Parametric Net Influx Rate Images of 68Ga-DOTATOC and 68Ga-DOTATATE: Quantitative Accuracy and Improved Image Contrast
Parametric Net Influx Rate Images of 68Ga-DOTATOC and 68Ga-DOTATATE: Quantitative Accuracy and Improved Image Contrast
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DOI：
10.2967/jnumed.116.180380
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发表时间：
2017-05-01
影响因子：
9.3
通讯作者：
Lubberink, Mark
中科院分区：
文献类型：
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作者：
Ilan, Ezgi;Sandstrom, Mattias;Lubberink, Mark
GA-68-DOTATOC和GA-68-DOTATE是用于诊断生长抑素受体表达的神经内分泌肿瘤(NETS)的放射性标记生长抑素类似物，SUV测量可用于治疗监测。然而，净流入速率(K)的变化可能比SUV的变化更好地反映治疗效果，因此需要计算在体素水平上显示KI的参数图像。本研究的目的是通过与基于感兴趣体积(VOI)的方法进行比较，来评价参数K1图像计算的参数方法，并根据肿瘤与肝脏的比率来评估图像对比度。方法：10例转移性NETs患者在注射Ga-68-DOTATOC和Ga-68-DOTATE后1h进行45min动态PET检查，然后进行全身PET/CT检查。使用降主动脉图像导出的输入函数，采用2组织不可逆室模型的基函数法(BFM)和Patlak方法计算参数K1图像，并确定50%等值线VOL的平均肿瘤KI值，并与基于全VOI时间-活动曲线的非线性回归(NLR)的KI值进行比较。在全身勾勒出健康肝脏的亚样本，计算K值，并计算肿瘤与肝脏的比率以评估图像对比度。通过回归和Bland-Altman分析评估基于VOI的K值与参数K值之间的相关性(R2)和一致性。结果：基于NLR的肿瘤K-I值与基于参数图像的肿瘤K-I值之间的R2分别为0.98(斜率0.81)和0.97(斜率0.88)。对于Patlak分析，基于NLR和基于参数(Patlak)的肿瘤Ki对于Ga-68-DOTATOC和Ga-68-DOTATE的R2分别为0.95(斜率，0.71)和0.92(斜率，0.74)。NLR和基于参数的K-I值之间没有偏差。对于68Ga-DOTATOC和Ga-68-DOTATE，参数BFM K1图像的肿瘤-肝脏对比度分别是全身图像的1.6倍和2.0倍，Patlak图像分别是全身图像的2.3倍和3.0倍。结论：基于NLR和基于参数的KI值具有较高的R2和一致性，表明K-I图像在定量上是准确的。此外，无论是Ga-68-DOTATOC还是Ga-66 DOTATE，在参数K-I图像上，肿瘤与肝脏的对比度都优于全身图像。
Ga-68-DOTATOC and Ga-68-DOTATATE are radiolabeled somatostatin analogs used for the diagnosis of somatostatin receptor-expressing neuroendocrine tumors (NETs), and SUV measurements are suggested for treatment monitoring. However, changes in net influx rate (K) may better reflect treatment effects than those of the SUV, and accordingly there is a need to compute parametric images showing Ki at the voxel level. The aim of this study was to evaluate parametric methods for computation of parametric K1 images by comparison to volume of interest (VOI) based methods and to assess image contrast in terms of tumor to -liver ratio. Methods: Ten patients with metastatic NETs underwent a 45-min dynamic PET examination followed by whole-body PET/CT at 1 h after injection of Ga-68-DOTATOC and Ga-68-DOTATATE on consecutive days. Parametric K1 images were computed using a basis function method (BFM) implementation of the 2-tissue-irreversible-compartment model and the Patlak method using a descending aorta image-derived input function, and mean tumor Ki values were determined for 50% isocontour VOls and compared with Ki values based on nonlinear regression (NLR) of the whole-VOI time-activity curve. A subsample of healthy liver was delineated in the whole-body and K, images, and tumor-to-liver ratios were calculated to evaluate image contrast. Correlation (R2) and agreement between VOI-based and parametric K, values were assessed using regression and Bland-Altman analysis. Results: The R2 between NLR-based and parametric image-based (BFM) tumor K-i values was 0.98 (slope, 0.81) and 0.97 (slope, 0.88) for Ga-68-DOTATOC and 68Ga-DOTATATE, respectively. For Patlak analysis, the R2 between NLR-based and parametric-based (Patlak) tumor Ki was 0.95 (slope, 0.71) and 0.92 (slope, 0.74) for Ga-68-DOTATOC and Ga-68-DOTATATE, respectively. There was no bias between NLR and parametric-based K-i values. Tumor-to-liver contrast was 1.6 and 2.0 times higher in the parametric BFM K1 images and 2.3 and 3.0 times in the Patlak images than in the whole body images for 68Ga-DOTATOC and Ga-68-DOTATATE, respectively. Conclusion: A high R2 and agreement between NLR- and parametric-based Ki values was found, showing that K-i images are quantitatively accurate. In addition, tumor-to-liver contrast was superior in the parametric K-i images compared with whole-body images for both Ga-68-DOTATOC and Ga-66 DOTATATE.