The effect of calibration factors and recovery coefficients on 177Lu SPECT activity quantification accuracy: a Monte Carlo study

Abstract

Background Different gamma camera calibration factor (CF) geometries have been proposed to convert SPECT data into units of activity concentration. However, no consensus has been reached on a standardised geometry. The CF is dependent on the selected geometry and is further affected by partial volume effects. This study investigated the effect of two CF geometries and their corresponding recovery coefficients (RCs) on the quantification accuracy of 177Lu SPECT images using Monte Carlo simulations. Methods The CF geometries investigated were (i) a radioactive-sphere surrounded by non-radioactive water (sphere-CF) and (ii) a cylindrical phantom uniformly filled with radioactive water (cylinder-CF). Recovery coefficients were obtained using the sphere-CF and cylinder-CF, yielding the sphere-RC and cylinder-RC values, respectively, for partial volume correction (PVC). The quantification accuracy was evaluated using four different-sized spheres (15.6–65.4 ml) and a kidney model with known activity concentrations inside a cylindrical, torso and patient phantom. Images were reconstructed with the 3D OS-EM algorithm incorporating attenuation, scatter and detector-response corrections. Segmentation was performed using the physical size and a small cylindrical volume inside the cylinder for the sphere-CF and cylinder-CF, respectively. Results The sphere quantification error (without PVC) was better for the sphere-CF (≤ − 5.54%) compared to the cylinder-CF (≤ − 20.90%), attributed to the similar geometry of the quantified and CF spheres. Partial volume correction yielded comparable results for the sphere-CF-RC (≤ 3.47%) and cylinder-CF-RC (≤ 3.53%). The accuracy of the kidney quantification was poorer (≤ 22.34%) for the sphere-CF without PVC compared to the cylinder-CF (≤ 2.44%). With PVC, the kidney quantification results improved and compared well for the sphere-CF-RC (≤ 3.50%) and the cylinder-CF-RC (≤ 3.45%). Conclusion The study demonstrated that upon careful selection of CF-RC combinations, comparable quantification errors (≤ 3.53%) were obtained between the sphere-CF-RC and cylinder-CF-RC, when all corrections were applied.

Evaluation of Iodine-123 and Iodine-131 SPECT Activity Quantification: A Monte Carlo Study

“…It is well known that increasing the number of OS-EM, increases image noise. Literature supports this statement for several isotopes, including 99m Tc (52), 131 I (43,55,56) and 177 Lu (27,57,58). The results in Figure 3 corroborate that stated in literature, showing that the image of the smallest sphere has the largest SD value, and that the value decreases as the sphere size increases.…”

“…As a consequence, when applying these RCs as PVE corrections for structures with irregular shapes, the result may be inaccurate (31). It is important to note that the CF source geometry chosen will influence the RCs (27). In this study, the CF was obtained from the CFpoint with a VOI diameter equal to the physical size plus a 3.0 cm margin.…”

“…There are various MC simulation codes available for NM imaging (34)(35)(36). In this study we used the SIMIND MC code which models a standard clinical scintillation camera and has been successfully used to evaluate activity quantification accuracy (27,(37)(38)(39). SIMIND allows for three methods to simulate the energy resolution, based on either (i) a simplified theoretical model assuming a 1/√ dependence (25,40), (ii) a fixed energy resolution used over the entire energy range, or (iii) a fitted model estimated from measured data (41).…”

“…Although activity quantification accuracy with SIMIND has been reported in literature (27,42,43), little work has been done using voxel-based digital phantoms for 123 I and 131 I.…”

Evaluation of Iodine-123 and Iodine-131 SPECT activity quantification: a Monte Carlo study

“…Although activity quantification accuracy with SIMIND has been reported in the literature [ 27 , 42 , 43 ], little work has been done using voxel-based digital phantoms for 123 I and 131 I. Furthermore, to our knowledge, evaluating activity quantification accuracy in a clinically realistic phantom, using SIMIND with the fitted energy resolution model, has not yet been reported in the literature.…”