This study aimed to determine the optimal β value of the relaxation control parameter and the post-smoothing filter in the list-mode dynamic row-action maximum likelihood algorithm (LM-DRAMA) to detect early stage breast cancer with high-resolution dedicated breast positron emission tomography (dbPET) in phantom and clinical studies.
A breast phantom containing four spheres (5, 7.5, 10, and 16 mm in diameter) was filled with F-fluorodeoxyglucose solution (sphere-to-background ratio, 8:1) and scanned on a dbPET scanner. The images were reconstructed using LM-DRAMA with different β values (5, 20, or 100) and Gaussian post-filters (0, 0.78, 1.17, 1.56, 1.95, or 2.34 mm). Other conditions were according to those routinely used (1 iteration and 128 subsets including attenuation and scatter correction). Image quality was evaluated visually and by computing the coefficient of variation of the background (CV), detectability index (DI), and contrast recovery coefficient. Parameters optimized in these phantom studies were applied to 25 clinical data sets. Variabilities for different reconstruction methods in visual scores, the maximum standardized uptake value of breast cancer, and the tumor-to-background uptake ratio were estimated.
The reconstruction images of the phantom with higher β values and smaller post-filters yielded higher visual scores for detectability and DI and lower smoothness and CV scores. Based on the phantom study, the β values and post-filter were optimized for clinical dbPET images except for β5 and 2.34 mm post-filter. Applying the other reconstructions to clinical studies showed that β100 provided higher quantitative parameter values. The detectability of lesions was similar for β100 and β20 and decreased with larger post-filters. The lesion detection rate was similar for β100 and β20 and decreased with larger post-filter.
The relaxation coefficient factor β20 and a 0.78- or 1.17-mm post-filter were optimal for dbPET image reconstruction with balanced spatial resolution and noise. However, they should be selected according to the impact on the dbPET image and the purpose of the examination.
About The Expert
Yoko Satoh
Masamichi Imai
Kenji Hirata
Yuzo Asakawa
Chihiro Ikegawa
Hiroshi Onishi
References
PubMed