Article: Towards accurate
2023 Volume 10, Issue 1, Page(s) 5
Abstract: Background: Conventional calibration of the gamma camera consists of the calculation of calibration factors (CFs) (ratio of counts/cc and true concentration activity) as the function of the volume of interest (VOI). However, such method shows ... ...
| Abstract | Background: Conventional calibration of the gamma camera consists of the calculation of calibration factors (CFs) (ratio of counts/cc and true concentration activity) as the function of the volume of interest (VOI). However, such method shows inconsistent results when the background activity varies. The aim of the present study was to propose a new calibration method by considering the sphere-to-background counts/voxel ratio (SBVR) in addition to the VOI for CFs calculation. A PET cylindrical flood phantom, a NEMA IQ body phantom, a Data spectrum Torso Phantom (ECT/TOR/P) and a LK-S Kyoto Liver/Kidney phantom were used. The NEMA IQ phantom was used to calibrate the camera and to produce CFs for the different spheres volumes and for varying sphere-to-background activity ratios. The spheres were filled with a uniform activity concentration of Results: The relative errors in quantification using the NEMA IQ phantom with the new calibration method were 0.16%, 5.77%, 9.34% for the large, medium and small sphere, respectively, for a time per view of 30-s. The conventional calibration method gave errors of 3.65%, 6.65%, 30.28% for 30-s. The LK-S Kyoto Liver/Kidney Phantom resulted in quantification errors of 3.40%, 2.14%, 11.18% for the large, medium and small spheres, respectively, for 30-s; compared to 11.31%, 17.54%, 14.43% for 30-s, respectively, for the conventional method. Similar results were obtained for shorter acquisitions times with 20-s and 10-s time per view. Conclusion: These results suggest that SBVR allows to improve quantification accuracy. The shorter time-per-view acquisitions had similar relative differences compared to the full-time acquisition which allows shorter imaging times with |
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| Language | English |
| Publishing date | 2023-01-23 |
| Publishing country | Germany |
| Document type | Journal Article |
| ZDB-ID | 2768912-8 |
| ISSN | 2197-7364 |
| ISSN | 2197-7364 |
| DOI | 10.1186/s40658-023-00526-x |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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