Cardiovascular device infections
Conditions
Brief summary
Diagnostic accuracy of radiomics applied to FDG-PET for CVDIs, compared with conventional visual and semiquantitative interpretation.
Detailed description
Performance of AI-based predictive models (combining radiomic and clinical features) for: o Distinguishing infection vs. non-infection. o Predicting resolution of infection and supporting discontinuation of suppressive antimicrobial therapy., Characterization of physiological 18F-FDG uptake patterns in cardiovascular device carriers without infection, stratified by sex and time since implantation.
Interventions
DRUGFludesoxiglucosa (18F)-Curium 185 MBq/ml
DRUGsolución inyectable
Sponsors
Fundacio De Recerca Clinic Barcelona-Institut D’Investigacions Biomediques August Pi I Sunyer
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diagnostic accuracy of radiomics applied to FDG-PET for CVDIs, compared with conventional visual and semiquantitative interpretation. | — |
Secondary
| Measure | Time frame |
|---|---|
| Performance of AI-based predictive models (combining radiomic and clinical features) for: o Distinguishing infection vs. non-infection. o Predicting resolution of infection and supporting discontinuation of suppressive antimicrobial therapy., Characterization of physiological 18F-FDG uptake patterns in cardiovascular device carriers without infection, stratified by sex and time since implantation. | — |
Outcome results
None listed