Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
CT Research Center, GE Healthcare China, Shanghai, 210000, China.
Abdom Radiol (NY). 2024 Sep;49(9):2979-2987. doi: 10.1007/s00261-024-04221-y. Epub 2024 Mar 14.
To demonstrate the clinical advantages of a deep-learning image reconstruction (DLIR) in low-dose dual-energy computed tomography enterography (DECTE) by comparing images with standard-dose adaptive iterative reconstruction-Veo (ASIR-V) images.
In this Institutional review board approved prospective study, 86 participants who underwent DECTE were enrolled. The early-enteric phase scan was performed using standard-dose (noise index: 8) and images were reconstructed at 5 mm and 1.25 mm slice thickness with ASIR-V at a level of 40% (ASIR-V40%). The late-enteric phase scan used low-dose (noise index: 12) and images were reconstructed at 1.25 mm slice thickness with ASIR-V40%, and DLIR at medium (DLIR-M) and high (DLIR-H). The 70 keV monochromatic images were used for image comparison and analysis. For objective assessment, image noise, artifact index, SNR and CNR were measured. For subjective assessment, subjective noise, image contrast, bowel wall sharpness, mesenteric vessel clarity, and small structure visibility were scored by two radiologists blindly. Radiation dose was compared between the early- and late-enteric phases.
Radiation dose was reduced by 50% in the late-enteric phase [(6.31 ± 1.67) mSv] compared with the early-enteric phase [(3.01 ± 1.09) mSv]. For the 1.25 mm images, DLIR-M and DLIR-H significantly improved both objective and subjective image quality compared to those with ASIR-V40%. The low-dose 1.25 mm DLIR-H images had similar image noise, SNR, CNR values as the standard-dose 5 mm ASIR-V40% images, but significantly higher scores in image contrast [5(5-5), P < 0.05], bowel wall sharpness [5(5-5), P < 0.05], mesenteric vessel clarity [5(5-5), P < 0.05] and small structure visibility [5(5-5), P < 0.05].
DLIR significantly reduces image noise at the same slice thickness, but significantly improves spatial resolution and lesion conspicuity with thinner slice thickness in DECTE, compared to conventional ASIR-V40% 5 mm images, all while providing 50% radiation dose reduction.
通过比较低剂量双能 CT 肠造影(DECTE)的深度学习图像重建(DLIR)与标准剂量自适应迭代重建-Veo(ASIR-V)图像,展示 DLIR 在临床方面的优势。
在这项经机构审查委员会批准的前瞻性研究中,共纳入 86 名接受 DECTE 的参与者。采用标准剂量(噪声指数:8)进行早期肠期扫描,以 5mm 和 1.25mm 层厚进行 ASIR-V40%(ASIR-V40%)图像重建。晚期肠期采用低剂量(噪声指数:12),以 1.25mm 层厚进行 ASIR-V40%和 DLIR-M 和 DLIR-H 图像重建。使用 70keV 单能图像进行图像比较和分析。客观评估方面,测量图像噪声、伪影指数、SNR 和 CNR。主观评估方面,由两位放射科医生盲法评估主观噪声、图像对比度、肠壁锐利度、肠系膜血管清晰度和小结构可见度。比较早期肠期和晚期肠期的辐射剂量。
与早期肠期(3.01±1.09)相比,晚期肠期的辐射剂量降低了 50%[(6.31±1.67)mSv]。1.25mm 图像方面,与 ASIR-V40%相比,DLIR-M 和 DLIR-H 显著改善了客观和主观图像质量。低剂量 1.25mm DLIR-H 图像的图像噪声、SNR、CNR 值与标准剂量 5mm ASIR-V40%图像相似,但在图像对比度[5(5-5),P<0.05]、肠壁锐利度[5(5-5),P<0.05]、肠系膜血管清晰度[5(5-5),P<0.05]和小结构可见度[5(5-5),P<0.05]方面得分显著更高。
与传统的 5mm ASIR-V40%图像相比,DLIR 在 DECTE 中以相同的层厚显著降低图像噪声,但以更薄的层厚显著提高空间分辨率和病变显示,同时降低 50%的辐射剂量。