Technical note: Respiratory impacts on static and respiratory gated ^99mTc‐MAA SPECT/CT for liver radioembolization: A simulation study

Abstract

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.

Dosimetric impact of 3D motion-compensated SPECT reconstruction for SIRT planning

“…Moreover, the ranges of motion used in the simulations are higher than those estimated for our patients: between 1 and 2 cm versus 0.9 cm in the cranio-caudal direction and between 0.6 and 1.2 cm versus 0.4 cm in the antero-posterior direction that could also explain differences in conclusions. There was no significant difference in the TN ratio between the two reconstructions in contrast to other authors who found an underestimation of the TN ratio in the absence of respiratory motion correction [ 23 , 24 ]. In the article by Bastiaannet et al [ 23 ], the lesions have a volume of less than 35 mL, in contrast to those of our patients (between 1.7 and 1828 mL).…”

“…Few studies have been published on the subject. In [ 23 , 24 ], the authors evaluated dosimetric impacts of motion by performing simulations from digital XCAT phantoms with different sets of parameters (body type, lung shunt fraction (LSF), tumor volume and localization). Likewise, Santoro et al [ 25 ] tested a novel method to compensate for motion on a modified CIRS dynamic phantom and applied it on the data of twelve selected patients (HCC, single lesion).…”

“…Likewise, Santoro et al [ 25 ] tested a novel method to compensate for motion on a modified CIRS dynamic phantom and applied it on the data of twelve selected patients (HCC, single lesion). However, the realism of simulations and phantoms is limited (perfect respiratory cycle and simplifications in the movement, characteristics of each patient, assumption of a perfectly compensated scatter [ 24 ]). In contrast to our method based on list-mode data, Santoro et al [ 25 ] corrected for respiratory motion by realigning the barycenters of the lesions in the projections with each other before realigning them on the CT to improve attenuation correction and VOI definitions [ 36 ].…”

“…There was no statistically significant difference for lung doses between the two reconstructions (same for LSF) which is in agreement with the results of Bastiaannet et al [ 23 ] for the LSF. However, Lu et al [ 24 ] showed that the LSF was overestimated when the respiratory motion was not corrected. The lesions considered are only located in segments V, VI and VIII of the liver unlike ours and in particular at the level of the hepatic dome where larger dose differences are expected.…”

“…However, to our knowledge, it is not used during SIRT although the liver movement due to breathing is well known [ 22 ]. Bastiaannet et al [ 23 ] and Lu et al [ 24 ] studied the dosimetric impact of breathing motion on numerical phantoms (physical phantoms in [ 25 ]) and showed that it is the main undesirable effect for the quantification in radioembolization. To our knowledge, this impact has only been evaluated by Santoro et al [ 25 ] on 12 SPECT patients images with a single liver lesion, which is not representative of all patients treated by SIRT.…”