深度学习重建算法优化能谱CT低单能量图像质量及检测肝脏低对比度小病灶能力  

Deep learning image reconstruction for optimizing image quality of low-energy spectral monochromatic CT and detecting liver small low-contrast lesions

作　　者：吕培杰[1] 刘娜娜 王落桐 Francesca Rigiroli Daniele Marin 高剑波[1] LYU Peijie;LIU Nana;WANG Luotong;Francesca Rigiroli;Daniele Marin;GAO Jianbo(Department of Radiology,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China;CT Imaging Research Center,GE Healthcare,Beijing 100176,China;Department of Radiology,Beth Israel Deaconess Medical Center Harvard Medical School,Massachusetts 22015,USA;Department of Radiology,Duke University Medical Center,North Carolina 27708,USA)

机构地区：[1]郑州大学第一附属医院放射科,河南郑州450052 [2]通用电气医疗集团CT影像研究中心,北京100176 [3]哈佛大学医学院贝斯以色列女执事医疗中心放射科,美国马萨诸塞22015 [4]杜克大学医学中心放射科,美国北卡罗来纳27708

出　　处：《中国医学影像技术》2023年第1期104-108,共5页Chinese Journal of Medical Imaging Technology

基　　金：河南省高等学校重点科研项目(22A320057)。

摘　　要：目的观察深度学习重建(DLIR)算法用于优化能谱CT低单能量图像质量及提高检测肝脏低对比度小病灶能力的可行性。方法纳入30例接受上腹部门脉期增强扫描的肝脏疾病患者,包括58个肝脏病灶,分别采用DLIR及基于混合模型的自适应统计迭代重建(ASIR-V)算法重建40~70 keV(间隔10 keV)单能量图像;根据肝脏、门静脉及肝脏病灶对比噪声比(CNR)和噪声进行主观评价,针对图像总体质量、病灶显著性和诊断信心评分进行主观评价,比较不同图像之间评价结果的差异。结果相比ASIR-V图像,40~70 keV能级下,DLIR图像的CNR_(肝脏)、CNR_(门静脉)及CNR_(肝脏病灶)均显著增加而噪声均显著减少(P均<0.05);40~60 keV能级下,DLIR图像总体质量、病灶显著性及诊断信心评分均高于ASIR-V图像(P均<0.05)。结论DLIR技术可显著减少低单能量成像噪声、改善图像质量并提高检测肝脏低对比度小病灶的能力。Objective To investigate the feasibility of deep learning image reconstruction(DLIR)for optimizing image quality of low-energy spectral monochromatic CT and improving detection of liver small low-contrast lesions.Methods Thirty patients with 58 hepatic lesions who underwent upper abdominal portal-venous-phase enhanced CT were enrolled.Monochromatic images with energy levels ranging from 40 to 70 keV(10 keV increment)were reconstructed using DLIR and hybrid model-based adaptive statistical iterative reconstruction V(ASIR-V),respectively.The contrast-to-noise ratio(CNR)of liver,portal vein and hepatic lesions,also image noise were evaluated,the overall image quality,lesion conspicuity and diagnostic confidence were subjectively scored,and the outcomes were compared among different images.Results At the energy levels of 40—70 keV,compared with ASIR-V images,CNR_(liver),CNR_(portal vein)and CNR_(hepatic lesion)of DLIR images significantly increased(all P<0.05),while the image noise significantly reduced(all P<0.05).At the energy levels of 40—60 keV,the overall image quality,lesion conspicuity and diagnostic confidence of DLIR images were higher than those of ASIR-V images(all P<0.05).Conclusion DLIR technique could reduce noise of low-energy monochromatic images,improve image quality and detectability of liver small low-contrast lesions.

关 键 词：肝肿瘤 深度学习 体层摄影术 X线计算机 图像质量 

分 类 号：R735.7[医药卫生—肿瘤] R814.42[医药卫生—临床医学]