Towards accurate 177Lu SPECT activity quantification and standardization using lesion-to-background voxel ratio

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 177Lu, while the background was first filled with cold water and activity was added between each SPECT scan. SPECT imaging was performed for 30-s, 20-s, and 10-s exposure per view. The calculated CFs were expressed as function of the sphere volume and SBVR. The obtained CFs were validated for an additional NEMA IQ acquisition with different activities in spheres and background and for the Torso and Liver/Kidney phantoms with inserted NEMA IQ spheres. The quantification accuracy was compared with the conventional method not taking SBVR into consideration. 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 177Lu and improved patient comfort. The SBVR method is simple to set up and can be proposed for standardization.

Tumor dosimetry using 177Lu: influence of background activity, measurement method and reconstruction algorithm

“…Apparently this linear behavior breaks down for the lower sphere-to-background ratio applied here (actual 2.7–9.5; SBVR 1.3–6.2 for the three largest spheres) as compared to Ref. [ 17 ] (actual 6–17; SBVR 2.4–14.6)—at least for the applied acquisition and reconstruction parameters. For the two smallest spheres, not analyzed in Ref.…”

“…11 a a linear increase of CF as a function of SBVR was anticipated on the basis of Fig. 4 in the paper by Raskin et al [ 17 ], but this is clearly not the case. Apparently this linear behavior breaks down for the lower sphere-to-background ratio applied here (actual 2.7–9.5; SBVR 1.3–6.2 for the three largest spheres) as compared to Ref.…”

“…For completeness, we also carried out analysis following the procedure proposed by Raskin et al [ 17 ], in order to investigate if this procedure would be feasible for the QSPECT protocol within the range of sphere-to-background ratios applied here. Only the unfiltered QSPECT reconstruction was considered as this was most analogous to the reconstruction used by Raskin et al The calibration factor CF, i.e., the count rate for a VOI divided by the known activity in that VOI, was determined for each sphere as where C true is the known activity concentration in the sphere and S = 10.9 s −1 MBq −1 is the sensitivity determined from the QSPECT calibration procedure [ 20 ].…”

“…CF versus SBVR and CF versus sphere volume was plotted and compared to the corresponding figures in Ref. [ 17 ].…”

“…Other methods include manual delineation [ 14 , 15 ] or an advanced software-based segmentation based on both planar, SPECT and CT images [ 16 ]. In a very recent proposal, lesion-volume and background dependent calibration factors were determined with the intent to apply these for correction of spill-in and spill-out [ 17 ], but this method has currently not been applied to patient data.…”