부산대학교 도서관

Purpose: We aimed to evaluate respiratory impacts on static and respiratory gated (RG) 99mTc‐MAA SPECT in terms of respiratory motion (RM) blur, attenuation correction (AC), and volume‐of‐interest (VOI) segmentation on lung shunt faction (LSF) and tumor‐to‐normal liver ratio (TNR) estimation for liver radioembolization therapy planning. Methods: The XCAT phantom was used to simulate a population of 300 phantoms, modeling various anatomical variations, tumor characteristics, RM amplitudes, LSFs, and TNRs. One hundred and twenty noisy projections of average activity maps near end‐expiration (End‐EX) and whole respiratory cycle were simulated analytically, modeling attenuation and geometric collimator‐detector‐response (GCDR). The OS‐EM algorithm was employed for reconstruction, modeling AC, and GCDR. RM effect was evaluated for static SPECT, while AC and VOI mismatch effects were investigated independently and together for static and RG SPECT utilizing one gate, that is, End‐EX. LSF and TNR errors were measured based on the ground truth. Lesions with different characteristics were also investigated for static and RG SPECT. Results: RM overestimates LSF and underestimates TNR. The VOI mismatch caused the largest errors in both RG and static SPECT for LSF and TNR estimation, reaching 160% and −52% correspondingly with extremely mismatched VOIs for RG SPECT, even larger than those for static SPECT. With matched AC and VOIs, RG SPECT has better performance than static SPECT. Larger TNR errors are associated with tumors of smaller sizes and higher TNR for static SPECT. Conclusions: The VOI segmentation mismatch has a stronger impact, followed by RM and AC in static 99mTc‐MAA SPECT/CT. This effect is more pronounced for RG SPECT. When VOI masks are derived from a matched CT, RG SPECT is generally superior to static SPECT for LSF and TNR estimation. The performance of RG SPECT could be worse than static SPECT when a mismatched CT is used for segmentation. [ABSTRACT FROM AUTHOR]