33 results on '"Dede' L"'
Search Results
2. Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics
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Regazzoni, F., Dedè, L., and Quarteroni, A.
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- 2020
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3. Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease
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Abhijeet K. Kohat, Samuel Y. E. Ng, Aidan S. Y. Wong, Nicole S. Y. Chia, Xinyi Choi, Dede L. Heng, Wei Li, Hwee-Lan Ng, Shu-Ting Chua, Shermyn X. M. Neo, Zheyu Xu, Kay-Yaw Tay, Wing-Lok Au, Eng-King Tan, and Louis C. S. Tan
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subtype ,parkinson's disease ,tremor dominant (TD) ,postural instability and gait difficulties ,indeterminate ,over time ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Background: Various classifications have been proposed to subtype Parkinson's disease (PD) based on their motor phenotypes. However, the stability of these subtypes has not been properly evaluated.Objective: The goal of this study was to understand the distribution of PD motor subtypes, their stability over time, and baseline factors that predicted subtype stability.Methods: Participants (n = 170) from two prospective cohorts were included: the Early PD Longitudinal Singapore (PALS) study and the National Neuroscience Institute Movement Disorders Database. Early PD patients were classified into tremor-dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate subtypes according to the Movement Disorder Society's Unified PD Rating Scale (MDS-UPDRS) criteria and clinically evaluated for three consecutive years.Results: At baseline, 60.6% patients were TD, 12.4% patients were indeterminate, and 27.1% patients were PIGD subtypes (p < 0.05). After 3 years, only 62% of patients in TD and 50% of patients in PIGD subtypes remained stable. The mean levodopa equivalent daily dose (LEDD) was higher in the PIGD subtype (276.92 ± 232.91 mg; p = 0.01). Lower LEDD [p < 0.05, odds ratio (OR) 0.99, 95% confidence interval (CI): 0.98–0.99] and higher TD/PIGD ratios (p < 0.05, OR 1.77, 95% CI: 1.29–2.43) were independent predictors of stability of TD subtype with an area under the curve (AUC) of 0.787 (95%CI: 0.669–0.876), sensitivity = 57.8%, and specificity = 89.7%.Conclusion: Only 50–62% of PD motor subtypes as defined by MDS-UPDRS remained stable over 3 years. TD/PIGD ratio and baseline LEDD were independent predictors for TD subtype stability over 3 years.
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- 2021
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4. Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease
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Kohat, Abhijeet K., primary, Ng, Samuel Y. E., additional, Wong, Aidan S. Y., additional, Chia, Nicole S. Y., additional, Choi, Xinyi, additional, Heng, Dede L., additional, Li, Wei, additional, Ng, Hwee-Lan, additional, Chua, Shu-Ting, additional, Neo, Shermyn X. M., additional, Xu, Zheyu, additional, Tay, Kay-Yaw, additional, Au, Wing-Lok, additional, Tan, Eng-King, additional, and Tan, Louis C. S., additional
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- 2021
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5. A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation
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Pagani, S., primary, Dede', L., additional, Frontera, A., additional, Salvador, M., additional, Limite, L. R., additional, Manzoni, A., additional, Lipartiti, F., additional, Tsitsinakis, G., additional, Hadjis, A., additional, Della Bella, P., additional, and Quarteroni, A., additional
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- 2021
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6. Posterior distributions, prior distributions and traceplots for model parameters from SUIHTER: a new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy
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Parolini, N., Dede’, L., Antonietti, P. F., Ardenghi, G., Manzoni, A., Miglio, E., Pugliese, A., Verani, M., and Quarteroni, A.
- Abstract
The COVID-19 epidemic is the latest in a long list of pandemics that have affected humankind in the last century. In this paper, we propose a novel mathematical epidemiological model named SUIHTER from the names of the seven compartments that it comprises: susceptible uninfected individuals (S), undetected (both asymptomatic and symptomatic) infected (U), isolated infected (I), hospitalized (H), threatened (T), extinct (E) and recovered (R). A suitable parameter calibration that is based on the combined use of the least-squares method and the Markov chain Monte Carlo method is proposed with the aim of reproducing the past history of the epidemic in Italy, which surfaced in late February and is still ongoing to date, and of validating SUIHTER in terms of its predicting capabilities. A distinctive feature of the new model is that it allows a one-to-one calibration strategy between the model compartments and the data that are made available daily by the Italian Civil Protection Department. The new model is then applied to the analysis of the Italian epidemic with emphasis on the second outbreak, which emerged in autumn 2020. In particular, we show that the epidemiological model SUIHTER can be suitably used in a predictive manner to perform scenario analysis at a national level.
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- 2021
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7. High Outpatient Attendance During COVID ‐19 Lockdown When Patients Were Given the Option to Return
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Teck Heng Chia, Eng-King Tan, Wei‐Shan Li, Dede L. Heng, and Ee-Chien Lim
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2019-20 coronavirus outbreak ,medicine.medical_specialty ,Coronavirus disease 2019 (COVID-19) ,business.industry ,SARS-CoV-2 ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Attendance ,MEDLINE ,Clinical Neurology ,COVID-19 ,Hospitalization ,Neurology ,Emergency medicine ,Communicable Disease Control ,Outpatients ,Medicine ,Humans ,Neurology (clinical) ,Letters: New Observation ,business - Published
- 2020
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8. Abstract 5110: Runx knockout in breast luminal stem/progenitor cells induced precancerous lesion via robust expression of ERα
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Akihiro Yamamura, Dede L. Heng, Motomi Osato, Naing Naing Mon, Junichi Matsuo, Linda Sh Chuang, and Yoshiaki Ito
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Cancer Research ,Hematopoietic stem cell ,Cancer ,Biology ,Hyperplasia ,medicine.disease ,chemistry.chemical_compound ,Haematopoiesis ,Breast cancer ,medicine.anatomical_structure ,Oncology ,RUNX1 ,chemistry ,Cancer research ,medicine ,Progenitor cell ,Stem cell - Abstract
In breast cancer, 83% of patients were diagnosed as hormone receptor positive, luminal-type, breast cancer (Anderson et al., 2014). Although primary luminal-type breast cancer can be controlled by endocrine therapy, more than 20% of patients have recurrence in 20 years (Pan et al., 2017). Understanding of luminal-type breast cancer would provide benefits to a large number of patients. However, cell of origin and genes responsible for luminal-type breast cancer have not been fully understood. Luminal epithelial cells are considered as origin of breast cancer (Anderson et al., 2014), although not fully proven yet. In addition, extensive genomic analysis of breast cancer patients in TCGA study showed that RUNX genes were downregulated in luminal-type breast cancer: RUNX1 mutation was found in multiple patients, and RUNX3 gene was highly methylated. We previously reported that 270 bp Runx1 enhancer element (eR1) marks hematopoietic stem cell and stomach stem cell (Ng et al., 2010; Matsuo et al., 2017). We also found that this eR1 marks a subset of luminal epithelial cells in mouse mammary gland. Lineage-tracing experiment showed that the eR1+ cells mainly differentiated into luminal cells, but not to basal cells in vivo. These eR1+ cells also contribute to differentiation of alveolar cells in pregnant mice. Interestingly, in vitro lineage tracing by using organoid culture showed that eR1+ cells differentiated into both liminal and basal cells. Runx1 and Runx3 knockout in luminal stem cells showed increase of cell growth, and histology was similar to precancerous lesion such as hyperplasia and ductal carcinoma in situ (DCIS). These lesions showed robust expression of ERα compared with control mice. These results suggested that depletion of Runx in luminal stem cells induces precancerous lesion via robust expression of ERα. References: Anderson WF, Rosenberg PS, Prat A, et al. How many etiological subtypes of breast cancer: Two, three, four, or more? J Natl Cancer Inst 2014;106. Pan H, Gray R, Braybrooke J, et al. 20-year risks of breast-cancer recurrence after stopping endocrine therapy at 5 years. N Engl J Med 2017:1836-46. Ng CE, Yokomizo T, Yamashita N, et al. A Runx1 intronic enhancer marks hemogenic endothelial cells and hematopoietic stem cells. Stem Cells 2010:1869-81. Matsuo J, Kimura S, Yamamura A, et al. Identification of stem cells in the epithelium of the stomach corpus and antrum of mice. Gastroenterology 2017:218-31. Citation Format: Junichi Matsuo, Naing Naing Mon, Akihiro Yamamura, Dede L. Heng, Linda SH Chuang, Motomi Osato, Yoshiaki Ito. Runx knockout in breast luminal stem/progenitor cells induced precancerous lesion via robust expression of ERα [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5110.
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- 2018
9. 590Development of a patient-specific computational fluid dynamics model of the LA in AF for stroke risk assessment
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Masci, A., primary, Forti, D., additional, Alessandrini, M., additional, Menghini, F., additional, Dede, L., additional, Corsi, C., additional, Quarteroni, A., additional, and Tomasi, C., additional
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- 2017
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10. Über das Vorkommen von Blei und Zink in den Sintern der Bad Nauheimer Sprudel
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Dede, L.
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- 1923
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11. Mikrochemie
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Schleicher, A., Blacet, Fr. E., Mac Donald, G. D., Pierce, H. F., Friedenwald, J. S., Freeman, D., Kofler, L., Fischer, R., Kofler, Adelheid, Winkelmann, J., Salvioni, E., Friedrich, A., Manley, J. J., Dede, L., Donau, J., Damianovich, H., and Sussmann, S.
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- 1936
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12. Über die Trennung des Kalziums vom Magnesium
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Kallauner, O., Preller, J., Liesse, Ch., Dede, L., Cappel, A., and Carron, E. C.
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- 1913
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13. Über die Beeinflussung der Sulfidfä,llung durch den Zusatz von Neutralsalzen
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Dede, L., Becker, Th., Bonin, P., Mertens, K. H., Biltz, W., and Marcus, E.
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- 1926
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14. Literatur
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Koppel, I., Peters, F., Jellinek, K., Berthoud, A., Lorenz, R., Roth, W. A., Michaelis, L., Kauffmann, H., Dede, L., Müller, Robert, Hückel, W., Ruzicka, L., Loewen, H., Klein, G., Strebinger, R., Benedetti-Pichler, A., and Houben, J.
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- 1928
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15. Zink und Cadmium
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Hackl, O., Dede, L., Springer, J. W., Kieper, K., Olivier, E., Boy, C., Beyne, E., Mohler, H., Widmer, R., Snell, Bordeianu, C. V., Chalupny, K., Breisch, K., de Koninck, L. L., Ludwig, A., Nyman, E., Lorck Hagen, L., Raymond, L. R., Brumbaugh, W. V., Leroy Adkins, E., Fiévet, A., Tananaeff, Iw., Knoppick, E., von Bogdandy, St., Polanyi, M., Merr, H. N., Bradley, H. F., Sarkar, P. B., Datta-Ray, B. K., Keefe, W. H., and Newell, I. L.
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- 1933
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16. Fällungsvorgänge
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von Zombory, L., Pollák, L., Dede, L., Karaoglanov, Z., and Sagortschev, B.
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- 1935
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17. Über die Oxydation des Nickelii-hydroxyds und Kobaltii-hydroxyds durch Persulfat
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Dede, L. and Zieriacks, Hedwig
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- 1942
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18. Isogeometric Analysis for Topology Optimization with a Phase Field Model
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TEXAS UNIV AT AUSTIN INST FOR COMPUTATIONAL ENGINEERING AND SCIENCES, Dede, L, Borden, M J, Hughes, T J, TEXAS UNIV AT AUSTIN INST FOR COMPUTATIONAL ENGINEERING AND SCIENCES, Dede, L, Borden, M J, and Hughes, T J
- Abstract
We consider a phase field model for the formulation and solution of topology optimization problems in the minimum compliance case. In this model, the optimal topology is obtained as the steady state of the phase transition described by the generalized Cahn-Hilliard equation which naturally embeds the volume constraint on the amount of material available for distribution in the design domain. We reformulate the model as a coupled system and we highlight the dependency of the optimal topologies on dimensionless parameters; also, we discuss the issue of mesh dependency of the solution. We consider Isogeometric Analysis for the spatial approximation which facilitates encapsulating the exactness of the representation of the design domain in the topology optimization and is particularly suitable for the analysis of phase field problems. We demonstrate the validity of the approach and numerical approximation by solving two and three dimensional topology optimization problems., Also supported by DOE contract DE-AC04-94AL85000.
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- 2011
19. Dreiphasige Emulsionen
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Bechhold, H., Dede, L., and Reiner, L.
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Colloid and Surface Chemistry ,Polymers and Plastics ,Materials Chemistry ,Physical and Theoretical Chemistry - Abstract
n/a
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- 1921
20. Wasser
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Ellms, I. W., Hauser, S. I., Winkler, L. W., Pecker, H., Froboese, V., Stuart, A. T., Malméjac, F., Tillmans, J., Heublein, O., Noll, H., Kolthoff, J. M., Klut, H., Dietl, Dede, L., Hauser, E., Chamot, E. M., Pratt, D. S., Johnson, A. E., Silvester, H., Vaubel, W., Denigès, G., Miller, E. H., Rothenfusser, S., Bornand, M., Rosenthaler, L., Jahn, V., Dané, A., Liebermann, L., Acel, D., Phelps, E. B., Shoub, H. L., Escaich, Berger, H., Elsdon, G. D., Evers, N., Brubaker, H. W., and Bruckmiller, F. W.
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n/a
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- 1922
21. Über die Verhinderung der Schwefelwasserstoff-Fällung durch neutrale Chloride. (Vorläufige Mitteilung)
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Dede, L. and Bonin, P.
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n/a
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- 1922
22. Simulation of the Hemodynamic Effects of the Left Atrial Appendage Occlusion in Atrial Fibrillation: Preliminary Results
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Luca Dedè, Alfio Quarteroni, Cristiana Corsi, Nadia D'Alessandro, Alice Andalo, Alessandro Masci, Corrado Tomasi, D'Alessandro N., Masci A., Andalo A., Dede L., Tomasi C., Quarteroni A., and Corsi C.
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medicine.medical_specialty ,Cardioembolic stroke ,Intracardiac thrombus ,business.industry ,medicine.medical_treatment ,Hemodynamics ,Atrial fibrillation ,030204 cardiovascular system & hematology ,medicine.disease ,Left atrial appendage occlusion ,03 medical and health sciences ,0302 clinical medicine ,Left atrial ,Internal medicine ,Occlusion ,medicine ,Cardiology ,030212 general & internal medicine ,cardiovascular diseases ,business ,Hemodynamic effects ,left atrial appenddage occlusion, thromboembolic risk, atrial fibrillation - Abstract
Atrial fibrillation (AF) is responsible for 15–18 % of all strokes. In AF patients, the left atrial appendage (LAA) represents the main thrombogenic spot, being the site of 90% of intracardiac thrombus formation. Therefore, the occlusion of the LAA (LAAO) is a novel strategy for cardioembolic stroke prophylaxis. The aim of this study was the simulation of the fluid dynamics effects of the LAAO in AF patients, by applying two different devices (Amulet™ and Watchman™), in order to predict patient-specific hemodynamic changes due to LAAO and to detect the most effective devices in reducing stroke risk as well.
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- 2020
23. 3282Evaluation of blood flow patterns for personalized stroke risk assessment in atrial fibrillation
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Alfio Quarteroni, Corrado Tomasi, Martino Alessandrini, Cristiana Corsi, Alessandro Masci, Luca Dedè, Masci, A, Alessandrini, M, Dede, L, Tomasi, C, Quarteroni, A, and Corsi, C
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medicine.medical_specialty ,business.industry ,Left atrium ,Atrial fibrillation ,Blood flow ,medicine.disease ,Stroke risk ,medicine.anatomical_structure ,Internal medicine ,medicine ,Cardiology ,atrial fibrillation, left atrium, left atrial appendage, computational fluid dynamics model ,Cardiology and Cardiovascular Medicine ,business - Published
- 2018
24. A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data.
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Zingaro A, Ahmad Z, Kholmovski E, Sakata K, Dede' L, Morris AK, Quarteroni A, and Trayanova NA
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- Humans, Female, Male, Middle Aged, Risk Assessment methods, Aged, Computer Simulation, Models, Cardiovascular, Magnetic Resonance Imaging, Cine methods, Stroke physiopathology, Heart Atria physiopathology, Heart Atria diagnostic imaging, Hydrodynamics, Hemodynamics
- Abstract
Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA 2 DS 2 -VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments., (© 2024. The Author(s).)
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- 2024
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25. Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations.
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Salvador M, Strocchi M, Regazzoni F, Augustin CM, Dede' L, Niederer SA, and Quarteroni A
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Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-based methods can make the creation of fast and accurate whole-heart digital twins feasible. We use Latent Neural Ordinary Differential Equations (LNODEs) to learn the pressure-volume dynamics of a heart failure patient. Our surrogate model is trained from 400 simulations while accounting for 43 parameters describing cell-to-organ cardiac electromechanics and cardiovascular hemodynamics. LNODEs provide a compact representation of the 3D-0D model in a latent space by means of an Artificial Neural Network that retains only 3 hidden layers with 13 neurons per layer and allows for numerical simulations of cardiac function on a single processor. We employ LNODEs to perform global sensitivity analysis and parameter estimation with uncertainty quantification in 3 hours of computations, still on a single processor., (© 2024. The Author(s).)
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- 2024
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26. A mathematical model to assess the effects of COVID-19 on the cardiocirculatory system.
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Tonini A, Vergara C, Regazzoni F, Dede' L, Scrofani R, Cogliati C, and Quarteroni A
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- Humans, Reproducibility of Results, Pulmonary Circulation, Models, Theoretical, COVID-19, Cardiovascular System
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Impaired cardiac function has been described as a frequent complication of COVID-19-related pneumonia. To investigate possible underlying mechanisms, we represented the cardiovascular system by means of a lumped-parameter 0D mathematical model. The model was calibrated using clinical data, recorded in 58 patients hospitalized for COVID-19-related pneumonia, to make it patient-specific and to compute model outputs of clinical interest related to the cardiocirculatory system. We assessed, for each patient with a successful calibration, the statistical reliability of model outputs estimating the uncertainty intervals. Then, we performed a statistical analysis to compare healthy ranges and mean values (over patients) of reliable model outputs to determine which were significantly altered in COVID-19-related pneumonia. Our results showed significant increases in right ventricular systolic pressure, diastolic and mean pulmonary arterial pressure, and capillary wedge pressure. Instead, physical quantities related to the systemic circulation were not significantly altered. Remarkably, statistical analyses made on raw clinical data, without the support of a mathematical model, were unable to detect the effects of COVID-19-related pneumonia in pulmonary circulation, thus suggesting that the use of a calibrated 0D mathematical model to describe the cardiocirculatory system is an effective tool to investigate the impairments of the cardiocirculatory system associated with COVID-19., (© 2024. The Author(s).)
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- 2024
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27. Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks.
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Regazzoni F, Pagani S, Salvador M, Dede' L, and Quarteroni A
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Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equations, thus demanding extensive computational resources. In contrast, data-driven approaches leverage deep learning algorithms to describe system evolution in low-dimensional spaces. We introduce an architecture, termed Latent Dynamics Network, capable of uncovering low-dimensional intrinsic dynamics in potentially non-Markovian systems. Latent Dynamics Networks automatically discover a low-dimensional manifold while learning the system dynamics, eliminating the need for training an auto-encoder and avoiding operations in the high-dimensional space. They predict the evolution, even in time-extrapolation scenarios, of space-dependent fields without relying on predetermined grids, thus enabling weight-sharing across query-points. Lightweight and easy-to-train, Latent Dynamics Networks demonstrate superior accuracy (normalized error 5 times smaller) in highly-nonlinear problems with significantly fewer trainable parameters (more than 10 times fewer) compared to state-of-the-art methods., (© 2024. The Author(s).)
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- 2024
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28. The role of computational methods in cardiovascular medicine: a narrative review.
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Fumagalli I, Pagani S, Vergara C, Dede' L, Adebo DA, Del Greco M, Frontera A, Luciani GB, Pontone G, Scrofani R, and Quarteroni A
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Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data with physical knowledge of the processes underlying the heart function. These models have been increasingly employed in clinical practice to understand pathological mechanisms and their progression, design medical devices, support clinicians in improving therapies. Hinging upon a long-year experience in cardiovascular modeling, we have recently constructed a computational multi-physics and multi-scale integrated model of the heart for the investigation of its physiological function, the analysis of pathological conditions, and to support clinicians in both diagnosis and treatment planning. This narrative review aims to systematically discuss the role that such model had in addressing specific clinical questions, and how further impact of computational models on clinical practice are envisaged., Methods: We developed computational models of the physical processes encompassed by the heart function (electrophysiology, electrical activation, force generation, mechanics, blood flow dynamics, valve dynamics, myocardial perfusion) and of their inherently strong coupling. To solve the equations of such models, we devised advanced numerical methods, implemented in a flexible and highly efficient software library. We also developed computational procedures for clinical data post-processing-like the reconstruction of the heart geometry and motion from diagnostic images-and for their integration into computational models., Key Content and Findings: Our integrated computational model of the heart function provides non-invasive measures of indicators characterizing the heart function and dysfunctions, and sheds light on its underlying processes and their coupling. Moreover, thanks to the close collaboration with several clinical partners, we addressed specific clinical questions on pathological conditions, such as arrhythmias, ventricular dyssynchrony, hypertrophic cardiomyopathy, degeneration of prosthetic valves, and the way coronavirus disease 2019 (COVID-19) infection may affect the cardiac function. In multiple cases, we were also able to provide quantitative indications for treatment., Conclusions: Computational models provide a quantitative and detailed tool to support clinicians in patient care, which can enhance the assessment of cardiac diseases, the prediction of the development of pathological conditions, and the planning of treatments and follow-up tests., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-23-184/coif). The series “The Impact of the Progresses of Knowledge and Technologies in Pediatrics” was commissioned by the editorial office without any funding or sponsorship. The authors have no other conflicts of interest to declare., (2024 Translational Pediatrics. All rights reserved.)
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- 2024
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29. lifex-ep: a robust and efficient software for cardiac electrophysiology simulations.
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Africa PC, Piersanti R, Regazzoni F, Bucelli M, Salvador M, Fedele M, Pagani S, Dede' L, and Quarteroni A
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- Humans, Computer Simulation, Myocardium, Africa, Electrophysiologic Techniques, Cardiac, Software
- Abstract
Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors of various research teams, comprehensive and user-friendly software programs for cardiac simulations, capable of accurately replicating both normal and pathological conditions, are still in the process of achieving full maturity within the scientific community., Results: This work introduces [Formula: see text]-ep, a publicly available software for numerical simulations of the electrophysiology activity of the cardiac muscle, under both normal and pathological conditions. [Formula: see text]-ep employs the monodomain equation to model the heart's electrical activity. It incorporates both phenomenological and second-generation ionic models. These models are discretized using the Finite Element method on tetrahedral or hexahedral meshes. Additionally, [Formula: see text]-ep integrates the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, previously released in Africa et al., 2023, within [Formula: see text]-fiber. As an alternative, users can also choose to import myofibers from a file. This paper provides a concise overview of the mathematical models and numerical methods underlying [Formula: see text]-ep, along with comprehensive implementation details and instructions for users. [Formula: see text]-ep features exceptional parallel speedup, scaling efficiently when using up to thousands of cores, and its implementation has been verified against an established benchmark problem for computational electrophysiology. We showcase the key features of [Formula: see text]-ep through various idealized and realistic simulations conducted in both normal and pathological scenarios. Furthermore, the software offers a user-friendly and flexible interface, simplifying the setup of simulations using self-documenting parameter files., Conclusions: [Formula: see text]-ep provides easy access to cardiac electrophysiology simulations for a wide user community. It offers a computational tool that integrates models and accurate methods for simulating cardiac electrophysiology within a high-performance framework, while maintaining a user-friendly interface. [Formula: see text]-ep represents a valuable tool for conducting in silico patient-specific simulations., (© 2023. BioMed Central Ltd., part of Springer Nature.)
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- 2023
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30. Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: An application to the Italian scenario.
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Ziarelli G, Dede' L, Parolini N, Verani M, and Quarteroni A
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In the context of SARS-CoV-2 pandemic, mathematical modelling has played a fundamental role for making forecasts, simulating scenarios and evaluating the impact of preventive political, social and pharmaceutical measures. Optimal control theory represents a useful mathematical tool to plan the vaccination campaign aimed at eradicating the pandemic as fast as possible. The aim of this work is to explore the optimal prioritisation order for planning vaccination campaigns able to achieve specific goals, as the reduction of the amount of infected, deceased and hospitalized in a given time frame, among age classes. For this purpose, we introduce an age stratified SIR -like epidemic compartmental model settled in an abstract framework for modelling two-doses vaccination campaigns and conceived with the description of COVID19 disease. Compared to other recent works, our model incorporates all stages of the COVID-19 disease, including death or recovery, without accounting for additional specific compartments that would increase computational complexity and that are not relevant for our purposes. Moreover, we introduce an optimal control framework where the model is the state problem while the vaccine doses administered are the control variables. An extensive campaign of numerical tests, featured in the Italian scenario and calibrated on available data from Dipartimento di Protezione Civile Italiana, proves that the presented framework can be a valuable tool to support the planning of vaccination campaigns. Indeed, in each considered scenario, our optimization framework guarantees noticeable improvements in terms of reducing deceased, infected or hospitalized individuals with respect to the baseline vaccination policy., (© 2023 The Authors.)
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- 2023
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31. A comprehensive mathematical model for cardiac perfusion.
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Zingaro A, Vergara C, Dede' L, Regazzoni F, and Quarteroni A
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- Reproducibility of Results, Perfusion, Heart Ventricles, Heart, Myocardium
- Abstract
The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, valve modeling, and a multicompartment Darcy model of perfusion. We consider a fully coupled electromechanical model of the left heart that provides input for a fully coupled Navier-Stokes-Darcy Model for myocardial perfusion. The fluid dynamics problem is modeled in a left heart geometry that includes large epicardial coronaries, while the multicompartment Darcy model is set in a biventricular myocardium. Using a realistic and detailed cardiac geometry, our simulations demonstrate the biophysical fidelity of our model in describing cardiac perfusion. Specifically, we successfully validate the model reliability by comparing in-silico coronary flow rates and average myocardial blood flow with clinically established values ranges reported in relevant literature. Additionally, we investigate the impact of a regurgitant aortic valve on myocardial perfusion, and our results indicate a reduction in myocardial perfusion due to blood flow taken away by the left ventricle during diastole. To the best of our knowledge, our work represents the first instance where electromechanics, hemodynamics, and perfusion are integrated into a single computational framework., (© 2023. Springer Nature Limited.)
- Published
- 2023
- Full Text
- View/download PDF
32. lifex-fiber: an open tool for myofibers generation in cardiac computational models.
- Author
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Africa PC, Piersanti R, Fedele M, Dede' L, and Quarteroni A
- Subjects
- Myocytes, Cardiac, Computer Simulation, Software, Medicine
- Abstract
Background: Modeling the whole cardiac function involves the solution of several complex multi-physics and multi-scale models that are highly computationally demanding, which call for simpler yet accurate, high-performance computational tools. Despite the efforts made by several research groups, no software for whole-heart fully-coupled cardiac simulations in the scientific community has reached full maturity yet., Results: In this work we present [Formula: see text]-fiber, an innovative tool for the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, which are the essential building blocks for modeling the electrophysiological, mechanical and electromechanical cardiac function, from single-chamber to whole-heart simulations. [Formula: see text]-fiber is the first publicly released module for cardiac simulations based on [Formula: see text], an open-source, high-performance Finite Element solver for multi-physics, multi-scale and multi-domain problems developed in the framework of the iHEART project, which aims at making in silico experiments easily reproducible and accessible to a wide community of users, including those with a background in medicine or bio-engineering., Conclusions: The tool presented in this document is intended to provide the scientific community with a computational tool that incorporates general state of the art models and solvers for simulating the cardiac function within a high-performance framework that exposes a user- and developer-friendly interface. This report comes with an extensive technical and mathematical documentation to welcome new users to the core structure of [Formula: see text]-fiber and to provide them with a possible approach to include the generated cardiac fibers into more sophisticated computational pipelines. In the near future, more modules will be successively published either as pre-compiled binaries for x86-64 Linux systems or as open source software., (© 2023. The Author(s).)
- Published
- 2023
- Full Text
- View/download PDF
33. Modelling the COVID-19 epidemic and the vaccination campaign in Italy by the SUIHTER model.
- Author
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Parolini N, Dede' L, Ardenghi G, and Quarteroni A
- Abstract
Several epidemiological models have been proposed to study the evolution of COVID-19 pandemic. In this paper, we propose an extension of the SUIHTER model, to analyse the COVID-19 spreading in Italy, which accounts for the vaccination campaign and the presence of new variants when they become dominant. In particular, the specific features of the variants (e.g. their increased transmission rate) and vaccines (e.g. their efficacy to prevent transmission, hospitalization and death) are modeled, based on clinical evidence. The new model is validated comparing its near-future forecast capabilities with other epidemiological models and exploring different scenario analyses., Competing Interests: 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., (© 2022 The Authors.)
- Published
- 2022
- Full Text
- View/download PDF
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