The lungs are supplied by both the pulmonary arteries carrying deoxygenated blood originating from the right ventricle and the bronchial arteries carrying oxygenated blood downstream from the left ventricle. However, this effect of dual blood supply has never been investigated using PET, partially because the temporal resolution of conventional dynamic PET scans is limited. The advent of PET scanners with a long axial field of view, such as the uEXPLORER total-body PET/CT system, permits dynamic imaging with high temporal resolution (HTR). In this work, we modeled the dual-blood input function (DBIF) and studied its impact on the kinetic quantification of normal lung tissue and lung tumors using HTR dynamic PET imaging. Methods: Thirteen healthy subjects and 6 cancer subjects with lung tumors underwent a dynamic ¹⁸F-FDG scan with the uEXPLORER for 1 h. Data were reconstructed into dynamic frames of 1 s in the early phase. Regional time–activity curves of lung tissue and tumors were analyzed using a 2-tissue compartmental model with 3 different input functions: the right ventricle input function, left ventricle input function, and proposed DBIF, all with time delay and dispersion corrections. These models were compared for time–activity curve fitting quality using the corrected Akaike information criterion and for differentiating lung tumors from lung tissue using the Mann–Whitney U test. Voxelwise multiparametric images by the DBIF model were further generated to verify the regional kinetic analysis. Results: The effect of dual blood supply was pronounced in the high-temporal-resolution time–activity curves of lung tumors. The DBIF model achieved better time–activity curve fitting than the other 2 single-input models according to the corrected Akaike information criterion. The estimated fraction of left ventricle input was low in normal lung tissue of healthy subjects but much higher in lung tumors (~0.04 vs. ~0.3, P < 0.0003). The DBIF model also showed better robustness in the difference in ¹⁸F-FDG net influx rate $${K}_{\hbox{ i }}$$ and delivery rate $${K}_{1}$$ between lung tumors and normal lung tissue. Multiparametric imaging with the DBIF model further confirmed the differences in tracer kinetics between normal lung tissue and lung tumors. Conclusion: The effect of dual blood supply in the lungs was demonstrated using HTR dynamic imaging and compartmental modeling with the proposed DBIF model. The effect was small in lung tissue but nonnegligible in lung tumors. HTR dynamic imaging with total-body PET can offer a sensitive tool for investigating lung diseases.

肺部由携带来自右心室的脱氧血液的肺动脉和携带来自左心室下游的含氧血液的支气管动脉供应。然而，双重供血的这种效应从未使用 PET 进行过研究，部分原因是传统动态 PET 扫描的时间分辨率有限。具有长轴向视场的 PET 扫描仪（例如 uEXPLORER 全身 PET/CT 系统）的出现，可以实现高时间分辨率 (HTR) 的动态成像。在这项工作中，我们对双血输入函数 (DBIF) 进行了建模，并使用 HTR 动态 PET 成像研究了其对正常肺组织和肺肿瘤的动​​力学定量的影响。方法： 13 名健康受试者和 6 名患有肺部肿瘤的癌症受试者使用 uEXPLORER 进行动态¹⁸ F-FDG 扫描 1 小时。前期将数据重构为1s的动态帧。使用具有 3 种不同输入函数的 2 组织室模型分析肺组织和肿瘤的区域时间-活动曲线：右心室输入函数、左心室输入函数和提出的 DBIF，所有函数均具有时间延迟和色散校正。使用校正的 Akaike 信息标准比较这些模型的时间-活动曲线拟合质量，并使用 Mann-Whitney U检验区分肺肿瘤和肺组织。通过 DBIF 模型进一步生成体素多参数图像以验证区域动力学分析。结果：双供血的效果在肺部肿瘤的高时间分辨率时间-活动曲线中很明显。根据修正的 Akaike 信息准则，DBIF 模型比其他 2 个单输入模型实现了更好的时间-活动曲线拟合。健康受试者正常肺组织中左心室输入的估计分数较低，但肺肿瘤中左心室输入的估计分数较高（~0.04 vs.~0.3，P < 0.0003）。 DBIF 模型在¹⁸ F-FDG 净流入率差异方面也表现出更好的稳健性$${K}_{\hbox{ i }}$$和交货率$${K}_{1}$$肺肿瘤和正常肺组织之间。 DBIF 模型的多参数成像进一步证实了正常肺组织和肺肿瘤之间示踪动力学的差异。结论：使用 HTR 动态成像和所提出的 DBIF 模型的隔室建模证明了肺部双重供血的效果。对肺组织的影响很小，但对肺肿瘤的影响不可忽略。全身 PET 的 HTR 动态成像可以为研究肺部疾病提供灵敏的工具。