Quantitative coronary plaque analysis predicts high-risk plaque morphology on coronary computed tomography angiography: results from the ROMICAT II trial

Semi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features and quantitative plaque measurements has not been studied. We analyzed the association between quantitative plaque measurements and qualitative high-risk plaque features on coronary CTA. We included 260 patients with plaque who underwent coronary CTA in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) II trial. Quantitative plaque assessment and qualitative plaque characterization were performed on a per coronary segment basis. Quantitative coronary plaque measurements included plaque volume, plaque burden, remodeling index, and diameter stenosis. In qualitative analysis, high-risk plaque was present if positive remodeling, low CT attenuation plaque, napkin-ring sign or spotty calcium were detected. Univariable and multivariable logistic regression analyses were performed to assess the association between quantitative and qualitative high-risk plaque assessment. Among 888 segments with coronary plaque, high-risk plaque was present in 391 (44.0%) segments by qualitative analysis. In quantitative analysis, segments with high-risk plaque had higher total plaque volume, low CT attenuation plaque volume, plaque burden and remodeling index. Quantitatively assessed low CT attenuation plaque volume (odds ratio 1.12 per 1 mm3, 95% CI 1.04-1.21), positive remodeling (odds ratio 1.25 per 0.1, 95% CI 1.10-1.41) and plaque burden (odds ratio 1.53 per 0.1, 95% CI 1.08-2.16) were associated with high-risk plaque. Quantitative coronary plaque characteristics (low CT attenuation plaque volume, positive remodeling and plaque burden) measured by semi-automated software correlated with qualitative assessment of high-risk plaque features

Knowledge, attitudes, behaviors, and serological status related to Chagas disease among Latin American migrants in Germany: A cross-sectional study in six German cities

BackgroundLittle is known about knowledge, attitudes and behaviors concerning Chagas disease (CD) among Latin American migrants in Germany to inform public health decision making.MethodsA cross-sectional, questionnaire-based study was conducted between March 2014 and October 2019 among Latin American migrants in six cities in Germany to obtain information on migration history, socioeconomic and insurance status, knowledge about CD, potential risk factors for Trypanosoma cruzi infection, and willingness to donate blood or organs.Results168 participants completed the questionnaire. The four countries with the highest proportion of participants contributing to the study population were Colombia, Mexico, Peru and Ecuador. Before migrating to Europe, the majority of the study population resided in an urban setting in houses made of stone or concrete, had higher academic education and was integrated into the German healthcare and healthcare insurance system. The majority of all study participants were also willing to donate blood and organs and a quarter of them had donated blood previously. However, many participants lacked basic knowledge about symptoms and modes of transmission of Chagas disease. One out of 56 serologic tests (1.8%) performed was positive. The seropositive female participant born in Argentina had a negative PCR test and no signs of cardiac or other organ involvement.ConclusionsThe study population does not reflect the population structure at risk for T. cruzi infection in endemic countries. Most participants had a low risk profile for infection with T. cruzi. Although the sample size was small and sampling was not representative of all persons at risk in Germany, the seroprevalence found was similar to studies previously conducted in Europe. As no systematic screening for T. cruzi in Latin American blood and organ donors as well as in women of child-bearing age of Latin American origin is implemented in Germany, a risk of occasional transmission of T. cruzi remains

A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography

Background: Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved in atherogenesis and we hypothesized that additional radiomic signatures of adverse fibrotic and microvascular PVAT remodelling, may further improve cardiac risk prediction. Methods and results: We present a new artificial intelligence-powered method to predict cardiac risk by analysing the radiomic profile of coronary PVAT, developed and validated in patient cohorts acquired in three different studies. In Study 1, adipose tissue biopsies were obtained from 167 patients undergoing cardiac surgery, and the expression of genes representing inflammation, fibrosis and vascularity was linked with the radiomic features extracted from tissue CT images. Adipose tissue wavelet-transformed mean attenuation (captured by FAI) was the most sensitive radiomic feature in describing tissue inflammation (TNFA expression), while features of radiomic texture were related to adipose tissue fibrosis (COL1A1 expression) and vascularity (CD31 expression). In Study 2, we analysed 1391 coronary PVAT radiomic features in 101 patients who experienced major adverse cardiac events (MACE) within 5 years of having a CCTA and 101 matched controls, training and validating a machine learning (random forest) algorithm (fat radiomic profile, FRP) to discriminate cases from controls (C-statistic 0.77 [95%CI: 0.62–0.93] in the external validation set). The coronary FRP signature was then tested in 1575 consecutive eligible participants in the SCOT-HEART trial, where it significantly improved MACE prediction beyond traditional risk stratification that included risk factors, coronary calcium score, coronary stenosis, and high-risk plaque features on CCTA (Δ[C-statistic] = 0.126, P  Conclusion: The CCTA-based radiomic profiling of coronary artery PVAT detects perivascular structural remodelling associated with coronary artery disease, beyond inflammation. A new artificial intelligence (AI)-powered imaging biomarker (FRP) leads to a striking improvement of cardiac risk prediction over and above the current state-of-the-art. </p

Characterization of contaminations on semiconductor surfaces and thin layer systems with Time of Flight - secondary ion mass spectrometry

Kontrollierte Oberflächeneigenschaften sind entscheidend für eine optimale Produktleistung und die Produktzuverlässigkeit, insbesondere auf Bondpads: Verschiedene Verunreinigungen (organisch und anorganisch) können Einfluss auf Bonddraht Haftung und Lebensdauer nehmen. Daher ist eine kontrollierte Probenoberfläche unbedingt notwendig um Fehler während der Herstellung zu vermeiden und um gegebenenfalls Fehlerursachen ermitteln zu können.Innerhalb dieser Arbeit wurden verschiedene analytische Techniken:Rutherford- Rückstreu- Spektrometrie (RBS), Elastic Recoil Detection (ERD), Rasterelektronenmikroskopie (REM), Auger- Elektronenspektroskopie (AES), Rasterkraftmikroskopie (AFM), Gaschromatographie- Massenspektrometrie (GC-MS), Laser Doppler Vibrometrie, Sheartests und Flugzeitsekundärionenspektrometrie (ToF-SIMS) verwendet um Kontaminationen in der Halbleiterindustrie zu überwachen und zu charakterisieren. Das Ziel dieser Arbeit war es, Verunreinigungen zu identifizieren, ihre Ursachen zu erforschen und ihren Einfluss auf die Produktzuverlässigkeit zu untersuchen.Ein Schwerpunkt lag auf Bondpad Kontamination ( d.h. hauptsächlich Oberflächenkontaminationen), ein weiterer Schwerpunkt auf Verunreinigungen in dünnen Schichten. Wafersplit-Experimente wurden entwickelt, um die Auswirkungen der durch Umwelt- bzw.Fertigungsschritte hervorgerufenen Verunreinigungen auf folgende Montageprozesse und die Produktlebensdauer zu untersuchen: Die Auswirkung unterschiedlicher Herstellungsschritte während der BEOL Verarbeitung auf dem Wasserstoff-Konzentration innerhalb des Gateoxides wurde charakterisiert und der Effekt auf die Drahtverbindungszuverlässigkeit von bewusst aufgebrachter Titanverunreinigung auf die Bondpadoberfläche wurde untersucht.Controlled surface characteristics are crucial for optimal product performance and device reliability, especially on bond pads:Various contaminations (organic and inorganic) might take influence on bond wire adhesion and reliability behavior. Hence, contamination monitoring - next to failure analysis - is essential to eliminate failures during manufacturing, to determine causes of failure respectively. Within this work different analytical techniques:Rutherford Backscattering (RBS), Elastic Recoil Detection (ERD), Electron microscopy (SEM), Auger Electron Spectroscopy (AES), Atomic Force Microscopy (AFM), Digital Holography Microscopy, Gas Chromatography-Mass Spectrometry (GC-MS) and Laser Doppler Vibrometry were used to support Time of Flight Secondary Ion Mass Spectrometry (ToF-SIMS) investigations in semiconductor research areas. The aim of this thesis was to identify contaminations in semiconductor industry and characterize their role on device reliability by means of process splits cooperating with Infineon Technologies Austria in Villach.One focus was on bond pad contamination, which have been identified and allocated to their sources, another focus on contaminations in thin layer systems. Wafer split experiments were designed to investigate the impact of different contaminations owing to transport, environment or manufacturing steps on sample formation and device reliability: The effect of manufacturing process steps during the back end of line (BEOL) processing on the hydrogen concentration within the gate oxide (GOX) was determinded and the impact of breeded titanium contamination on the wire bond reliability was demonstrated.12

Multimodal magnetic resonance imaging increases the overall diagnostic accuracy in brain tumours: Correlation with histopathology

Background: The aim of this retrospective study was to assess the contribution of multimodal MRI techniques, specifically perfusion-weighted imaging (PWI), and/or MR spectroscopy (MRS), in increasing the diagnostic accuracy of MRI in brain tumours. Methods: Forty-four patients with suspected brain tumours (27 (61%) patients male, mean age 58±17 (mean±SD) years) were included in this retrospective analysis. Patients were examined with conventional MR sequences, DWI, and with PWI and/or MRS. The concordance between the diagnoses obtained with multimodal MRI and with the conventional MR sequences, and the final diagnosis obtained by biopsy, was estimated. Fisher’s exact test and/or chi-square test was performed to estimate the added utility of multimodal MRI. Statistical significance was set at p<0.05. Results: With multimodal MRI, the diagnosis in 41 (93%) patients was the same as that obtained by biopsy, compared with 39% (17/44) patients when the readers were allowed to give one diagnostic possibility during the evaluation of the conventional MR sequences alone (p<0.001). The concordance between the diagnoses provided by evaluating the multimodal MRIs and the final diagnoses was almost perfect (κ value 0.92, 95% CI 0.82 - 1). PWI primarily helped to differentiate lymphomas from other solid tumours, whereas MRS helped to differentiate malignant glioma from metastasis. Both PWI and MRS helped in grading astrocytomas. Conclusion: Multimodal MRI increases diagnostic accuracy and should, wherever available, be performed in the work-up of brain tumours, although this entails increased examination cost and time