New AI-based Technologies in Nuclear Medicine
The study aims to identify and predict radiopharmaceutical extravasation events using new semi-quantitative parameters and machine learning models. It involves dose rate measurements to develop metrics for real-time monitoring. It also investigates the correlation between extravasation and SUV correction in PET/CT diag
| Condition(s) | Patients Undergoing PET/CT Investigation or Nuclear Medicine Therapy |
|---|---|
| Status | Recruiting |
| Study type | Observational |
| Summary | The study aims to identify and predict radiopharmaceutical extravasation events using new semi-quantitative parameters and machine learning models. It involves dose rate measurements to develop metrics for real-time monitoring. It also investigates the correlation between extravasation and SUV correction in PET/CT diagnostics, providing an estimate of the correction factor necessary for accurate SUV evaluation in case of an extravasation event. |
| Who can participate | Inclusion Criteria: * patients undergoing PET/CT scans or therapeutic treatments with radiopharmaceuticals labelled with alpha or beta emitting nuclides Exclusion Criteria: * patients whose clinical or psychological conditions do not allow for their involvement |
| Ages | 18 Years to 90 Years |
| Sex | All |
| Lead sponsor | Azienda USL Reggio Emilia - IRCCS |
| Locations | Reggio Emilia, Italy |
| Start date | 2021-07-30 |
| NCT ID | NCT07174089 |
| Official listing | https://clinicaltrials.gov/study/NCT07174089 |