[Comparison of Monitor Unit between Electron Monte Carlo Algorithm by Different Dose Normalization Methods and Conventional Manual Calculation].

The purpose of this study was to evaluate the discrepancy between the monitor unit (MU) calculated by different dose normalization methods in the electron Monte Carlo (eMC) algorithm and the conventional manual MU. In the water phantom condition, the manual MU obtained from the measured output factor was compared with the calculated MU by the eMC algorithm, using 24 different irradiation field shapes and several different energies of electron beam. In the breast boost condition, calculated MUs by both calculation methods were evaluated for 45 cases. As a result, the MUs computed by the eMC algorithm in the water phantom varied according to the dose normalization methods, and the mean±standard deviation of the difference between the manual and calculated MU were 1.1±1.4%, 0.0±1.0% and 0.4±1.2% in peak depth normalization (PN), no plan normalization (NPN) and 100% at body maximum (100%BM), respectively. In breast-boost cases, the MU difference between the manual and the calculated MU were 6.1±3.7%, 3.4±2.8% and 1.1±2.9% in PN, NPN and 100%BM, respectively. We revealed that the resultant MU calculated by eMC algorithm was dependent on the dose normalization method and the averaged differences exceeded 6% in PN, especially in breast boost condition. When using the eMC in the breast boost condition, it is desirable to select an appropriate dose normalization method according to dose prescription policies at each facility.

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 18F 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 SUVmax of each hot sphere was measured. To investigate the resulting variation in the SUVmax, the coefficient of variation (CV) of each SUVmax was calculated. Results: The CV of the SUVmax increased as the matrix size and the diameter of the hot sphere decreased in all reconstruction settings. With PSF correction, the CV of SUVmax increased as the TBR increased except when the TBR was 2. The CV of the SUVmax 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 SUVmax measurements. To reduce the variability of SUV measurements, it is necessary to use sufficient matrix sizes to satisfy sampling criterion and appropriate filters.