A specific and widely accepted protocol for quality controls in DWI is still lacking. The DWI quality assurance protocol proposed in this study can be applied in order to assess the reliability of DWI-derived indices before tackling single- as well as multicenter studies.
Several updated Monte Carlo (MC) codes are available to perform calculations of voxel S values for radionuclide targeted therapy. The aim of this work is to analyze the differences in the calculations obtained by different MC codes and their impact on absorbed dose evaluations performed by voxel dosimetry. Voxel S values for monoenergetic sources (electrons and photons) and different radionuclides (90Y, 131I, and 188Re) were calculated. Simulations were performed in soft tissue. Three general-purpose MC codes were employed for simulating radiation transport: MCNP4C, EGSnrc, and GEANT4. The data published by the MIRD Committee in Pamphlet No. 17, obtained with the EGS4 MC code, were also included in the comparisons. The impact of the differences (in terms of voxel S values) among the MC codes was also studied by convolution calculations of the absorbed dose in a volume of interest. For uniform activity distribution of a given radionuclide, dose calculations were performed on spherical and elliptical volumes, varying the mass from 1 to 500 g. For simulations with monochromatic sources, differences for self-irradiation voxel S values were mostly confined within 10% for both photons and electrons, but with electron energy less than 500 keV, the voxel S values referred to the first neighbor voxels showed large differences (up to 130%, with respect to EGSnrc) among the updated MC codes. For radionuclide simulations, noticeable differences arose in voxel S values, especially in the bremsstrahlung tails, or when a high contribution from electrons with energy of less than 500 keV is involved. In particular, for 90Y the updated codes showed a remarkable divergence in the bremsstrahlung region (up to about 90% in terms of voxel S values) with respect to the EGS4 code. Further, variations were observed up to about 30%, for small source-target voxel distances, when low-energy electrons cover an important part of the emission spectrum of the radionuclide (in our case, for 131I). For 90Y and 188Re, the differences among the various codes have a negligible impact (within few percents) on convolution calculations of the absorbed dose; thus either one of the MC programs is suitable to produce voxel S values for radionuclide targeted therapy dosimetry. However, if a low-energy beta-emitting radionuclide is considered, these differences can affect also dose depositions at small source-target voxel distances, leading to more conspicuous variations (about 9% for 1311) when calculating the absorbed dose in the volume of interest.
Phantom model was performed to study the effect of breast compression on signal-to-noise ratio (SNR) for a dedicated high-resolution gamma camera (Single Photon Emission Mammography, or 'SPEM') and a conventional one as typically employed in prone scintimammography. The phantom was designed to simulate the effects of lesion size and of scatter from nearby torso activity. The phantom studies showed that lesions SNR was higher with the SPEM camera than with the conventional camera, and that SNR was always improved with compression for both cameras. Since the stage of breast cancer diagnosis affects patient prognosis, it is important to optimize breast examinations for small (i.e., T1a and T1b) lesions. For one-cm size lesions (clinical stage T1c), SNR was maximized when compression was less than 12 cm, and little additional benefit was derived from further compression. For subcentimeter (clinical stage T1b) lesions, SNR was maximized when compression was less than 6 cm. These data are consistent with a short clinical study in which detection sensitivity for small cancers was improved with the SPEM camera as compared to a conventional gamma camera. We conclude that, in order to image early breast cancers (stage T1b), it is important to apply breast compression
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