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.

Background: Quantitative activity estimation is essential in targeted radionuclide therapy dosimetry. Misregistration between SPECT and CT images at the same imaging time point due to patient movement degrades accuracy. This work aims to study the mismatch effects between CT and SPECT data on attenuation correction (AC), volume-of-interest (VOI) delineation and registration for activity estimation.Methods: Nine 4D XCAT phantoms were generated at 1, 24, and 144 hrs post In-111 Zevalin injection, varying in activity distributions, body and organ sizes. Realistic noisy SPECT projections were generated by an analytical projection and reconstructed with quantitative OS-EM method. CT images were shifted from -5 to 5 voxels as well as according to clinical reference corresponding to SPECT images at each time point. For AC effect, mismatched CT images were used for AC in SPECT reconstruction while VOIs were mapped out from matched CTs. For VOI effect, target organs were mapped out using mismatched CTs with matched CTs for AC. For registration effect, non-rigid registrations were performed on sequential mismatched CTs to align corresponding SPECT images, with no AC and VOI mismatch. Bi-exponential curve fitting was performed to obtain time-integrated activity (TIA). Organ activity errors (%OAE) and TIA errors (%TIAE) were calculated.Results: According to clinical reference, %OAE was larger for organs near ribs for AC effect, e.g., -2.58%±0.81% for liver. For VOI effect, %OAE was larger for small and low uptake organs, e.g., -11.94%±10.34% for spleen. %OAE was proportional to mismatch magnitude, e.g., 4.77%±1.41%, 12.01%±3.97% and 42.81%±6.38% for 1-, 2-, and 5-voxel mismatch for lungs. For registration effect, %TIAE were larger when mismatch existed in more numbers of SPECT/CT images, while no substantial difference was observed when using mismatched CT at different time points for registration reference. %TIAE was highest for VOI, followed by registration and AC, e.g., 37.61%±5.08%, 14.25%±7.07% and 1.13%±0.90% respectively for kidneys.Conclusions: The mismatch between CT and SPECT images poses a significant impact on accuracy of quantitative activity estimation in dosimetry, attributed particularly from VOI delineation errors. It is recommended to perform registration between emission and transmission images at the same time point to ensure dosimetric accuracy.

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