Differential diagnosis of ground-glass opacity nodules - CT number analysis by three-dimensional computerized quantification
Differential diagnosis of ground-glass opacity nodules - CT number analysis by three-dimensional computerized quantification
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DOI：
10.1378/chest.07-0793
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发表时间：
2007-09-01
期刊：
影响因子：
9.6
通讯作者：
Nomori, Hiroaki
中科院分区：
文献类型：
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作者：
Ikeda, Koei;Awai, Kazuo;Nomori, Hiroaki
目的：为了区分 CT 扫描上的非典型腺瘤性增生 (AAH)、细支气管肺泡癌 (BAC) 和显示磨玻璃样混浊的腺癌 (GGO)，我们进行了一项研究，以确定使用三维 (3D) 计算机量化进行 CT 数分析的最佳参数。方法：从通过 3D 计算机量化获得的 GGO 病变 CT 数、CT 数直方图模式、直方图上的峰值 CT 数、平均 CT 数以及第 5 至 95 个百分位 CT 数进行分析，以确定区分 AAH (n = 10)、BAC (n = 21) 和腺癌 (n = 12) 的最佳参数。结果：CT 编号直方图在 10 个 AAH 病灶中显示一个峰值（100%），在 21 个 BAC 病灶中的 8 个（38%）和 12 个腺癌病灶中的 5 个（42%）中显示两个峰值。对于区分 AAH 和 BAC，截断值为 -584 Hounsfield 单位 (HU) 的第 75 个百分位 CT 数是最佳的，灵敏度为 0.90，特异性为 0.81。对于区分 BAC 和腺癌，截止值为 -472 HU 的平均 CT 数是最佳的，敏感性为 0.75，特异性为 0.81。结论：通过对3D计算机量化获得的GGO病灶CT值进行分析，我们得出以下结论：（1）CT值直方图上出现两个峰值可以排除AAH； (2) 第 75 个百分位数是区分 AAH 和 BAC 的最佳 CT 值； (3)平均CT值是区分BAC和腺癌的最佳CT值。
Objectives: To differentiate among atypical adenomatous hyperplasia (AAH), bronchioloalveolar carcinoma (BAC), and adenocarcinoma showing ground-glass opacity (GGO) on CT scans, we conducted a study to determine the optimal parameter on CT number analysis using three-dimensional (3D) computerized quantification. Methods: From the CT numbers of GGO lesions obtained by 3D computerized quantification, CT number histogram pattern, peak CT number on the histogram, mean CT number, and the 5th to 95th percentile CT numbers were analyzed to determine the optimal parameter for differentiation among AAH (n = 10), BAC (n = 21), and adenocarcinoma (n = 12). Results: While the CT number histogram showed one peak in an 10 of the AAH lesions (100%), it showed two peaks in 8 of 21 BAC lesions (38%), and in 5 of 12 adenocarcinoma lesions (42%). For differentiation between AAH and BAC, the 75th percentile CT number with a cutoff value of -584 Hounsfield units (HU) was optimal, with a sensitivity of 0.90 and a specificity of 0.81. For differentiation between BAC and adenocarcinoma, a mean CT number with a cutoff value of -472 HU was optimal, with a sensitivity of 0.75 and a specificity of 0.81. Conclusions: From the analysis of CT numbers of GGO lesions obtained by 3D computerized quantification, we conclude the following: (1) two peaks on the CT number histogram can rule out AAH; (2) the 75th percentile is the optimal CT number for differentiating between AAH and BAC; and (3) the mean CT number is the optimal CT number for differentiating between BAC and adenocarcinoma.