Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
Department of Medical Physics, Bravis Hospital, Roosendaal, Netherlands.
Br J Radiol. 2023 Sep;96(1149):20220157. doi: 10.1259/bjr.20220157. Epub 2023 Jun 29.
Renal lesions are sometimes incidentally detected during computed tomography (CT) examinations in which an unenhanced series is not included, preventing the lesions from being fully characterized. The aim of this study was to investigate the feasibility to use virtual non-contrast (VNC) images, acquired using a detector-based dual-energy CT, for the characterization of renal lesions.
Twenty-seven patients (12 women) underwent a renal CT scan, including a non-contrast, an arterial, and a venous phase contrast-enhanced series, using a detector-based dual-energy CT scanner. VNC images were reconstructed from the venous contrast-enhanced series. The mean attenuation values of 65 renal lesions in both the VNC and true non-contrast (TNC) images were measured and compared quantitatively. Three radiologists blindly assessed all lesions using either VNC or TNC images in combination with contrast-enhanced images.
Sixteen patients had cystic lesions, five had angiomyolipoma (AML), and six had suspected renal cell carcinomas (RCC). Attenuation values in VNC and TNC images were strongly correlated (ρ = 0.7, mean difference -6.0 ± 13 HU). The largest differences were found for unenhanced high-attenuation lesions. Radiologists classified 86% of the lesions correctly using VNC images.
In 70% of the patients, incidentally detected renal lesions could be accurately characterized using VNC images, resulting in less patient burden and a reduction in radiation exposure.
This study shows that renal lesions can be accurately characterized using VNC images acquired by detector-based dual-energy CT, which is in agreement with previous studies using dual-source and rapid X-ray tube potential switching technique.
在未增强系列未包含的计算机断层扫描(CT)检查中,有时会偶然发现肾脏病变,从而无法对病变进行全面特征描述。本研究旨在探讨使用基于探测器的双能 CT 获得的虚拟非对比(VNC)图像对肾脏病变进行特征描述的可行性。
27 例患者(12 例女性)接受了肾脏 CT 扫描,包括非增强期、动脉期和静脉期增强系列扫描,使用基于探测器的双能 CT 扫描仪。从静脉对比增强系列中重建 VNC 图像。在 VNC 和真实非对比(TNC)图像中测量并比较了 65 个肾脏病变的平均衰减值,并进行了定量分析。三位放射科医生分别使用 VNC 或 TNC 图像与增强图像相结合对所有病变进行了盲法评估。
16 例患者为囊性病变,5 例为血管平滑肌脂肪瘤(AML),6 例为疑似肾细胞癌(RCC)。VNC 和 TNC 图像中的衰减值具有很强的相关性(ρ=0.7,平均差值为-6.0±13 HU)。最大的差异出现在未增强的高衰减病变中。放射科医生使用 VNC 图像正确分类了 86%的病变。
在 70%的患者中,使用 VNC 图像可以准确地对偶然发现的肾脏病变进行特征描述,从而减轻患者的负担并减少辐射暴露。
本研究表明,使用基于探测器的双能 CT 获得的 VNC 图像可以准确地对肾脏病变进行特征描述,这与以前使用双源和快速 X 射线管电位切换技术的研究结果一致。