Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No.1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
Canon Medical Systems, Beijing, China.
Eur Radiol. 2022 Sep;32(9):5954-5963. doi: 10.1007/s00330-022-08739-x. Epub 2022 Mar 31.
To determine the diagnostic accuracy and image quality of ultra-low-dose computed tomography (ULDCT) with deep learning reconstruction (DLR) to evaluate patients with suspected urolithiasis, compared with ULDCT with hybrid iterative reconstruction (HIR) by using low-dose CT (LDCT) with HIR as the reference standard.
Patients with suspected urolithiasis were prospectively enrolled and underwent abdominopelvic LDCT, followed by ULDCT if any urinary stone was observed. Radiation exposure, stone characteristics, image noise, signal-to-noise ratio (SNR), and subjective image quality on a 5-point Likert scale were evaluated and compared.
The average effective radiation dose of ULDCT was significantly lower than that of LDCT (1.28 ± 0.34 vs. 5.49 ± 1.00 mSv, p < 0.001). According to the reference standard (LDCT-HIR), 148 urinary stones were observed in 85.0% (51/60) of patients. ULDCT-DLR detected 143 stones with a rate of 96.6%, and ULDCT-HIR detected 142 stones with a rate of 95.9%. The urinary stones that were not observed with ULDCT-DLR or ULDCT-HIR were renal calculi smaller than 3 mm. There were no significant differences in the detection of clinically significant calculi (≥ 3 mm) or stone size estimation among ULDCT-DLR, ULDCT-HIR, and LDCT-HIR. The image quality of ULDCT-DLR was better than that of ULDCT-HIR and LDCT-HIR with lower image noise, higher SNR, and higher average subjective score.
ULDCT-DLR performed comparably to LDCT-HIR in urinary stone detection and size estimation with better image quality and decreased radiation exposure. ULDCT-DLR may have potential to be considered the first-line choice to evaluate urolithiasis in practice.
• Ultra-low-dose computed tomography (ULDCT) has been investigated for diagnosis of urolithiasis, but stone evaluation may be adversely impacted by compromised image quality. • This study evaluated the value of novel deep learning reconstruction (DLR) at ULDCT by comparing the stone evaluation and image quality of ULDCT-DLR to the reference standard of low-dose CT (LDCT) with hybrid iterative reconstruction (HIR). • ULDCT-DLR performed comparably to LDCT-HIR in urinary stone detection and size estimation with better image quality and reduced radiation exposure.
通过使用低剂量 CT（LDCT）与混合迭代重建（HIR）作为参考标准，比较基于深度学习重建（DLR）的超低剂量 CT（ULDCT）与基于混合迭代重建（HIR）的 ULDCT 在评估疑似尿路结石患者中的诊断准确性和图像质量。
前瞻性纳入疑似尿路结石患者，行腹部骨盆 LDCT 检查，如果发现任何尿路结石，则进行 ULDCT 检查。评估并比较辐射暴露量、结石特征、图像噪声、信噪比（SNR）和 5 分李克特量表的主观图像质量。
ULDCT 的平均有效辐射剂量明显低于 LDCT（1.28±0.34 与 5.49±1.00 mSv，p<0.001）。根据参考标准（LDCT-HIR），在 60 名患者中，85.0%（51/60）的患者观察到 148 个尿路结石。ULDCT-DLR 检测到 143 个结石，检出率为 96.6%，ULDCT-HIR 检测到 142 个结石，检出率为 95.9%。ULDCT-DLR 或 ULDCT-HIR 未检测到的结石为直径小于 3mm 的肾结石。ULDCT-DLR、ULDCT-HIR 和 LDCT-HIR 在检测临床意义上较大的结石（≥3mm）或结石大小估计方面无显著差异。ULDCT-DLR 的图像质量优于 ULDCT-HIR 和 LDCT-HIR，具有较低的图像噪声、较高的 SNR 和较高的平均主观评分。
ULDCT-DLR 在尿路结石检测和大小估计方面与 LDCT-HIR 性能相当，具有更好的图像质量和更低的辐射暴露。ULDCT-DLR 有可能成为实践中评估尿路结石的首选方法。
• 超低剂量 CT（ULDCT）已被用于尿路结石的诊断，但图像质量的降低可能会对结石评估产生不利影响。• 本研究通过比较基于深度学习重建（DLR）的 ULDCT 与低剂量 CT（LDCT）与混合迭代重建（HIR）的参考标准，评估了新型 DLR 在 ULDCT 中的应用价值。• ULDCT-DLR 在尿路结石检测和大小估计方面与 LDCT-HIR 性能相当，具有更好的图像质量和更低的辐射暴露。
