Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Eur Radiol. 2023 Jun;33(6):4344-4354. doi: 10.1007/s00330-022-09298-x. Epub 2022 Dec 28.
Low monoenergetic images obtained using noise-reduction techniques may reduce CT contrast media requirements. We aimed to investigate the effectiveness of low-contrast-dose CT using dual-energy CT and deep learning-based denoising (DLD) techniques in patients at high risk of hepatocellular carcinoma (HCC).
We performed a prospective, randomized controlled noninferiority trial at a tertiary hospital between June 2019 and August 2020 (NCT04027556). Patients at high risk of HCC were randomly assigned (1:1) to the standard-contrast-dose group or low-contrast-dose group, which targeted a 40% reduction in contrast medium dose based on lean body weight. HCC conspicuity on arterial phase images was the primary endpoint with a noninferiority margin of 0.2. Images were independently assessed by three radiologists; model-based iterative reconstruction (MBIR) images of the standard-contrast-dose group and low monoenergetic (50-keV) DLD images of the low-contrast-dose group were compared using a generalized estimating equation.
Ninety participants (age 59 ± 10 years; 68 men) were analyzed. Compared with the standard-contrast-dose group (n = 47), 40% less contrast media was used in the low-contrast-dose group (n = 43) (107.0 ± 17.1 mL vs. 64.5 ± 11.3 mL, p < 0.001). In the arterial phase, HCC conspicuity on 50-keV DLD images in the low-contrast-dose group was noninferior to that of MBIR images in the standard-contrast-dose group (2.92 vs. 2.56; difference, 0.36; 95% confidence interval, -0.13 to ∞; p = 0.013).
The contrast dose in liver CT can be reduced by 40% without impairing HCC conspicuity when using 50-keV and DLD techniques.
• In the arterial phase, hepatocellular carcinoma conspicuity on 50-keV deep learning-based denoising images in the low-contrast-dose group was noninferior to that of model-based iterative reconstruction images in the standard-contrast-dose group. • HCC detection was comparable between 50-keV deep learning-based denoising images in the low-contrast-dose group and model-based iterative reconstruction images in the standard-contrast-dose group.
使用降噪技术获得的低单能量图像可能会降低 CT 造影剂的需求。我们旨在研究双能 CT 和基于深度学习的降噪（DLD）技术在肝细胞癌（HCC）高危患者中降低低对比剂量 CT 的效果。
我们在 2019 年 6 月至 2020 年 8 月在一家三级医院进行了一项前瞻性、随机对照非劣效性试验（NCT04027556）。将 HCC 高危患者随机（1:1）分为标准对比剂量组或低对比剂量组，基于瘦体重将造影剂剂量减少 40%。动脉期图像上的 HCC 显影是主要终点，非劣效性边界为 0.2。由三位放射科医生独立评估；使用广义估计方程比较标准对比剂量组的基于模型的迭代重建（MBIR）图像和低对比剂量组的低单能（50keV）DLD 图像。
共分析了 90 名参与者（年龄 59±10 岁；68 名男性）。与标准对比剂量组（n=47）相比，低对比剂量组（n=43）的造影剂使用量减少了 40%（107.0±17.1mL 比 64.5±11.3mL，p<0.001）。在动脉期，低对比剂量组 50keV DLD 图像上的 HCC 显影不劣于标准对比剂量组的 MBIR 图像（2.92 比 2.56；差异，0.36；95%置信区间，-0.13 至 ∞；p=0.013）。
使用 50keV 和 DLD 技术，肝 CT 的造影剂量可减少 40%，而不会影响 HCC 的显影。
在动脉期，低对比剂量组的 50keV 基于深度学习的降噪图像上的 HCC 显影不劣于标准对比剂量组的基于模型的迭代重建图像。
低对比剂量组的 50keV 基于深度学习的降噪图像与标准对比剂量组的基于模型的迭代重建图像的 HCC 检测结果相当。
