系统评估5种不同的图像衍生输入功能,用于临床实施18F-NaF骨PET/CT在慢性肾脏疾病-矿物质和骨骼疾病患者

Jørn Theil, Marie Houmaa Vrist, Jesper Nørgaard Bech, Claire Anne Fynbo
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引用次数: 0

摘要

本研究的目的是研究在一组患有慢性肾脏疾病-矿物质和骨骼障碍(CKD-MBD)的患者中,使用不同的输入参数对骨血浆清除率(Ki)和其他动力学建模参数的影响胸主动脉。将标准化VOI放置在四个胸椎中,并将结果汇总并取平均值。对基本的图像导出输入函数(IDIF)进行了部分体积效应和溢出校正,并通过用从血液样本导出的相应血浆指数替换终端图像指数进行了修改。然后使用非线性回归(NLR)分析和图形Patlak分析计算Ki并进行比较。我们的原始结果是可重复的,观察者之间的差异约为6%。校正系数随VOI体积的变化而变化,从0.73 ± 最大LV-VOI为0.17(48.7 ± 25.3 cm3)至0.99 ± AO-VOI为0.10(3.4 ± 1.2 cm3)。平均NLR-Ki结果在0.0378之间变化 ± 0.0112和0.0432 ± 0.0095 毫升/分钟 ml−1,具有固定vB和0.0408 ± 0.0111和0.045 ± 0.0102 毫升/分钟 ml−1,具有自由拟合的vB。相应的Patl-Ki结果在0.0302之间变化 ± 0.0071和0.0325 ± 0.0070 毫升/分钟 ml−1,具有较小的差异和方差。与NLR结果相比,方差和平均差最小的输入函数来自VOI体积为19.2的左心室 ± 11.3 cm3校正PVE和Bg,平均Ki差:0.0097 ± 0.0370 毫升/分钟 ml−1和95%置信限(−0.023至0.004)。我们的结果表明,体积约为20 cm3,校正系数为0.83 ± 0.13的Patlak结果与NLR结果相比具有最小的方差和差异。在NLR分析中使用自由拟合的vB显示了所有输入序列中最稳健的结果。相比之下,Patlak结果通常低于NLR结果(−17.3%至−23.4%),但在各种输入序列中非常稳健,结果与之前公布的数据相当,因此建议未来进行分析。
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A systematic evaluation of five different image-derived input functions for the clinical implementation of 18F-NaF bone PET/CT in patients with chronic kidney disease-mineral and bone disorder.

Introduction: The aim of this study was to investigate the impact of the use of varying input parameters on resulting bone plasma clearance (Ki ) and other kinetic modelling parameters in a group of patients with chronic kidney disease-mineral and bone disorder (CKD-MBD).

Methods: Raw PET/CT data and blood data were systematically analyzed using five different VOIs for the input functions in the left ventricle and in the thoracic aorta. Standardized VOIs were placed in four thoracic vertebrae and the results pooled and averaged. The basic image-derived input functions (IDIFs) were corrected for partial volume effect and spill-over and modified by substitution of the terminal image exponential with the corresponding plasma-exponentials derived from blood samples. Ki was then calculated using both a non-linear regression (NLR) analysis and a graphical Patlak analysis and compared.

Results: Our original results were reproducible with an inter-observer difference of approximately 6%. The correction factors varied with the VOI volumes from 0.73 ± 0.17 for the largest LV-VOI (48.7 ± 25.3 cm3) to 0.99 ± 0.10 for the AO-VOI (3.4 ± 1.2 cm3). The mean NLR-Ki results varied between 0.0378 ± 0.0112 and 0.0432 ± 0.0095 ml/min ml-1 with a fixed vB and 0.0408 ± 0.0111 and 0.045 ± 0.0102 ml/min ml-1 with a free-fitted vB. The corresponding Patl-Ki -results varied between 0.0302 ± 0.0071 and 0.0325 ± 0.0070 ml/min ml-1, having lesser differences and variances. The input functions with least variance and mean differences compared with NLR results were derived from the left ventricle with a VOI volume of 19.2 ± 11.3 cm3 corrected for PVE and Bg with a mean Ki -difference: 0.0097 ± 0.0370 ml/min ml-1 and 95% confidence limits (-0.023 to 0.004).

Conclusions: Our results indicated that a VOI with a volume of approximately 20 cm3 with a correction factor of 0.83 ± 0.13 results in Patlak results with the least variance and difference compared with the NLR results. The use of free-fitted vB in the NLR analysis showed the most robust results in all input series. The Patlak results were in comparison generally lower than the NLR results (-17.3% to -23.4%) but very robust across the various input series and with results comparable to previously published data and are therefore recommended for future analysis.

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