分子影像学杂志2026，Vol.49Issue(1)：44-49,6.DOI:10.12122/j.issn.1674-4500.2026.01.07
深度学习图像重建实现胸部能谱CT虚拟平扫对真实平扫的临床替代
Deep learning image reconstruction enables virtual non-contrast to replace true non-contrast in chest spectral CT
摘要
Abstract
Objective To explore the application value of deep learning image reconstruction(DLIR)in optimizing the image quality of virtual non-contrast(VNC)chest spectral CT.Methods Forty-five patients undergoing true non-contrast(TNC)and dual-phase contrast-enhanced spectral CT of the chest at the Affiliated Hospital of Shaanxi University of Chinese Medicine from June to October 2024 were prospectively enrolled.ASIR-V50%weighted reconstruction at 120 kVp-like settings served as the true non-contrast reference(TNC-AR50).Based on arterial and venous phase contrast data,four DLIR-reconstructed VNC groups(VP-VNC-DM,VP-VNC-DH,AP-VNC-DM,AP-VNC-DH).CT values,noise(SD),SNR,and CNR were measured for the aorta,subcutaneous fat,erector spinae muscles,and lesions across all five image sets(TNC-AR50+4 VNC sets).Objective metrics were compared using one-way ANOVA and Kruskal-Wallis tests.Two radiologists independently performed subjective blinded evaluations of overall image quality and lesion visibility using a 5-point Likert scale.Results In objective image quality assessment,the VP-VNC-DH group demonstrated superior quality compared to TNC-AR50,with no statistically significant differences in CT values among the five groups(P>0.05).The VP-VNC-DH group exhibited the lowest image noise and the highest SNR and CNR.In subjective evaluation,the VP-VNC-DH group received the highest image quality scores and performed best in lesion conspicuity.The total effective radiation dose for chest CT with and without the TNC scan was 9.40±0.41 mSv and 6.27±0.28 mSv,respectively.Omitting the TNC scan reduced the total radiation dose by approximately 33.3%.Conclusion In chest-enhanced CT examinations,VNC images reconstructed using DLIR(especially venous-phase DLIR-H)demonstrated significantly superior image quality compared to TNC images reconstructed using ASIR-V 50%,with good CT value consistency.It is recommended to use venous-phase high-level DLIR(DLIR-H)reconstruction for VNC images as an alternative to true non-contrast scans to effectively reduce radiation dose.关键词
深度学习重建算法/虚拟平扫/胸部CT/辐射剂量Key words
deep learning reconstruction algorithm/virtual plain scan/chest CT/radiation dose引用本文复制引用
徐龙,李鑫,党珊,于楠,贾永军,段海峰..深度学习图像重建实现胸部能谱CT虚拟平扫对真实平扫的临床替代[J].分子影像学杂志,2026,49(1):44-49,6.基金项目
陕西省教育厅青年创新团队科学研究计划项目(24JP049) （24JP049）
