使用低衰减体积百分比和低衰减肺区域大小分布在低剂量CT上进行肺气肿定量分析：采用三维处理的自适应迭代剂量降低的效果
Emphysema quantification on low-dose CT using percentage of low-attenuation volume and size distribution of low-attenuation lung regions: effects of adaptive iterative dose reduction using 3D processing.
作者信息
Nishio Mizuho, Matsumoto Sumiaki, Seki Shinichiro, Koyama Hisanobu, Ohno Yoshiharu, Fujisawa Yasuko, Sugihara Naoki, Yoshikawa Takeshi, Sugimura Kazuro
机构信息
Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017, Japan; Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017, Japan.
Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo 650-0017, Japan.
出版信息
Eur J Radiol. 2014 Dec;83(12):2268-2276. doi: 10.1016/j.ejrad.2014.09.011.
PURPOSE
To evaluate the effects of adaptive iterative dose reduction using 3D processing (AIDR 3D) for quantification of two measures of emphysema: percentage of low-attenuation volume (LAV%) and size distribution of low-attenuation lung regions.
METHOD AND MATERIALS
Fifty-two patients who underwent standard-dose (SDCT) and low-dose CT (LDCT)were included. SDCT without AIDR 3D, LDCT without AIDR 3D, and LDCT with AIDR 3D were used for emphysema quantification. First, LAV% was computed at 10 thresholds from −990 to −900 HU. Next, at the same thresholds, linear regression on a log–log plot was used to compute the power law exponent (D)for the cumulative frequency-size distribution of low-attenuation lung regions. Bland–Altman analysis was used to assess whether AIDR 3D improved agreement between LDCT and SDCT for emphysema quantification of LAV% and D.
RESULTS
The mean relative differences in LAV% between LDCT without AIDR 3D and SDCT were 3.73%–88.18% and between LDCT with AIDR 3D and SDCT were −6.61% to 0.406%. The mean relative differences in D between LDCT without AIDR 3D and SDCT were 8.22%–19.11% and between LDCT with AIDR3D and SDCT were 1.82%–4.79%. AIDR 3D improved agreement between LDCT and SDCT at thresholds from −930 to −990 HU for LAV% and at all thresholds for D.
CONCLUSION
AIDR 3D improved the consistency between LDCT and SDCT for emphysema quantification of LAV% and D.
目的
评估使用三维处理的自适应迭代剂量降低技术（AIDR 3D）对两种肺气肿测量指标进行定量分析的效果，这两种指标分别为低衰减体积百分比（LAV%）和低衰减肺区域的大小分布。
方法与材料
纳入52例行标准剂量CT（SDCT）和低剂量CT（LDCT）检查的患者。使用未采用AIDR 3D的SDCT、未采用AIDR 3D的LDCT以及采用AIDR 3D的LDCT进行肺气肿定量分析。首先，在-990至-900 HU的10个阈值处计算LAV%。接下来，在相同阈值下，使用对数-对数图上的线性回归计算低衰减肺区域累积频率-大小分布的幂律指数（D）。采用Bland-Altman分析评估AIDR 3D是否改善了LDCT与SDCT在LAV%和D的肺气肿定量分析方面的一致性。
结果
未采用AIDR 3D的LDCT与SDCT之间LAV%的平均相对差异为3.73%至88.18%，采用AIDR 3D的LDCT与SDCT之间LAV%的平均相对差异为-6.61%至0.406%。未采用AIDR 3D的LDCT与SDCT之间D的平均相对差异为8.22%至19.11%，采用AIDR 3D的LDCT与SDCT之间D的平均相对差异为1.82%至4.79%。对于LAV%，AIDR 3D在-930至-990 HU的阈值下改善了LDCT与SDCT之间的一致性；对于D，在所有阈值下均有改善。
结论
AIDR 3D改善了LDCT与SDCT在LAV%和D的肺气肿定量分析方面的一致性。
Zotero 插件