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Background: Elevated N-terminal pro-B-type natriuretic peptides (NT-proBNP) and cardiac troponin T (cTnT) are associated with poor outcome in patients with chronic coronary syndrome (CCS). The performance of these biomarkers in diagnosing ischemia, and their association with myocardial hypoperfusion and hypokinesis is unclear. Methods: Patients with suspected CCS (history of angina, estimated cardiovascular risk >15% or a positive stress test) were included in the prospective, multi-center DOPPLER-CIP study. Patients underwent Single Positron Emission Computed Tomography for assessment of ischemia and NT-proBNP and cTnT were measured in venous blood samples. Results: We included 430 patients (25% female) aged 64 +/- 8 years. Reversible hypoperfusion and hypokinesis were present in 139 (32%) and 89 (21%), respectively. Concentrations of NT-proBNP and cTnT correlated moderately (rho = 0.50, p < 0.001). NT-proBNP and cTnT concentrations (median [IQR]) were higher in patients with versus without reversible ischemia: 150 (73-294) versus 87 (44-192) ng/L and 10 (6-13) versus 7 (4-11) ng/L, respectively (p < 0.001 for both), and the associations persisted after adjusting for possible confounders. The C-statistics to discriminate ischemia ranged from 63%-73%, were comparable for cTnT and NT-proBNP, and higher for hypokinesis than hypoperfusion, and both were superior to exercise electrocardiography and stress echocardiography. Very low concentrations (<= 5 ng/L cTnT and <= 60 ng/L NT-proBNP) ruled out reversible hypokinesis with negative predictive value >90%. Conclusion: cTnT and NT-proBNP are associated with irreversible and reversible ischemia in patients with suspected CCS, particularly hypokinesis. The diagnostic performance was comparable between the biomarkers, and very low concentrations may reliably rule out ischemia., Funding Agencies|Akershus University Hospital; Norwegian Research Council; South-Eastern Norway Regional Health Authority; EU (FP7) framework program; SouthEastern Norway Regional Health Authority

Objective. External beam radiotherapy is aimed to precisely deliver a high radiation dose to malignancies, while optimally sparing surrounding healthy tissues. With the advent of increasingly complex treatment plans, the delivery should preferably be verified by quality assurance methods. Recently, online ultrasound imaging of vaporized radiosensitive nanodroplets was proposed as a promising tool for in vivo dosimetry in radiotherapy. Previously, the detection of sparse vaporization events was achieved by applying differential ultrasound (US) imaging followed by intensity thresholding using subjective parameter tuning, which is sensitive to image artifacts. Approach. A generalized deep learning solution (i.e. BubbleNet) is proposed to localize vaporized nanodroplets on differential US frames, while overcoming the aforementioned limitation. A 5-fold cross-validation was performed on a diversely composed 5747-frame training/validation dataset by manual segmentation. BubbleNet was then applied on a test dataset of 1536 differential US frames to evaluate dosimetric features. The intra-observer variability was determined by scoring the Dice similarity coefficient (DSC) on 150 frames segmented twice. Additionally, the BubbleNet generalization capability was tested on an external test dataset of 432 frames acquired by a phased array transducer at a much lower ultrasound frequency and reconstructed with unconventional pixel dimensions with respect to the training dataset. Main results. The median DSC in the 5-fold cross validation was equal to 1/40.88, which was in line with the intra-observer variability (=0.86). Next, BubbleNet was employed to detect vaporizations in differential US frames obtained during the irradiation of phantoms with a 154 MeV proton beam or a 6 MV photon beam. BubbleNet improved the bubble-count statistics by 1/430% compared to the earlier established intensity-weighted thresholding. The proton range was verified with a -0.8 mm accuracy. Significa

BACKGROUND: Cardiac troponin T concentrations measured with high-sensitivity assays (hs-cTnT) provide important prognostic information for patients with stable coronary artery disease (CAD). However, whether hsc-TnT concentrations mainly reflect left ventricular (LV) remodeling or recurrent myocardial ischemia in this population is not known. METHODS: We measured hs-cTnT concentrations in 619 subjects with suspected stable CAD in a prospectively designed multicenter study. We identified associations with indices of LV remodeling, as assessed by cardiac MRI and echocardiography, and evidence of myocardial ischemia diagnosed by single positron emission computed tomography. RESULTS: Median hs-cTnT concentration was 7.8 ng/L (interquartile range, 4.8 -11.6 ng/L), and 111 patients (18%) had hs-cTnT concentrations above the upper reference limit (amp;gt; 14 ng/L). Patients with hs-cTnT amp;gt; 14 ng/L had increased LV mass (144 +/- 40 g vs 116 +/- 34 g; P amp;lt; 0.001) and volume (179 +/- 80 mL vs 158 +/- 44 mL; P = 0.006), lower LV ejection fraction (LVEF) (59 +/- 14 vs 62 +/- 11; P = 0.006) and global longitudinal strain (14.1 +/- 3.4% vs 16.9 +/- 3.2%; P amp;lt; 0.001), and more reversible perfusion defects (P amp;lt; 0.001) and reversible wall motion abnormalities (P = 0.008). Age (P = 0.009), estimated glomerular filtration rate (P = 0.01), LV mass (P = 0.003), LVEF (P = 0.03), and evidence of reversible myocardial ischemia (P = 0.004 for perfusion defects and P = 0.02 for LV wall motion) were all associated with increasing hs-cTnT concentrations in multivariate analysis. We found analogous results when using the revised US upper reference limit of 19 ng/L. CONCLUSIONS: hs-cTnT concentrations reflect both LV mass and reversible myocardial ischemia in patients with suspected stable CAD. (c) 2018 American Association for Clinical Chemistry, Funding Agencies|Akershus University Hospital; Norwegian Research Council; South-Eastern Regional Health Authority; EU (FP7) framework program; South-Eastern Norway Regional Health Authority; Roche Diagnostics

Cardiovascular diseases are among the leading causes of death and frequently result in local myocardial dysfunction. Among the numerous imaging modalities available to detect these dysfunctional regions, cardiac deformation imaging through tagged magnetic resonance imaging (t-MRI) has been an attractive approach. Nevertheless, fully automatic analysis of these data sets is still challenging. In this work, we present a fully automatic framework to estimate left ventricular myocardial deformation from t-MRI. This strategy performs automatic myocardial segmentation based on B-spline explicit active surfaces, which are initialized using an annular model. A non-rigid image-registration technique is then used to assess myocardial deformation. Three experiments were set up to validate the proposed framework using a clinical database of 75 patients. First, automatic segmentation accuracy was evaluated by comparing against manual delineations at one specific cardiac phase. The proposed solution showed an average perpendicular distance error of 2.35 +/- 1.21 mm and 2.27 +/- 1.02 mm for the endo- and epicardium, respectively. Second, starting from either manual or automatic segmentation, myocardial tracking was performed and the resulting strain curves were compared. It is shown that the automatic segmentation adds negligible differences during the strain-estimation stage, corroborating its accuracy. Finally, segmental strain was compared with scar tissue extent determined by delay-enhanced MRI. The results proved that both strain components were able to distinguish between normal and infarct regions. Overall, the proposed framework was shown to be accurate, robust, and attractive for clinical practice, as it overcomes several limitations of a manual analysis., Funding Agencies|FCT-Fundacao para a Ciencia e a Tecnologia, Portugal [SFRH/BD/95438/2013, SFRH/BD/93443/2013]; European Social Found, European Union [SFRH/BD/95438/2013, SFRH/BD/93443/2013]; Programa Operacional Regional do Norte, Quadro de Referencia Estrategico Nacional, through Fundo Europeu de Desenvolvimento Regional (FEDER) [NORTE-07-0124-FEDER-000017, NORTE-01-0145-FEDER-000013]; EU (FP7) framework program [223615]

Aims This study aims at validating a software tool for automated segmentation and quantification of the left atrium (LA) from 3D echocardiography. Methods and results The LA segmentation tool uses a dual-chamber model of the left side of the heart to automatically detect and track the atrio-ventricular plane and the LA endocardium in transthoracic 3D echocardiography. The tool was tested in a dataset of 121 ultrasound images from patients with several cardiovascular pathologies (in a multi-centre setting), and the resulting volumes were compared with those assessed manually by experts in a blinded analysis using conventional contouring. Bland-Altman analysis showed good agreement between the automated method and the manual references, with differences (mean +/- 1.96 SD) of 0.5 +/- 5.7 mL for LA minimum volume and -1.6 +/- 9.7 mL for LA maximum volume (comparable to the inter-observer variability of manual tracings). The automated tool required no user interaction in 93% of the recordings, while 4% required a single click and only 2% required contour adjustments, reducing considerably the amount of time and effort required for LA volumetric analysis. Conclusion The automated tool was validated in a multi-centre setting, providing quantification of the LA volume over the cardiac cycle with minimal user interaction. The results of the automated analysis were in agreement with those estimated manually by experts. This study shows that such approach has clinical utility for the assessment of the LA morphology and function, automating and facilitating the time-consuming task of analysing 3D echocardiographic recordings., Funding Agencies|European Union under a Marie Curie Initial Training Network USART-project [PITN-GA-2012-317132]; DOPPLER-CIP project (EU FP7 framework programme) [223615]

The aim of this study was to analyze the whole temporal profiles of the segmental deformation curves of the left ventricle (LV) and describe their interrelations to obtain more detailed information concerning global LV function in order to be able to identify abnormal changes in LV mechanics. The temporal characteristics of the segmental LV deformation curves were compactly described using an efficient decomposition into major patterns of variation through a statistical method, called Principal Component Analysis (PCA). In order to describe the spatial relations between the segmental traces, the PCA-derived temporal features of all LV segments were concatenated. The obtained set of features was then used to build an automatic classification system. The proposed methodology was applied to a group of 60 MRI-delayed enhancement confirmed infarct patients and 60 controls in order to detect myocardial infarction. An average classification accuracy of 87% with corresponding sensitivity and specificity rates of 89% and 85%, respectively was obtained by the proposed methodology applied on the strain rate curves. This classification performance was better than that obtained with the same methodology applied on the strain curves, reading of two expert cardiologists as well as comparative classification systems using only the spatial distribution of the end-systolic strain and peak-systolic strain rate values. This study shows the potential of machine learning in the field of cardiac deformation imaging where an efficient representation of the spatio-temporal characteristics of the segmental deformation curves allowed automatic classification of infarcted from control hearts with high accuracy.

Cardiac volume/function assessment remains a critical step in daily cardiology, and 3-D ultrasound plays an increasingly important role. Fully automatic left ventricular segmentation is, however, a challenging task due to the artifacts and low contrast-to-noise ratio of ultrasound imaging. In this paper, a fast and fully automatic framework for the full-cycle endocardial left ventricle segmentation is proposed. This approach couples the advantages of the B-spline explicit active surfaces framework, a purely image information approach, to those of statistical shape models to give prior information about the expected shape for an accurate segmentation. The segmentation is propagated throughout the heart cycle using a localized anatomical affine optical flow. It is shown that this approach not only outperforms other state-of-the-art methods in terms of distance metrics with a mean average distances of 1.81 +/- 0.59 and 1.98 +/- 0.66 mm at end-diastole and end-systole, respectively, but is computationally efficient (in average 11 s per 4-D image) and fully automatic., Funding Agencies|European Research Council under the European Union [281748]; FCT Fundacao para a Ciencia e a Tecnologia, Portugal [SFRH/BD/93443/2013]

Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left ventricular (LV) volume assessment. However, identification of the LV endocardium remains a challenging task, mainly because of the low tissue/blood contrast of the images combined with typical artifacts. Several semi and fully automatic algorithms have been proposed for segmenting the endocardium in RT3DE data in order to extract relevant clinical indices, but a systematic and fair comparison between such methods has so far been impossible due to the lack of a publicly available common database. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms developed to segment the LV border in RT3DE. A database consisting of 45 multivendor cardiac ultrasound recordings acquired at different centers with corresponding reference measurements from 3 experts are made available. The algorithms from nine research groups were quantitatively evaluated and compared using the proposed online platform. The results showed that the best methods produce promising results with respect to the experts' measurements for the extraction of clinical indices, and that they offer good segmentation precision in terms of mean distance error in the context of the experts' variability range. The platform remains open for new submissions., QC 20230927

The recent advent of three-dimensional echocardiography has led to an increased interest from the scientific community in left ventricle segmentation frameworks for cardiac volume and function assessment. An automatic orientation of the segmented left ventricular mesh is an important step to obtain a point-to-point correspondence between the mesh and the cardiac anatomy. Furthermore, this would allow for an automatic division of the left ventricle into the standard 17 segments and, thus, fully automatic per-segment analysis, e.g. regional strain assessment. In this work, a method for fully automatic short axis orientation of the segmented left ventricle is presented. The proposed framework aims at detecting the inferior right ventricular insertion point. 211 three-dimensional echocardiographic images were used to validate this framework by comparison to manual annotation of the inferior right ventricular insertion point. A mean unsigned error of 8, 05 degrees +/- 18, 50 degrees was found, whereas the mean signed error was 1, 09 degrees. Large deviations between the manual and automatic annotations (amp;gt; 30 degrees) only occurred in 3, 79% of cases. The average computation time was 666ms in a non-optimized MATLAB environment, which potentiates real-time application. In conclusion, a successful automatic real-time method for orientation of the segmented left ventricle is proposed.

Aims Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting. Methods and results Analyses of 318 CMR studies, acquired at the enrolment of patients in a multi-centre imaging trial (DOPPLER-CIP), were performed automatically, as well as manually. For comparative purposes, intra-and inter-observer variability was also assessed in a subset of patients. The extracted morphological and functional parameters were compared between both analyses, and time efficiency was evaluated. The automatic analysis was feasible in 95% of the cases (302/318) and showed a good agreement with manually derived reference measurements, with small biases and narrow limits of agreement particularly for end-diastolic volume (-4.08 +/- 8.98 mL), end-systolic volume (1.18 +/- 9.74 mL), and ejection fraction (-1.53 +/- 4.93%). These results were comparable with the agreement between two independent observers. A complete automatic analysis took 5.61 +/- 1.22 s, which is nearly 150 times faster than manual contouring (14 +/- 2 min, P amp;lt; 0.05). Conclusion The proposed automatic framework provides a fast, robust, and accurate quantification of relevant left ventricular clinical indices in real-world cine CMR images., Funding Agencies|FCT-Fundacao para a Ciencia e a Tecnologia, Portugal [SFRH/BD/93443/2013]; EU [223615]

Objectives. DOPPLER-CIP aims to determine the optimal noninvasive parameters (myocardial function, perfusion, ventricular blood flow, cell integrity) and methodology (ergometry, echocardiography, scintigraphy, MRI) in a given ischemic substrate that best predicts the impact of an intervention (or the lack thereof) on adverse morphological ventricular remodeling and functional recovery. Moreover, the relative predictive value of each of these parameters, in respect to the cost of extracting this information in order to enable optimization of cost-effectiveness for improved health care, will be determined by this project. Design. DOPPLER-CIP is a multi-center registry study. All patients with ischemic heart disease included in this study undergo at least two noninvasive stress imaging examinations at baseline. The presence/or absence of left ventricular (LV) remodeling will be assessed after a follow-up of 2 years, during which all cardiac events will be registered. Results. 676 patients were included. Currently, baseline data analysis is almost finished and the follow-up is ongoing. Conclusions. After completion, DOPPLER-CIP will provide evidence-based guidelines toward the most effective use of cardiac imaging in the chronically ischemic heart disease patient. The study will generate information, knowledge, and insight into the new imaging methodologies and into the pathophysiology of chronic ischemic heart disease., Funding Agencies|EU (FP7) framework program

Aims: Thrombospondin-2 (TSP-2) modulates matrix integrity and myocyte survival in the hypertensive or ageing heart. Whether TSP-2 may affect cardiac inflammation and injury, in particular during acute viral myocarditis, is completely unknown. Methods and results: Therefore, mortality, cardiac inflammation, and function were assessed in TSP-2-null (KO) and wild-type (WT) mice in human Coxsackie virus B3 (CVB3)-induced myocarditis. TSP-2 KO had an increased mortality when compared with WT mice during viral myocarditis. The absence of TSP-2 resulted in increased cardiac inflammation and injury at 14 days, which resulted in depressed systolic function [fractional shortening (FS); 34 ± 2.6 in WT vs. 24 ± 1.8 in KO mice, P< 0.05] and increased cardiac dilatation (end-diastolic dimensions, mm; 3.7 ± 0.09 in WT vs. 4.8 ± 0.06 in KO mice, P< 0.05) 35 days post-infection. Lack of TSP-2 resulted in a decreased activation of the anti-inflammatory T-regulatory cells, as indicated by a lower number of CD25-positive T-cells, and significantly decreased gene expression of regulatory T-cell markers, Foxp3 and CTLA-4. Finally, overexpression of TSP-2 in WT hearts using cardiotropic vectors derived from adeno-associated virus serotype 9 (AAV9) inhibited cardiac inflammation and injury at 14 days and improved cardiac function at 35 days post-CVB3 infection when compared with control AAV9. Conclusion: TSP-2 has a protective role against cardiac inflammation, injury, and dysfunction in acute viral myocarditis. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2012., SCOPUS: ar.j, info:eu-repo/semantics/published