Accuracy Assessment of SUV Measurements in SPECT/CT: A Phantom Study
Fatin Nadhirah binti A Halim, Hizwan Yahya, Khairul Nizam Jaafar, Syahir Mansor
Abstract
Advances in iterative image reconstruction enable absolute quantification of SPECT/CT studies by incorporating compensations for collimator–detector response, attenuation, and scatter. This study aimed to assess the quantitative accuracy of SPECT/CT based on different levels of <sup>99m</sup>Tc activity (low/high) using different SUV metrics (SUV<sub>mean</sub>, SUV<sub>max</sub>, SUV<sub>0.6 max</sub>, and SUV<sub>0.75 max</sub> [the average values that include pixels greater than 60% and 75% of the SUV<sub>max</sub> in the volume of interest, respectively]). <b>Methods:</b> A Jaszczak phantom equipped with 6 fillable spheres was set up with low and high activity ratios of 1:4 and 1:10 (background-to-sphere) on background activities of 10 and 60 kBq/mL, respectively. The fixed-size volume of interest based on the diameter of each sphere was drawn on SPECT images using various metrics for SUV quantification purposes. <b>Results:</b> The convergence of activity concentration was dependent on the number of iterations and application of postfiltering. For the background-to-sphere ratio of 1:10 with a low background activity concentration, the SUV<sub>mean</sub> metric showed an underestimation of about 38% from the actual SUV, and SUV<sub>max</sub> exhibited an overestimation of about 24% for the largest sphere diameter. Meanwhile, bias reductions of as much as −6% and −7% for SUV<sub>0.6 max</sub> and SUV<sub>0.75 max</sub>, respectively, were observed. SUV<sub>max</sub> gave a more accurate reading than the others, although points that exceeded the actual value were detected. At 1:4 and 1:10 background activity of 10 kBq/mL, a low activity concentration attained a value close to the actual ratio. Use of 2 iterations and 10 subsets without postfiltering gave the most accurate values for reconstruction and the best image overall. <b>Conclusion:</b> SUV<sub>max</sub> is the best metric in a high- or low-contrast-ratio phantom with at least 2 iterations, 10 subsets, and no postfiltering.