PT  - JOURNAL ARTICLE
AU  - Stephanie Sanchez
AU  - Geoffrey M. Currie
TI  - Topical Sensor for the Assessment of PET Dose Administration: Metric Performance with an Autoinjector
AID  - 10.2967/jnmt.120.245043
DP  - 2020 Dec 01
TA  - Journal of Nuclear Medicine Technology
PG  - 363--371
VI  - 48
IP  - 4
4099  - http://tech.snmjournals.org/content/48/4/363.short
4100  - http://tech.snmjournals.org/content/48/4/363.full
SO  - J. Nucl. Med. Technol.2020 Dec 01; 48
AB  - Extravasation or partial extravasation of the radiopharmaceutical dose in PET can undermine SUV and image quality. A topical sensor has been validated using several metrics to characterize injection quality after manual injection. The performance of these metrics for autoinjector administration has been assessed. Methods: A single PET/CT scanner at a single site was used to characterize injections using an autoinjector with standardized apparatus, flush volume, and infusion rate (1-min infusion followed by 2 syringe flushes) for 18F-FDG, 68Ga-prostate-specific membrane antigen, and 68Ga-DOTATATE. In total, 296 patients with topical application of sensors were retrospectively analyzed using conventional statistical analysis and an artificial neural network. Results: Partial extravasation was noted in 1.3% of studies, with 9.1% (inclusive of partial extravasation) identified to have an injection anomaly (e.g., venous retention). Extravasation was independently predicted by the time that elapsed as the counts recorded by the injection sensor fell from the maximum value to within 200% of the reference sensor counts greater than 1,200 s; as the difference in counts for injection and reference sensors, normalized by dose, from 4 min after injection greater than 25; and as the ratio of the average counts per second recorded by the injection sensor at the end of a monitoring period to those of the reference sensor greater than 2. Conclusion: Extravasation and partial extravasation of PET doses are readily detected and differentiated using time–activity curve metrics. The metrics can provide the insight that could inform image quality or SUV accuracy issues. Further validation of key metrics is recommended in a larger and more diverse cohort.