Population-based input function (PBIF) applied to dynamic whole-body 68Ga-DOTATOC-PET/CT acquisition.

Philippe Thuillier, David Bourhis, Mathieu Pavoine, Jean-Philippe Metges, Romain Le Pennec, Ulrike Schick, Frédérique Blanc-Béguin, Simon Hennebicq, Pierre-Yves Salaun, Véronique Kerlan, Nicolas A Karakatsanis, Ronan Abgral
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Abstract

Rational: To validate a population-based input function (PBIF) model that alleviates the need for scanning since injection time in dynamic whole-body (WBdyn) PET.

Methods: Thirty-seven patients with suspected/known well-differentiated neuroendocrine tumors were included (GAPETNET trial NTC03576040). All WBdyn 68Ga-DOTATOC-PET/CT acquisitions were performed on a digital PET system (one heart-centered 6 min-step followed by nine WB-passes). The PBIF model was built from 20 image-derived input functions (IDIFs) obtained from a respective number of patients' WBdyn exams using an automated left-ventricle segmentation tool. All IDIF peaks were aligned to the median time-to-peak, normalized to patient weight and administrated activity, and then fitted to an exponential model function. PBIF was then applied to 17 independent patient studies by scaling it to match the respective IDIF section at 20-55 min post-injection time windows corresponding to WB-passes 3-7. The ratio of area under the curves (AUCs) of IDIFs and PBIF3-7 were compared using a Bland-Altman analysis (mean bias ± SD). The Patlak-estimated mean Ki for physiological uptake (Ki-liver and Ki-spleen) and tumor lesions (Ki-tumor) using either IDIF or PBIF were also compared.

Results: The mean AUC ratio (PBIF/IDIF) was 0.98 ± 0.06. The mean Ki bias between PBIF3-7 and IDIF was -2.6 ± 6.2% (confidence interval, CI: -5.8; 0.6). For Ki-spleen and Ki-tumor, low relative bias with low SD were found [4.65 ± 7.59% (CI: 0.26; 9.03) and 3.70 ± 8.29% (CI: -1.09; 8.49) respectively]. For Ki-liver analysis, relative bias and SD were slightly higher [7.43 ± 13.13% (CI: -0.15; 15.01)].

Conclusion: Our study showed that the PBIF approach allows for reduction in WBdyn DOTATOC-PET/CT acquisition times with a minimum gain of 20 min.

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基于群体的输入函数(PBIF)在动态全身68Ga DOTATOC PET/CT采集中的应用
合理验证基于人群的输入函数(PBIF)模型,该模型减轻了动态全身(WBdyn)PET自注射时间以来对扫描的需求。方法纳入37例疑似/已知的高分化神经内分泌肿瘤患者(GAPETNET试验NTC03576040)。所有WBdyn 68Ga DOTATOC PET/CT采集均在数字PET系统(一个以心脏为中心的6 最小步进,随后进行9次WB通过)。PBIF模型是由20个图像衍生输入函数(IDIF)构建的,这些函数是使用自动左心室分割工具从相应数量的患者的WBdyn检查中获得的。将所有IDIF峰值与达到峰值的中位时间对齐,标准化为患者体重和给药活动,然后拟合指数模型函数。然后将PBIF应用于17项独立的患者研究,将其按比例缩放以匹配20-55的相应IDIF部分 与WB通过3-7相对应的最小注射后时间窗口。使用Bland–Altman分析(平均偏差 ± SD)。还比较了使用IDIF或PBIF的生理摄取(Ki肝脏和Ki脾脏)和肿瘤病变(Ki肿瘤)的Patlak估计平均Ki。结果平均AUC比值(PBIF/IDIF)为0.98 ± 0.06。PBIF3–7和IDIF之间的平均Ki偏差为−2.6 ± 6.2%(置信区间,CI:−5.8;0.6)。对于Ki脾脏和Ki肿瘤,发现低相对偏差和低SD[4.65 ± 7.59%(CI:0.26;9.03)和3.70 ± 8.29%(CI:−1.09;8.49)]。Ki肝分析的相对偏倚和SD略高[7.43 ± 13.13%(CI:-0.15;15.01)]。结论我们的研究表明,PBIF方法可以减少WBdyn DOTATOC-PET/CT的采集时间,最小增益为20 最小。
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