Cargando…
Cardiac (123)I-mIBG Imaging in Heart Failure
Cardiac sympathetic upregulation is one of the neurohormonal compensation mechanisms that play an important role in the pathogenesis of chronic heart failure (CHF). In the past decades, cardiac (123)I-mIBG scintigraphy has been established as a feasible technique to evaluate the global and regional...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9230638/ https://www.ncbi.nlm.nih.gov/pubmed/35745574 http://dx.doi.org/10.3390/ph15060656 |
Sumario: | Cardiac sympathetic upregulation is one of the neurohormonal compensation mechanisms that play an important role in the pathogenesis of chronic heart failure (CHF). In the past decades, cardiac (123)I-mIBG scintigraphy has been established as a feasible technique to evaluate the global and regional cardiac sympathetic innervation. Although cardiac (123)I-mIBG imaging has been studied in many cardiac and neurological diseases, it has extensively been studied in ischemic and non-ischemic CHF. Therefore, this review will focus on the role of (123)I-mIBG imaging in CHF. This non-invasive, widely available technique has been established to evaluate the prognosis in CHF. Standardization, especially among various combinations of gamma camera and collimator, is important for identifying appropriate thresholds for adequate risk stratification. Interestingly, in contrast to the linear relationship between (123)I-mIBG-derived parameters and overall prognosis, there seems to be a “bell-shape” curve for (123)I-mIBG-derived parameters in relation to ventricular arrhythmia or appropriate implantable cardioverter defibrillator (ICD) therapy in patients with ischemic CHF. In addition, there is a potential clinical role for cardiac (123)I-mIBG imaging in optimizing patient selection for implantation of expensive devices such as ICD and cardiac resynchronization therapy (CRT). Based on cardiac (123)I-mIBG data risk models and machine learning, models have been developed for appropriate risk assessment in CHF. |
---|