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3 results on '"Aquaro G. D."'

1. AI Cardiac MRI Scar Analysis Aids Prediction of Major Arrhythmic Events in the Multicenter DERIVATE Registry

Author

Ghanbari, F, Joyce, T, Lorenzoni, V, Guaricci, A, Pavon, A, Fusini, L, Andreini, D, Rabbat, M, Aquaro, G, Abete, R, Bogaert, J, Camastra, G, Carigi, S, Carrabba, N, Casavecchia, G, Censi, S, Cicala, G, De Cecco, C, De Lazzari, M, Di Giovine, G, Di Roma, M, Focardi, M, Gaibazzi, N, Gismondi, A, Gravina, M, Lanzillo, C, Lombardi, M, Lozano-Torres, J, Masi, A, Moro, C, Muscogiuri, G, Nese, A, Pradella, S, Sbarbati, S, Schoepf, U, Valentini, A, Crelier, G, Masci, P, Pontone, G, Kozerke, S, Schwitter, J, Ghanbari F., Joyce T., Lorenzoni V., Guaricci A. I., Pavon A. -G., Fusini L., Andreini D., Rabbat M. G., Aquaro G. D., Abete R., Bogaert J., Camastra G., Carigi S., Carrabba N., Casavecchia G., Censi S., Cicala G., De Cecco C. N., De Lazzari M., Di Giovine G., Di Roma M., Focardi M., Gaibazzi N., Gismondi A., Gravina M., Lanzillo C., Lombardi M., Lozano-Torres J., Masi A., Moro C., Muscogiuri G., Nese A., Pradella S., Sbarbati S., Schoepf U. J., Valentini A., Crelier G., Masci P. G., Pontone G., Kozerke S., Schwitter J., Ghanbari, F, Joyce, T, Lorenzoni, V, Guaricci, A, Pavon, A, Fusini, L, Andreini, D, Rabbat, M, Aquaro, G, Abete, R, Bogaert, J, Camastra, G, Carigi, S, Carrabba, N, Casavecchia, G, Censi, S, Cicala, G, De Cecco, C, De Lazzari, M, Di Giovine, G, Di Roma, M, Focardi, M, Gaibazzi, N, Gismondi, A, Gravina, M, Lanzillo, C, Lombardi, M, Lozano-Torres, J, Masi, A, Moro, C, Muscogiuri, G, Nese, A, Pradella, S, Sbarbati, S, Schoepf, U, Valentini, A, Crelier, G, Masci, P, Pontone, G, Kozerke, S, Schwitter, J, Ghanbari F., Joyce T., Lorenzoni V., Guaricci A. I., Pavon A. -G., Fusini L., Andreini D., Rabbat M. G., Aquaro G. D., Abete R., Bogaert J., Camastra G., Carigi S., Carrabba N., Casavecchia G., Censi S., Cicala G., De Cecco C. N., De Lazzari M., Di Giovine G., Di Roma M., Focardi M., Gaibazzi N., Gismondi A., Gravina M., Lanzillo C., Lombardi M., Lozano-Torres J., Masi A., Moro C., Muscogiuri G., Nese A., Pradella S., Sbarbati S., Schoepf U. J., Valentini A., Crelier G., Masci P. G., Pontone G., Kozerke S., and Schwitter J.

Abstract

Background: Scar burden with late gadolinium enhancement (LGE) cardiac MRI (CMR) predicts arrhythmic events in patients with postinfarction in single-center studies. However, LGE analysis requires experienced human observers, is time consuming, and introduces variability. Purpose: To test whether postinfarct scar with LGE CMR can be quantified fully automatically by machines and to compare the ability of LGE CMR scar analyzed by humans and machines to predict arrhythmic events. Materials and Methods: This study is a retrospective analysis of the multicenter, multivendor CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry. Patients with chronic heart failure, echocardiographic left ventricular ejection fraction (LVEF) of less than 50%, and LGE CMR were recruited (from January 2015 through December 2020). In the current study, only patients with ischemic cardiomyopathy were included. Quantification of total, dense, and nondense scars was carried out by two experienced readers or a Ternaus network, trained and tested with LGE images of 515 and 246 patients, respectively. Univariable and multivariable Cox analyses were used to assess patient and cardiac characteristics associated with a major adverse cardiac event (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare model performances. Results: In 761 patients (mean age, 65 years ± 11, 671 men), 83 MACEs occurred. With use of the testing group, univariable Cox-analysis found New York Heart Association class, left ventricle volume and/or function parameters (by echocardiography or CMR), guideline criterion (LVEF of ≤35% and New York Heart Association class II or III), and LGE scar analyzed by humans or the machine-learning algorithm as predictors of MACE. Machine-based dense or total scar conferred incremental value over the guideline criterion for the association with MACE (AUC: 0.68 vs 0.63, P = .02 and AUC: 0.67 vs 0.63

Published
2023

2. Cardiovascular Magnetic Resonance in Patients with Cardiac Electronic Devices: Evidence from a Multicenter Study

Author

Barison, A, Ricci, F, Pavon, A, Muscogiuri, G, Bisaccia, G, Camastra, G, De Lazzari, M, Lanzillo, C, Raguso, M, Monti, L, Vargiu, S, Pedrotti, P, Piacenti, M, Todiere, G, Pontone, G, Indolfi, C, Dellegrottaglie, S, Lombardi, M, Schwitter, J, Aquaro, G, Barison A., Ricci F., Pavon A. G., Muscogiuri G., Bisaccia G., Camastra G., De Lazzari M., Lanzillo C., Raguso M., Monti L., Vargiu S., Pedrotti P., Piacenti M., Todiere G., Pontone G., Indolfi C., Dellegrottaglie S., Lombardi M., Schwitter J., Aquaro G. D., Barison, A, Ricci, F, Pavon, A, Muscogiuri, G, Bisaccia, G, Camastra, G, De Lazzari, M, Lanzillo, C, Raguso, M, Monti, L, Vargiu, S, Pedrotti, P, Piacenti, M, Todiere, G, Pontone, G, Indolfi, C, Dellegrottaglie, S, Lombardi, M, Schwitter, J, Aquaro, G, Barison A., Ricci F., Pavon A. G., Muscogiuri G., Bisaccia G., Camastra G., De Lazzari M., Lanzillo C., Raguso M., Monti L., Vargiu S., Pedrotti P., Piacenti M., Todiere G., Pontone G., Indolfi C., Dellegrottaglie S., Lombardi M., Schwitter J., and Aquaro G. D.

Abstract

Background: Most recent cardiac implantable electronic devices (CIEDs) can safely undergo a cardiovascular magnetic resonance (CMR) scan under certain conditions, but metal artifacts may degrade image quality. The aim of this study was to assess the overall diagnostic yield of CMR and the extent of metal artifacts in a multicenter, multivendor study on CIED patients referred for CMR. Methods: We analyzed 309 CMR scans from 292 patients (age 57 ± 16 years, 219 male) with an MR-conditional pacemaker (n = 122), defibrillator (n = 149), or loop recorder (n = 38); CMR scans were performed in 10 centers from 2012 to 2020; MR-unsafe implants were excluded. Clinical and device parameters were recorded before and after the CMR scan. A visual analysis of metal artifacts was performed for each sequence on a segmental basis, based on a 5-point artifact score. Results: The vast majority of CMR scans (n = 255, 83%) were completely performed, while only 32 (10%) were interrupted soon after the first sequences and 22 (7%) were only partly acquired; CMR quality was non-diagnostic in 34 (11%) scans, poor (<1/3 sequences were diagnostic) in 25 (8%), or acceptable (1/3 to 2/3 sequences were diagnostic) in 40 (13%), while most scans (n = 201, 68%) were of overall good quality. No adverse event or device malfunctioning occurred, and only nonsignificant changes in device parameters were recorded. The most affected sequences were SSFP (median score 0.32 [interquartile range 0.07–0.91]), followed by GRE (0.18 [0.02–0.59]) and LGE (0.14 [0.02–0.55]). ICDs induced more artifacts (median score in SSFP images 0.87 [0.50–1.46]) than PMs (0.11 [0.03–0.28]) or ILRs (0.11 [0.00–0.56]). Moreover, most artifacts were located in the anterior, anteroseptal, anterolateral, and apical segments of the LV and in the outflow tract of the RV. Conclusions: CMR is a versatile imaging technique, with a high safety profile and overall good image quality even in patients with MR-conditional CIEDs. Several stra

Published
2023

3. Acute Myocarditis Associated With Desmosomal Gene Variants

Author

Ammirati, E, Raimondi, F, Piriou, N, Sardo Infirri, L, Mohiddin, S, Mazzanti, A, Shenoy, C, Cavallari, U, Imazio, M, Aquaro, G, Olivotto, I, Pedrotti, P, Sekhri, N, Van de Heyning, C, Broeckx, G, Peretto, G, Guttmann, O, Dellegrottaglie, S, Scatteia, A, Gentile, P, Merlo, M, Goldberg, R, Reyentovich, A, Sciamanna, C, Klaassen, S, Poller, W, Trankle, C, Abbate, A, Keren, A, Horowitz-Cederboim, S, Cadrin-Tourigny, J, Tadros, R, Annoni, G, Bonoldi, E, Toquet, C, Marteau, L, Probst, V, Trochu, J, Kissopoulou, A, Grosu, A, Kukavica, D, Trancuccio, A, Gil, C, Tini, G, Pedrazzini, M, Torchio, M, Sinagra, G, Gimeno, J, Bernasconi, D, Valsecchi, M, Klingel, K, Adler, E, Camici, P, Cooper, L, Ammirati E., Raimondi F., Piriou N., Sardo Infirri L., Mohiddin S. A., Mazzanti A., Shenoy C., Cavallari U. A., Imazio M., Aquaro G. D., Olivotto I., Pedrotti P., Sekhri N., Van de Heyning C. M., Broeckx G., Peretto G., Guttmann O., Dellegrottaglie S., Scatteia A., Gentile P., Merlo M., Goldberg R. I., Reyentovich A., Sciamanna C., Klaassen S., Poller W., Trankle C. R., Abbate A., Keren A., Horowitz-Cederboim S., Cadrin-Tourigny J., Tadros R., Annoni G. A., Bonoldi E., Toquet C., Marteau L., Probst V., Trochu J. N., Kissopoulou A., Grosu A., Kukavica D., Trancuccio A., Gil C., Tini G., Pedrazzini M., Torchio M., Sinagra G., Gimeno J. R., Bernasconi D., Valsecchi M. G., Klingel K., Adler E. D., Camici P. G., Cooper L. T., Ammirati, E, Raimondi, F, Piriou, N, Sardo Infirri, L, Mohiddin, S, Mazzanti, A, Shenoy, C, Cavallari, U, Imazio, M, Aquaro, G, Olivotto, I, Pedrotti, P, Sekhri, N, Van de Heyning, C, Broeckx, G, Peretto, G, Guttmann, O, Dellegrottaglie, S, Scatteia, A, Gentile, P, Merlo, M, Goldberg, R, Reyentovich, A, Sciamanna, C, Klaassen, S, Poller, W, Trankle, C, Abbate, A, Keren, A, Horowitz-Cederboim, S, Cadrin-Tourigny, J, Tadros, R, Annoni, G, Bonoldi, E, Toquet, C, Marteau, L, Probst, V, Trochu, J, Kissopoulou, A, Grosu, A, Kukavica, D, Trancuccio, A, Gil, C, Tini, G, Pedrazzini, M, Torchio, M, Sinagra, G, Gimeno, J, Bernasconi, D, Valsecchi, M, Klingel, K, Adler, E, Camici, P, Cooper, L, Ammirati E., Raimondi F., Piriou N., Sardo Infirri L., Mohiddin S. A., Mazzanti A., Shenoy C., Cavallari U. A., Imazio M., Aquaro G. D., Olivotto I., Pedrotti P., Sekhri N., Van de Heyning C. M., Broeckx G., Peretto G., Guttmann O., Dellegrottaglie S., Scatteia A., Gentile P., Merlo M., Goldberg R. I., Reyentovich A., Sciamanna C., Klaassen S., Poller W., Trankle C. R., Abbate A., Keren A., Horowitz-Cederboim S., Cadrin-Tourigny J., Tadros R., Annoni G. A., Bonoldi E., Toquet C., Marteau L., Probst V., Trochu J. N., Kissopoulou A., Grosu A., Kukavica D., Trancuccio A., Gil C., Tini G., Pedrazzini M., Torchio M., Sinagra G., Gimeno J. R., Bernasconi D., Valsecchi M. G., Klingel K., Adler E. D., Camici P. G., and Cooper L. T.

Abstract

Background: The risk of adverse cardiovascular events in patients with acute myocarditis (AM) and desmosomal gene variants (DGV) remains unknown. Objectives: The purpose of this study was to ascertain the risk of death, ventricular arrhythmias, recurrent myocarditis, and heart failure (main endpoint) in patients with AM and pathogenic or likely pathogenetic DGV. Methods: In a retrospective international study from 23 hospitals, 97 patients were included: 36 with AM and DGV (DGV[+]), 25 with AM and negative gene testing (DGV[−]), and 36 with AM without genetics testing. All patients had troponin elevation plus findings consistent with AM on histology or at cardiac magnetic resonance (CMR). In 86 patients, CMR changes in function and structure were re-assessed at follow-up. Results: In the DGV(+) AM group (88.9% DSP variants), median age was 24 years, 91.7% presented with chest pain, and median left ventricular ejection fraction (LVEF) was 56% on CMR (P = NS vs the other 2 groups). Kaplan-Meier curves demonstrated a higher risk of the main endpoint in DGV(+) AM compared with DGV(−) and without genetics testing patients (62.3% vs 17.5% vs 5.3% at 5 years, respectively; P < 0.0001), driven by myocarditis recurrence and ventricular arrhythmias. At follow-up CMR, a higher number of late gadolinium enhanced segments was found in DGV(+) AM. Conclusions: Patients with AM and evidence of DGV have a higher incidence of adverse cardiovascular events compared with patients with AM without DGV. Further prospective studies are needed to ascertain if genetic testing might improve risk stratification of patients with AM who are considered at low risk.

Published
2022

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