Department of Radiology B, University Hospital of Strasbourg - New Civil Hospital, Strasbourg, Cedex, France.
Department of Statistics, University Hospital of Strasbourg - New Civil Hospital, Strasbourg, Cedex, France.
Medicine (Baltimore). 2023 Sep 1;102(35):e34579. doi: 10.1097/MD.0000000000034579.
To evaluate the impact of a reduced iodine load using deep learning reconstruction (DLR) on the hepatic parenchyma compared to conventional iterative reconstruction (hybrid IR) and its consequence on the radiation dose and image quality. This retrospective monocentric intraindividual comparison study included 66 patients explored at the portal phase using different multidetector computed tomography parameters: Group A, hybrid IR algorithm (hybrid IR) and a nonionic low-osmolality contrast agent (350 mgI/mL); Group B, DLR algorithm (DLR) and a nonionic iso-osmolality contrast agent (270 mgI/mL). We recorded the attenuation of the liver parenchyma, image quality, and radiation dose parameters. The mean hounsfield units (HU) value of the liver parenchyma was significantly lower in group B, at 105.9 ± 10.9 HU versus 118.5 ± 14.6 HU in group A. However, the 90%IC of mean liver attenuation in the group B (DLR) was between 100.8 HU and 109.3 HU. The signal-to-noise ratio of the liver parenchyma was significantly higher on DLR images, increasing by 56%. However, for both the contrast-to-noise ratio (CNR) and CNR liver/PV no statistical difference was found, even if the CNR liver/PV ratio was slightly higher for group A. The mean dose-length product and computed tomography dose index volume values were significantly lower with DLR, corresponding to a radiation dose reduction of 36% for the DLR. Using a DLR algorithm for abdominal multidetector computed tomography with a low iodine load can provide sufficient enhancement of the liver parenchyma up to 100 HU in addition to the advantages of a higher image quality, a better signal-to-noise ratio and a lower radiation dose.
为了评估与传统迭代重建（混合 IR）相比，使用深度学习重建（DLR）降低碘负荷对肝脏实质的影响及其对辐射剂量和图像质量的影响。这项回顾性单中心个体间比较研究纳入了 66 例采用不同多层螺旋 CT 参数进行门静脉期扫描的患者：A 组，混合 IR 算法（混合 IR）和一种非离子低渗透压造影剂（350 mgI/mL）；B 组，DLR 算法（DLR）和一种非离子等渗透压造影剂（270 mgI/mL）。我们记录了肝脏实质的衰减、图像质量和辐射剂量参数。B 组肝脏实质的平均 hounsfield 单位（HU）值明显较低，为 105.9±10.9 HU，而 A 组为 118.5±14.6 HU。然而，B 组（DLR）的平均肝脏衰减 90%置信区间（IC）在 100.8 HU 和 109.3 HU 之间。肝脏实质的信噪比在 DLR 图像上显著提高，增加了 56%。然而，对于对比噪声比（CNR）和 CNR 肝脏/PV，没有发现统计学差异，即使 A 组的 CNR 肝脏/PV 比值略高。DLR 的平均剂量长度乘积和 CT 剂量指数体积值显著降低，DLR 的辐射剂量降低了 36%。在腹部多层螺旋 CT 中使用 DLR 算法进行低碘负荷检查，除了具有更高的图像质量、更好的信噪比和更低的辐射剂量等优点外，还可以提供高达 100 HU 的肝脏实质充分增强。
