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206 results on '"N. Bettencourt"'

3. Simplified and Detailed Evaluations of the Uncertainty of the Measurement of Microbiological Contamination of Pharmaceutical Products.

Author

Lourenço, Felipe Rebello and Silva, Ricardo J N Bettencourt da

Subjects
*MICROBIAL contamination, *LOGNORMAL distribution, *POISSON regression, *POISSON distribution, *MICROBIAL growth, *PREDICATE calculus
Abstract

Background The control of the microbial contamination of pharmaceutical products (PP) is crucial to ensure their safety and efficacy. The validity of the monitoring of such contamination depends on the uncertainty of this quantification. Highly uncertain quantifications due to the variability of determinations or the magnitude of systematic effects affecting microbial growth or other analytical operations make analysis unfit for the intended use. The quantification of the measurement uncertainty expressing the combined effects of all random and systematic effects affecting the analysis allows for a sound decision about quantification adequacy for their intended use. The complexity of the quantification of microbial analysis uncertainty led to the development of simplified ways of performing this evaluation. Objective This work assesses the adequacy of the simplified quantification of the uncertainty of the determination of the microbial contamination of PP by log transforming microbial count and dilution factor of the test sample whose uncertainty is combined in a log scale using the uncertainty propagation law. Methods This assessment is performed by a parallel novel bottom-up and accurate evaluation of microbial analysis uncertainty involving the Monte Carlo method simulation of the Poisson log-normal distribution of counts and of the normally distributed measured volumes involved in the analysis. Systematic effects are assessed and corrected on results to compensate for their impact on the determinations. Poisson regression is used to predict precision affecting determinations on unknown test samples. Result Simplified and detailed models of the uncertainty of the measurement of the microbial contamination of PP are provided, allowing objective comparisons of several determinations and those with a maximum contamination level. Conclusions This work concludes that triplicate determinations are required to produce results with adequately low uncertainty and that simplified uncertainty quantification underevaluates or overevaluates the uncertainty from determinations based on low or high colony numbers, respectively. Therefore, detailed uncertainty evaluations are advised for determinations between 50 and 200% of PP's maximum admissible contamination value Highlight User-friendly tools for detailed and simplified evaluations of the uncertainty of the measurement of microbial contamination of PP are provided together with the understanding of when simplifications are adequate. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Teaching Metrology and Examinology in Chemistry at the University

Author

Ricardo J. N. Bettencourt da Silva

Subjects
University course, metrology, examinology, chemistry, General Works
Abstract

This communication presents the teaching experience of Ricardo Bettencourt da Silva in the scientific areas of metrology and examinology in chemistry at various universities.

Published
2020
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8. Determination of Intrinsic and Metrological Correlations of Components of Product Impact on Risks of False Decisions in Conformity Assessment

Author

Luciana Separovic, Ricardo J. N. Bettencourt da Silva, and Felipe Rebello Lourenço

Subjects
covariance, correlation, drug association, conformity assessment, General Works
Abstract

The correlation between the measured values of product components can influence the total risk of false decisions in conformity assessment. This correlation can originate from the characteristics of the product (intrinsic) or from how the components are measured (metrological). This work aimed to determine both correlations by testing a medicine with two compounds separately and together (correlated). The same intrinsic correlation was estimated regardless of whether the measurements were independent or correlated. Furthermore, the intrinsic covariance contributed significantly to the total covariance between the components evaluated. Both metrological and intrinsic correlations should be considered, as they can affect the risks of false decisions in conformity assessment when there are two or more compounds associated in the product.

Published
2020
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11. Bottom-Up Evaluation of the Uncertainty of the Quantification of Microplastics Contamination in Sediment Samples

Author

Vanessa Morgado, Carla Palma, and Ricardo J. N. Bettencourt da Silva

Subjects
Geologic Sediments, Microplastics, Uncertainty, Environmental Chemistry, General Chemistry, Plastics, Water Pollutants, Chemical, Environmental Monitoring
Abstract

The quantification and comparison of microplastic contamination of sediments are affected by sample heterogeneity and the systematic and random effects affecting sample analysis. The quantification and combination of these components in the measurement uncertainty allows the objective interpretation of analysis results. This work presents the first detailed evaluation of the uncertainty of microplastic contamination quantification in sediments. The random and systematic effects affecting microplastic counts are modeled by the Poisson-lognormal distribution with inputs estimated from duplicate sediment analysis and the analysis of sediments spiked with microparticles. The uncertainty from particle counting was combined with the uncertainty from the determination of the dry mass of the analytical portion by the Monte Carlo method. The developed methodology was implemented in a user-friendly spreadsheet made available as the Supporting Information. The contamination of sediment samples collected in various inland Portuguese waters was determined, ranging from [0; 160] to [361; 2932] kg

Published
2022

12. Bottom-up uncertainty evaluation of complex measurements from correlated performance data: Determination of total Cr in yeast by ICP-MS after acid digestion

Author

Tomáš, Pluháček, Radka, Pechancová, David, Milde, and Ricardo J N, Bettencourt da Silva

Subjects
Yeast, Dried, Uncertainty, Digestion, Saccharomyces cerevisiae, General Medicine, Acids, Mass Spectrometry, Food Science, Analytical Chemistry
Abstract

The objective interpretation of a measurement result requires knowing the associated uncertainty. The cost-effective collection of measurement performance data on the same day produces correlated values that can affect measurement uncertainty evaluation. This work describes a novel methodology for the bottom-up evaluation of measurements based on complex sample pretreatment and the instrumental quantification of the prepared sample applicable to correlated inputs. The numerical Kragten method is used to combine the uncertainty components shared in various analyte recovery determinations. The developed methodology was applied to the determination of total chromium in yeast samples by ICP-MS after microwave-assisted acid digestion. The developed analysis of yeast samples is fit for monitoring the contamination of this product since it is associated with a relative expanded uncertainty, U', lower than 20%, ranging from 8.4% to 10.0% in determinations of Cr between 0.125 mg/kg and 305.5 mg/kg. Duplicate analyses are adequate for reference materials production (U' 7%).

Published
2023
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14. Microplastics contamination in sediments from Portuguese inland waters: Physical-chemical characterisation and distribution

Author

Vanessa, Morgado, Luís, Gomes, Ricardo J N, Bettencourt da Silva, and Carla, Palma

Subjects
Geologic Sediments, Environmental Engineering, Portugal, Microplastics, Environmental Chemistry, Plastics, Pollution, Waste Management and Disposal, Water Pollutants, Chemical, Environmental Monitoring
Abstract

Plastics are the major constituent of waste accumulated in inland waters and subsequently transferred to the ocean. The smaller plastic particles, typically obtained from the fragmentation of larger pieces, are vehicles for food chain accumulation of plastic components and contaminants sorbed to these particles through their ingestion by small organisms. The monitoring of the level and trends of the contamination by microplastics is essential to determine the relevance and potential sources of this contamination necessary to define strategies to reduce this threat. This work presents microplastic contamination levels and trends of sediments of four Portuguese inland waters, namely Ria de Aveiro, Ria Formosa, Mira river, and Mondego river, between 02/2019 and 09/2020. The contamination is classified considering the type of polymer and size, shape, and colour of particles. Polymers are identified by micro-ATR-FTIR with true and false identification rates larger and lower than 95% and 5%, respectively. Duplicate analysis results are used to quantify contamination heterogeneity subsequently applied to assess if a specific contamination trend is not meaningful for a 99% confidence level. The analytical procedure is described in detail to clarify the scope of the analysis. Tests' quality is controlled by following strict quality control measures. Results from sixty-three sediment samples proved the ubiquitous presence of microplastic (MP) in these inland waters with contamination levels ranging between 20 MP kg

Published
2022
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15. Evaluation and validation of detailed and simplified models of the uncertainty of unified [Formula: see text] measurements in aqueous solutions

Author

Ricardo J N Bettencourt, da Silva, Jaan, Saame, Bárbara, Anes, Agnes, Heering, Ivo, Leito, Teemu, Näykki, Daniela, Stoica, Lisa, Deleebeeck, Frank, Bastkowski, Alan, Snedden, and M Filomena, Camões

Subjects
Uncertainty, Computer Simulation, Monte Carlo Method
Abstract

The use of the unified pH concept, [Formula: see text] , applicable to aqueous and non-aqueous solutions, which allows interpreting and comparison of the acidity of different types of solutions, requires reliable and objective determination. The [Formula: see text] can be determined by a single differential potentiometry measurement referenced to an aqueous reference buffer or by a ladder of differential potentiometric measurements that allows minimisation of inconsistencies of various determinations. This work describes and assesses bottom-up evaluations of the uncertainty of these measurements, where uncertainty components are combined by the Monte Carlo Method (MCM) or Taylor Series Approximation (TSM). The MCM allows a detailed simulation of the measurements, including an iterative process involving in minimising ladder deviations. On the other hand, the TSM requires the approximate determination of minimisation uncertainty. The uncertainty evaluation was successfully applied to measuring aqueous buffers with pH of 2.00, 4.00, 7.00, and 10.00, with a standard uncertainty of 0.01. The reference and estimated values from both approaches are metrologically compatible for a 95% confidence level even when a negligible contribution of liquid junction potential uncertainty is assumed. The MCM estimated pH values with an expanded uncertainty, for the 95% confidence level, between 0.26 and 0.51, depending on the pH value and ladder inconsistencies. The minimisation uncertainty is negligible or responsible for up to 87% of the measurement uncertainty. The TSM quantified measurement uncertainties on average only 0.05 units larger than the MCM estimated ones. Additional experimental tests should be performed to test these uncertainty models for analysis performed in other laboratories and on non-aqueous solutions.

Published
2021

18. USE OF MONTE CARLO SIMULATIONS FOR THE CALCULATION OF THE UNCERTAINTY ESTIMATE IN THE ELECTROCHEMICAL DETECTION OF URIC ACID IN PLASMA SAMPLES

Author

Airton J. Damaceno, T. R. de L. Dadamos, R. J. N. Bettencourt Silva, and Fernando Luis Fertonani

Subjects
Multidisciplinary, Uncertainty estimate, Plasma samples, Monte Carlo method, Analytical chemistry, Environmental science, Measurement uncertainty, General Chemistry, Pharmacy, Electrochemical detection, Education
Abstract

This work presents a low cost, simple and adequately reliable electrochemical alternative for the determination of uric acid in human serum in comparison to the enzymatic colorimetric reference method. The quality of the electrochemical measurements was assessed by comparing its uncertainty with a target value of 0.56 mg dL-1 and the measurements were carried out by the standard addition method. The modified working electrode consists of 25% lignin, 60% nanocarbon, 15% mineral oil and electrodeposited metallic copper. The uncertainty of measurement was estimated by the bottom-up approach, from which uncertainty components were combined by applying the uncertainty propagation law (LPI), the numerical method of Kragten and the Monte Carlo Simulation Method (MCM). The analytical procedure was successfully applied in the analysis of physiological sera added at 1.0, 3.0, 5.0, 7.0 and 9.0 mg dL-1 of AU and for two other samples of human saline. The results of the measurements carried out for the different serum samples using the proposed method, associated to the different methods for estimating the uncertainty, showed sufficiently low and metrologically equivalent values, in which the results were shown to be compatible with the estimated reference values.

Published
2018
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20. Calibration of a portable X-ray fluorescence spectrometer in the analysis of archaeological samples using influence coefficients

Author

A. Van Hoose, J. A. Wolff, Melissa Goodman-Elgar, A. Seyfarth, N. Bettencourt, and Richard M. Conrey

Subjects
Correction method, Chemistry, Mineralogy, General Chemistry, Archaeology, Spectral line, Absorbance, Wavelength, Geochemistry and Petrology, Calibration, General Earth and Planetary Sciences, Portable X-ray, Statistical analysis, Fluorescence spectrometer, General Environmental Science
Abstract

This paper responds to the expanding interest in archaeology in the use of portable X-Ray fluorescence (pXRF) technologies. Accurate analysis using pXRF requires correction for absorbance and secondary enhancement of the excited element X-rays by the other elements present. Several correction methods are widely used, including fundamental parameters, influence coefficients, Compton ratioing, multi-variate statistical analysis, and dilution. Most pXRF calibrations use either fundamental parameters or multi-variate statistics. However, influence coefficients are known to be the most certain calibration method for XRF analysis of geological materials. Portable XRF calibrations using influence coefficients in the analysis of obsidian, flint, mudbrick, and sediment have far less bias and include a wider range of elements (Mg through Ce) than multi-variate statistical or fundamental parameter calibrations using beam filtered spectra. Bias v. wavelength dispersive XRF data using influence coefficients is mostly less than 1 % for obsidian and flint, and less than 2 % for mudbrick and sediment, in contrast with the large biases (up to 36 %) found using fundamental parameters or multi-variate statistical methods.

Published
2014
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21. Moderated Posters session: cardiovascular magnetic resonanceP967Simplified segmental calculation of extracellular volume with T1 mapping for evaluation of diffuse interstitial fibrosisP968Diffuse myocardial fibrosis quantification by magnetic resonance imaging in patients with aortic valve diseasesP969Occult anthracycline cardiac injury in adolescents and young adults cancer survivors with normal left ventricular ejection fractionP970Reference values for regional and global myocardial T2 mapping with cardiovascular magnetic resonance at 1.5T vs 3TP971The accuracy of a real-time MR method in the assessment of right ventricular volume and functionP972Can blunted heart rate response to adenosine vasodilator stress have prognostic implications on myocardial perfusion imaging by cardiovascular magnetic resonance?P973Association of vitamin d with left atrial fibrosis in patients with lone AF undergoing cryoablationP974Left ventricular remodelling after mitral valve reconstruction: a 1-year prospective cMRI studyP975Abnormal regional myocardial motion in patients with left ventricular pressure overload detected by MR tissue phase mapping at rest and during stressP976Potential utility of splenic switch-off to improve the diagnostic performance of vasodilator stress cardiac magnetic resonance. Preliminary study

Author

E Castillo, F Von Knobelsdorff, I Kammerer, N Ozer, V Ramos, J Kowal, A M Maceira Gonzalez, MS Vieira, O-A Nastase, P Bazal, F Olaz, V Alvarez, R Sadaba, M Ciriza, V Arrieta, E Escribano, MT Beunza, S G Solana, N Lopez, M Amzulescu, L Boileu, M Page, C De Meester, J Boulif, S Lazam, A-C Pouleur, J-L Vanoverschelde, B-L Gerber, J Kowallick, I Rafiq, R Chabiniok, A Figueroa, R Carr, T Hussain, B Igual, JV Monmeneu, P Lopez-Lereu, MP Garcia, JV Cosin-Sales, J Bigaj, A Hazik, Z Kulisiewicz, M Slupska, J Bitt, J Silva, N Ferreira, N Bettencourt, V Gama, U Canpolat, K Aytemir, T Hazirolan, H Yorgun, A Oto, G Layer, A-H Kiessling, FU Sack, P Hennig, M Menza, MA Dieringer, D Foell, B Jung, J Schulz-Menger, A Maceira, A Llopis, O Velez, and L Tebar

Subjects
Radiology, Nuclear Medicine and imaging, General Medicine, Cardiology and Cardiovascular Medicine
Published
2015
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22. Poster Session 3: Friday 9 December 2011, 08:30-12:30 * Location: Poster Area

Author

C. Kenny, S. Adhya, R. Dworakowski, B. Brickham, P. Maccarthy, M. Monaghan, A. Guzzo, F. Innocenti, S. Vicidomini, D. Lazzeretti, S. Squarciotta, E. De Villa, C. Donnini, F. Bulletti, E. Guerrini, R. Pini, K. Bendjelid, J. Viale, S. Duperret, V. Piriou, D. Jacques, K. Shahgaldi, C. Silva, F. Pedro, L. Deister, L.-A. Brodin, A. Sahlen, A. Manouras, R. Winter, N. Berjeb, C. Cimadevilla, J. Dreyfus, C. Cueff, M. Malanca, A. Chiampan, A. Vahanian, D. Messika-Zeitoun, D. Muraru, D. Peluso, L. Dal Bianco, M. Beraldo, E. Solda', M. Tuveri, U. Cucchini, A. Al Mamary, L. Badano, S. Iliceto, I. Almuntaser, G. King, S. Norris, C. Daly, E. Ellis, R. Murphy, T. Erdei, M. Denes, A. Kardos, C. Foldesi, A. Temesvari, M. Lengyel, A. Bouzas Mosquera, F. Broullon, N. Alvarez-Garcia, J. Peteiro, G. Barge-Caballero, M. Lopez-Perez, A. Lopez-Sainz, A. Castro-Beiras, M. Luotolahti, H. Luotolahti, I. Kantola, J. Viikari, M. Andersen, M. Ersboell, J. Bro-Jeppesen, F. Gustafsson, L. Koeber, C. Hassager, J. Moller, D. Coisne, C. Diakov, F. Vallet, B. Lequeux, P. Blouin, L. Christiaens, R. Esposito, A. Santoro, V. Schiano Lomoriello, R. Raia, C. Santoro, G. De Simone, M. Galderisi, G. Abdula, W. Kosmala, H. Szczepanik-Osadnik, M. Przewlocka-Kosmala, A. Mysiak, T. O' Moore-Sullivan, T. Marwick, Y. T. Tan, F. Wenzelburger, F. Leyva, J. Sanderson, P. Pichler, B. Syeda, P. Hoefer, A. Zuckermann, T. Binder, M. Fijalkowski, A. Koprowski, R. Galaska, K. Blaut, K. Sworczak, A. Rynkiewicz, S. Lee, W. Kim, L. Jung, H. Yun, M. Song, J. Ko, E. A. Khalifa, P. Szymanski, M. Lipczynska, A. Klisieiwcz, P. Hoffman, C. Jorge, J. Silva Marques, S. Robalo Martins, C. Calisto, M. Mieiro, S. Vieira, M. Correia, J. Carvalho De Sousa, A. Almeida, A. Nunes Diogo, C. Park, K. March, T. Tillin, J. Mayet, N. Chaturvedi, A. Hughes, V. Di Bello, C. Giannini, M. Delle Donne, F. De Sanctis, P. Spontoni, C. Cucco, A. Corciu, C. Grigoratos, F. Bogazzi, A. Balbarini, O. Enescu, B. Suran, M. Florescu, M. Cinteza, D. Vinereanu, Y. Higuchi, K. Iwakura, A. Okamura, M. Date, K. Fujii, N. Cortez-Dias, D. Silva, P. Carrilho-Ferreira, A. Magalhaes, S. Ribeiro, S. Goncalves, M. Fiuza, F. Pinto, R. Placido, A. Bordalo, P. Grzywocz, K. Mizia-Stec, J. Chudek, Z. Gasior, A. M. Maceira Gonzalez, J. Cosin Sales, E. Dalli, B. Igual, J. Diago, J. Aguilar, J. Ruvira, S. Cimino, G. Pedrizzetti, G. Tonti, E. Canali, V. Petronilli, F. Boccalini, A. Mattatelli, Y. Hiramoto, C. Iacoboni, L. Agati, D. Trifunovic, M. Ostojic, B. Vujisic-Tesic, M. Petrovic, I. Nedeljkovic, M. Banovic, M. Boricic-Kostic, G. Draganic, M. Tesic, C. Gavina, R. Lopes, A. Lourenco, J. Almeida, J. Rodrigues, P. Pinho, J. Zamorano, A. Leite-Moreira, F. Rocha-Goncalves, M.-A. Clavel, R. Capoulade, J. Dumesnil, P. Mathieu, J.-P. Despres, P. Pibarot, S. Bull, A. Pitcher, D. Augustine, J. D'arcy, T. Karamitsos, A. Rai, B. Prendergast, H. Becher, S. Neubauer, S. Myerson, J. Magne, E. Donal, L. Davin, K. O'connor, C. Pirlet, M. Rosca, C. Szymanski, B. Cosyns, L. Pierard, P. Lancellotti, A. Calin, B. Popescu, C. Beladan, R. Enache, L. Lupascu, C. Sandu, C. Ginghina, V. Kamperidis, S. Hadjimiltiadis, G. Sianos, K. Anastasiadis, V. Grosomanidis, G. Efthimiadis, H. Karvounis, G. Parharidis, I. Styliadis, C. Gonzalez Canovas, C. Munoz-Esparza, J. Bonaque Gonzalez, A. Fernandez, M. Salar Alcaraz, D. Saura Espin, E. Pinar Bermudez, M. Oliva-Sandoval, G. De La Morena Valenzuela, M. Valdes Chavarri, E. Brochet, L. Lepage, D. Attias, D. Detaint, D. Himbert, B. Iung, B. Pirat, S. Little, S. Chang, L. Tiller, R. Kumar, W. Zoghbi, A. P.-W. Lee, M. Hsiung, S. Wan, R. Wong, F. Luo, F. Fang, J. Xie, M. Underwood, J. Sun, C. Yu, R. Jansen, W. Tietge, K. Sijbrandij, M. Cramer, L. De Heer, J. Kluin, S. A. J. Chamuleau, T. Oliveras Vila, E. Ferrer Sistach, L. Delgado Ramis, J. Lopez Ayerbe, N. Vallejo Camazon, F. Gual Capllonch, C. Garcia Alonso, A. Teis Soley, X. Ruyra Baliarda, A. Bayes Genis, S. Negrea, C. Alexandrescu, F. Bourlon, F. Civaia, G. Dreyfus, S. Paetzold, O. Luha, R. Hoedl, G. Stoschitzky, K. Pfeiffer, D. Zweiker, B. Pieske, R. Maier, T. Sevilla, A. Revilla, J. Lopez, I. Vilacosta, R. Arnold, I. Gomez, J. San Roman, G. Nikcevic, A. Djordjevic Dikic, S. Djordjevic, S. Raspopovic, V. Jovanovic, B. Kircanski, S. Pavlovic, G. Milasinovic, I. Ruiz-Zamora, F. Cabrera Bueno, M. Molina, J. Fernandez-Pastor, J. Pena, A. Linde, A. Barrera, J. Alzueta, C. Bremont, A. Bensaid, H. Alonso, O. Zaghden, J. Nahum, J. Dubois-Rande, P. Gueret, P. Lim, S.-P. Lee, K. Park, H.-R. Kim, J.-H. Lee, H.-S. Ahn, J.-H. Kim, H.-K. Kim, Y.-J. Kim, D.-W. Sohn, M. Niemann, S. Herrmann, K. Hu, D. Liu, M. Beer, G. Ertl, C. Wanner, T. Takenaka, C. Tei, F. Weidemann, H. Madeira, M. Mendes Pedro, D. Brito, R. Ippolito, D. De Palma, S. Gati, D. Oxborough, M. Reed, A. Zaidi, S. Ghani, N. Sheikh, M. Papadakis, S. Sharma, V. Chow, A. Ng, T. Pasqualon, W. Zhao, D. Hanzek, T. Chung, T. Yeoh, L. Kritharides, L. Magda, D. Mihalcea, D. Jinga, R. Mincu, E. Ferrazzi, G. Segato, F. Folino, G. Famoso, M. Senzolo, R. Bellu, F. Corbetti, F. Tona, O. Azevedo, I. Quelhas, J. Guardado, M. Fernandes, V. Pereira, R. Medeiros, P. Sousa, W. Santos, S. Pereira, N. Marques, J. Mimoso, V. Marques, I. Jesus, L. Rustad, K. Nytroen, L. Gullestad, B. Amundsen, S. Aakhus, K. Linhartova, G. Sterbakova, J. Necas, S. Kovalova, R. Cerbak, N. Nelassov, N. Korotkijan, A. Shishkina, B. Gagieva, M. Nagaplev, O. Eroshenko, M. Morgunov, S. Parmon, S. Velthuis, M. Van Gent, M. Post, C. Westermann, J. Mager, R. Snijder, S. P. Koyalakonda, M. Anderson, M. Burgess, L. Bergenzaun, M. Chew, H. Ohlin, G. F. Gjerdalen, J. Hisdal, E. Solberg, T. Andersen, Z. Radunovic, K. Steine, T. Rutz, A. Kuehn, K. Petzuch, M. Pekala, J. Elmenhorst, S. Fratz, J. Mueller, A. Hager, J. Hess, M. Vogt, D. Van Der Linde, I. Van De Laar, M. Wessels, J. Bekkers, A. Moelker, H. Tanghe, F. Van Kooten, R. Oldenburg, A. Bertoli-Avella, J. Roos-Hesselink, A. Cresti, L. Fontani, P. Calabria, E. Capati, S. Severi, M. Lynch, S. Saraf, B. Sandler, S. Yoon, S. Kim, C. Ko, S. Ryu, Y. Byun, H. Seo, Q. Ciampi, F. Rigo, L. Pratali, S. Gherardi, B. Villari, E. Picano, R. Sicari, J. Celutkiene, D. Zakarkaite, V. Skorniakov, V. Zvironaite, V. Grabauskiene, J. Sinicyna, G. Gruodyte, K. Janonyte, A. Laucevicius, J. O'driscoll, K. Schmid, A. Marciniak, A. Saha, S. Gupta, R. Smith, R. Sharma, N. Alvarez Garcia, O. Prada, A. Rodriguez Vilela, G. Barge Caballero, M. Lopez Perez, A. Lopez Sainz, A. Castro Beiras, J. Kochanowski, P. Scislo, R. Piatkowski, M. Grabowski, M. Marchel, M. Roik, D. Kosior, G. Opolski, C. M. Van De Heyning, H. Mahjoub, H. Clausen, C. Basaggianis, J. Newton, A. Del Pasqua, A. Carotti, D. Di Carlo, E. Cetrano, A. Toscano, R. Iacobelli, C. Esposito, M. Chinali, G. Pongiglione, G. Rinelli, M. Larsson, A. Bjallmark, K. Caidahl, L. Brodin, H. Gao, M. Lugiez, C. Guivier, R. Rieu, J. D'hooge, G. Hang, C. Guerin, M. Menard, J.-U. Voigt, J. Dungu, G. Campos, R. Jaffarulla, S. Gomes-Pereira, N. Sutaria, C. Baker, P. Nihoyannopoulos, M. Bellamy, D. Harries, N. Walker, P. Pearson, J. Reiken, J. Batteson, R. Kamdar, F. Murgatroyd, A. D'andrea, L. Riegler, R. Scarafile, E. Pezzullo, G. Salerno, E. Bossone, G. Limongelli, M. Russo, G. Pacileo, R. Calabro', Y. Kang, J. Cui, H. Chen, C. Pan, X. Shu, A. Kiotsekoglou, S. Saha, R. Toole, S. Govind, A. Gopal, F. Crispi, B. Bijnens, E. Sepulveda-Swatson, J. Rojas-Benavente, J. Dominguez, M. Illa, E. Eixarch, M. Sitges, E. Gratacos, C. Prinz, R. Faludi, A. Walker, M. Amzulescu, T. Uejima, A. Fraser, J. Voigt, M. Esmaeilzadeh, M. Maleki, A. Amin, F. Vakilian, F. Noohi, Z. Ojaghi Haghighi, P. Nakhostin Davari, H. Bakhshandeh Abkenar, R. Rimbas, R. Dulgheru, A. Margulescu, M. D' Asaro, C. Mizzon, F. Parisi, B.-C. Jung, B.-Y. Lee, H.-J. Kang, M. Kim, Y. Kim, D. Cho, S. Park, S. Hong, D. Lim, W. Shim, H. Bellsham-Revell, S. Tibby, A. J. Bell, O. I. Miller, G. Greil, J. M. Simpson, R. A. Providencia, J. Trigo, A. Botelho, P. Gomes, L. Seca, S. Barra, A. Faustino, G. Costa, N. Quintal, A. Leitao-Marques, E. Nestaas, A. Stoylen, D. Fugelseth, C. Mornos, A. Ionac, L. Petrescu, D. Cozma, D. Dragulescu, A. Mornos, S. Pescariu, A. Fontana, M. Abbate, M. Cazzaniga, C. Giannattasio, G. Trocino, K. Laser, L. Faber, M. Fischer, H. Koerperich, D. Kececioglu, M. F. Elnoamany, A. Dawood, M. Elhabashy, Y. Khalil, N. Piriou, K. Warin-Fresse, M. Caza, G. Fau, D. Crochet, N. Xhabija, I. Allajbeu, E. Petrela, M. Heba, M. Barreiro Perez, M. Martin Fernandez, A. Renilla Gonzalez, J. Florez Munoz, O. Fernandez Cimadevilla, I. Alvarez Pichel, E. Velasco Alonso, D. Leon Duran, E. Benito Martin, S. Secades Gonzalez, L. Gargani, P. Pang, E. Davis, A. Schumacher, A. Silva Ferreira, N. Bettencourt, P. Matos, L. Oliveira, J. Cosin-Sales, M. Lopez Lereu, J. Monmeneu, J. Estornell, M. Tsverava, D. Tsverava, A. Varela, M. Salagianni, I. Galani, E. Andreakos, C. Davos, I. Ikonomidis, J. Lekakis, V. Tritakis, N. Kadoglou, J. Papadakis, P. Trivilou, S. Tzortzis, C. Koukoulis, I. Paraskevaidis, M. Anastasiou-Nana, G. Kim, H. Youn, P. Ibrahimi, G. Bajraktari, F. Jashari, A. Ahmeti, A. Poniku, E. Haliti, M. Henein, B. Pezo Nikolic, H. Jurin, D. Lovric, Z. Baricevic, I. Ivanac Vranesic, M. Lovric Bencic, A. Ernst, and J. Separovic Hanzevacki

Subjects
Novel technique, business.industry, Medicine, Radiology, Nuclear Medicine and imaging, Computer vision, Nanotechnology, General Medicine, Contrast (music), Artificial intelligence, Cardiology and Cardiovascular Medicine, business
Published
2011
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23. Abstracts

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V. Dunet, A. Dabiri, G. Allenbach, A. Goyeneche Achigar, B. Waeber, F. Feihl, R. Heinzer, J. O. Prior, J. E. Van Velzen, J. D. Schuijf, F. R. De Graaf, M. A. De Graaf, M. J. Schalij, L. J. Kroft, A. De Roos, J. W. Jukema, E. E. Van Der Wall, J. J. Bax, E. Lankinen, A. Saraste, T. Noponen, R. Klen, M. Teras, T. Kokki, S. Kajander, M. Pietila, H. Ukkonen, J. Knuuti, A. P. Pazhenkottil, R. N. Nkoulou, J. R. Ghadri, B. A. Herzog, R. R. Buechel, S. M. Kuest, M. Wolfrum, O. Gaemperli, L. Husmann, P. A. Kaufmann, D. Andreini, G. Pontone, S. Mushtaq, L. Antonioli, E. Bertella, A. Formenti, S. Cortinovis, G. Ballerini, C. Fiorentini, M. Pepi, A. S. Koh, J. S. Flores, F. Y. J. Keng, R. S. Tan, T. S. J. Chua, A. D. Annoni, G. Tamborini, M. Fusari, A. L. Bartorelli, S. H. Ewe, A. C. T. Ng, V. Delgado, J. Schuijf, F. Van Der Kley, A. Colli, A. De Weger, N. A. Marsan, K. H. Yiu, A. C. Ng, S. A. J. Timmer, P. Knaapen, T. Germans, P. A. Dijkmans, M. Lubberink, J. M. Ten Berg, F. J. Ten Cate, I. K. Russel, A. A. Lammertsma, A. C. Van Rossum, Y. Y. Wong, G. Ruiter, P. Raijmakers, W. J. Van Der Laarse, N. Westerhof, A. Vonk-Noordegraaf, G. Youssef, E. Leung, G. Wisenberg, C. Marriot, K. Williams, J. Etele, R. A. Dekemp, J. Dasilva, D. Birnie, R. S. B. Beanlands, R. C. Thompson, A. H. Allam, L. S. Wann, A. H. Nureldin, G. Adelmaksoub, I. Badr, M. L. Sutherland, J. D. Sutherland, M. I. Miyamoto, G. S. Thomas, H. J. Harms, S. De Haan, M. C. Huisman, R. C. Schuit, A. D. Windhorst, C. Allaart, A. J. Einstein, T. Khawaja, C. Greer, A. Chokshi, M. Jones, K. Schaefle, K. Bhatia, D. Shimbo, P. C. Schulze, A. Srivastava, R. Chettiar, J. Moody, C. Weyman, D. Natale, W. Bruni, Y. Liu, E. Ficaro, A. J. Sinusas, A. Peix, E. Batista, L. O. Cabrera, K. Padron, L. Rodriguez, B. Sainz, V. Mendoza, R. Carrillo, Y. Fernandez, E. Mena, A. Naum, T. Bach-Gansmo, N. Kleven-Madsen, M. Biermann, B. Johnsen, J. Aase Husby, S. Rotevatn, J. E. Nordrehaug, J. Schaap, R. M. Kauling, M. C. Post, B. J. W. M. Rensing, J. F. Verzijlbergen, J. Sanchez, G. Giamouzis, N. Tziolas, P. Georgoulias, G. Karayannis, A. Chamaidi, N. Zavos, K. Koutrakis, G. Sitafidis, J. Skoularigis, F. Triposkiadis, S. Radovanovic, A. Djokovic, D. V. Simic, M. Krotin, A. Savic-Radojevic, M. Pljesa-Ercegovac, M. Zdravkovic, J. Saponjski, S. Jelic, T. Simic, R. Eckardt, B. J. Kjeldsen, L. I. Andersen, T. Haghfelt, P. Grupe, A. Johansen, B. Hesse, H. Pena, G. Cantinho, M. Wilk, Y. Srour, F. Godinho, N. Zafrir, A. Gutstein, I. Mats, A. Battler, A. Solodky, E. Sari, N. Singh, A. Vara, A. M. Peters, A. De Belder, S. Nair, N. Ryan, R. James, S. Dizdarevic, G. Depuey, M. Friedman, R. Wray, R. Old, H. Babla, B. Chuanyong, J. Maddahi, E. Tragardh Johansson, K. Sjostrand, L. Edenbrandt, S. Aguade-Bruix, G. Cuberas-Borros, M. N. Pizzi, M. Sabate-Fernandez, G. De Leon, D. Garcia-Dorado, J. Castell-Conesa, J. Candell-Riera, D. Casset-Senon, M. Edjlali-Goujon, D. Alison, A. Delhommais, P. Cosnay, C. S. Low, A. Notghi, J. O'brien, A. C. Tweddel, N. Bingham, P. O Neil, M. Harbinson, O. Lindner, W. Burchert, M. Schaefers, C. Marcassa, R. Campini, P. Calza, O. Zoccarato, A. Kisko, J. Kmec, M. Babcak, M. Vereb, M. Vytykacova, J. Cencarik, P. Gazdic, J. Stasko, A. Abreu, E. Pereira, L. Oliveira, P. Colarinha, V. Veloso, I. Enriksson, G. Proenca, P. Delgado, L. Rosario, J. Sequeira, I. Kosa, I. Vassanyi, C. S. Egyed, G. Y. Kozmann, S. Morita, M. Nanasato, I. Nanbu, Y. Yoshida, H. Hirayama, A. Allam, A. Sharef, I. Shawky, M. Farid, M. Mouden, J. P. Ottervanger, J. R. Timmer, M. J. De Boer, S. Reiffers, P. L. Jager, S. Knollema, G. M. Nasr, M. Mohy Eldin, M. Ragheb, I. Casans-Tormo, R. Diaz-Exposito, F. J. Hurtado-Mauricio, R. Ruano, M. Diego, F. Gomez-Caminero, C. Albarran, A. Martin De Arriba, A. Rosero, R. Lopez, C. Martin Luengo, J. R. Garcia-Talavera, I. E. K. Laitinen, M. Rudelius, E. Weidl, G. Henriksen, H. J. Wester, M. Schwaiger, X. B. Pan, T. Schindler, A. Quercioli, H. Zaidi, O. Ratib, J. M. Declerck, E. Alexanderson Rosas, R. Jacome, M. Jimenez-Santos, E. Romero, M. A. Pena-Cabral, A. Meave, J. Gonzalez, F. Rouzet, L. Bachelet, J. M. Alsac, M. Suzuki, L. Louedec, A. Petiet, F. Chaubet, D. Letourneur, J. B. Michel, D. Le Guludec, A. Aktas, A. Cinar, G. Yaman, T. Bahceci, K. Kavak, A. Gencoglu, A. Jimenez-Heffernan, E. Sanchez De Mora, J. Lopez-Martin, R. Lopez-Aguilar, C. Ramos, C. Salgado, A. Ortega, C. Sanchez-Gonzalez, J. Roa, A. Tobaruela, S. V. Nesterov, O. Turta, M. Maki, C. Han, D. Daou, M. Tawileh, S. O. Chamouine, C. Coaguila, E. Mariscal-Labrador, N. Kisiel-Gonzalez, P. De Araujo Goncalves, P. J. Sousa, H. Marques, J. O'neill, J. Pisco, R. Cale, J. Brito, A. Gaspar, F. P. Machado, J. Roquette, M. Martinez, G. Melendez, E. Kimura, J. M. Ochoa, A. M. Alessio, A. Patel, R. Lautamaki, F. M. Bengel, J. B. Bassingthwaighte, J. H. Caldwell, K. Rahbar, H. Seifarth, M. Schafers, L. Stegger, T. Spieker, A. Hoffmeier, D. Maintz, H. Scheld, O. Schober, M. Weckesser, H. Aoki, I. Matsunari, K. Kajinami, M. Martin Fernandez, M. Barreiro Perez, O. V. Fernandez Cimadevilla, D. Leon Duran, E. Velasco Alonso, J. P. Florez Munoz, L. H. Luyando, C. Templin, C. E. Veltman, J. H. C. Reiber, S. Venuraju, A. Yerramasu, S. Atwal, A. Lahiri, T. Kunimasa, M. Shiba, K. Ishii, J. Aikawa, E. S. J. Kroner, K. T. Ho, Q. W. Yong, K. C. Chua, C. Panknin, C. J. Roos, J. M. Van Werkhoven, A. J. Witkowska-Grzeslo, M. J. Boogers, D. V. Anand, D. Dey, D. Berman, F. Mut, R. Giubbini, L. Lusa, T. Massardo, A. Iskandrian, M. Dondi, A. Sato, Y. Kakefuda, E. Ojima, T. Adachi, A. Atsumi, T. Ishizu, Y. Seo, M. Hiroe, K. Aonuma, M. Kruk, R. Pracon, C. Kepka, J. Pregowski, A. Kowalewska, M. Pilka, M. Opolski, I. Michalowska, Z. Dzielinska, M. Demkow, V. Stoll, N. Sabharwal, A. Chakera, O. Ormerod, H. Fernandes, M. Bernardes, E. Martins, P. Oliveira, T. Vieira, G. Terroso, A. Oliveira, T. Faria, F. Ventura, J. Pereira, S. Fukuzawa, M. Inagaki, J. Sugioka, A. Ikeda, S. Okino, J. Maekawa, T. Uchiyama, N. Kamioka, S. Ichikawa, M. Afshar, R. Alvi, N. Aguilar, R. Ippili, H. Shaqra, J. Bella, N. Bhalodkar, A. Dos Santos, M. Daicz, L. O. Cendoya, H. G. Marrero, J. Casuscelli, M. Embon, G. Vera Janavel, E. Duronto, E. P. Gurfinkel, C. M. Cortes, Y. Takeishi, K. Nakajima, Y. Yamasaki, T. Nishimura, K. Hayes Brown, F. Collado, M. Alhaji, J. Green, S. Alexander, R. Vashistha, S. Jain, F. Aldaas, J. Shanes, R. Doukky, K. Ashikaga, Y. J. Akashi, M. Uemarsu, R. Kamijima, K. Yoneyama, K. Omiya, Y. Miyake, Y. Brodov, U. Raval, A. Berezin, V. Seden, E. Koretskaya, T. A. Panasenko, S. Matsuo, S. Kinuya, J. Chen, R. J. Van Bommel, B. Van Der Hiel, P. Dibbets-Schneider, E. V. Garcia, I. Rutten-Vermeltfoort, M. M. J. Gevers, B. Verhoeven, A. B. Dijk Van, E. Raaijmakers, P. G. H. M. Raijmakers, J. E. Engvall, M. Gjerde, J. De Geer, E. Olsson, P. Quick, A. Persson, M. Mazzanti, M. Marini, L. Pimpini, G. P. Perna, C. Marciano, P. Gargiulo, M. Galderisi, C. D'amore, G. Savarese, L. Casaretti, S. Paolillo, A. Cuocolo, P. Perrone Filardi, M. Al-Amoodi, E. C. Thompson, K. Kennedy, K. A. Bybee, A. I. Mcghie, J. H. O'keefe, T. M. Bateman, R. L. F. Van Der Palen, A. M. Mavinkurve-Groothuis, B. Bulten, L. Bellersen, H. W. M. Van Laarhoven, L. Kapusta, L. F. De Geus-Oei, P. P. Pollice, M. B. Bonifazi, F. P. Pollice, I. P. Clements, D. O. Hodge, C. G. Scott, M. De Ville De Goyet, B. Brichard, T. Pirotte, S. Moniotte, R. A. Tio, A. Elvan, R. A. I. O. Dierckx, R. H. J. A. Slart, T. Furuhashi, M. Moroi, H. Hase, N. Joki, H. Masai, R. Nakazato, H. Fukuda, K. Sugi, K. Kryczka, E. Kaczmarska, J. Petryka, L. Mazurkiewicz, W. Ruzyllo, P. Smanio, E. Vieira Segundo, M. Siqueira, J. Kelendjian, J. Ribeiro, J. Alaca, M. Oliveira, F. Alves, I. Peovska, J. Maksimovic, M. Vavlukis, N. Kostova, D. Pop Gorceva, V. Majstorov, M. Zdraveska, S. Hussain, M. Djearaman, E. Hoey, L. Morus, O. Erinfolami, A. Macnamara, M. P. Opolski, A. Witkowski, V. Berti, F. Ricci, R. Gallicchio, W. Acampa, G. Cerisano, C. Vigorito, R. Sciagra', A. Pupi, H. Sliem, F. M. Collado, S. Schmidt, A. Maheshwari, R. Kiriakos, V. Mwansa, S. Ljubojevic, S. Sedej, M. Holzer, G. Marsche, V. Marijanski, J. Kockskaemper, B. Pieske, A. Ricalde, G. Alexanderson, A. Mohani, P. Khanna, A. Sinusas, F. Lee, V. A. Pinas, B. L. F. Van Eck-Smit, H. J. Verberne, C. M. De Bruin, G. Guilhermina, L. Jimenez-Angeles, O. Ruiz De Jesus, O. Yanez-Suarez, E. Vallejo, E. Reyes, M. Chan, M. L. Hossen, S. R. Underwood, A. Karu, S. Bokhari, V. Pineda, L. M. Gracia-Sanchez, A. Garcia-Burillo, K. Zavadovskiy, Y. U. Lishmanov, W. Saushkin, I. Kovalev, A. Chernishov, A. Annoni, M. Tarkia, T. Saanijoki, V. Oikonen, T. Savunen, M. A. Green, M. Strandberg, A. Roivainen, M. C. Gaeta, C. Artigas, J. Deportos, L. Geraldo, A. Flotats, V. La Delfa, I. Carrio, W. J. Laarse, M. M. Izquierdo Gomez, J. Lacalzada Almeida, A. Barragan Acea, A. De La Rosa Hernandez, R. Juarez Prera, G. Blanco Palacios, J. A. Bonilla Arjona, J. J. Jimenez Rivera, J. L. Iribarren Sarrias, I. Laynez Cerdena, A. Dedic, A. Rossi, G. J. R. Ten Kate, A. Dharampal, A. Moelker, T. W. Galema, N. Mollet, P. J. De Feyter, K. Nieman, D. Trabattoni, A. Broersen, M. Frenay, M. M. Boogers, P. H. Kitslaar, J. Dijkstra, D. A. Annoni, M. Muratori, N. Johki, M. Tokue, A. S. Dharampal, A. C. Weustink, L. A. E. Neefjes, S. L. Papadopoulou, C. Chen, N. R. A. Mollet, E. H. Boersma, G. P. Krestin, J. A. Purvis, D. Sharma, S. M. Hughes, D. S. Berman, R. Taillefer, J. Udelson, M. Devine, J. Lazewatsky, G. Bhat, D. Washburn, D. Patel, T. Mazurek, S. Tandon, S. Bansal, S. Inzucchi, L. Staib, J. Davey, D. Chyun, L. Young, F. Wackers, M. T. Harbinson, G. Wells, J. Dougan, S. Borges-Neto, H. Phillips, A. Farzaneh-Far, Z. Starr, L. K. Shaw, M. Fiuzat, C. O'connor, M. Henzlova, W. L. Duvall, A. Levine, U. Baber, L. Croft, S. Sahni, S. Sethi, L. Hermann, A. Nureldin, A. Gomaa, M. A. T. Soliman, H. A. R. Hany, F. De Graaf, A. Pazhenkottil, H. M. J. Siebelink, J. H. Reiber, M. Ayub, T. Naveed, M. Azhar, A. Van Tosh, T. L. Faber, J. R. Votaw, N. Reichek, B. Pulipati, C. Palestro, K. J. Nichols, K. Okuda, Y. Kirihara, T. Ishikawa, J. Taki, M. Yoshita, M. Yamada, A. Salacata, S. Keavey, V. Chavarri, J. Mills, H. Nagaraj, P. Bhambhani, D. E. Kliner, P. Soman, J. Heo, A. E. Iskandrian, M. Jain, B. Lin, A. Walker, C. Nkonde, S. Bond, A. Baskin, J. Declerck, M. E. Soto, G. Mendoza, M. Aguilar, S. P. Williams, G. Colice, J. R. Mcardle, A. Lankford, D. K. Kajdasz, C. R. Reed, L. Angelini, F. Angelozzi, G. Ascoli, A. Jacobson, H. J. Lessig, M. C. Gerson, M. D. Cerqueira, J. Narula, M. Uematsu, K. Kida, K. Suzuki, P. E. Bravo, K. Fukushima, M. Chaudhry, J. Merrill, A. Alonso Tello, J. F. Rodriguez Palomares, G. Marti Aguasca, S. Aguade Bruix, V. Aliaga, P. Mahia, T. Gonzalez-Alujas, J. Candell, A. Evangelista, R. Mlynarski, A. Mlynarska, M. Sosnowski, B. Zerahn, P. Hasbak, C. E. Mortensen, H. F. Mathiesen, M. Andersson, D. Nielsen, L. Ferreira Santos, M. J. Ferreira, D. Ramos, D. Moreira, M. J. Cunha, A. Albuquerque, A. Moreira, J. Oliveira Santos, G. Costa, L. A. Providencia, Y. Arita, S. Kihara, N. Mitsusada, M. Miyawaki, H. Ueda, H. Hiraoka, Y. Matsuzawa, J. Askew, M. O'connor, L. Jordan, R. Ruter, R. Gibbons, T. Miller, L. Emmett, A. Ng, N. Sorensen, R. Mansberg, L. Kritharides, T. Gonzalez, H. Majmundar, N. P. Coats, S. Vernotico, J. H. Doan, T. M. Hernandez, M. Evini, A. D. Hepner, T. K. Ip, W. A. Chalela, A. M. Falcao, L. O. Azouri, J. A. F. Ramires, J. C. Meneghetti, F. Manganelli, M. Spadafora, P. Varrella, G. Peluso, R. Sauro, E. Di Lorenzo, F. Rotondi, S. Daniele, P. Miletto, A. J. M. Rijnders, B. W. Hendrickx, W. Van Der Bruggen, Y. G. C. J. America, P. J. Thorley, F. U. Chowdhury, C. J. Dickinson, S. I. Sazonova, I. Y. U. Proskokova, A. M. Gusakova, S. M. Minin, Y. U. B. Lishmanov, V. V. Saushkin, G. Rodriguez, F. Roffe, H. Ilarraza, D. Bialostozky, A. N. Kitsiou, P. Arsenos, I. Tsiantis, S. Charizopoulos, S. Karas, R. C. Vidal Perez, M. Garrido, V. Pubul, S. Argibay, C. Pena, M. Pombo, A. B. Ciobotaru, A. Sanchez-Salmon, A. Ruibal Morell, J. R. Gonzalez-Juanatey, E. Rodriguez-Gomez, B. Martinez, D. Pontillo, F. Benvissuto, F. Fiore Melacrinis, S. Maccafeo, E. V. Scabbia, R. Schiavo, Y. Golzar, C. Gidea, J. Golzar, D. Pop-Gorceva, M. Zdravkovska, S. Stojanovski, L. J. Georgievska-Ismail, T. Katsikis, A. Theodorakos, A. Kouzoumi, M. Koutelou, Y. Yoshimura, T. Toyama, H. Hoshizaki, S. Ohshima, M. Inoue, T. Suzuki, A. Uitterdijk, M. Dijkshoorn, M. Van Straten, W. J. Van Der Giessen, D. J. Duncker, D. Merkus, G. Platsch, J. Sunderland, C. Tonge, P. Arumugam, T. Dey, H. Wieczorek, R. Bippus, R. L. Romijn, B. E. Backus, T. Aach, M. Lomsky, L. Johansson, J. Marving, S. Svensson, J. L. Pou, F. P. Esteves, P. Raggi, R. Folks, Z. Keidar, J. W. Askew, L. Verdes, L. Campos, V. Gulyaev, A. Pankova, J. Santos, S. Carmona, I. Henriksson, A. Prata, M. Carrageta, A. I. Santos, K. Yoshinaga, M. Naya, C. Katoh, O. Manabe, S. Yamada, H. Iwano, S. Chiba, H. Tsutsui, N. Tamaki, I. Vassiliadis, E. Despotopoulos, O. Kaitozis, E. Hatzistamatiou, R. Thompson, J. Hatch, M. Zink, B. S. Gu, G. D. Bae, C. M. Dae, G. H. Min, E. J. Chun, S. I. Choi, M. Al-Mallah, K. Kassem, O. Khawaja, D. Goodman, D. Lipkin, L. Christiaens, B. Bonnet, J. Mergy, D. Coisne, J. Allal, N. Dias Ferreira, D. Leite, J. Rocha, M. Carvalho, D. Caeiro, N. Bettencourt, P. Braga, V. Gama Ribeiro, U. S. Kristoffersen, A. M. Lebech, H. Gutte, R. S. Ripa, N. Wiinberg, C. L. Petersen, G. Jensen, A. Kjaer, C. Bai, R. Conwell, R. D. Folks, L. Verdes-Moreiras, D. Manatunga, A. F. Jacobson, D. Belzer, Y. Hasid, M. Rehling, R. H. Poulsen, L. Falborg, J. T. Rasmussen, L. N. Waehrens, C. W. Heegaard, J. M. U. Silvola, S. Forsback, J. O. Laine, S. Heinonen, S. Ylaherttuala, A. Broisat, M. Ruiz, N. C. Goodman, J. Dimastromatteo, D. K. Glover, F. Hyafil, F. Blackwell, G. Pavon-Djavid, L. Sarda-Mantel, L. J. Feldman, A. Meddahi-Pelle, V. Tsatkin, Y.- H. Liu, R. De Kemp, P. J. Slomka, R. Klein, G. Germano, R. S. Beanlands, A. Rohani, V. Akbari, J. G. J. Groothuis, M. Fransen, A. M. Beek, S. L. Brinckman, M. R. Meijerink, M. B. M. Hofman, C. Van Kuijk, S. Kogure, E. Yamashita, J. Murakami, R. Kawaguchi, H. Adachi, S. Oshima, S. Minin, S. Popov, Y. U. Saushkina, G. Savenkova, D. Lebedev, E. Alexandridis, D. Rovithis, C. Parisis, I. Sazonova, V. Saushkin, V. Chernov, L. Zaabar, H. Bahri, S. Hadj Ali, A. Sellem, I. Slim, N. El Kadri, H. Slimen, H. Hammami, S. Lucic, A. Peter, S. Tadic, K. Nikoletic, R. Jung, M. Lucic, K. Tagil, D. Jakobsson, S.- E. Svensson, P. Wollmer, L. Leccisotti, L. Indovina, L. Paraggio, M. L. Calcagni, A. Giordano, M. Kapitan, A. Paolino, M. Nunez, J. Sweeny, N. Kulkarni, K. Guma, Y. Akashi, M. Takano, M. Takai, S. Koh, F. Miyake, N. Torun, G. Durmus Altun, A. Altun, E. Kaya, H. Saglam, D. T. Matsuoka, A. Sanchez, C. Bartolozzi, D. Padua, G. Ponta, A. Ponte, A. Carneiro, A. Thom, R. Ashrafi, P. Garg, G. Davis, A. Falcao, M. Costa, F. Bussolini, J. A. C. Meneghetti, M. Tobisaka, E. Correia, J. W. Jansen, P. A. Van Der Vleuten, T. P. Willems, F. Zijlstra, M. Sato, K. Taniguchi, M. Kurabayashi, D. Pop Gjorcheva, M. Zdraveska-Kochovska, K. Moriwaki, A. Kawamura, K. Watanabe, T. Omura, S. Sakabe, T. Seko, A. Kasai, M. Ito, M. Obana, T. Akasaka, C. Hruska, D. Truong, C. Pletta, D. Collins, C. Tortorelli, D. Rhodes, M. El-Prince, A. Martinez-Moeller, M. Marinelli, S. Weismueller, C. Hillerer, B. Jensen, S. G. Nekolla, H. Wakabayashi, K. Tsukamoto, S. M. E. A. Baker, K. M. H. S. Sirajul Haque, A. Siddique, S. Krishna Banarjee, A. Ahsan, F. Rahman, M. Mukhlesur Rahman, T. Parveen, M. Lutfinnessa, F. Nasreen, H. Sano, S. Naito, M. L. De Rimini, G. Borrelli, F. Baldascino, P. Calabro, C. Maiello, A. Russo, C. Amarelli, P. Muto, I. Danad, P. G. Raijmakers, Y. E. Appelman, O. S. Hoekstra, J. T. Marcus, A. Boonstra, D. V. Ryzhkova, T. V. Kuzmina, O. S. Borodina, M. A. Trukshina, I. S. Kostina, H. Hommel, G. Feuchtner, O. Pachinger, G. Friedrich, A. M. Stel, J. W. Deckers, V. Gama, A. Ciarka, L. A. Neefjes, N. R. Mollet, E. J. Sijbrands, J. Wilczek, C. Llibre Pallares, O. Abdul-Jawad Altisent, H. Cuellar Calabria, P. Mahia Casado, M. T. Gonzalez-Alujas, A. Evangelista Masip, D. Garcia-Dorado Garcia, Y. Tekabe, X. Shen, Q. Li, J. Luma, D. Weisenberger, A. M. Schmidt, R. Haubner, L. Johnson, L. Sleiman, S. Thorn, M. Hasu, M. Thabet, J. N. Dasilva, S. C. Whitman, D. Genovesi, A. Giorgetti, A. Gimelli, G. Cannizzaro, F. Bertagna, G. Fagioli, M. Rossi, R. Bonini, P. Marzullo, C. A. Paterson, S. A. Smith, A. D. Small, N. E. R. Goodfield, W. Martin, S. Nekolla, H. Sherif, S. Reder, M. Yu, A. Kusch, D. Li, J. Zou, M. S. Lloyd, K. Cao, D. W. Motherwell, A. Rice, G. M. Mccurrach, S. M. Cobbe, M. C. Petrie, I. Al Younis, E. Van Der Wall, T. Mirza, M. Raza, H. Hashemizadeh, L. Santos, B. A. Krishna, F. Perna, M. Lago, M. Leo, G. Pelargonio, G. Bencardino, M. L. Narducci, M. Casella, F. Bellocci, S. Kirac, O. Yaylali, M. Serteser, T. Yaylali, A. Okizaki, Y. Urano, M. Nakayama, S. Ishitoya, J. Sato, Y. Ishikawa, M. Sakaguchi, N. Nakagami, T. Aburano, S. V. Solav, R. Bhandari, S. Burrell, S. Dorbala, I. Bruno, C. Caldarella, A. Collarino, M. V. Mattoli, A. Stefanelli, A. Cannarile, F. Maggi, V. Soukhov, S. Bondarev, A. Yalfimov, M. Khan, P. P. Priyadharshan, G. Chandok, T. Aziz, M. Avison, R. A. Smith, D. S. Bulugahapitya, T. Vakhtangadze, F. Todua, M. Baramia, G. Antelava, N.- C. Roche, P. Paule, S. Kerebel, J.- M. Gil, L. Fourcade, A. Tzonevska, K. Tzvetkov, M. Atanasova, V. Parvanova, A. Chakarova, E. Piperkova, B. Kocabas, H. Muderrisoglu, C. P. Allaart, E. Entok, S. Simsek, B. Akcay, I. Ak, E. Vardareli, M. Stachura, P. J. Kwasiborski, G. J. Horszczaruk, E. Komar, A. Cwetsch, B. Zraik, R. Morales Demori, A. D. J. Almeida, M. E. Siqueira, E. Vieira, I. Balogh, G. Kerecsen, E. Marosi, Z. S. Szelid, A. Sattar, T. Swadia, J. Chattahi, W. Qureshi, F. Khalid, A. Gonzalez, S. Hechavarria, K. Takamura, S. Fujimoto, R. Nakanishi, S. Yamashina, A. Namiki, J. Yamazaki, K. Koshino, Y. Hashikawa, N. Teramoto, M. Hikake, S. Ishikane, T. Ikeda, H. Iida, Y. Takahashi, N. Oriuchi, H. Higashino, K. Endo, T. Mochizuki, K. Murase, A. Baali, R. Moreno, M. Chau, H. Rousseau, F. Nicoud, P. Dolliner, L. Brammen, G. Steurer, T. Traub-Weidinger, P. Ubl, P. Schaffarich, G. Dobrozemsky, A. Staudenherz, M. Ozgen Kiratli, B. Temelli, N. B. Kanat, T. Aksoy, G. A. Slavich, G. Piccoli, M. Puppato, S. Grillone, D. Gasparini, S. Perruchoud, C. Poitry-Yamate, M. Lepore, R. Gruetter, T. Pedrazzini, D. Anselm, A. Anselm, H. Atkins, J. Renaud, R. Dekemp, I. Burwash, A. Guo, R. Beanlands, C. Glover, I. Vilardi, B. Zangheri, L. Calabrese, P. Romano, A. Bruno, O. C. Fernandez Cimadevilla, V. A. Uusitalo, M. Luotolahti, M. Wendelin-Saarenhovi, J. Sundell, O. Raitakari, S. Huidu, R. Gadiraju, M. Ghesani, Q. Uddin, B. Wosnitzer, N. Takahashi, E. Alhaj, A. Legasto, B. Abiri, K. Elsaban, T. El Khouly, T. El Kammash, A. Al Ghamdi, B. Kyung Deok, K. Bon Seung, Y. Sang Geun, D. Chang Min, and M. Gwan Hong

Subjects
Cardiology and Cardiovascular Medicine
Published
2011
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25. Can Semi-empirical Calculations Help Solve Mass Spectrometry Problems? Protonation Sites and Proton Affinities of Amino Acids

Author

M. Helena Florêncio, R. J. N. Bettencourt da Silva, Pedro D. Vaz, and Paulo J. Amorim Madeira

Subjects
Proton, NDDO, Computational chemistry, Chemistry, Proton affinity, Experimental data, Protonation, General Chemistry, Mass spectrometry, Affinities, Diatomic molecule
Abstract

Owing to the recent development of the PM6 and PM6-DH+ semi-empirical methodologies, which belong to the neglect of diatomic differential overlap (NDDO) family, it was decided to carry out a study to assess whether these inexpensive and fast methodologies could be used with confidence to help solve mass spectrometry problems. As such, a report on the feasibility of using semi-empirical calculations to identify probable protonation sites in amino acids is presented. The optimised geometries obtained by the semi-empirical calculations were compared to several structures reported in the literature (obtained through high-level theoretical calculations) and reasonable agreement was found. The proton affinities derived from semi-empirical calculations were also compared with experimental data and benchmarked as well with predicted values from the literature (also obtained through high-level theoretical calculations). Semi-empirical calculations accurately predicted the most probable protonation site for all amino acids considered; thus leading to results comparable to those obtained by high-level calculations at an extremely low computational cost. Regarding the proton affinity estimates, deviations from the available experimental values are greater for the semi-empirical proton affinities than for those observed for high-level calculations. A statistical analysis of the data, at a confidence level of 99 %, also showed that the semi-empirical proton affinities were different from experimental values and high-level proton affinities were equivalent to experimental values. Nevertheless, the overall correlation of the semi-empirical data with experimental values is, at least, satisfactory. We believe therefore that this paper shows that semi-empirical methodologies, which are fast and inexpensive, can indeed solve mass spectrometry problems, or at least, facilitate a quicker path to the solution.

Published
2013

26. Setting Target Measurement Uncertainty in Water Analysis.

Author

da Silva, Ricardo J. N. Bettencourt

Subjects
WATER analysis, MATHEMATICAL models of uncertainty, ALGORITHMS, COMPOSITION of water, DRINKING water quality
Abstract

Water is the most frequently and thoroughly characterised product due to the impact of the chemical composition of water of different sources or destinations on public health and on economy. The adequacy of water characterisation relies on measurement quality, which is a function of measurement traceability and uncertainty. In some analytical fields, target values of measurement performance parameters are set to ensure that the measurements quality is fit for the intended use. Nevertheless, frequently, these performance parameters do not allow the control of the magnitude of relevant components of measurement uncertainty. This work discusses the need for assessing fitness of the measurement for its intended use through the magnitude of uncertainty associated to the measurement value. The way this evaluation should be performed, when no guidelines are available, is also suggested. Target values of relevant performance parameters, results of interlaboratory tests, or the magnitude of trends of the measured quantity, are some types of information useful to define the maximum admissible uncertainty, i.e., target uncertainty. The information and algorithms used to define the target uncertainty are presented from the most suitable to the less likely to produce consensual values. Calculations are illustrated with application examples of different analytical fields. In this work, the way in which variability of uncertainty evaluation is taken into account when comparing estimated with target uncertainty is also discussed. [ABSTRACT FROM AUTHOR]

Published
2013
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28. Worst case uncertainty estimates for routine instrumental analysis

Author

Silva, Ricardo J. N. Bettencourt da, Santos, Júlia R., and Camões, M. Filomena G. F. C.

Abstract

A methodology for the worst case measurement uncertainty estimation for analytical methods which include an instrumental quantification step, adequate for routine determinations, is presented. Although the methodology presented should be based on a careful evaluation of the analytical method, the resulting daily calculations are very simple. The methodology is based on the estimation of the maximum value for the different sources of uncertainty and requires the definition of limiting values for certain analytical parameters. The simplification of the instrumental quantification uncertainty estimation involves the use of the standard deviation obtained from control charts relating to the concentrations estimated from the calibration curves for control standards at the highest calibration level. Three levels of simplification are suggested, as alternatives to the detailed approach, which can be selected according to the proximity of the sample results to decision limits. These approaches were applied to the determination of pesticide residues in apples (CEN, EN 12393), for which the most simplified approach showed a relative expanded uncertainty of 37.2% for a confidence level of approximately 95%.

Published
2002
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29. Expression of results with uncertainty for the determination of pesticides in melon – experience in a proficiency test

Author

Silva, Ricardo J. N. Bettencourt da, Lino, M. João, Ribeiro, Alzira, and Santos, Júlia R.

Abstract

The expression of results with an uncertainty through the “bottom-up” approach, involving the estimation and combination of all the sources of uncertainty, represents a challenge when the analytical method includes mass transfer steps (MTS). These steps (e.g. extraction, evaporation, digestion, etc.) with inherently different from 100% recoveries lack models capable of describing their precision and efficiency. Recently, a new methodology was published aimed at the estimation of the performance of these critical steps. Comparison of the experimental dispersion from the replicated analysis of spiked samples with the combination of the uncertainty associated with gravimetric, volumetric and instrumental quantification steps (described by well established models) allows the estimation of the MTS uncertainty. Evaluation of the behaviour of the MTS within the analytical range supports the use of developed estimations over a wide concentration range. This methodology was applied, with success, to the determination of pesticide residues in melon in one particular proficiency test organised by the Food Analysis Performance Assessment Scheme (FAPAS) between November 2000 and February 2001.

Published
2001

30. Estimation of precision and efficiency mass transfer steps for the determination of pesticides in vegetables aiming at the expression of results with reliable uncertainty

Author

Silva, Ricardo J. N. Bettencourt da, Lino, M. João, Santos, Júlia R., and Camões, M. FilomenaG. F. C.

Abstract

A ‘bottom-up’ approach for the expression of results obtained from analytical methods that include analytical steps with recovery inherently different from 100% [mass transfer steps (MTS): extraction, evaporation, clean-up procedures, digestion, etc.] is presented. The estimation of the combination of all MTS uncertainty involves the comparison of the experimental dispersion of replicated analyses of spiked samples with the estimation of the uncertainty obtained for the combination of all uncertainty sources except MTS ones (‘incomplete’ estimation). The estimation of MTS uncertainty by difference is performed after evaluating the statistical difference between the ‘incomplete’ estimation and the experimental dispersion (F-test). When the two estimations are statistically equivalent, the MTS uncertainty is considered to be negligible in relation to the other sources budget. The assumption of constancy of MTS performance within the analytical range is tested through single analyses at several concentration levels and is evaluated by the inclusion of the expected values at the intervals resulting from the combination of the MTS uncertainty estimation performed at one concentration level and the ‘incomplete’ estimation. The developed methodology can also be useful for method optimisation and validation and for the detection of small trends in results. The determination of pesticides in sweet peppers by GC-NPD was used to explore the above concepts.

Published
2000

31. Statistically sound identification of compounds by low-resolution GC-MS: Identification of tear agents in tear gas sprays.

Author

Salgueiro PAS and Ricardo J N BDS

Subjects
Tear Gases analysis, Gas Chromatography-Mass Spectrometry methods, Monte Carlo Method
Abstract

Gas-chromatography hyphenated with low-resolution mass spectrometry is a very flexible tool for the cost-effective identification and quantification of volatile compounds in complex matrices. In some analytical fields, criteria for the agreement between retention time and mass spectra of the analyte in calibrators and samples are defined based on the general understanding of the performance of these parameters. However, since this harmonisation is not based on experimental performance observed for specific GC-MS conditions and analyte it leads to false identifications. This research proposes a novel and robust tool for defining statistically sound criteria for the identification of compounds by GC-MS and LC-MS using experimental data. The Monte Carlo Method (MCM) simulation of the correlated abundance of characteristic ions of analyte mass spectrum allows simulating the abundance ratio difference of the analyte in a calibrator and sample used for statistically sound identifications. The Cholesky decomposition of the covariance matrix of ion abundances for MCM simulations allows the reliable use of many ion abundance ratios in identifications. The developed methodology was implemented in a user-friendly Excel spreadsheet and applied to the identification of tear gas agents in tear gas sprays. Criteria defined by SANTE for identifying pesticide residues in foodstuffs were compared with the developed tool. The cross-validation of computational and SANTE tools allowed concluding that the statistical control of retention time and mass spectra performs according to the defined confidence level. On the other hand, the SANTE criteria can produce up to 92 % false identifications for being too strict considering signal dispersion., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Published
2025
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32. From the armchair to contemporary cardiac rehabilitation: the remarkable ongoing journey of exercise training in ischemic heart disease.

Author

Vilela EM, Almeida MC, Oliveira C, Nogueira T, Torres S, Teixeira M, Sampaio F, Ribeiro J, Oliveira M, Bettencourt N, Viamonte S, and Fontes-Carvalho R

Abstract

Exercise is an important physiological activity with several health benefits. In the setting of ischemic heart disease (IHD), the view toward exercise has greatly evolved throughout the years, concurrently to several major advances in the management of this complex entity. Currently, exercise training has broad applications across the IHD continuum as a powerful tool in its overall management, being a core component of comprehensive cardiac rehabilitation programs. Beyond this, exercise has also been incorporated as an integral part of contemporary methodologies aiming to provide diagnostic and prognostic data, such as cardiopulmonary exercise stress testing or stress echocardiography. In this article, we provide a pragmatic overview concerning the role of exercise in IHD, with a focus on its incorporation in cardiac rehabilitation frameworks, while also discussing some of the challenges and unmet needs concerning these interventions., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of PBJ-Associação Porto Biomedical/Porto Biomedical Society.)

Published
2024
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34. Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging.

Author

Xie C, Zhang R, Mensink S, Gandharva R, Awni M, Lim H, Kachel SE, Cheung E, Crawley R, Churilov L, Bettencourt N, Chiribiri A, Scannell CM, and Lim RP

Subjects
Humans, Retrospective Studies, Heart diagnostic imaging, Male, Female, Neural Networks, Computer, Middle Aged, Contrast Media, Magnetic Resonance Imaging methods, Gadolinium, Deep Learning
Abstract

Objectives: To develop and share a deep learning method that can accurately identify optimal inversion time (TI) from multi-vendor, multi-institutional and multi-field strength inversion scout (TI scout) sequences for late gadolinium enhancement cardiac MRI., Materials and Methods: Retrospective multicentre study conducted on 1136 1.5-T and 3-T cardiac MRI examinations from four centres and three scanner vendors. Deep learning models, comprising a convolutional neural network (CNN) that provides input to a long short-term memory (LSTM) network, were trained on TI scout pixel data from centres 1 to 3 to identify optimal TI, using ground truth annotations by two readers. Accuracy within 50 ms, mean absolute error (MAE), Lin's concordance coefficient (LCCC) and reduced major axis regression (RMAR) were used to select the best model from validation results, and applied to holdout test data. Robustness of the best-performing model was also tested on imaging data from centre 4., Results: The best model (SE-ResNet18-LSTM) produced accuracy of 96.1%, MAE 22.9 ms and LCCC 0.47 compared to ground truth on the holdout test set and accuracy of 97.3%, MAE 15.2 ms and LCCC 0.64 when tested on unseen external (centre 4) data. Differences in vendor performance were observed, with greatest accuracy for the most commonly represented vendor in the training data., Conclusion: A deep learning model was developed that can identify optimal inversion time from TI scout images on multi-vendor data with high accuracy, including on previously unseen external data. We make this model available to the scientific community for further assessment or development., Clinical Relevance Statement: A robust automated inversion time selection tool for late gadolinium-enhanced imaging allows for reproducible and efficient cross-vendor inversion time selection., Key Points: • A model comprising convolutional and recurrent neural networks was developed to extract optimal TI from TI scout images. • Model accuracy within 50 ms of ground truth on multi-vendor holdout and external data of 96.1% and 97.3% respectively was achieved. • This model could improve workflow efficiency and standardise optimal TI selection for consistent LGE imaging., (© 2024. The Author(s).)

Published
2024
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36. Combination of computed tomography angiography with coronary artery calcium score for improved diagnosis of coronary artery disease: a collaborative meta-analysis of stable chest pain patients referred for invasive coronary angiography.

Author

Mohamed M, Bosserdt M, Wieske V, Dubourg B, Alkadhi H, Garcia MJ, Leschka S, Zimmermann E, Shabestari AA, Nørgaard BL, Meijs MFL, Øvrehus KA, Diederichsen ACP, Knuuti J, Halvorsen BA, Mendoza-Rodriguez V, Wan YL, Bettencourt N, Martuscelli E, Buechel RR, Mickley H, Sun K, Muraglia S, Kaufmann PA, Herzog BA, Tardif JC, Schütz GM, Laule M, Newby DE, Achenbach S, Budoff M, Haase R, Biavati F, Mézquita AV, Schlattmann P, and Dewey M

Subjects
Female, Humans, Male, Calcium, Chest Pain diagnosis, Computed Tomography Angiography methods, Coronary Angiography methods, Predictive Value of Tests, Tomography, X-Ray Computed methods, Middle Aged, Aged, Coronary Artery Disease diagnostic imaging, Coronary Stenosis diagnostic imaging
Abstract

Objectives: Coronary computed tomography angiography (CCTA) has higher diagnostic accuracy than coronary artery calcium (CAC) score for detecting obstructive coronary artery disease (CAD) in patients with stable chest pain, while the added diagnostic value of combining CCTA with CAC is unknown. We investigated whether combining coronary CCTA with CAC score can improve the diagnosis of obstructive CAD compared with CCTA alone., Methods: A total of 2315 patients (858 women, 37%) aged 61.1 ± 10.2 from 29 original studies were included to build two CAD prediction models based on either CCTA alone or CCTA combined with the CAC score. CAD was defined as at least 50% coronary diameter stenosis on invasive coronary angiography. Models were built by using generalized linear mixed-effects models with a random intercept set for the original study. The two CAD prediction models were compared by the likelihood ratio test, while their diagnostic performance was compared using the area under the receiver-operating-characteristic curve (AUC). Net benefit (benefit of true positive versus harm of false positive) was assessed by decision curve analysis., Results: CAD prevalence was 43.5% (1007/2315). Combining CCTA with CAC improved CAD diagnosis compared with CCTA alone (AUC: 87% [95% CI: 86 to 89%] vs. 80% [95% CI: 78 to 82%]; p < 0.001), likelihood ratio test 236.3, df: 1, p < 0.001, showing a higher net benefit across almost all threshold probabilities., Conclusion: Adding the CAC score to CCTA findings in patients with stable chest pain improves the diagnostic performance in detecting CAD and the net benefit compared with CCTA alone., Clinical Relevance Statement: CAC scoring CT performed before coronary CTA and included in the diagnostic model can improve obstructive CAD diagnosis, especially when CCTA is non-diagnostic., Key Points: • The combination of coronary artery calcium with coronary computed tomography angiography showed significantly higher AUC (87%, 95% confidence interval [CI]: 86 to 89%) for diagnosis of coronary artery disease compared to coronary computed tomography angiography alone (80%, 95% CI: 78 to 82%, p < 0.001). • Diagnostic improvement was mostly seen in patients with non-diagnostic C. • The improvement in diagnostic performance and the net benefit was consistent across age groups, chest pain types, and genders., (© 2023. The Author(s).)

Published
2024
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39. Sixty years of the Bruce protocol: reappraising the contemporary role of exercise stress testing with electrocardiographic monitoring.

Author

Vilela EM, Oliveira C, Oliveira C, Torres S, Sampaio F, Primo J, Ribeiro J, Teixeira M, Oliveira M, Bettencourt N, Viamonte S, and Fontes-Carvalho R

Abstract

The cardiovascular response to exercise has long been a focus of interest. Over a century ago, the first descriptions of electrocardiographic changes occurring during exercise highlighted the possible relevance of this dynamic assessment. In this background, the inception of the Bruce protocol circa 60 years ago allowed for a major leap in this field by providing a standardized framework with which to address this issue, by means of an integrated and structured methodology. Since then, exercise stress testing with electrocardiographic monitoring (ExECG) has become one of the most widely appraised tests in cardiovascular medicine. Notably, past few decades have been profoundly marked by substantial advances in the approach to cardiovascular disease, challenging prior notions concerning both its physiopathology and overall management. Among these, the ever-evolving presentations of cardiovascular disease coupled with the development and implementation of several novel diagnostic modalities (both invasive and noninvasive) has led to a shifting paradigm in the application of ExECG. This technique, however, has continuously shown to be of added value across various momentums of the cardiovascular continuum, as depicted in several contemporary guidelines. This review provides a pragmatical reflexion on the development of ExECG, presenting a comprehensive overview concerning the current role of this modality, its challenges, and its future perspectives., (Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of PBJ-Associação Porto Biomedical/Porto Biomedical Society.)

Published
2023
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40. Mitral annular disjunction: Beyond mitral valve prolapse.

Author

Faria B, Ribeiro S, Calvo L, Oliveira M, von Hafe P, Bettencourt N, Sanfins V, and Lourenço A

Subjects
Male, Female, Humans, Mitral Valve diagnostic imaging, Arrhythmias, Cardiac, Death, Sudden, Cardiac, Echocardiography, Mitral Valve Prolapse complications
Abstract

Mitral annular disjunction (MAD) is an easily identifiable entity on transthoracic echocardiography, but is still poorly recognized or ignored. It is often associated with mitral valve prolapse and is itself a risk marker for ventricular arrhythmias and sudden cardiac death, but the management and risk stratification of these patients is not systematized. Two clinical cases of MAD associated with mitral valve prolapse and ventricular arrhythmias are presented. The first case is of a patient with a history of surgical intervention on the mitral valve due to Barlow's disease. He presented to the emergency department with sustained monomorphic ventricular tachycardia requiring emergent electrical cardioversion. MAD with transmural fibrosis at the level of the inferolateral wall was documented. The second report is of a young woman with palpitations and frequent premature ventricular contractions on Holter with documentation of valvular prolapse and MAD, and focuses on the risk stratification approach. The present article offers a review of the literature regarding the arrhythmic risk of MAD and mitral valve prolapse, as well as a review of risk stratification in these patients., (Copyright © 2023. Publicado por Elsevier España, S.L.U.)

Published
2023
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41. A Rebalancing of Financial Valuations and Expectations Moving Forward in the Telehealth Sector as the United States Moves Toward a Post-COVID-19 Reality.

Author

Bettencourt N, Wilson CJ, Johnson PJ, and D'Souza F

Subjects
Humans, Delivery of Health Care, Motivation, Pandemics prevention & control, United States, COVID-19 prevention & control, Telemedicine
Abstract

The telehealth sector of health care delivery experienced significant growth at the start of the pandemic as web-based care quickly became essential for the ongoing safety of patients and health care providers, such as clinicians and other health care professionals. After vaccines were introduced, however, telehealth companies lost value as the need for web-based care appeared to lessen. Presently, both existing telehealth companies and new entrants to the space are seeking ways to innovate, gain investor and customer buy-in, and overcome competitors. New companies are hoping to be seen not as pandemic-era substitutes, but instead as reinforcements to in-person care, valuable in their own right thanks to the convenience and technological advancements they bring. This struggle to reframe the value proposition, or perceived benefit, of telehealth is reflected in fluctuating stock prices and dropping valuations. This viewpoint summarizes the market volatility seen in the telehealth sector since the start of the COVID-19 pandemic and suggests potential opportunities for growth in the space. This is accomplished through a qualitative secondary research approach, leveraging contemporary sources, financial references such as Yahoo! Finance, and peer-reviewed literature to support predictions for the future market. We found that, in 2020, the size of the US telehealth market rose to US $17.9 billion and is estimated to reach US $140.7 billion by 2030. Additionally, digital health venture funding nearly doubled in 2020 over the prior 2 years with total funding rising to US $14.1 billion. However, these factors produced an oversaturated market in which the volume of supply was higher than demand, resulting in a sharp drop in valuations for some as vaccination rates climbed in 2021. In the face of this rebalancing, or return to normal following excessively high or unsustainable valuations, we suggest a possible path forward for telehealth companies in the postpandemic era. Suppliers' current role in the telehealth space-whether health care industry incumbents, that is, traditional health care delivery systems and companies, or "telehealth-first" challengers-are especially relevant to the specific growth strategies they should pursue. Furthermore, consideration of the areas of medicine and characteristics that best lend themselves to web-based care may lead to a greater chance for long-term success in a postpandemic health care delivery system. In the future, we believe investors should expect a bullish market, that is, one characterized by growing share prices. Success is likely to occur in part through changing the actual models of care, as opposed to moving traditional care to a web-based format. The oversaturated market will likely condense into select established telehealth giants who were able to adapt to the changing landscape. While investors may be reasonably hesitant regarding individual telehealth companies, the industry can expect slowed but continued growth., (©Nicholas Bettencourt, Conor John Wilson, Philippa Jaye Johnson, Fabian D'Souza. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.07.2023.)

Published
2023
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42. The Association of Leptin with Left Ventricular Hypertrophy in End-Stage Kidney Disease Patients on Dialysis.

Author

Coimbra S, Catarino C, Sameiro Faria M, Nunes JPL, Rocha S, Valente MJ, Rocha-Pereira P, Bronze-da-Rocha E, Bettencourt N, Beco A, Marques SHM, Oliveira JG, Madureira J, Fernandes JC, Miranda V, Belo L, and Santos-Silva A

Abstract

Left ventricular hypertrophy (LVH) is a common cardiovascular complication in end-stage kidney disease (ESKD) patients. We aimed at studying the association of LVH with adiponectin and leptin levels, cardiovascular stress/injury biomarkers and nutritional status in these patients. We evaluated the LV mass (LVM) and calculated the LVM index (LVMI) in 196 ESKD patients on dialysis; the levels of hemoglobin, calcium, phosphorus, parathyroid hormone, albumin, adiponectin, leptin, N-terminal pro B-type natriuretic peptide (NT-proBNP) and growth differentiation factor (GDF)-15 were analyzed. ESKD patients with LVH ( n = 131) presented higher NT-proBNP and GDF-15, lower hemoglobin and, after adjustment for gender, lower leptin levels compared with non-LVH patients. LVH females also showed lower leptin than the non-LVH female group. In the LVH group, LVMI presented a negative correlation with leptin and a positive correlation with NT-proBNP. Leptin emerged as an independent determinant of LVMI in both groups, and NT-proBNP in the LVH group. Low hemoglobin and leptin and increased calcium, NT-proBNP and dialysis vintage are associated with an increased risk of developing LVH. In ESKD patients on dialysis, LVH is associated with lower leptin values (especially in women), which are negatively correlated with LVMI, and with higher levels of biomarkers of myocardial stress/injury. Leptin and NT-proBNP appear as independent determinants of LVMI; dialysis vintage, hemoglobin, calcium, NT-proBNP and leptin emerged as predicting markers for LVH development. Further studies are needed to better understand the role of leptin in LVH in ESKD patients.

Published
2023
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43. Syncope in the athlete - Minor changes, major diagnosis!

Author

Costa Oliveira C, Vieira C, Galvão Braga C, Martins J, Durães Campos I, Bettencourt N, Rocha S, and Marques J

Subjects
Male, Humans, Adolescent, Electrocardiography, Heart Ventricles diagnostic imaging, Echocardiography, Arrhythmias, Cardiac, Syncope etiology, Arrhythmogenic Right Ventricular Dysplasia complications, Arrhythmogenic Right Ventricular Dysplasia diagnosis
Abstract

We report the case of a 17-year-old athlete who resorted to the emergency department for palpitations and dizziness while exercising. He mentioned two exercise-associated episodes of syncope in the last six months. He was tachycardic and hypotensive. The electrocardiogram showed regular wide complex tachycardia, left bundle branch block morphology with superior axis restored to sinus rhythm after electrical cardioversion. In sinus rhythm, it showed T-wave inversion in V1-V5. Transthoracic echocardiography revealed mild dilation and dysfunction of the right ventricle (RV) with global hypocontractility. Cardiac magnetic resonance (CMR) revealed a RV end diastolic volume indexed to body surface area of 180 ml/m 2 , global hypokinesia and RV dyssynchrony, subepicardial late enhancement in the distal septum and in the middle segment of the inferoseptal wall. The patient underwent a genetic study which showed a mutation in the gene that encodes the desmocolin-2 protein (DSC-2), which is involved in the pathogenesis of arrhythmogenic right ventricular cardiomyopathy (ARVC). According to the modified Task Force Criteria for this diagnosis, the patient presented four major criteria for ARVC. Thus, a subcutaneous cardioverter was implanted, and the patient was followed up at the cardiology department. Arrhythmogenic right ventricular cardiomyopathy diagnosis is based on structural, functional, electrophysiological and genetic criteria reflecting underlying histological changes. This case depicts the essential characteristics for disease recognition., (Copyright © 2022 Sociedade Portuguesa de Cardiologia. Publicado por Elsevier España, S.L.U. All rights reserved.)

Published
2023
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44. Correction to: Computed tomography angiography versus Agatston score for diagnosis of coronary artery disease in patients with stable chest pain: individual patient data meta-analysis of the international COME-CCT Consortium.

Author

Wieske V, Walther M, Dubourg B, Alkadhi H, Nørgaard BL, Meijs MFL, Diederichsen ACP, Wan YL, Mickley H, Nikolaou K, Shabestari AA, Halvorsen BA, Martuscelli E, Sun K, Herzog BA, Marcus RP, Leschka S, Garcia MJ, Ovrehus KA, Knuuti J, Mendoza-Rodriguez V, Bettencourt N, Muraglia S, Buechel RR, Kaufmann PA, Zimmermann E, Tardif JC, Budoff MJ, Schlattmann P, and Dewey M

Published
2022
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45. Multimodality imaging in cardiac amyloidosis: State-of-the-art review.

Author

Timóteo AT, Rosa SA, Brás PG, Ferreira MJV, and Bettencourt N

Subjects
Echocardiography, Humans, Multimodal Imaging methods, Radionuclide Imaging, Amyloid, Amyloidosis diagnostic imaging, Amyloidosis pathology
Abstract

Amyloidosis is a systemic disease, characterized by deposition of amyloid fibrils in various organs, including the heart. For the diagnosis of cardiac amyloidosis (CA) it is required a high level of clinical suspicion and in the presence of clinical, laboratorial, and electrocardiographic red flags, a comprehensive multimodality imaging evaluation is warranted, including echocardiography, magnetic resonance, scintigraphy, and computed tomography, that will confirm diagnosis and define the CA subtype, which is of the utmost importance to plan a treatment strategy. We will review the use of multimodality imaging in the evaluation of CA, including the latest applications, and a practical flow-chart will sum-up this evidence., (© 2022 Wiley Periodicals LLC.)

Published
2022
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47. CardiSort: a convolutional neural network for cross vendor automated sorting of cardiac MR images.

Author

Lim RP, Kachel S, Villa ADM, Kearney L, Bettencourt N, Young AA, Chiribiri A, and Scannell CM

Subjects
Heart diagnostic imaging, Humans, Image Processing, Computer-Assisted methods, Retrospective Studies, Magnetic Resonance Imaging methods, Neural Networks, Computer
Abstract

Objectives: To develop an image-based automatic deep learning method to classify cardiac MR images by sequence type and imaging plane for improved clinical post-processing efficiency., Methods: Multivendor cardiac MRI studies were retrospectively collected from 4 centres and 3 vendors. A two-head convolutional neural network ('CardiSort') was trained to classify 35 sequences by imaging sequence (n = 17) and plane (n = 10). Single vendor training (SVT) on single-centre images (n = 234 patients) and multivendor training (MVT) with multicentre images (n = 434 patients, 3 centres) were performed. Model accuracy and F1 scores on a hold-out test set were calculated, with ground truth labels by an expert radiologist. External validation of MVT (MVT external ) was performed on data from 3 previously unseen magnet systems from 2 vendors (n = 80 patients)., Results: Model sequence/plane/overall accuracy and F1-scores were 85.2%/93.2%/81.8% and 0.82 for SVT and 96.1%/97.9%/94.3% and 0.94 MVT on the hold-out test set. MVT external yielded sequence/plane/combined accuracy and F1-scores of 92.7%/93.0%/86.6% and 0.86. There was high accuracy for common sequences and conventional cardiac planes. Poor accuracy was observed for underrepresented classes and sequences where there was greater variability in acquisition parameters across centres, such as perfusion imaging., Conclusions: A deep learning network was developed on multivendor data to classify MRI studies into component sequences and planes, with external validation. With refinement, it has potential to improve workflow by enabling automated sequence selection, an important first step in completely automated post-processing pipelines., Key Points: • Deep learning can be applied for consistent and efficient classification of cardiac MR image types. • A multicentre, multivendor study using a deep learning algorithm (CardiSort) showed high classification accuracy on a hold-out test set with good generalisation to images from previously unseen magnet systems. • CardiSort has potential to improve clinical workflows, as a vital first step in developing fully automated post-processing pipelines., (© 2022. The Author(s).)

Published
2022
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48. Decoding the radiomic and proteomic phenotype of epicardial adipose tissue associated with adverse left atrial remodelling and post-operative atrial fibrillation in aortic stenosis.

Author

Mancio J, Sousa-Nunes F, Martins R, Fragao-Marques M, Conceicao G, Pessoa-Amorim G, Barros AS, Santa C, Ferreira W, Carvalho M, Miranda IM, Vitorino R, Falcao-Pires I, Manadas B, Ribeiro VG, Leite-Moreira A, Bettencourt N, and Fontes-Carvalho R

Subjects
Adipose Tissue diagnostic imaging, Adipose Tissue metabolism, Humans, Phenotype, Proteomics, Aortic Valve Stenosis complications, Aortic Valve Stenosis diagnostic imaging, Aortic Valve Stenosis surgery, Atrial Fibrillation diagnostic imaging, Atrial Fibrillation epidemiology, Atrial Fibrillation surgery, Atrial Remodeling
Abstract

Aims: Epicardial adipose tissue (EAT) volume and attenuation on computed tomography (CT) have been associated with atrial fibrillation. Beyond these conventional CT measures, radiomics allows extraction of high-dimensional data and deep quantitative adipose tissue phenotyping, which may capture its underlying biology. We aimed to explore the EAT proteomic and CT-radiomic signatures associated with impaired left atrial (LA) remodelling and post-operative atrial fibrillation (POAF)., Methods and Results: We prospectively included 132 patients with severe aortic stenosis with no prior atrial fibrillation referred for aortic valve replacement. Pre-operative non-contrast CT images were obtained for extraction of EAT volume and other radiomic features describing EAT texture. The LA function was assessed by 2D-speckle-tracking echocardiography peak atrial longitudinal strain and peak atrial contraction strain. The EAT biopsies were performed during surgery for proteomic analysis by sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS). The POAF incidence was monitored from surgery until discharge. Impaired LA function and incident POAF were associated with EAT up-regulation of inflammatory and thrombotic proteins, and down-regulation of cardioprotective proteins with anti-inflammatory and anti-lipotoxic properties. The EAT volume was independently associated with LA enlargement, impaired function, and POAF risk. On CT images, EAT texture of patients with POAF was heterogeneous and exhibited higher maximum grey-level values than sinus rhythm patients, which correlated with up-regulation of inflammatory and down-regulation of lipid droplet-formation EAT proteins. The CT radiomics of EAT provided an area under the curve of 0.80 (95% confidence interval: 0.68-0.92) for discrimination between patients with POAF and sinus rhythm., Conclusion: Pre-operative CT-radiomic profile of EAT detected adverse EAT proteomics and identified patients at risk of developing POAF., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Published
2022
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49. Computed tomography angiography versus Agatston score for diagnosis of coronary artery disease in patients with stable chest pain: individual patient data meta-analysis of the international COME-CCT Consortium.

Author

Wieske V, Walther M, Dubourg B, Alkadhi H, Nørgaard BL, Meijs MFL, Diederichsen ACP, Wan YL, Mickley H, Nikolaou K, Shabestari AA, Halvorsen BA, Martuscelli E, Sun K, Herzog BA, Marcus RP, Leschka S, Garcia MJ, Ovrehus KA, Knuuti J, Mendoza-Rodriguez V, Bettencourt N, Muraglia S, Buechel RR, Kaufmann PA, Zimmermann E, Tardif JC, Budoff MJ, Schlattmann P, and Dewey M

Subjects
Calcium, Chest Pain diagnostic imaging, Computed Tomography Angiography methods, Coronary Angiography methods, Humans, Predictive Value of Tests, Tomography, X-Ray Computed, Coronary Artery Disease diagnostic imaging, Coronary Stenosis
Abstract

Objectives: There is conflicting evidence about the comparative diagnostic accuracy of the Agatston score versus computed tomography angiography (CTA) in patients with suspected obstructive coronary artery disease (CAD)., Purpose: To determine whether CTA is superior to the Agatston score in the diagnosis of CAD., Methods: In total 2452 patients with stable chest pain and a clinical indication for invasive coronary angiography (ICA) for suspected CAD were included by the Collaborative Meta-analysis of Cardiac CT (COME-CCT) Consortium. An Agatston score of > 400 was considered positive, and obstructive CAD defined as at least 50% coronary diameter stenosis on ICA was used as the reference standard., Results: Obstructive CAD was diagnosed in 44.9% of patients (1100/2452). The median Agatston score was 74. Diagnostic accuracy of CTA for the detection of obstructive CAD (81.1%, 95% confidence interval [CI]: 77.5 to 84.1%) was significantly higher than that of the Agatston score (68.8%, 95% CI: 64.2 to 73.1%, p < 0.001). Among patients with an Agatston score of zero, 17% (101/600) had obstructive CAD. Diagnostic accuracy of CTA was not significantly different in patients with low to intermediate (1 to < 100, 100-400) versus moderate to high Agatston scores (401-1000, > 1000)., Conclusions: Results in our international cohort show CTA to have significantly higher diagnostic accuracy than the Agatston score in patients with stable chest pain, suspected CAD, and a clinical indication for ICA. Diagnostic performance of CTA is not affected by a higher Agatston score while an Agatston score of zero does not reliably exclude obstructive CAD., Key Points: • CTA showed significantly higher diagnostic accuracy (81.1%, 95% confidence interval [CI]: 77.5 to 84.1%) for diagnosis of coronary artery disease when compared to the Agatston score (68.8%, 95% CI: 64.2 to 73.1%, p < 0.001). • Diagnostic performance of CTA was not affected by increased amount of calcium and was not significantly different in patients with low to intermediate (1 to <100, 100-400) versus moderate to high Agatston scores (401-1000, > 1000). • Seventeen percent of patients with an Agatston score of zero showed obstructive coronary artery disease by invasive angiography showing absence of coronary artery calcium cannot reliably exclude coronary artery disease., (© 2022. The Author(s).)

Published
2022
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