Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Background: Cardiac magnetic resonance imaging (CMR) based T1 mapping and extracellular volume fraction (ECV) are powerful tools for identifying myocardial fibrosis. This systematic review and -analysis aims to characterize the utility of native T1 mapping and ECV in patients with non-ischemic cardiomyopathy (NICM) and to clarify the prognostic significance of elevated values.

Methods: A literature search was conducted for studies reporting on use of CMR-based native T1 mapping and ECV measurement in NICM patients and their association with major adverse cardiac events (MACE), ventricular arrhythmias (VAs), and left ventricular reverse remodeling (LVRR). Databases searched included: Ovid MEDLINE, EMBASE, Web of Science, and Google Scholar. The search was not restricted to time or publication status.

Results: Native T1 and ECV were significantly higher in NICM patients compared to controls (MD 78.80, 95 % CI 50.00, 107.59; p < 0.01; MD 5.86, 95 % CI 4.55, 7.16; p < 0.01). NICM patients who experienced MACE had higher native T1 and ECV (MD 52.87, 95 % CI 26.59, 79.15; p < 0.01; MD 6.03, 95 % CI 3.79, 8.26; p < 0.01). There was a non-statistically significant trend toward higher native T1 time in NICM patients who experienced VAs. NICM patients who were poor treatment responders had higher baseline native T1 and ECV (MD 40.58, 95 % CI 12.90, 68.25; p < 0.01; MD 3.29, 95 % CI 2.25, 4.33; p < 0.01).

Conclusions: CMR-based native T1 and ECV quantification may be useful tools for risk stratification of patients with NICM. They may provide additional diagnostic utility in combination with LGE, which poorly characterizes fibrosis in patients with diffuse myocardial involvement.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10873728PMC
http://dx.doi.org/10.1016/j.ijcha.2024.101339DOI Listing

Publication Analysis

Top Keywords

native mapping
12
utility native
8
extracellular volume
8
volume fraction
8
systematic review
8
mapping ecv
8
nicm patients
8
mapping
4
mapping myocardial
4
myocardial extracellular
4

Similar Publications

Objectives: Rheumatoid arthritis (RA) is associated with increased cardiovascular (CV) risk, yet the mechanisms remain unclear. This study aimed to evaluate myocardial structure, function, and tissue characterization using cardiovascular magnetic resonance (CMR) in RA patients and explore associations with RA disease severity.

Methods: This mixed case-control study included 48 RA patients and 34 age- and sex-matched controls.

View Article and Find Full Text PDF

Objectives: Patients with connective tissue diseases (CTD) have a high incidence of cardiac involvement, which often presents insidiously and can progress rapidly, making it one of the leading causes of death. Multiparametric cardiovascular magnetic resonance (CMR) provides a comprehensive quantitative evaluation of myocardial injury and is emerging as a valuable tool for detecting cardiac involvement in CTD. This study aims to investigate the correlations between CMR features and serological biomarkers in CTD patients, assess their potential clinical value, and further explore the impact of pre-CMR immunotherapy intensity on CMR-specific parameters, thereby evaluating the role of CMR in the early diagnosis of CTD-related cardiac involvement.

View Article and Find Full Text PDF

Background: Most countries have endorsed a national action plan (NAP) on antimicrobial resistance. We previously used a governance framework to assess NAPs on antimicrobial resistance available for the period of 2020-21 from 114 countries, finding substantial variation worldwide in the commitment of resources to address an escalating global health challenge. We sought to expand and advance this analysis to include the NAPs of more low-income and middle-income countries, to cover the period of 2021-22, and to examine the strength of NAPs to address antimicrobial resistance.

View Article and Find Full Text PDF

Recent advancements in spatial transcriptomics (ST) have revolutionized our ability to simultaneously profile gene expression, spatial location, and tissue morphology, enabling the precise mapping of cell types and signaling pathways within their native tissue context. However, the high cost of sequencing remains a significant barrier to its widespread adoption. Although existing methods often leverage histopathological images to predict transcriptomic profiles and identify cellular heterogeneity, few approaches directly estimate cell-type abundance from these images.

View Article and Find Full Text PDF

Artificial intelligence (AI) and combinatorial optimization drive applications across science and industry, but their increasing energy demands challenge the sustainability of digital computing. Most unconventional computing systems target either AI or optimization workloads and rely on frequent, energy-intensive digital conversions, limiting efficiency. These systems also face application-hardware mismatches, whether handling memory-bottlenecked neural models, mapping real-world optimization problems or contending with inherent analog noise.

View Article and Find Full Text PDF