Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.
Department of Nuclear Medicine, Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Med Phys. 2022 Aug;49(8):5330-5339. doi: 10.1002/mp.15682. Epub 2022 May 4.
We aimed to evaluate respiratory impacts on static and respiratory gated (RG) Tc-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.
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.
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.
The VOI segmentation mismatch has a stronger impact, followed by RM and AC in static Tc-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.
本研究旨在评估在静态和呼吸门控（RG）Tc-MAA SPECT 中，呼吸运动（RM）模糊、衰减校正（AC）以及感兴趣区（VOI）分割对肺分流分数（LSF）和肿瘤-正常肝比（TNR）估计的影响，以便进行肝放射性栓塞治疗计划。
使用 XCAT 体模模拟了 300 个体模的人群，模拟了各种解剖变异、肿瘤特征、RM 幅度、LSF 和 TNR。通过分析模拟了接近呼气末（End-EX）和整个呼吸周期的平均活性图的 120 个噪声投影，模拟了衰减和几何准直器-探测器响应（GCDR）。采用 OS-EM 算法进行重建，模拟了 AC 和 GCDR。评估了静态 SPECT 的 RM 影响，同时独立和共同研究了静态和 RG SPECT 的 AC 和 VOI 不匹配效应，使用一个门，即 End-EX。基于真实值测量了 LSF 和 TNR 误差。还研究了不同特征的病灶在静态和 RG SPECT 中的情况。
RM 高估了 LSF，低估了 TNR。VOI 不匹配在 RG 和静态 SPECT 中对 LSF 和 TNR 估计的误差最大，对于 RG SPECT 达到了 160%和-52%，对于 RG SPECT，即使是非常不匹配的 VOI，误差也比静态 SPECT 大。在匹配 AC 和 VOI 的情况下，RG SPECT 的性能优于静态 SPECT。对于静态 SPECT，较小的肿瘤和较高的 TNR 与较大的 TNR 误差相关。
在静态 Tc-MAA SPECT/CT 中，VOI 分割不匹配的影响最大，其次是 RM 和 AC。这种影响在 RG SPECT 中更为明显。当 VOI 掩模源自匹配的 CT 时，对于 LSF 和 TNR 估计，RG SPECT 通常优于静态 SPECT。当使用不匹配的 CT 进行分割时，RG SPECT 的性能可能会比静态 SPECT 差。
