Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.
Eur Radiol. 2024 Jan;34(1):28-38. doi: 10.1007/s00330-023-10033-3. Epub 2023 Aug 2.
To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR).
In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images.
Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates.
DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT.
Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose.
• The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.
与标准剂量单能量 CT（SECT）的深度学习图像重建（DLIR）或迭代重建（IR）相比，评估低剂量双能 CT（DECT）与深度学习图像重建（DLIR）的图像质量和肝转移瘤检测。
在这项前瞻性研究中，两组各有 40 名参与者接受腹部对比增强扫描，使用全剂量 SECT（120kVp 图像、DLIR 和 IR 算法）或低剂量 DECT（40-60keV 虚拟单色图像[VMI]、DLIR 算法），分别有 122 个和 106 个转移灶。两组按年龄、性别比例、体重指数和横截面积匹配。计算肝脏图像的噪声功率谱和转移灶的基于任务的转移函数，以评估噪声纹理和低对比度分辨率。在 1.25mm 重建图像上比较两组之间的图像噪声、肝和门静脉的信噪比（SNR）、肝与病灶的对比噪声比（LLR）、病灶显影性、病灶检出率和主观图像质量指标。
与 120kVp 图像的 IR 相比，40keV 和 50keV 的 VMI 的 DLIR 显示出相似的噪声纹理和 LLR，相似或更高的图像噪声和低对比度分辨率，改善的 SNR 和病灶显影性，以及相似或更好的感知图像质量。与 120kVp 图像的 DLIR 相比，50keV 的 VMI 的 DLIR 具有相似的低对比度分辨率、SNR、LLR、病灶显影性和感知图像质量，但噪声纹理频率较低，图像噪声较高。对于肝脏转移瘤的检测，降低 34%的剂量的 DECT 保持了观察者的病灶检出率。
DECT 辅助 DLIR 可以在检测肝转移瘤时降低 34%的剂量，同时保持与全剂量 SECT 相当的感知图像质量。
使用深度学习图像重建的低剂量双能 CT 与标准剂量单能量 CT 一样准确，可用于检测肝转移瘤，并可节省超过 30%的辐射剂量。
40keV 和 50keV 的虚拟单色图像（VMI）的 DLIR 与迭代重建的 120kVp 图像相比，提高了病灶的显影性，同时提供了相似或更好的感知图像质量。
50keV 的 VMI 的 DLIR 提供了与 120kVp 图像的 DLIR 相当的感知图像质量和病灶显影性。
低 keV VMI 降低 34%的剂量足以在临床上检测低对比度的肝转移瘤。
