Header

UZH-Logo

Maintenance Infos

Multimodality Imaging in Sarcomeric Hypertrophic Cardiomyopathy: Get It Right…on Time


Galluzzo, Alessandro; Fiorelli, Francesca; Rossi, Valentina A; Monzo, Luca; Montrasio, Giulia; Camilli, Massimiliano; Halasz, Geza; Uccello, Giuseppe; Mollace, Rocco; Beltrami, Matteo (2023). Multimodality Imaging in Sarcomeric Hypertrophic Cardiomyopathy: Get It Right…on Time. Life, 13(1):171.

Abstract

Hypertrophic cardiomyopathy (HCM) follows highly variable paradigms and disease-specific patterns of progression towards heart failure, arrhythmias and sudden cardiac death. Therefore, a generalized standard approach, shared with other cardiomyopathies, can be misleading in this setting. A multimodality imaging approach facilitates differential diagnosis of phenocopies and improves clinical and therapeutic management of the disease. However, only a profound knowledge of the progression patterns, including clinical features and imaging data, enables an appropriate use of all these resources in clinical practice. Combinations of various imaging tools and novel techniques of artificial intelligence have a potentially relevant role in diagnosis, clinical management and definition of prognosis. Nonetheless, several barriers persist such as unclear appropriate timing of imaging or universal standardization of measures and normal reference limits. This review provides an overview of the current knowledge on multimodality imaging and potentialities of novel tools, including artificial intelligence, in the management of patients with sarcomeric HCM, highlighting the importance of specific "red alerts" to understand the phenotype-genotype linkage.

Abstract

Hypertrophic cardiomyopathy (HCM) follows highly variable paradigms and disease-specific patterns of progression towards heart failure, arrhythmias and sudden cardiac death. Therefore, a generalized standard approach, shared with other cardiomyopathies, can be misleading in this setting. A multimodality imaging approach facilitates differential diagnosis of phenocopies and improves clinical and therapeutic management of the disease. However, only a profound knowledge of the progression patterns, including clinical features and imaging data, enables an appropriate use of all these resources in clinical practice. Combinations of various imaging tools and novel techniques of artificial intelligence have a potentially relevant role in diagnosis, clinical management and definition of prognosis. Nonetheless, several barriers persist such as unclear appropriate timing of imaging or universal standardization of measures and normal reference limits. This review provides an overview of the current knowledge on multimodality imaging and potentialities of novel tools, including artificial intelligence, in the management of patients with sarcomeric HCM, highlighting the importance of specific "red alerts" to understand the phenotype-genotype linkage.

Statistics

Citations

Dimensions.ai Metrics
1 citation in Web of Science®
3 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

22 downloads since deposited on 01 Feb 2023
16 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, further contribution
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Cardiology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Ecology, Evolution, Behavior and Systematics
Life Sciences > General Biochemistry, Genetics and Molecular Biology
Physical Sciences > Space and Planetary Science
Physical Sciences > Paleontology
Language:English
Date:6 January 2023
Deposited On:01 Feb 2023 12:10
Last Modified:28 Jun 2024 01:41
Publisher:MDPI Publishing
ISSN:2075-1729
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.3390/life13010171
PubMed ID:36676118
  • Content: Published Version
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)