胸部超低剂量CT应用深度学习重建行肺癌筛查的可行性研究  

Feasibility study of chest ultra-low dose CT with deep learning reconstruction for lung cancer screening

作　　者：宋兰[1] 田杜雪 王金华 王沄[1] 杜华阳 赵瑞杰 马壮飞 许英浩 隋昕[1] 陆晓平 宋伟[1] 金征宇[1] Song Lan;Tian Duxue;Wang Jinhua;Wang Yun;Du Huayang;Zhao Ruijie;Ma Zhuangfei;Xu Yinghao;Sui Xin;Lu Xiaoping;Song Wei;Jin Zhengyu(Department of Radiology,Peking Union Medical College Hospital,Peking Union Medical College,Chinese Academy of Medical Sciences,Beijing 100730,China;Canon Medical Systems(China)Co.,Ltd.,Beijing 100024,China)

机构地区：[1]中国医学科学院北京协和医学院北京协和医院放射科,北京100730 [2]佳能医疗系统(中国)有限公司,北京100024

出　　处：《中华放射学杂志》2022年第6期667-672,共6页Chinese Journal of Radiology

基　　金：北京市科学技术委员会AI+健康协同创新培育项目(Z201100005620008);国家自然科学基金面上项目(82171934);科技创新2030-“新一代人工智能”重大项目(2020AAA0109503);中国医学科学院医学与健康科技创新工程项目(2021-I2M-C&T-A-007)。

摘　　要：目的:探讨胸部超低剂量CT(ULDCT)应用深度学习重建(DLR)进行肺癌筛查的可行性,并比较其与ULDCT混合迭代重建(Hybrid IR)及常规剂量CT(RDCT)Hybrid IR的图像质量和结节检出率。方法:前瞻性纳入2020年10月至2021年3月在北京协和医院因肺结节接受胸部CT检查的患者。对患者分别进行胸部RDCT(120 kVp,自动管电流)和ULDCT(100 kVp,20 mA)扫描,并采用Hybrid IR(AIDR 3D)重建RDCT图像,采用AIDR 3D和DLR(AICE)重建ULDCT图像。记录辐射剂量和结节数。使用主气管及左肺上叶的客观噪声、信噪比(SNR)、肺部总体及结节的主观图像评分评估图像质量。主观评分由2名经验丰富的放射科医师采用Likert 5分制评分。采用配对t检验比较ULDCT与RDCT辐射剂量的差异。采用单因素方差分析或Friedman检验对3种重建方法的定量指标、客观图像噪声及主观评分进行比较。结果:共纳入45例,男17例、女28例,年龄32~74(55±11)岁。ULDCT的辐射剂量为(0.17±0.01)mSv,显著低于RDCT[(1.35±0.41)mSv,t=15.46,P<0.001]。ULDCT-AICE、ULDCT-AIDR 3D及RDCT-AIDR 3D图像在气管CT值、气管噪声、气管SNR、肺实质噪声及肺实质SNR的总体差异均有统计学意义(P<0.05),其中ULDCT-AICE的气管及肺实质图像噪声、气管CT值显著低于ULDCT-AIDR 3D(P<0.05),与RDCT-AIDR 3D差异无统计学意义(P>0.05)。RDCT-AIDR 3D、ULDCT-AIDR 3D、ULDCT-AICE总体图像质量和肺结节图像质量主观评分差异有统计学意义(χ2=50.57、117.20,P<0.001),其中ULDCT-AICE总体图像质量和肺结节图像质量主观评分优于ULDCT-AIDR 3D(P<0.05),与RDCT-AIDR 3D差异无统计学意义(P>0.05)。RDCT-AIDR 3D、ULDCT-AIDR 3D、ULDCT-AICE方法检出结节的数量一致,均为72个。结论:胸部ULDCT采用DLR重建可显著降低辐射剂量,且与Hybrid IR相比,能够有效降低图像噪声并提高SNR,并对肺结节的显示良好,图像质量及结节检出效果不弱于目前临床中常规使用的RDCT Hybrid IR。Objective To investigate the feasibility of chest ultra-low dose CT(ULDCT)using deep learning reconstruction(DLR)for lung cancer screening,and to compare its image quality and nodule detection rate with ULDCT iterative reconstruction(Hybrid IR)and conventional dose CT(RDCT)Hybrid IR.Methods The patients who underwent chest CT examination for pulmonary nodules in Peking Union Medical College Hospital from October 2020 to March 2021 were prospectively included and underwent chest RDCT(120 kVp,automatic tube current),followed by ULDCT(100 kVp,20 mA).The RDCT images were reconstructed with Hybrid IR(adaptive iterative dose reduction 3D,AIDR 3D),and ULDCT was reconstructed with AIDR3D and DLR.Radiation dose parameters and nodule numbers were recorded.Image quality was assessed using objective noise,signal-to-noise ratio(SNR)of the main trachea and left upper lobe,subjective image scores of the lung and nodules.Subjective scores were scored by 2 experienced radiologists on a Likert 5-point scale.The difference of radiation dose was compared with paired t-test between ULDCT and RDCT.The differences of quantitative indexes,objective image noise and subjective scores of the three reconstruction methods were compared with one-way analysis of variance or Friedman test.Results Forty-five patients were enrolled,including 17 males and 28 females,aged from 32 to 74(55±11)years.The radiation dose of ULDCT was(0.17±0.01)mSv,which was significantly lower than that of RDCT[(1.35±0.41)mSv,t=15.46,P<0.001].There were significant differences in the image noise and SNR in the trachea and lung parenchyma and in the CT value of the trachea among ULDCT-AICE,ULDCT-AIDR 3D and RDCT-AIDR 3D images(P<0.05).Image noise in the trachea and lung parenchyma and CT value in the trachea of ULDCT-AICE were significantly lower than those of ULDCT-AIDR 3D(P<0.05)and comparable to RDCT-AIDR 3D(P>0.05).There were significant differences in subjective image scores of the lung and nodules among ULDCT-AICE,ULDCT-AIDR 3D and RDCT-AIDR 3D images(χ²=50.57

关 键 词：肺肿瘤 体层摄影术 X线计算机 深度学习重建 图像质量 

分 类 号：R734.2[医药卫生—肿瘤] R730.44[医药卫生—临床医学]