Effect of Tumor-Pixel Positioning on the Variability of SUV Measurements in PET Images.

OBJECTIVES: The aim of this study was to investigate the effect on standardized uptake value (SUV) measurement variability of the positional relationship between objects of different sizes and the pixel of a positron emission tomography (PET) image. METHODS: We used a NEMA IEC body phantom comprising six spheres with diameters of 10, 13, 17, 22, 28, and 37 mm. The phantom was filled with (18)F solution and contained target-to-background ratios (TBRs) of 2, 4, and 8. The PET data were acquired for 30 min using a SIGNA PET/MR scanner. The PET images were reconstructed with the ordered subsets expectation maximization (OSEM) algorithm with and without point-spread function (PSF) correction (OSEM + PSF + Filter and OSEM + Filter, respectively). A Gaussian filter of 4 mm full width at half maximum was applied in all reconstructions, except for one model (OSEM + PSF + no Filter). The matrix sizes were 128×128, 192×192, 256×256 and 384×384. Reconstruction was performed by shifting the reconstruction center position by 1 mm in the range 0 to 3 mm in the upward or rightward direction for each parameter. For all reconstructed images, the SUV(max) of each hot sphere was measured. To investigate the resulting variation in the SUV(max), the coefficient of variation (CV) of each SUV(max) was calculated. RESULTS: The CV of the SUV(max) increased as the matrix size and the diameter of the hot sphere decreased in all reconstruction settings. With PSF correction, the CV of SUV(max) increased as the TBR increased except when the TBR was 2. The CV of the SUV(max) measured in the OSEM + PSF + no Filter images were larger than those measured in the OSEM + PSF + Filter images. The amount of this increase was higher for smaller spheres and larger matrix sizes and was independent of TBR. CONCLUSIONS: Shifting the reconstruction center position of the PET image causes variability in SUV(max) measurements. To reduce the variability of SUV measurements, it is necessary to use sufficient matrix sizes to satisfy sampling criterion and appropriate filters.