU - Schmitz, T.* AU - Harmel, E.* AU - Heier, M. AU - Peters, A. AU - Linseisen, J.* AU - Meisinger, C.* C1 - 65006 C2 - 52121 TI - Undiagnosed impaired glucose tolerance and type-2 diabetes in acute myocardial infarction patients: Fequency, characteristics and long-term mortality. JO - Front. Cardiovasc. Med. VL - 9 PY - 2022 SN - 2297-055X ER - TY - JOUR AB - Background: Left ventricular ejection fraction (LVEF) is the gold standard for evaluating heart failure (HF) in coronary artery disease (CAD) patients. It is an essential metric in categorizing HF patients as preserved (HFpEF), mid-range (HFmEF), and reduced (HFrEF) ejection fraction but differs, depending on whether the ASE/EACVI or ESC guidelines are used to classify HF. Objectives: We sought to investigate the effectiveness of using deep learning as an automated tool to predict LVEF from patient clinical profiles using regression and classification trained models. We further investigate the effect of utilizing other LVEF-based thresholds to examine the discrimination ability of deep learning between HF categories grouped with narrower ranges. Methods: Data from 303 CAD patients were obtained from American and Greek patient databases and categorized based on the American Society of Echocardiography and the European Association of Cardiovascular Imaging (ASE/EACVI) guidelines into HFpEF (EF > 55%), HFmEF (50% ≤ EF ≤ 55%), and HFrEF (EF < 50%). Clinical profiles included 13 demographical and clinical markers grouped as cardiovascular risk factors, medication, and history. The most significant and important markers were determined using linear regression fitting and Chi-squared test combined with a novel dimensionality reduction algorithm based on arc radial visualization (ArcViz). Two deep learning-based models were then developed and trained using convolutional neural networks (CNN) to estimate LVEF levels from the clinical information and for classification into one of three LVEF-based HF categories. Results: A total of seven clinical markers were found important for discriminating between the three HF categories. Using statistical analysis, diabetes, diuretics medication, and prior myocardial infarction were found statistically significant (p < 0.001). Furthermore, age, body mass index (BMI), anti-arrhythmics medication, and previous ventricular tachycardia were found important after projections on the ArcViz convex hull with an average nearest centroid (NC) accuracy of 94%. The regression model estimated LVEF levels successfully with an overall accuracy of 90%, average root mean square error (RMSE) of 4.13, and correlation coefficient of 0.85. A significant improvement was then obtained with the classification model, which predicted HF categories with an accuracy ≥93%, sensitivity ≥89%, 1-specificity <5%, and average area under the receiver operating characteristics curve (AUROC) of 0.98. Conclusions: Our study suggests the potential of implementing deep learning-based models clinically to ensure faster, yet accurate, automatic prediction of HF based on the ASE/EACVI LVEF guidelines with only clinical profiles and corresponding information as input to the models. Invasive, expensive, and time-consuming clinical testing could thus be avoided, enabling reduced stress in patients and simpler triage for further intervention. AU - Alkhodari, M.* AU - Jelinek, H.F.* AU - Karlas, A. AU - Soulaidopoulos, S.* AU - Arsenos, P.* AU - Doundoulakis, I.* AU - Gatzoulis, K.A.* AU - Tsioufis, K.* AU - Hadjileontiadis, L.J.* AU - Khandoker, A.H.* C1 - 63798 C2 - 51763 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Deep learning predicts heart failure with preserved, mid-range, and reduced left ventricular ejection fraction from patient clinical profiles. JO - Front. Cardiovasc. Med. VL - 8 PB - Frontiers Media Sa PY - 2021 SN - 2297-055X ER - TY - JOUR AB - Background: Optical coherence tomography is a powerful modality to assess atherosclerotic lesions, but detecting lesions in high-resolution OCT is challenging and requires expert knowledge. Deep-learning algorithms can be used to automatically identify atherosclerotic lesions, facilitating identification of patients at risk. We trained a deep-learning algorithm (DeepAD) with co-registered, annotated histopathology to predict atherosclerotic lesions in optical coherence tomography (OCT). Methods: Two datasets were used for training DeepAD: (i) a histopathology data set from 7 autopsy cases with 62 OCT frames and co-registered histopathology for high quality manual annotation and (ii) a clinical data set from 51 patients with 222 OCT frames in which manual annotations were based on clinical expertise only. A U-net based deep convolutional neural network (CNN) ensemble was employed as an atherosclerotic lesion prediction algorithm. Results were analyzed using intersection over union (IOU) for segmentation. Results: DeepAD showed good performance regarding the prediction of atherosclerotic lesions, with a median IOU of 0.68 ± 0.18 for segmentation of atherosclerotic lesions. Detection of calcified lesions yielded an IOU = 0.34. When training the algorithm without histopathology-based annotations, a performance drop of >0.25 IOU was observed. The practical application of DeepAD was evaluated retrospectively in a clinical cohort (n = 11 cases), showing high sensitivity as well as specificity and similar performance when compared to manual expert analysis. Conclusion: Automated detection of atherosclerotic lesions in OCT is improved using a histopathology-based deep-learning algorithm, allowing accurate detection in the clinical setting. An automated decision-support tool based on DeepAD could help in risk prediction and guide interventional treatment decisions. AU - Holmberg, O. AU - Lenz, T.* AU - Koch, V. AU - Alyagoob, A.* AU - Utsch, L.* AU - Rank, A.* AU - Sabic, E.* AU - Seguchi, M.* AU - Xhepa, E.* AU - Kufner, S.* AU - Cassese, S.* AU - Kastrati, A.* AU - Marr, C. AU - Joner, M.* AU - Nicol, P.* C1 - 64021 C2 - 51699 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Histopathology-based deep-learning predicts atherosclerotic lesions in intravascular imaging. JO - Front. Cardiovasc. Med. VL - 8 PB - Frontiers Media Sa PY - 2021 SN - 2297-055X ER - TY - JOUR AB - The diagnostic strategy for chronic thromboembolic pulmonary hypertension (CTEPH) is composed of two components required for a diagnosis of CTEPH: the presence of chronic pulmonary embolism and an elevated pulmonary artery pressure. The current guidelines require that ventilation-perfusion single-photon emission computed tomography (VQ-SPECT) is used for the first step diagnosis of chronic pulmonary embolism. However, VQ-SPECT exposes patients to ionizing radiation in a radiation sensitive population. The prospective, multicenter, comparative phase III diagnostic trial CTEPH diagnosis Europe - MRI (CHANGE-MRI, identifier NCT02791282) aims to demonstrate whether functional lung MRI can serve as an equal rights alternative to VQ-SPECT in a diagnostic strategy for patients with suspected CTEPH. Positive findings are verified with catheter pulmonary angiography or computed tomography pulmonary angiography (gold standard). For comparing the imaging methods, a co-primary endpoint is used. (i) the proportion of patients with positive MRI in the group of patients who have a positive SPECT and gold standard diagnosis for chronic pulmonary embolism and (ii) the proportion of patients with positive MRI in the group of patients with negative SPECT and gold standard. The CHANGE-MRI trial will also investigate the performance of functional lung MRI without i.v. contrast agent as an index test and identify cardiac, hemodynamic, and pulmonary MRI-derived parameters to estimate pulmonary artery pressures and predict 6-12 month survival. Ultimately, this study will provide the necessary evidence for the discussion about changes in the recommendations on the diagnostic approach to CTEPH. AU - Lasch, F.* AU - Karch, A.* AU - Koch, A.* AU - Derlin, T.* AU - Voskrebenzev, A.* AU - Alsady, T.M.* AU - Hoeper, M.M.* AU - Gall, H.* AU - Roller, F.* AU - Harth, S.* AU - Steiner, D.* AU - Krombach, G.* AU - Ghofrani, H.A.* AU - Rengier, F.* AU - Heußel, C.P.* AU - Grünig, E.* AU - Beitzke, D.* AU - Hacker, M.* AU - Lang, I.M.* AU - Behr, J. AU - Bartenstein, P.* AU - Dinkel, J. AU - Schmidt, K.H.* AU - Kreitner, K.F.* AU - Frauenfelder, T.* AU - Ulrich, S.* AU - Hamer, O.W.* AU - Pfeifer, M.* AU - Johns, C.S.* AU - Kiely, D.G.* AU - Swift, A.J.* AU - Wild, J.* AU - Vogel-Claussen, J.* C1 - 58937 C2 - 48522 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Comparison of MRI and VQ-SPECT as a screening test for patients with suspected CTEPH: CHANGE-MRI study design and rationale. JO - Front. Cardiovasc. Med. VL - 7 PB - Frontiers Media Sa PY - 2020 SN - 2297-055X ER - TY - JOUR AB - Genetic variants at hundreds of loci associated with cardiovascular phenotypes have been identified by genome wide association studies. Most of these variants are located in intronic or intergenic regions rendering the functional and mechanistic follow up difficult. These non-protein-coding regions harbor regulatory sequences. Thus the study of genetic variants associated with transcription—so called expression quantitative trait loci—has emerged as a promising approach to identify regulatory sequence variants. The genes and pathways they control constitute candidate causal drivers at cardiovascular risk loci. This review provides an overview of the expression quantitative trait loci resources available for cardiovascular genetics research and the most commonly used approaches for candidate gene identification. AU - Heinig, M. C1 - 53633 C2 - 44776 TI - Using gene expression to annotate cardiovascular GWAS loci. JO - Front. Cardiovasc. Med. VL - 5 PY - 2018 SN - 2297-055X ER - TY - JOUR AB - Extracellular vesicles (EVs) have emerged as a novel intercellular communication system. By carrying bioactive lipids, miRNAs and proteins they can modulate target cell functions and phenotype. Circulating levels of EVs are increased in inflammatory conditions, e.g., cardiovascular disease patients, and their functional contribution to atherosclerotic disease development is currently heavily studied. This review will describe how EVs can modulate vascular cell functions relevant to vascular inflammation and atherosclerosis, particularly highlighting the role of EV-associated proteolytic activity and effector proteins involved. Furthermore, we will discuss key questions and challenges, especially for EV-based therapeutics. AU - van der Vorst, E.P.C.* AU - de Jong, R.J. AU - Donners, M.M.P.C.* C1 - 52888 C2 - 44436 TI - Message in a microbottle: Modulation of vascular inflammation and atherosclerosis by extracellular vesicles. JO - Front. Cardiovasc. Med. VL - 5 PY - 2018 SN - 2297-055X ER -