Michele Boldrini1, Francesco Cappelli2, Liza Chacko3, Maria Alejandra Restrepo-Cordoba4, Angela Lopez-Sainz4, Alberto Giannoni5, Alberto Aimo6, Andrea Baggiano7, Ana Martinez-Naharro3, Carol Whelan3, Cristina Quarta3, Claudio Passino5, Vincenzo Castiglione8, Vladyslav Chubuchnyi9, Valentina Spini9, Claudia Taddei9, Giuseppe Vergaro5, Aviva Petrie10, Luis Ruiz-Guerrero11, Vanessa Moñivas12, Susana Mingo-Santos12, Jesus G Mirelis4, Fernando Dominguez4, Esther Gonzalez-Lopez4, Stefano Perlini13, Gianluca Pontone7, Julian Gillmore3, Philip N Hawkins3, Pablo Garcia-Pavia14, Michele Emdin5, Marianna Fontana15. 1. National Amyloidosis Centre, University College London, Royal Free Campus, London, United Kingdom; Emergency Department, Internal Medicine Department, Amyloidosis Research and Treatment Center, Istituto di Ricerca a Carattere Clinico e Scientifico Policlinico San Matteo Foundation, Pavia, Italy. 2. Tuscan Regional Amyloid Centre, Careggi University Hospital, Florence, Italy. 3. National Amyloidosis Centre, University College London, Royal Free Campus, London, United Kingdom. 4. Department of Cardiology, Hospital Puerta de Hierro Majadahonda, Madrid, Spain; Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares, Madrid, Spain. 5. Fondazione Toscana Gabriele Monasterio, Pisa, Italy; Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. 6. National Amyloidosis Centre, University College London, Royal Free Campus, London, United Kingdom; Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. 7. Centro Cardiologico Monzino, IRCCS, Milan, Italy. 8. Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. 9. Fondazione Toscana Gabriele Monasterio, Pisa, Italy. 10. Eastman Dental Institute, University College London, Grays Inn Road, London, United Kingdom. 11. Department of Cardiology, Hospital Puerta de Hierro Majadahonda, Madrid, Spain. 12. University Francisco de Vitoria, Pozuelo de Alarcón, Madrid, Spain. 13. Emergency Department, Internal Medicine Department, Amyloidosis Research and Treatment Center, Istituto di Ricerca a Carattere Clinico e Scientifico Policlinico San Matteo Foundation, Pavia, Italy. 14. Department of Cardiology, Hospital Puerta de Hierro Majadahonda, Madrid, Spain; Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares, Madrid, Spain; University Francisco de Vitoria, Pozuelo de Alarcón, Madrid, Spain. 15. National Amyloidosis Centre, University College London, Royal Free Campus, London, United Kingdom. Electronic address: m.fontana@ucl.ac.uk.
Abstract
OBJECTIVES: This study aimed to investigate the accuracy of a broad range of echocardiographic variables to develop multiparametric scores to diagnose CA in patients with proven light chain (AL) amyloidosis or those with increased heart wall thickness who had amyloid was suspected. We also aimed to further characterize the structural and functional changes associated with amyloid infiltration. BACKGROUND: Cardiac amyloidosis (CA) is a serious but increasingly treatable cause of heart failure. Diagnosis is challenging and frequently unclear at echocardiography, which remains the most often used imaging tool. METHODS: We studied 1,187 consecutive patients evaluated at 3 referral centers for CA and analyzed morphological, functional, and strain-derived echocardiogram parameters with the aim of developing a score-based diagnostic algorithm. Cardiac amyloid burden was quantified by using extracellular volume measurements at cardiac magnetic resonance. RESULTS: A total of 332 patients were diagnosed with AL amyloidosis and 339 patients with transthyretin CA. Concentric remodeling and strain-derived parameters displayed the best diagnostic performance. A multivariable logistic regression model incorporating relative wall thickness, E wave/e' wave ratio, longitudinal strain, and tricuspid annular plane systolic excursion had the greatest diagnostic performance in AL amyloidosis (area under the curve: 0.90; 95% confidence interval: 0.87 to 0.92), whereas the addition of septal apical-to-base ratio yielded the best diagnostic accuracy in the increased heart wall thickness group (area under the curve: 0.80; 95% confidence interval: 0.85 to 0.90). CONCLUSIONS: Specific functional and structural parameters characterize different burdens of CA deposition with different diagnostic performances and enable the definition of 2 scores that are sensitive and specific tools with which diagnose or exclude CA.
OBJECTIVES: This study aimed to investigate the accuracy of a broad range of echocardiographic variables to develop multiparametric scores to diagnose CA in patients with proven light chain (AL) amyloidosis or those with increased heart wall thickness who had amyloid was suspected. We also aimed to further characterize the structural and functional changes associated with amyloid infiltration. BACKGROUND:Cardiac amyloidosis (CA) is a serious but increasingly treatable cause of heart failure. Diagnosis is challenging and frequently unclear at echocardiography, which remains the most often used imaging tool. METHODS: We studied 1,187 consecutive patients evaluated at 3 referral centers for CA and analyzed morphological, functional, and strain-derived echocardiogram parameters with the aim of developing a score-based diagnostic algorithm. Cardiac amyloid burden was quantified by using extracellular volume measurements at cardiac magnetic resonance. RESULTS: A total of 332 patients were diagnosed with AL amyloidosis and 339 patients with transthyretin CA. Concentric remodeling and strain-derived parameters displayed the best diagnostic performance. A multivariable logistic regression model incorporating relative wall thickness, E wave/e' wave ratio, longitudinal strain, and tricuspid annular plane systolic excursion had the greatest diagnostic performance in AL amyloidosis (area under the curve: 0.90; 95% confidence interval: 0.87 to 0.92), whereas the addition of septal apical-to-base ratio yielded the best diagnostic accuracy in the increased heart wall thickness group (area under the curve: 0.80; 95% confidence interval: 0.85 to 0.90). CONCLUSIONS: Specific functional and structural parameters characterize different burdens of CA deposition with different diagnostic performances and enable the definition of 2 scores that are sensitive and specific tools with which diagnose or exclude CA.
Authors: Viktor Löfbacka; Jan Axelsson; Björn Pilebro; Ole B Suhr; Per Lindqvist; Torbjörn Sundström Journal: Eur J Nucl Med Mol Imaging Date: 2020-12-26 Impact factor: 9.236
Authors: Andrea Baggiano; Alberico Del Torto; Marco Guglielmo; Giuseppe Muscogiuri; Laura Fusini; Mario Babbaro; Ada Collevecchio; Rocco Mollace; Stefano Scafuri; Saima Mushtaq; Edoardo Conte; Andrea Daniele Annoni; Alberto Formenti; Maria Elisabetta Mancini; Giulia Mostardini; Daniele Andreini; Andrea Igoren Guaricci; Mauro Pepi; Marianna Fontana; Gianluca Pontone Journal: Diagnostics (Basel) Date: 2020-09-29