Indovina Luca, Scolozzi Valentina, Capotosti Amedeo, Sestini Stelvio, Taralli Silvia, Cusumano Davide, Giancipoli Romina Grazia, Ciasca Gabriele, Cardillo Giuseppe, Calcagni Maria Lucia
Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Unità Operativa Complessa (UOC) di Medicina Nucleare, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Front Med (Lausanne). 2021 Nov 22;8:725387. doi: 10.3389/fmed.2021.725387. eCollection 2021.
To test a short 2-[F]Fluoro-2-deoxy-D-glucose (2-[F]FDG) PET dynamic acquisition protocol to calculate K using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC). 24 patients with NSCLC who underwent standard dynamic 2-[F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 ( = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10-60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 ( = 14), K was obtained by standard regional Patlak plot analysis using IDIF (0-60 min) and tissue response (10-60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain K using IDIF curve obtained from PET counts (0-10 min) followed by monoexponential coefficients of pIDIF (10-60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIF curves were modeled to assume the value of 2-[F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing-Bablok regression were used for the comparison between K and K. Finally, K was obtained with our method in a separate group of patients (group 3, = 8) that perform two short dynamic acquisitions. Population-based image-derived input function (10-60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: = 9.684, = 16.410, and = 0.068 min. The LOOCV error was 0.4%. In patients of group 2, the mean values of K and K were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively ( = 0.9970). The Passing-Bablok regression for comparison between K and K showed a slope of 0.992 (95% CI: 0.94-1.06) and intercept value of -0.0003 (95% CI: -0.0033-0.0011). Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional K estimation.
为了测试一种简短的2-[F]氟-2-脱氧-D-葡萄糖(2-[F]FDG)PET动态采集方案,以便在非小细胞肺癌(NSCLC)患者中使用区域Patlak图形分析来计算K值。24例接受标准动态2-[F]FDG采集(60分钟)的NSCLC患者被随机分为两组。在第1组(n = 10)中,使用单指数趋势(10 - 60分钟)构建基于人群的图像衍生输入函数(pIDIF),并采用留一法交叉验证(LOOCV)方法来验证pIDIF模型。在第2组(n = 14)中,通过标准区域Patlak图分析,分别使用放置在降主动脉和肿瘤组织上的感兴趣体积(VOI)的IDIF(0 - 60分钟)和组织反应(10 - 60分钟)曲线来获得K值。此外,采用我们的方法,利用从PET计数(0 - 10分钟)获得的IDIF曲线,随后是pIDIF的单指数系数(10 - 60分钟)以及在10分钟和40至60分钟之间从PET计数获得的组织反应曲线来进行Patlak分析以获得K值,模拟两次简短的动态采集。IDIF和IDIF曲线均被建模以假定在每位患者45分钟时进行的静脉血采样中测量的2-[F]FDG血浆活性值。使用Spearman等级相关性、决定系数和Passing - Bablok回归来比较K和K。最后,在另一组进行两次简短动态采集的患者(第3组,n = 8)中使用我们的方法获得K值。基于人群的图像衍生输入函数(10 - 60分钟)用单指数曲线建模,在第1组中获得以下拟合参数:A = 9.684,B = 16.410,k = 0.068分钟。LOOCV误差为0.4%。在第2组患者中,K和K的平均值分别为0.0442±0.0302和0.33±0.0298(r = 0.9970)。K和K比较的Passing - Bablok回归显示斜率为0.992(95%CI:0.94 - 1.06),截距值为 - 0.0003(95%CI: - 0.0033 - 0.0011)。尽管存在一些实际限制,如需要患者定位两次并进行两次CT扫描,但我们的方法考虑了两次简短的2-[F]FDG动态采集、基于人群的输入函数模型以及一次晚期静脉血样本采集,以获得稳健且个性化的输入函数和组织反应曲线,并提供可靠的区域K值估计。