OBJECTIVES:To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm. METHODS:Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175–545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI > 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FBP), 40% and 80% strength. Both the quantitative measurement and qualitative analysis of the five types of reconstruction methods were compared. In addition, radiation dose and image quality between the early-arterial phase ASIR-V images using standard-dose and the late-arterial phase DLIR images using low-dose were compared. RESULTS:For the late-arterial phase, all five reconstructions had similar CT value (P > 0.05). DLIR-H, DLIR-M and ASIR-V80% images significantly reduced the image noise and improved the image contrast noise ratio, compared with the standard ASIR-V40% images (P < 0.05). ASIR-V80% images had undesirable image characteristics with obvious “waxy” artifacts, while DLIR-H images maintained high spatial resolution and had the highest subjective image quality. Compared with the early-arterial scans, the late-arterial phase scans significantly reduced the radiation dose (P < 0.05), while the DLIR-H images exhibited lower image noise and good display of the specific image details of lesions. CONCLUSIONS:DLIR algorithm improves image quality under low-dose scan condition and may be used to reduce the radiation dose without adversely affecting the image quality.

中文翻译：

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利用深度学习图像重建算法实现低剂量腹部CT的可行性研究

目的：探讨使用深度学习图像重建（DLIR）算法在低剂量腹部 CT 中获得诊断图像的可行性。方法：前瞻性招募了 47 名需要腹部 CT 增强扫描的患者。使用低剂量模式（管电流范围，175-545 mA；对于 BMI ≤ 24 kg/m2 的患者为 80 kVp，对于 BMI > 24 kg/m2 的患者为 100 kVp）和用中等设置 (DLIR-M) 和高设置 (DLIR-H) 的 DLIR、0% (FBP)、40% 和 80% 强度的 ASIR-V 重建。对五种重建方法的定量测量和定性分析进行了比较。此外，比较了使用标准剂量的早期动脉期 ASIR-V 图像和使用低剂量的晚期动脉期 DLIR 图像之间的辐射剂量和图像质量。结果：对于晚期动脉期，所有 5 次重建的 CT 值相似（P > 0.05）。与标准 ASIR-V40% 图像相比，DLIR-H、DLIR-M 和 ASIR-V80% 图像显着降低了图像噪声并提高了图像对比度噪声比（P < 0.05）。ASIR-V80% 图像具有不理想的图像特征，具有明显的“蜡状”伪影，而 DLIR-H 图像保持高空间分辨率并具有最高的主观图像质量。与早期动脉扫描相比，晚期动脉期扫描显着降低了辐射剂量（P < 0.05），而DLIR-H图像表现出较低的图像噪声和良好的病灶特定图像细节显示。结论：DLIR算法提高了低剂量扫描条件下的图像质量，可用于降低辐射剂量而不会对图像质量产生不利影响。