目的:我们的研究目的是通过逐体素分析评估神经母细胞瘤(NB)中[18F]FDG标准摄取值(SUV)与表观扩散系数(ADC)之间的关联。
方法:根据我们的前瞻性观察性PET/MRI研究,我们进一步调查了一个基线影像学和化疗后影像学均诊断为NB的患者亚队列.配准和肿瘤分割后,使用允许体素分析的专用软件,根据ADC和SUV值计算代谢和功能性肿瘤体积.在阈值的平均值下,每个体素被分配到三个虚拟组织组之一:高生命(V)(低ADC和高SUV),可能是低生命(lv)(高ADC和低SUV),以及高ADC和高SUV或低ADC和低SUV的模棱两可(e)。此外,使用多高斯分布方法从总肿瘤体积中产生三个簇.计算各组ADC和SUV之间的Pearson相关系数。
结果:在21例NB患者的43例PET/MRI中,8例患者中16例MRI符合纳入标准(化疗前后PET/MRI)。肿瘤体积的比例为26%,36%,和38%(v,lv,e)基线时,0.03%,66%,34%的患者在治疗后有反应,42%,25%,33%患有进行性疾病,分别。在所有集群中,ADC与SUV呈负相关。在对应于高度重要组织的集群中,治疗前ADC与SUV呈中度负相关(R=-0.18;p<0.0001),治疗后呈最强负相关(R=-0.45;p<0.0001)。有趣的是,只有治疗中进展的患者(n=2)在治疗后出现相关部分.
结论:我们的结果表明,ADC和SUV的体素分析是可行的,并且可以量化神经母细胞性肿瘤中组织的不同质量。监测ADC以及SUV水平可以量化治疗期间的肿瘤动力学。
OBJECTIVE: The purpose of our study was to evaluate the association between the [18F]FDG standard uptake value (SUV) and the apparent diffusion coefficient (ADC) in neuroblastoma (NB) by voxel-wise analysis.
METHODS: From our prospective observational PET/MRI study, a subcohort of patients diagnosed with NB with both baseline imaging and post-chemotherapy imaging was further investigated. After registration and tumor segmentation, metabolic and functional tumor volumes were calculated from the ADC and SUV values using dedicated software allowing for voxel-wise analysis. Under the mean of thresholds, each voxel was assigned to one of three virtual tissue groups: highly vital (v) (low ADC and high SUV), possibly low vital (lv) (high ADC and low SUV), and equivocal (e) with high ADC and high SUV or low ADC and low SUV. Moreover, three clusters were generated from the total tumor volumes using the method of multiple Gaussian distributions. The Pearson\'s correlation coefficient between the ADC and the SUV was calculated for each group.
RESULTS: Out of 43 PET/MRIs in 21 patients with NB, 16 MRIs in 8 patients met the inclusion criteria (PET/MRIs before and after chemotherapy). The proportion of tumor volumes were 26%, 36%, and 38% (v, lv, e) at baseline, 0.03%, 66%, and 34% after treatment in patients with response, and 42%, 25%, and 33% with progressive disease, respectively. In all clusters, the ADC and the SUV correlated negatively. In the cluster that corresponded to highly vital tissue, the ADC and the SUV showed a moderate negative correlation before treatment (R = -0.18; p < 0.0001) and the strongest negative correlation after treatment (R = -0.45; p < 0.0001). Interestingly, only patients with progression (n = 2) under therapy had a relevant part in this cluster post-treatment.
CONCLUSIONS: Our results indicate that voxel-wise analysis of the ADC and the SUV is feasible and can quantify the different quality of tissue in neuroblastic tumors. Monitoring ADCs as well as SUV levels can quantify tumor dynamics during therapy.