Tumor volume measurement error using computed tomography imaging in a phase II clinical trial in lung cancer
Tumor volume measurement error using computed tomography imaging in a phase II clinical trial in lung cancer
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DOI：
10.1117/1.jmi.3.3.035505
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发表时间：
2016-07-01
影响因子：
2.4
通讯作者：
Avila, Ricardo
中科院分区：
文献类型：
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作者：
Henschke, Claudia I.;Yankelevitz, David F.;Avila, Ricardo
为了解决计算机断层扫描 (CT) 扫描仪在评估实体瘤体积和一维测量时引入的误差，我们与参加肺癌临床试验的患者同时扫描了精密制造的袖珍模型。专用软件量化 X 中的偏差和随机误差；聚四氟乙烯球体的 Y 和 Z 尺寸，以及使用恒定阈值和自适应阈值量化实体瘤和体积测量的响应评估标准。我们发现 X 的低估偏差本质上是相同的； Y 和 Z 维度使用恒定阈值，并且具有相似的自适应阈值值。通过标准偏差和变异系数测量的这些长度测量值的随机误差对于恒定阈值分别为 0.10 毫米 (0.65)、0.11 毫米 (0.71) 和 0.59 毫米 (3.75)，对于自适应阈值分别为 0.08 毫米 (0.51)、0.09 毫米 (0.56) 和 0.58 毫米 (3.68)。然而，对于随机误差，Z 长度的标准偏差和变异系数至少比 X 和 Y 高五倍。对于某些 8 和 16 层 CT 模型，观察到的 Z 尺寸误差特别高。 CT 图像形成中的误差，特别是对于探测器行数较少的模型，可能大到足以被误解为代表治疗反应或疾病进展。 (C) 作者。由 SPIE 根据 Creative Commons Attribution 3.0 Unported 许可证发布。全部或部分分发或复制本作品需要原始出版物的完整归属，包括其 DOI。
To address the error introduced by computed tomography (CT) scanners when assessing volume and unidimensional measurement of solid tumors, we scanned a precision manufactured pocket phantom simultaneously with patients enrolled in a lung cancer clinical trial. Dedicated software quantified bias and random error in the X; Y, and Z dimensions of a Teflon sphere and also quantified response evaluation criteria in solid tumors and volume measurements using both constant and adaptive thresholding. We found that underestimation bias was essentially the same for X; Y, and Z dimensions using constant thresholding and had similar values for adaptive thresholding. The random error of these length measurements as measured by the standard deviation and coefficient of variation was 0.10 mm (0.65), 0.11 mm (0.71), and 0.59 mm (3.75) for constant thresholding and 0.08 mm (0.51), 0.09 mm (0.56), and 0.58 mm (3.68) for adaptive thresholding, respectively. For random error, however, Z lengths had at least a fivefold higher standard deviation and coefficient of variation than X and Y. Observed Z-dimension error was especially high for some 8 and 16 slice CT models. Error in CT image formation, in particular, for models with low numbers of detector rows, may be large enough to be misinterpreted as representing either treatment response or disease progression. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.