ISSN 1004-4140
CN 11-3017/P
CAO Juntao, CHEN Qiqi, HU Ming, XU Ting, TU Jianchun, ZHANG Huan. A Preliminary Analysis of Using the Sinogram-affirmed Iterative Reconstruction Strength Levels based on the Original Data of Low-dose Chest CT to Evaluate Different Types of Small Pulmonary Nodules[J]. CT Theory and Applications, 2021, 30(6): 735-742. DOI: 10.15953/j.1004-4140.2021.30.06.09
Citation: CAO Juntao, CHEN Qiqi, HU Ming, XU Ting, TU Jianchun, ZHANG Huan. A Preliminary Analysis of Using the Sinogram-affirmed Iterative Reconstruction Strength Levels based on the Original Data of Low-dose Chest CT to Evaluate Different Types of Small Pulmonary Nodules[J]. CT Theory and Applications, 2021, 30(6): 735-742. DOI: 10.15953/j.1004-4140.2021.30.06.09

A Preliminary Analysis of Using the Sinogram-affirmed Iterative Reconstruction Strength Levels based on the Original Data of Low-dose Chest CT to Evaluate Different Types of Small Pulmonary Nodules

More Information
  • Received Date: April 06, 2021
  • Available Online: November 03, 2021
  • Objective: We intend to explore the Corresponding relations between the Sinogram-affirmed iterative reconstruction (SAFIRE) strength levels and the optimized display of different types (solid, partially solid, and pure ground glass) of small pulmonary nodules in low-dose chest CT (LDCT). Materials and methods: We analyzed 105 small pulmonary nodules in 101 patients who underwent LDCT from September 2020 to January 2021 and also met the criteria for small pulmonary nodules. Based on nodule composition, they were divided into the solid nodule Group (n=27), the partially solid nodule group (n=37) and the pure ground glass nodule group (n=41). First we adopted the one-way analysis of variance, Chi-square test or Kruskal-Wallis H test to analyze the general data in groups, then took the filtered back projection algorithm (FBP, B50f) as the reference to compare the difference in objective image quality (including noise value, CT value of small pulmonary nodules, SNR and CNR) and subjective image quality in groups under different SAFIRE modes (I50f and I70f, strength levels 1 to 5 respectively).Results: 1 There was no significant difference in gender, body mass index, and nodule distribution in three groups. The age and length of the nodules in the pure ground-glass nodule group were smaller than those in the solid and partial solid nodule groups; 2 The image noise values in SAFIRE I50f 1-5 and I70f-5 were lower than that in FBP B50f while SAFIRE I50f-5 showed the lowest noise value. There was no significant difference in CT values of small pulmonary nodules in the three groups under different modes, the SNR and CNR of small pulmonary nodules in SAFIRE I50f-5 were higher than those of FBP B50f and other SAFIRE modes; 3 SAFIRE I50f 3~5 of solid and partial solid pulmonary nodule groups obtained higher subjective scores than that of FBP B50f and other SAFIRE modes except I70f-5. SAFIRE I50f-4 of pure ground glass nodule group obtained a higher subjective score than those of FBP B50f and other SAFIRE modes except I50f-3 and I50f-5, and there was no significant difference in the subjective scores in three groups under this mode (P=0.428). Conclusion: SAFIRE I50f-4 performed well and displayed a balanced effect in the objective and subjective evaluation of solid, partial solid and pure ground glass small pulmonary nodules in LDCT. We suggest it can be applied to evaluate different types of small pulmonary nodules in LDCT.
  • [1]
    CHEN W, ZHENG R, BAADE P D, et al. Cancer statistics in China, 2015[J]. CA:A Cancer Journal for Clinicians, 2016, 66(2):115-32.
    [2]
    赫捷, 里霓, 陈万青, 等. 中国肺癌筛查与早诊早治指南(2021, 北京)[J]. 中华肿瘤杂志, 2021, 43(3):243-268.

    DOI:10.3760/cma.j.cn112152-20210119-00060. HE J, LI N, CHEN W Q, et al. China guideline for the screening and early detection of lung cancer(2021, Beijing)[J]. Chinese Journal of Oncology, 2021, 43(3):243-268. DOI:10.3760/cma.j.cn112152-20210119-00060. (in Chinese).
    [3]
    中华医学会呼吸病学分会肺癌学组, 中国肺癌防治联盟专家组. 肺结节诊治中国专家共识(2018年版)[J]. 中华结核和呼吸杂志, 2018, 41(10):763-771.
    [4]
    MACMAHON H, NAIDICH D P, GOO J M, et al. Guidelines for management of incidental pulmonary nodules detected on CT images:From the fleischner society 2017[J]. Radiology, 2017, 284:228-243.
    [5]
    de JONG P A, LEINER T, LAMMERS J W, et al. Can low-dose unenhanced chest CT be used for follow-up of pulmonary nodules?[J]. American Journal of Roentgenology, 2012, 199(4):777-780.
    [6]
    National Pulmonary Screening Trial Research Team, ABERLE D R, ADAMS A M, et al. Reduced pulmonary-cancer mortality with low-dose computed tomographic screening[J]. The New England Journal of Medicine, 2011, 365(5):395-409.
    [7]
    JIN S, ZHANG B, ZHANG L, et al. Pulmonary nodules assessment in ultra-low-dose CT with iterative reconstruction compared to conventional dose CT[J]. Quantitative Imaging in Medicine and Surgery, 2018, 8(5):480-490.
    [8]
    王海燕. SAFIRE迭代重建技术在低剂量胸部CT检查中的临床应用研究[D]. 济南:山东大学, 2014. Wang H Y. Application study of Sinogram-affirmed iterative reconstruction on low dose chest CT[D]. Ji'nan:Shandong University, 2014. (in Chinese).
    [9]
    SWENSEN S J, JETT J R, HARTMAN T E, et al. Pulmonary cancer screening with CT:Mayo Clinic experience[J]. Radiology, 2003, 226(3):756-761.
    [10]
    YANG W, QIAN F, TENG J, et al. Community-based pulmonary cancer screening with low-dose CT in China:Results of the baseline screening[J]. Lung Cancer, 2018, 117:20-26.
    [11]
    HOREWEG N, VAN ROSMALEN J, HEUVELMANS M A, et al. Pulmonary cancer probability in patients with CT-detected pulmonary nodules:A prespecified analysis of data from the NELSON trial of low-dose CT screening[J]. The Lancet Oncology, 2014, 15:1332-1341.
    [12]
    中华医学会放射学分会心胸学组. 低剂量螺旋CT肺癌筛查专家共识[J]. 中华放射学杂志, 2015, (5):328-335.
    [13]
    赵子健, 李若梅, 苏祝平, 等. LDCT平扫联合ASiR算法在新型冠状病毒肺炎检查中的应用价值[J]. 医疗卫生装备, 2020, 41(7):69-72

    , 92. ZHAO Z J, LI R M, SU Z P, et al. Application value of LDCT combined with ASiR algorithm for diagnosing COVID-19[J]. Chinese Medical Equipment Journal, 2020, 41(7):69-72, 92. (in Chinese).
    [14]
    WILLEMINK M J, NOËL P B. The evolution of image reconstruction for CT-from filtered back projection to artificial intelligence[J]. European Radiology, 2019, 29(5):2185-2195.
    [15]
    WANG G, YU H, DE MAN B. An outlook on X-ray CT research and development[J]. Medical physics, 2008, 35(3):1051-1064.
    [16]
    STILLER W. Basics of iterative reconstruction methods in computed tomography:A vendorindependent overview[J]. European Journal of Radiology, 2018, 109:147-154.
    [17]
    AHN H, LEE K H, KIM J, et al. Diameter of the solid component in subsolid nodules on Low-dose unenhanced chest computed tomography:Measurement accuracy for the prediction of invasive component in pulmonary adenocarcinoma[J]. Korean Journal of Radiology, 2018, 19(3):508-515.
    [18]
    张可名, 王小红, 孙世元, 等. SAFIRE迭代重建技术在肺磨玻璃密度结节低剂量高分辨率CT检查中的应用[J]. 中国老年学杂志, 2016, 36(11):2736-2738.
    [19]
    MIRONOVA V, BLASBERG J D. Evaluation of ground glass nodules[J]. Current Opinion in Pulmonary Medicine, 2018, 24(4):350-354.
    [20]
    MILANESE G, SILVA M, FRAUENFELDER T, et al. Comparison of ultra-low dose chest CT scanning protocols for the detection of pulmonary nodules:A phantom study[J]. Tumori Journal, 2019, 105(5):394-403.
    [21]
    朱熹, 夏巍, 周中柱, 等. 低剂量CT不同重建技术对计算机辅助诊断肺结节的影响[J]. 放射学实践, 2019, 34(11):1255-1259.

    ZHU X, XIA W, ZHOU Z Z, et a1. Effect of different reconstruction techniques on computer-aided diagnosis of pulmonary nodules in low-dose CT[J]. Radiology Practice, 2019, 34(11):1255-1259. (in Chinese).
    [22]
    CHRISTE A, HEVERHAGEN J, OZDOBA C, et al. CT dose and image quality in the last three scanner generations[J]. World Journal of Radiology, 2013, 5(11):421-429.
    [23]
    GEYER L L, SCHOEPF U J, MEINEL F G, et al. State of the art:Iterative CT reconstruction techniques[J]. Radiology, 2015, 276(2):339-357.
    [24]
    LAURENT G, VILLANI N, HOSSU G, et al. Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance[J]. European Radiology, 2019, 29(8):4016-4025.
  • Related Articles

    [1]JIANG Nan, YANG Yang, LI Gangfeng, QU Xiaoyan, ZHANG Yabin, CHEN Han, CUI Guangbin. Advances in Dual-energy CT for the Diagnosis of Solitary Pulmonary Nodules[J]. CT Theory and Applications, 2024, 33(6): 733-739. DOI: 10.15953/j.ctta.2024.066
    [2]LIU Yuting, LIU Aishi. Research Progress of Radiomics in the Diagnosis of Pulmonary Nodules[J]. CT Theory and Applications, 2023, 32(4): 573-578. DOI: 10.15953/j.ctta.2022.056
    [3]JIANG Yi, TIAN Kui, SHA Jinlu, QIN Lixin. Application of Energy Spectrum Purification Combined with Iterative Reconstruction Algorithm in Low-dose CT Examination of Patients with Secondary Pulmonary Tuberculosis[J]. CT Theory and Applications, 2022, 31(1): 95-101. DOI: 10.15953/j.1004-4140.2022.31.01.11
    [4]LIU Na, ZHAO Zhengkai, ZOU Jiayu, LI Yi, LIU Jian. Evaluation of Detection and Diagnostic Efficiency of Pulmonary Nodules by Chest CT Based on Artificial Intelligence[J]. CT Theory and Applications, 2021, 30(6): 709-715. DOI: 10.15953/j.1004-4140.2021.30.06.06
    [5]REN Changjuan. The Value of CT Guided Coaxial Needle Biopsy in the Diagnosis of Solitary Pulmonary Nodules[J]. CT Theory and Applications, 2020, 29(3): 361-367. DOI: 10.15953/j.1004-4140.2020.29.03.13
    [6]XIA Zhenying, SUN Jun, WANG Xing, WU Dan, DING Jinli, LI Hongjun. Application of iDose4 Iterative Reconstruction on Low Dose CT Scanning in AIDS Patients with PJP[J]. CT Theory and Applications, 2020, 29(2): 195-202. DOI: 10.15953/j.1004-4140.2020.29.02.10
    [7]YAO Benbo, YU Jianqun. Advance of CT Texture Feature Analysis in Diagnosis of Solitary Pulmonary Nodules[J]. CT Theory and Applications, 2020, 29(1): 111-118. DOI: 10.15953/j.1004-4140.2020.29.01.14
    [8]XIONG Shan, XU Lei, CHENG Jian-min, CHEN Bo, ZHENG Li, DAI Ting-ting, LIU Si-bin, HUANG Yuan-yi. Application of Iterative Reconstruction in Low-dose Chest CT Scans of Preschool Children[J]. CT Theory and Applications, 2017, 26(6): 729-736. DOI: 10.15953/j.1004-4140.2017.26.06.09
    [9]ZHANG Ming-xia, WANG Ren-gui. Preliminary Study of Diagnostic Value of Ultra High Resolution Thin Slice CT on Small Pulmonary Nodules Diameter Less Than 2cm[J]. CT Theory and Applications, 2014, 23(1): 123-130.
    [10]XIANG Zi-yun, SHI Chang-zheng, ZHOU Jie, ZHAN Yong, LUO Liang-ping. Application of Gray-scale Texture Feature in the Diagnosis of Pulmonary Nodules on CT Imaging[J]. CT Theory and Applications, 2013, 22(1): 155-160.
  • Cited by

    Periodical cited type(8)

    1. 王军辉. 低剂量胸部CT扫描诊断肺癌的临床价值研究. 中国城乡企业卫生. 2024(09): 140-143 .
    2. 刘晓静,吴红英,马金强,雷子乔,余建明. 双层探测器光谱CT虚拟平扫在儿童胸部CT增强扫描中的应用. CT理论与应用研究. 2024(06): 709-716 . 本站查看
    3. 朱宏历,徐川,徐君逸. 中医化痰散结化瘀联合审因论治肺小结节的效果. 中国城乡企业卫生. 2023(09): 132-134 .
    4. 罗彩华. 孤立性肺小结节的胸部高分辨CT诊断与病理检查结果对比. 世界复合医学. 2023(05): 95-98 .
    5. 帕丽旦·尼亚孜,伊斯拉木江·吐尔逊,王姗姗. 肺小磨玻璃结节胸腔镜切除术前CT引导下Hook-wire定位的应用价值. 实用临床医药杂志. 2022(15): 36-39+44 .
    6. 张华. 不同剂量128层螺旋CT扫描孤立性肺内结节的诊断价值比较. 实用中西医结合临床. 2022(13): 66-68 .
    7. 贾欣,刘浩岩. 低剂量CT联合迭代重建技术在早期肺癌及肺部结节中的应用. 中外医学研究. 2022(32): 80-84 .
    8. 吴景强,赖发明,邓开盛. 超高分辨率CT对小于3 cm肺孤立性磨玻璃密度结节的诊断价值. 深圳中西医结合杂志. 2022(24): 78-81 .

    Other cited types(0)

Catalog

    Article views (277) PDF downloads (31) Cited by(8)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return