Department of Radiology, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan.
Department of Radiology Services, Gifu University Hospital, 1-1 Yanagido, Gifu 501-1194, Japan.
Eur J Radiol. 2023 Aug;165:110960. doi: 10.1016/j.ejrad.2023.110960. Epub 2023 Jul 4.
To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them between hybrid-iterative reconstruction (IR) and deep-learning image reconstruction (DLIR) algorithms.
A total of 56 patients who underwent 80-kVp pancreatic protocol CT for pancreatic disease evaluation from January 2022 to July 2022 were included in this retrospective study. Among them, 20 PDACs were observed. The CT raw data were reconstructed using 40% adaptive statistical IR-Veo (hybrid-IR group) and DLIR at medium- and high-strength levels (DLIR-M and DLIR-H groups, respectively). The CT attenuation of the abdominal aorta, pancreas, and PDAC (if present) at the pancreatic phase and those of the portal vein and liver at the portal venous phase; background noise; signal-to-noise ratio (SNR) of these anatomical structures; and tumor-to-pancreas contrast-to-noise ratio (CNR) were calculated. The confidence scores for the image noise, overall image quality, and visibility of PDAC were qualitatively assigned using a five-point scale. Quantitative and qualitative parameters were compared among the three groups using Friedman test.
The CT attenuation of all anatomical structures were comparable among the three groups (P = .26-.86), except that of the pancreas (P = .001). Background noise was lower (P <.001) and SNRs (P <.001) and tumor-to-pancreas CNR (P <.001) were higher in the DLIR-H group than those in the other two groups. The image noise, overall image quality, and visibility of PDAC were better in the DLIR-H group than in the other two groups (P <.001-.003).
In 80-kVp pancreatic CT protocol, DLIR at a high-strength level improved image quality and visibility of PDAC.
评估 80kVp 胰腺 CT 方案中胰腺导管腺癌（PDAC）的图像质量和可探测性，并比较混合迭代重建（IR）和深度学习图像重建（DLIR）算法之间的差异。
本回顾性研究纳入了 2022 年 1 月至 7 月期间因胰腺疾病行 80kVp 胰腺协议 CT 检查的 56 例患者，其中 20 例为 PDAC。对胰腺期的腹主动脉、胰腺和 PDAC（如有）以及门静脉期的门静脉和肝脏的 CT 衰减值、背景噪声、这些解剖结构的信噪比（SNR）以及肿瘤与胰腺的对比噪声比（CNR）进行了计算。采用五分制对图像噪声、整体图像质量和 PDAC 可探测性的置信度评分进行了定性评估。采用 Friedman 检验比较了三组之间的定量和定性参数。
除胰腺外（P=0.001），三组间所有解剖结构的 CT 衰减值均无显著差异（P=0.26-0.86）。DLIR-H 组的背景噪声更低（P<0.001），SNR（P<0.001）和肿瘤与胰腺的 CNR（P<0.001）更高。DLIR-H 组的图像噪声、整体图像质量和 PDAC 的可探测性均优于其他两组（P<0.001-0.003）。
在 80kVp 胰腺 CT 方案中，高强度的 DLIR 可提高 PDAC 的图像质量和可探测性。
