Abstract：
To evaluate the usefulness of low-keV multiphasic computed tomography (CT) with deep learning image reconstruction (DLIR) in improving the delineation of pancreatic ductal adenocarcinoma (PDAC) compared to conventional hybrid iterative reconstruction (HIR). Thirty-five patients with PDAC who underwent multiphasic CT were retrospectively evaluated. Raw data were reconstructed with two energy levels (40 keV and 70 keV) of virtual monochromatic imaging (VMI) using HIR (ASiR-V50%) and DLIR (TrueFidelity-H). Contrast-to-noise ratio (CNRtumor) was calculated from the CT values within regions of interest in tumor and normal pancreas in the pancreatic parenchymal phase images. Lesion conspicuity of PDAC in pancreatic parenchymal phase on 40-keV HIR, 40-keV DLIR, and 70-keV DLIR images was qualitatively rated on a 5-point scale, using 70-keV HIR images as reference (score 1 = poor; score 3 = equivalent to reference; score 5 = excellent) by two radiologists. CNRtumor of 40-keV DLIR images (median 10.4, interquartile range (IQR) 7.8-14.9) was significantly higher than that of the other VMIs (40 keV HIR, median 6.2, IQR 4.4-8.5, P < 0.0001; 70-keV DLIR, median 6.3, IQR 5.1-9.9, P = 0.0002; 70-keV HIR, median 4.2, IQR 3.1-6.1, P < 0.0001). CNRtumor of 40-keV DLIR images were significantly better than those of the 40-keV HIR and 70-keV HIR images by 72 ± 22% and 211 ± 340%, respectively. Lesion conspicuity scores on 40-keV DLIR images (observer 1, 4.5 ± 0.7; observer 2, 3.4 ± 0.5) were significantly higher than on 40-keV HIR (observer 1, 3.3 ± 0.9, P < 0.0001; observer 2, 3.1 ± 0.4, P = 0.013). DLIR is a promising reconstruction method to improve PDAC delineation in 40-keV VMI at the pancreatic parenchymal phase compared to conventional HIR.
摘要：
与传统的混合迭代重建（HIR）相比，评估具有深度学习图像重建（DLIR）的低keV多相计算机断层扫描（CT）在改善胰腺导管腺癌（PDAC）勾画中的有用性。回顾性评估了35例接受多相CT检查的PDAC患者。使用HIR（ASiR-V50％）和DLIR（TrueFidelity-H），用两个能级（40keV和70keV）的虚拟单色成像（VMI）重建原始数据。根据胰腺实质期图像中肿瘤和正常胰腺中感兴趣区域内的CT值计算对比噪声比(CNRtoma)。PDAC在40-keVHIR胰腺实质期的显着性病变，40-keVDLIR,70-keVDLIR图像以5分制进行定性评级，使用两名放射科医生的70-keVHIR图像作为参考（评分1=较差；评分3=相当于参考；评分5=优秀）。40-keVDLIR图像的CNR肿瘤（中位数10.4，四分位距（IQR）7.8-14.9）明显高于其他VMI（40keVHIR，中位数6.2，IQR4.4-8.5，P<0.0001；70keVDLIR，中位数6.3，IQR5.1-9.9，P=0.0002；70keVHIR，中位数4.2，IQR3.1-6.1，P<0.0001）。40-keVDLIR图像的CNR肿瘤明显优于40-keVHIR和70-keVHIR图像的CNR肿瘤72±22％和211±340％，分别。40-keVDLIR图像（观察者1，4.5±0.7；观察者2，3.4±0.5）的病变显著性得分显着高于40-keVHIR（观察者1，3.3±0.9，P<0.0001；观察者2，3.1±0.4，P=0.013）。与常规HIR相比，DLIR是一种有前途的重建方法，可改善胰腺实质期40-keVVMI中的PDAC轮廓。
