Quantitative kinetic modeling requires an input function. A noninvasive image-derived input function (IDIF) can be obtained from dynamic PET images. However, a robust IDIF location (e.g., aorta) may be far from a tissue of interest, particularly in total-body PET, introducing a time delay between the IDIF and the tissue. The standard practice of joint estimation (JE) of delay, along with model fitting, is computationally expensive. To improve the efficiency of delay correction for total-body PET parametric imaging, this study investigated the use of pulse timing methods to estimate and correct for delay. Methods: Simulation studies were performed with a range of delay values, frame lengths, and noise levels to test the tolerance of 2 pulse timing methods—leading edge (LE) and constant fraction discrimination and their thresholds. The methods were then applied to data from 21 subjects (14 healthy volunteers, 7 cancer patients) who underwent a 60-min dynamic total-body ¹⁸F-FDG PET acquisition. Region-of-interest kinetic analysis was performed and parametric images were generated to compare LE and JE methods of delay correction, as well as no delay correction. Results: Simulations demonstrated that a 10% LE threshold resulted in biases and SDs at tolerable levels for all noise levels tested, with 2-s frames. Pooled region-of-interest–based results (n = 154) showed strong agreement between LE (10% threshold) and JE methods in estimating delay (Pearson r = 0.96, P < 0.001) and the kinetic parameters v_b (r = 0.96, P < 0.001), K_i (r = 1.00, P < 0.001), and K₁ (r = 0.97, P < 0.001). When tissues with minimal delay were excluded from pooled analyses, there were reductions in v_b (69.4%) and K₁ (4.8%) when delay correction was not performed. Similar results were obtained for parametric images; additionally, lesion K_i contrast was improved overall with LE and JE delay correction compared with no delay correction and Patlak analysis. Conclusion: This study demonstrated the importance of delay correction in total-body PET. LE delay correction can be an efficient surrogate for JE, requiring a fraction of the computational time and allowing for rapid delay correction across more than 10⁶ voxels in total-body PET datasets.

定量动力学建模需要输入函数。可以从动态 PET 图像获得非侵入性图像衍生输入函数 (IDIF)。然而，稳健的 IDIF 位置（例如，主动脉）可能远离感兴趣的组织，特别是在全身 PET 中，从而在 IDIF 和组织之间引入时间延迟。延迟的联合估计 (JE) 以及模型拟合的标准做法在计算上非常昂贵。为了提高全身 PET 参数成像延迟校正的效率，本研究调查了使用脉冲计时方法来估计和校正延迟。方法：使用一系列延迟值、帧长度和噪声水平执行仿真研究，以测试 2 脉冲定时方法的容差——前沿 (LE) 和恒定分数鉴别及其阈值。然后将这些方法应用于来自 21 名受试者（14 名健康志愿者，7 名癌症患者）的数据，这些受试者接受了 60 分钟动态全身¹⁸ F-FDG PET 采集。执行感兴趣区域动力学分析并生成参数图像以比较延迟校正的 LE 和 JE 方法，以及无延迟校正。结果：模拟表明，10% 的 LE 阈值导致偏差和 SD 处于可容忍水平的所有测试噪声水平，具有 2-s 帧。合并的基于感兴趣区域的结果 ( n= 154) 在估计延迟 (Pearson r = 0.96, P < 0.001) 和动力学参数v _b ( r = 0.96, P < 0.001), K _i ( r = 1.00，P < 0.001）和K ₁（r = 0.97，P < 0.001）。当具有最小延迟的组织被排除在汇总分析之外时，v _b (69.4%) 和K _1会减少(4.8%) 未执行延迟校正时。参数图像获得了类似的结果；此外，与无延迟校正和_Patlak分析相比，LE 和 JE 延迟校正的病变Ki对比度总体得到改善。结论：本研究证明了延迟校正在全身 PET 中的重要性。LE 延迟校正可以作为 JE 的有效替代物，需要一小部分计算时间并允许在全身 PET 数据集中超过 10 ^{6体素的快速延迟校正。}