基于深度学习的重建可提高低剂量 CT 结肠成像的图像质量。
Deep Learning-Based Reconstruction Improves the Image Quality of Low-Dose CT Colonography.
机构信息
Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Department of Radiology, Jinling Hospital, the First School of Clinical Medicine, Southern Medical University, Nanjing, Jiangsu 210002, China (Y.C.).
Department of Radiology, the Six Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Biomedical Innovation Center, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, China (Y.C., Z.H., L.F., W.Z., D.K., D.Z., M.L.); Department of Radiology, Guangdong Second Traditional Chinese Medicine Hospital, Guangzhou, Guangdong 510095, China (Z.H.).
出版信息
Acad Radiol. 2024 Aug;31(8):3191-3199. doi: 10.1016/j.acra.2024.01.021. Epub 2024 Jan 29.
RATIONALE AND OBJECTIVES
To evaluate the image quality of low-dose CT colonography (CTC) using deep learning-based reconstruction (DLR) compared to iterative reconstruction (IR).
MATERIALS AND METHODS
Adults included in the study were divided into four groups according to body mass index (BMI). Routine-dose (RD: 120 kVp) CTC images were reconstructed with IR (RD-IR); low-dose (LD: 100kVp) images were reconstructed with IR (LD-IR) and DLR (LD-DLR). The subjective image quality was rated on a 5-point scale by two radiologists independently. The parameters for objective image quality included noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The Friedman test was used to compare the image quality among RD-IR, LD-IR and LD-DLR. The KruskalWallis test was used to compare the results among different BMI groups.
RESULTS
A total of 270 volunteers (mean age: 47.94 years ± 11.57; 115 men) were included. The effective dose of low-dose CTC was decreased by approximately 83.18% (5.18mSv ± 0.86 vs. 0.86mSv ± 0.05, P < 0.001). The subjective image quality score of LD-DLR was superior to that of LD-IR (3.61 ± 0.56 vs. 2.70 ± 0.51, P < 0.001) and on par with the RD- IR's (3.61 ± 0.56 vs. 3.74 ± 0.52, P = 0.486). LD-DLR exhibited the lowest noise, and the maximum SNR and CNR compared to RD-IR and LD-IR (all P < 0.001). No statistical difference was found in the noise of LD-DLR images between different BMI groups (all P > 0.05).
CONCLUSION
Compared to IR, DLR provided low-dose CTC with superior image quality at an average radiation dose of 0.86mSv, which may be promising in future colorectal cancer screening.
背景与目的
评估基于深度学习的重建（DLR）与迭代重建（IR）相比在低剂量 CT 结肠成像（CTC）中的图像质量。
材料与方法
将研究中的成年人根据体重指数（BMI）分为四组。常规剂量（RD：120kVp）CTC 图像采用 IR（RD-IR）重建；低剂量（LD：100kVp）图像采用 IR（LD-IR）和 DLR（LD-DLR）重建。两名放射科医生独立对 5 分制的主观图像质量进行评分。客观图像质量的参数包括噪声、信噪比（SNR）和对比噪声比（CNR）。采用 Friedman 检验比较 RD-IR、LD-IR 和 LD-DLR 之间的图像质量。采用 KruskalWallis 检验比较不同 BMI 组之间的结果。
结果
共纳入 270 名志愿者（平均年龄：47.94 岁±11.57 岁；男性 115 名）。低剂量 CTC 的有效剂量降低了约 83.18%（5.18mSv±0.86 比 0.86mSv±0.05，P<0.001）。LD-DLR 的主观图像质量评分优于 LD-IR（3.61±0.56 比 2.70±0.51，P<0.001），与 RD-IR 相当（3.61±0.56 比 3.74±0.52，P=0.486）。与 RD-IR 和 LD-IR 相比，LD-DLR 具有最低的噪声和最大的 SNR 和 CNR（均 P<0.001）。不同 BMI 组之间，LD-DLR 图像的噪声无统计学差异（均 P>0.05）。
结论
与 IR 相比，DLR 在平均辐射剂量为 0.86mSv 时提供了低剂量 CTC 的更好的图像质量，这可能在未来的结直肠癌筛查中具有应用前景。
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