Andrea Pandolfi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Andrea Pandolfi has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Alessandra Stefania Rizzuto
Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
1 shared publication - Ciro Canetta
High Care Internal Medicine Unit, Foundation IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan, Milan, Italy
1 shared publication - Eleonora Gnan
Department of Cardio-Thoracic-Vascular Diseases, Foundation IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
1 shared publication - Fabiola B. Sozzi
Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico
1 shared publication - Jin Kyung Kim
Mary & Steve Wen Cardiovascular Division, Department of Medicine, University of California Irvine School of Medicine, 101 The City Drive, City Tower, Suite 400, Cardiology, Orange, CA 92868-3298
1 shared publication - Laura Iacuzio
Cardiothoracic Centre CCM, 98000 Monaco, Monaco
1 shared publication
Latest Publications
- Open Access
- 15 January 2025
- Published by MDPI AG in Journal of Clinical Medicine
- Vol. 14 (2) , 508
Diagnostic Algorithm Using Multimodal Imaging for the Differential Diagnosis of Intra-Cardiac Masses
Cardiac masses are complex clinical conditions that frequently pose diagnostic challenges in cardiology practice. These masses can form within heart chambers or near the pericardium and are generally categorized as either non-neoplastic or neoplastic. These latter are further classified into benign and malignant (primary and secondary or metastatic). Diagnosing these conditions often requires a multiparametric approach that includes both clinical features, such as the patient’s and associated clinical conditions, and multimodality imaging. However, histological examination of the resected specimen is often necessary to ascertain the nature of the mass. Given their heterogeneity and the rarity of many cardiac masses, there are no guidelines or consensus on the best diagnostic approach. Modern imaging protocols must be tailored to the specific clinical issues and patient characteristics, given the rapid advancements in technology. Thus, it is imperative to use a multimodality approach, combining different imaging techniques and multidisciplinary teamwork. Hereby, we propose a practical algorithm for evaluating cardiac lesions using a step-by-step implementation of multimodal imaging. Ultimately, the goal is to tailor the most suitable imaging technique to the patient’s needs.
- 15 January 2025
- Published by MDPI AG in Journal of Clinical Medicine
- Vol. 14 (2) , 508
Open AccessDiagnostic Algorithm Using Multimodal Imaging for the Differential Diagnosis of Intra-Cardiac Masses
Cardiac masses are complex clinical conditions that frequently pose diagnostic challenges in cardiology practice. These masses can form within heart chambers or near the pericardium and are generally categorized as either non-neoplastic or neoplastic. These latter are further classified into benign and malignant (primary and secondary or metastatic). Diagnosing these conditions often requires a multiparametric approach that includes both clinical features, such as the patient’s and associated clinical conditions, and multimodality imaging. However, histological examination of the resected specimen is often necessary to ascertain the nature of the mass. Given their heterogeneity and the rarity of many cardiac masses, there are no guidelines or consensus on the best diagnostic approach. Modern imaging protocols must be tailored to the specific clinical issues and patient characteristics, given the rapid advancements in technology. Thus, it is imperative to use a multimodality approach, combining different imaging techniques and multidisciplinary teamwork. Hereby, we propose a practical algorithm for evaluating cardiac lesions using a step-by-step implementation of multimodal imaging. Ultimately, the goal is to tailor the most suitable imaging technique to the patient’s needs.