Department of Surgical Sciences/Nuclear Medicine & PET, Uppsala University, Uppsala, Sweden.
Centre for Research and Development, Uppsala/Gävleborg County, Gävle, Sweden.
J Nucl Cardiol. 2022 Aug;29(4):1742-1752. doi: 10.1007/s12350-021-02550-9. Epub 2021 Mar 2.
Patient motion is a common problem during cardiac PET. The purpose of the present study was to investigate to what extent motions influence the quantitative accuracy of cardiac O-water PET/CT and to develop a method for automated motion detection.
Frequency and magnitude of motion was assessed visually using data from 50 clinical O-water PET/CT scans. Simulations of 4 types of motions with amplitude of 5 to 20 mm were performed based on data from 10 scans. An automated motion detection algorithm was evaluated on clinical and simulated motion data. MBF and PTF of all simulated scans were compared to the original scan used as reference.
Patient motion was detected in 68% of clinical cases by visual inspection. All observed motions were small with amplitudes less than half the LV wall thickness. A clear pattern of motion influence was seen in the simulations with a decrease of myocardial blood flow (MBF) in the region of myocardium to where the motion was directed. The perfusable tissue fraction (PTF) trended in the opposite direction. Global absolute average deviation of MBF was 3.1% ± 1.8% and 7.3% ± 6.3% for motions with maximum amplitudes of 5 and 20 mm, respectively. Automated motion detection showed a sensitivity of 90% for simulated motions ≥ 10 mm but struggled with the smaller (≤ 5 mm) simulated (sensitivity 45%) and clinical motions (accuracy 48%).
Patient motion can impair the quantitative accuracy of MBF. However, at typically occurring levels of patient motion, effects are similar to or only slightly larger than inter-observer variability, and downstream clinical effects are likely negligible.
患者运动是心脏 PET 中常见的问题。本研究旨在探讨运动在何种程度上影响心脏 O-水 PET/CT 的定量准确性，并开发一种自动运动检测方法。
使用来自 50 例临床 O-水 PET/CT 扫描的数据，通过视觉评估运动的频率和幅度。根据来自 10 次扫描的数据，模拟了 4 种幅度为 5 至 20mm 的运动。评估了自动运动检测算法在临床和模拟运动数据上的性能。比较了所有模拟扫描的 MBF 和 PTF 与用作参考的原始扫描。
通过视觉检查，在 68%的临床病例中检测到患者运动。所有观察到的运动幅度都很小，小于 LV 壁厚度的一半。在模拟中，运动方向的心肌血流（MBF）明显减少，可见运动影响的清晰模式。可灌注组织分数（PTF）呈相反趋势。最大运动幅度为 5mm 和 20mm 时，MBF 的全球绝对平均偏差分别为 3.1%±1.8%和 7.3%±6.3%。自动运动检测对模拟运动（≥10mm）的敏感性为 90%，但对较小的（≤5mm）模拟运动（敏感性为 45%）和临床运动（准确性为 48%）的敏感性较差。
患者运动可能会降低 MBF 的定量准确性。然而，在通常发生的患者运动水平下，其影响与观察者间差异相似或仅略大，且下游的临床影响可能可以忽略不计。
