Comparison Of Ordered-Subset Expectation Maximization And Filtered Back Projection Reconstruction Based On Quantitative Outcome From Dynamic [F-18]Naf Pet Images

NUCLEAR MEDICINE COMMUNICATIONS(2021)

引用 4|浏览0
暂无评分
摘要
[18F]NaF PET imaging is a useful tool for measuring regional bone metabolism. However, due to tracer in urine, [18F]NaF PET images of the hip reconstructed using filtered back projection (FBP) frequently show streaking artifacts in slices through the bladder leading to noisy time-activity curves unsuitable for quantification. This study compares differences between quantitative outcomes at the hip derived from images reconstructed using the FBP and ordered-subset expectation maximization (OSEM) methods. Dynamic [18F]NaF PET data at the hip for four postmenopausal women were reconstructed using FBP and nine variations of the OSEM algorithm (all combinations of 1, 5, 15 iterations and 10, 15, 21 subsets). Seven volumes of interest were placed in the hip. Bone metabolism was measured using standardized uptake values, Patlak analysis (Ki-PAT) and Hawkins model Ki-4k. Percentage differences between the standardized uptake values and Ki values from FBP and OSEM images were assessed. OSEM images appeared visually smoother and without the streaking artifacts seen with FBP. However, due to loss of counts, they failed to recover the quantitative values in VOIs close to the bladder, including the femoral head and femoral neck. This was consistent for all quantification methods. Volumes of interest farther from the bladder or larger and receiving greater counts showed good convergence with 5 iterations and 21 subsets. For VOIs close to the bladder, including the femoral neck and femoral head, 15 iterations and 10, 15 or 21 subsets were not enough to obtain OSEM images suitable for measuring bone metabolism and showed no improvement compared to FBP.
更多
查看译文
关键词
bone metabolism, filtered back projection, [F-18]NaF, ordered-subset expectation maximization, PET, reconstruction
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要