Defining a radiotherapy target with positron emission tomography
Defining a radiotherapy target with positron emission tomography
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DOI：
10.1016/j.ijrobp.2004.06.254
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发表时间：
2004-11-15
影响因子：
7
通讯作者：
Yan, D
中科院分区：
文献类型：
--
作者：
Black, QC;Grills, IS;Yan, D
目的：F-18氟脱氧葡萄糖正电子发射断层扫描（FDG-PET）成像现在被认为是非小细胞肺癌（NSCLC）最准确的临床分期研究，在多种其他恶性肿瘤的分期中也很重要。然而，用于放射治疗的总肿瘤体积（GTV）定义通常完全基于计算机断层扫描数据。我们进行了一系列的幻影研究，以确定一个准确的和统一适用的方法定义一个GTV与FDG-PET.Methods和材料：一个模型为基础的方法进行了测试的幻影研究，以确定一个阈值，或独特的截止标准化摄取值的基础上体重（标准化摄取值[SUV]）FDG-PET为基础的GTV定义。评估平均靶SUV、背景FDG浓度和靶体积对GTV定义的影响程度。构建了由9.0 L圆柱形罐组成的体模。将体积范围为12.2至291.0 cc的玻璃球悬浮在罐内，球边缘之间的最小间隔为4 cm。根据我们诊所中观察到的NSCLC患者肿瘤体积范围选择球体体积。在几个实验中，罐和球体填充有各种已知浓度的FDG，然后使用General Electric Advance PET扫描仪进行扫描。在最初的实验中，具有相同体积的六个球体填充有不同浓度的FDG（平均SUV = 1.85，类似于9.68），并以与临床实践中使用的浓度（0.144 μ Ci/mL）类似的浓度悬浮在FDG的背景浴中。第二个实验与第一个实验相同，但在0.144和0.036 μ Ci/mL背景浓度下进行，以确定背景FDG浓度对球体清晰度的影响。在第三个实验中，体积为12.2至291.0 cc的六个球体填充有相等浓度的FDG，并悬浮在浓度为0.144 μ Ci/mL的标准背景FDG中。每个实验中的球体图像都使用阈值SUV进行自动轮廓绘制（模拟GTV），从而产生与已知球体体积相匹配的体积。构建回归函数来表示阈值SUV和平均目标SUV之间的关系。然后应用该函数定义15例NSCLC患者的GTV。GTV体积进行了比较，由一个固定的图像强度阈值所确定的其他Investigator.Results：阈值SUV和平均目标SUV之间有很强的线性关系。得到的线性回归函数为：阈值SUV = 0.307 x（平均目标SUV）+0.588。背景浓度和靶体积通过影响平均靶SUV间接影响阈值SUV。我们应用线性回归函数，以及一个固定的图像强度阈值（最大强度的42%）的球体phantomy和15例NSCLC患者。结果表明，与固定图像强度阈值相比，阈值SUV回归函数用于估计体模体积时发生的偏差要小得多。相对于真实体模体积，两种方法之间的平均绝对差异为21%。当应用于真实患者GTV体积时，偏差变得更加明显，两种方法之间的平均差异为67%。这在很大程度上是由于更大程度的异质性在SUV的肿瘤phanasthene.Conclusions：FDG-PET为基础的GTV可以系统地定义使用阈值SUV根据上述回归函数。用于定义目标的阈值SUV强烈依赖于目标的平均目标SUV，并且可以通过所提出的迭代过程唯一地确定。(C)2004年爱思唯尔公司
Purpose: F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) imaging is now considered the most accurate clinical staging study for non-small-cell lung cancer (NSCLC) and is also important in the staging of multiple other malignancies. Gross tumor volume (GTV) definition for radiotherapy, however, is typically based entirely on computed tomographic data. We performed a series of phantom studies to determine an accurate and uniformly applicable method for defining a GTV with FDG-PET.Methods and Materials: A model-based method was tested by a phantom study to determine a threshold, or unique cutoff of standardized uptake value based on body weight (standardized uptake value [SUV]) for FDG-PET based GTV definition. The degree to which mean target SUV, background FDG concentration, and target volume influenced that GTV definition were evaluated. A phantom was constructed consisting of a 9.0-L cylindrical tank. Glass spheres with volumes ranging from 12.2 to 291.0 cc were suspended within the tank, with a minimum separation of 4 cm between the edges of the spheres. The sphere volumes were selected based on the range of NSCLC patient tumor volumes seen in our clinic. The tank and spheres were filled with a variety of known concentrations of FDG in several experiments and then scanned using a General Electric Advance PET scanner. In the initial experiment, six spheres with identical volumes were filled with varying concentrations of FDG (mean SUV = 1.85 similar to 9.68) and suspended within a background bath of FDG at a similar concentration to that used in clinical practice (0.144 muCi/mL). The second experiment was identical to the first, but was performed at 0.144 and 0.036 muCi/mL background concentrations to determine the effect of background FDG concentration on sphere definition. In the third experiment, six spheres with volumes of 12.2 to 291.0 cc were filled with equal concentrations of FDG and suspended in a standard background FDG concentration of 0.144 muCi/mL. Sphere images in each experiment were auto-contoured (simulating a GTV) using the threshold SUV that yielded a volume matching that of the known sphere volume. A regressive function was constructed to represent the relationship between the threshold SUV and the mean target SUV. This function was then applied to define the GTV of 15 NSCLC patients. The GTV volumes were compared to those determined by a fixed image intensity threshold proposed by other investigators.Results: There was a strong linear relationship between the threshold SUV and the mean target SUV. The linear regressive function derived was: threshold SUV = 0.307 x (mean target SUV) + 0.588. The background concentration and target volume indirectly affect the threshold SUV by way of their influence on the mean target SUV. We applied the linear regressive function, as well as a fixed image intensity threshold (42% of maximum intensity) to the sphere phantoms and 15 patients with NSCLC. The results indicated that a much smaller deviation occurred when the threshold SUV regressive function was utilized to estimate the phantom volume as compared to the fixed image intensity threshold. The average absolute difference between the two methods was 21% with respect to the true phantom volume. The deviation became even more pronounced when applied to true patient GTV volumes, with a mean difference between the two methods of 67%. This was largely due to a greater degree of heterogeneity in the SUV of tumors over phantoms.Conclusions: An FDG-PET-based GTV can be systematically defined using a threshold SUV according to the regressive function described above. The threshold SUV for defining the target is strongly dependent on the mean target SUV of the target, and can be uniquely determined through the proposed iteration process. (C) 2004 Elsevier Inc.