Ye Kai, Chen Min, Zhu Qiao, Lu Yuliu, Yuan Huishu
Department of Radiology, Peking University Third Hospital, Beijing, China.
Department of Radiology, Ghent University Hospital, Corneel Heymanslaan 10,9000, Ghent, Belgium.
Quant Imaging Med Surg. 2021 Jun;11(6):2344-2353. doi: 10.21037/qims-20-932.
The weightings of iterative reconstruction algorithm can affect CT radiomic quantification. But, the effect of ASiR-V levels on the reproducibility of CT radiomic features between ultra-low-dose computed tomography (ULDCT) and low-dose computed tomography (LDCT) is still unknown. The purpose of study is to investigate whether adaptive statistical iterative reconstruction-V (ASiR-V) levels affect radiomic feature quantification using ULDCT and to assess the reproducibility of radiomic features between ULDCT and LDCT.
Sixty-three patients with pulmonary nodules underwent LDCT (0.70±0.16 mSv) and ULDCT (0.15±0.02 mSv). LDCT was reconstructed with ASiR-V 50%, and ULDCT with ASiR-V 50%, 70%, and 90%. Radiomics analysis was applied, and 107 features were extracted. The concordance correlation coefficient (CCC) was calculated to describe agreement among ULDCTs and between ULDCT and LDCT for each feature. The proportion of features with CCC >0.9 among ULDCTs and between ULDCT and LDCT, and the mean CCC for all features between ULDCT and LDCT were also compared.
Sixty-three solid nodules (SNs) and 48 pure ground-glass nodules (pGGNs) were analyzed. There was no difference for the proportion of features in SNs among ULDCTs and between ULDCT and LDCT (P>0.05). The proportion of features in pGGNs were highest for ULDCT (78.5%) and ULDCT LDCT (50.5%). In SNs, the mean CCC for ULDCT LDCT was 0.67±0.26, not different with that for ULDCT LDCT (0.68±0.24) and ULDCT LDCT (0.64±0.21) (P>0.05). In pGGNs, the mean CCC for ULDCT LDCT was 0.79±0.19, higher than that for ULDCT LDCT (0.61±0.28) and ULDCT LDCT (0.76±0.24) (P<0.05).
ASiR-V levels significantly affected ULDCT radiomic feature quantification in pulmonary nodules, with stronger effects in pGGNs than in SNs. The reproducibility of radiomic features was highest between ULDCT and LDCT.
迭代重建算法的权重会影响CT影像组学定量分析。但是，自适应统计迭代重建-V（ASiR-V）水平对超低剂量计算机断层扫描（ULDCT）和低剂量计算机断层扫描（LDCT）之间CT影像组学特征可重复性的影响尚不清楚。本研究的目的是探讨ASiR-V水平是否会影响ULDCT的影像组学特征定量分析，并评估ULDCT和LDCT之间影像组学特征的可重复性。
63例肺结节患者接受了LDCT（0.70±0.16 mSv）和ULDCT（0.15±0.02 mSv）检查。LDCT采用ASiR-V 50%进行重建，ULDCT分别采用ASiR-V 50%、70%和90%进行重建。应用影像组学分析，提取107个特征。计算一致性相关系数（CCC）以描述各特征在不同ULDCT之间以及ULDCT与LDCT之间的一致性。还比较了ULDCT之间以及ULDCT与LDCT之间CCC>0.9的特征比例，以及ULDCT与LDCT之间所有特征的平均CCC。
分析了63个实性结节（SNs）和48个纯磨玻璃结节（pGGNs）。SNs中，不同ULDCT之间以及ULDCT与LDCT之间的特征比例无差异（P>0.05）。pGGNs中，ULDCT的特征比例最高（78.5%），ULDCT与LDCT之间的特征比例为50.5%。在SNs中，ULDCT与LDCT之间的平均CCC为0.67±0.26，与ULDCT与LDCT之间（P>0.05）以及ULDCT与LDCT之间（0.64±0.21）无差异。在pGGNs中，ULDCT与LDCT之间的平均CCC为0.79±0.19，高于ULDCT与LDCT之间（0.61±0.28）以及ULDCT与LDCT之间（0.76±0.24）（P<0.05）。
ASiR-V水平显著影响肺结节中ULDCT的影像组学特征定量分析，对pGGNs的影响比对SNs更强。ULDCT与LDCT之间影像组学特征的可重复性最高。
