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Parametric Image of Regional Bone Metabolism using F-18 PET using a Multiple Linear Regression Analysis Method

机译:使用多元线性回归分析方法使用F-18宠物的区域骨代谢的参数图像

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Dynamic PET data can be quantified several biological parameter using Nonlinear Least Square (NLS) and compartment modeling. However, NLS is inappropriate to voxel based analysis because of initial problem and excessive calculation time. Graphical method is able to reduce the computation time, but sensitive to noise and time duration. In this study, we applied a novel multiple linear regression analysis (MLAIR) method for the estimator of fluoride bone influx rate (K{sub}i) compared with patlak graphical method in minipig using [18{sup left}F]Fluoride PET. In ROI analysis, estimated K{sub}i values using MLAIR and Gjedde-Patlak graphical analysis (PGA) method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. However, Patlak slopes (K{sub}i) were changed with different t{sup}* in low uptake region. The parametric image quality was considerably improved when we used a new MLAIR method compared with Patlak. MLAIR showed reliable and robust properties for the voxel-wise parameter estimation in [18{sup left}F]Fluoride PET study. It is expected that this method will be a good alternative to PGA for the radiotracers with irreversible 2-tissue compartment model.
机译:可以使用非线性最小二乘(NLS)和隔室建模来量化动态PET数据。然而,由于初始问题和过度计算时间,NLS对基于体素的分析不合适。图形方法能够减少计算时间,但对噪声和持续时间敏感。在这项研究中,与MINIPIG中的Patlak图形方法使用[18 {Sup左} F]应用了用于氟化物骨流入速率(K {Sub} I)的估计器的新型多元线性回归分析(MLAIR)方法。在ROI分析中,使用MLAIR和GJEDDE-PATLAK图形分析(PGA)方法的估计k {Sub} I值略高于NLS,但MLAIR和PGA的结果是等同的。但是,Patlak斜率(k {sub} i)在低摄取区域中以不同的t {sup} *更改。当我们使用新的MLAIR方法与Patlak相比,参数图像质量显着提高。 MLAIR显示了氟化物宠物研究中的[18 {SUP} F]氟化酶的Voxel-Wise参数估计的可靠和鲁棒性能。预计该方法将是对具有不可逆2组织隔室模型的无反脱机构的PGA的替代品。

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