ISSN 1004-4140
CN 11-3017/P

O-MAR联合迭代重建技术在腰椎内固定术后CT成像中的应用

程天馨, 张永县

程天馨, 张永县. O-MAR联合迭代重建技术在腰椎内固定术后CT成像中的应用[J]. CT理论与应用研究(中英文), 2025, 34(2): 285-293. DOI: 10.15953/j.ctta.2024.091.
引用本文: 程天馨, 张永县. O-MAR联合迭代重建技术在腰椎内固定术后CT成像中的应用[J]. CT理论与应用研究(中英文), 2025, 34(2): 285-293. DOI: 10.15953/j.ctta.2024.091.
CHENG T X, ZHANG Y X. Orthopedic Metal Artifact Reduction Combined with Iterative Reconstruction in CT Imaging after Lumbar Internal Fixation[J]. CT Theory and Applications, 2025, 34(2): 285-293. DOI: 10.15953/j.ctta.2024.091. (in Chinese).
Citation: CHENG T X, ZHANG Y X. Orthopedic Metal Artifact Reduction Combined with Iterative Reconstruction in CT Imaging after Lumbar Internal Fixation[J]. CT Theory and Applications, 2025, 34(2): 285-293. DOI: 10.15953/j.ctta.2024.091. (in Chinese).

O-MAR联合迭代重建技术在腰椎内固定术后CT成像中的应用

详细信息
    作者简介:

    程天馨,女,影像医学与核医学专业硕士研究生,主要从事CT新技术和图像后处理方面的研究,E-mail:chengtianxin666@163.com

    通讯作者:

    张永县✉,男,副主任技师,主要从事头颈部CT质量控制和图像后处理研究,E-mail:zhyx20000@163.com

  • 中图分类号: O 242;R 814

Orthopedic Metal Artifact Reduction Combined with Iterative Reconstruction in CT Imaging after Lumbar Internal Fixation

  • 摘要:

    目的:探讨金属伪影抑制技术(O-MAR)联合迭代算法对腰椎内固定术后患者CT图像质量的影响,为术后效果评估提供准确依据。方法:回顾性分析20例行腰椎内固定术后CT检查,使用O-MAR和滤波反投影算法、iDose4重建骨算法图像(iDose4-1~7级)及软组织算法图像(iDose4-1~6级)。重组螺钉显示最佳的横断面和矢状面的骨算法图像及螺钉显示最佳及螺钉区域内椎间盘正中层面的横断面软组织算法图像,测量骨质和肌肉的噪声值(SD)并计算伪影指数(AI)。由两名放射科医师对骨及软组织算法图像的金属伪影抑制和诊断信息显示两方面分别评分。对主客观评价指标进行两组间比较和组间多重比较。结果:骨算法图像:使用O-MAR的图像SD、AI显著低于未使用的图像,不同等级iDose4图像的AI值随等级升高而逐渐降低;O-MAR图像金属伪影主观分显著提高,且iDose4-5~7评分高于FBP及iDose4-1~2;使用O-MAR时诊断信息评分显著提高,iDose4-2~4评分高于FBP及其他迭代等级,且iDose4-3为最佳。软组织算法图像:使用O-MAR的图像SD、AI低于未使用的图像;使用O-MAR的图像金属伪影评分高于未使用,诊断信息评分未使用O-MAR高于使用;对不同迭代等级,无论是否使用O-MAR,图像伪影和诊断信息评分均无差异。结论:建议联合使用O-MAR技术及中间迭代等级iDose4-3重建骨算法图像;软组织算法图像重建时不推荐使用迭代算法,建议同时重建使用和不使用O-MAR的图像以便配合观察。

    Abstract:

    Objective: Exploring the effect of metal artifact reduction (O-MAR) technology combined with iterative algorithms on the computed tomography (CT) image quality of patients after lumbar spine internal fixation surgery, to provide an accurate basis for postoperative effect evaluation. Methods: CT images were collected from 20 patients who underwent lumbar spine internal fixation surgery. Using O-MAR, filtered back projection (FBP), and iDose4 algorithms, bone (iDose4-1~7 levels) and soft tissue images (iDose4-1~6 levels) were reconstructed. Screws were displayed the best in transverse and sagittal bone reconstructed images. The screw area (center plane) of the transverse soft tissue images of the intervertebral disc was also reconstructed. Noise levels in standard deviation (SD) of bone and muscle were measured, and the artifact index (AI) was calculated. Two radiologists separately rated the metal artifact suppression and diagnostic information in the bone and soft tissue images. The subjective and objective evaluation indicators of the two groups were compared, conducting multiple comparisons between groups. Statistical analyses were further performed on subjective and objective evaluation indicators, including O-MAR comparisons and/or multiple comparisons between groups with different levels of iDose4. Results: In the bone images, the SD and AI of images using O-MAR were significantly lower than those without O-MAR, and the AI values of iDose4 images at different levels gradually decreased as the dose level increased. The subjective score of metal artifacts in O-MAR images significantly improved, and the score of iDose4-5~7 was higher than those of filtered back projection (FBP) and iDose4-1~2. With O-MAR, the diagnostic information score significantly improved. The score of iDose4-2~4 was higher than that of FBP and other iterative levels, with iDose4-3 being the best. In soft tissue images, the SD and AI of images using O-MAR were lower than those without O-MAR. The metal artifact score of images using O-MAR was higher than that of images without, but the diagnostic information score of images not using O-MAR was higher than that of images with O-MAR; For different iteration levels, regardless of whether O-MAR was used or not, no difference was observed in image artifacts and diagnostic information scores. Conclusions: We suggest combining O-MAR technology with intermediate iteration level iDose4-3 for bone image reconstruction. The use of iterative algorithms for image reconstruction using soft-tissue algorithms is not recommended. The images with and without O-MAR should be simultaneously reconstructed for comparative observations.

  • 图  1   客观评价感兴趣区和对照区示意图

    注:女,59岁,因腰椎骨折行内固定术。

    Figure  1.   Schematic diagram of objective evaluation

    图  2   使用/不使用O-MAR重建骨算法图像比较(iDose4-3)

    注:男,62岁,因腰椎外伤行内固定术。

    Figure  2.   Comparison of image quality before and after reconstruction using O-MAR

    图  3   使用/不使用O-MAR重建软组织算法图像比较(FBP)

    注:女,56岁,因腰椎滑脱行内固定术。

    Figure  3.   Comparison of soft tissue algorithm images before and after reconstruction using O-MAR

    图  4   使用FBP及不同等级iDose4的O-MAR图像质量比较

    注:男,62岁,因脊柱侧弯行内固定术。(a)~(h)分别为O-MAR技术基础上,使用FBP及迭代算法iDose4-1~7等级重建的骨算法图像。可见由(a)至(h),图像平滑程度增高,锐利度降低。

    Figure  4.   Comparison of O-MAR image quality using FBP and different levels of iDose4

    表  1   使用/不使用O-MAR的图像SD值、AI值比较

    Table  1   Comparison of SD and AI values of images with/without O-MAR

    重建算法 评价指标 骨算法 统计检验 软组织算法 统计检验
    不使用O-MAR 使用O-MAR t P 不使用O-MAR 使用O-MAR Z P
    FBP SD 372.93±95.17 336.37±89.86 10.059 < 0.001 61.65
    (49.75,76.88)
    45.90
    (38.48,50.80)
    −3.920 < 0.001
    AI 364.55±95.95 327.23±90.88 9.939 59.37
    (46.22,70.46)
    40.64
    (31.65,46.43)
    −3.920
    iDose4-1 SD 335.27±85.25 301.74±80.54 9.103 < 0.001 54.10
    (45.38,70.98)
    40.05
    (35.60,46.78)
    −3.920 < 0.001
    AI 327.52±85.81 292.91±81.49 9.066 51.59
    (42.21,61.82)
    35.45
    (28.78,42.47)
    −3.920
    iDose4-2 SD 314.66±79.66 282.22±75.32 8.157 < 0.001 50.45
    (43.20,66.65)
    37.75
    (33.45,44.53)
    −3.921 < 0.001
    AI 307.26±80.20 273.72±76.22 8.157 48.05
    (40.18,58.50)
    32.24
    (27.19,39.86)
    −3.920
    iDose4-3 SD 293.10±73.82 262.18±69.79 7.628 < 0.001 46.75
    (40.73,62.08)
    34.85
    (30.88,42.28)
    −3.920 < 0.001
    AI 286.09±74.37 254.07±70.66 7.598 44.22
    (37.72,55.54)
    29.84
    (25.23,37.15)
    −3.920
    iDose4-4 SD 268.78±67.41 239.97±63.74 6.880 < 0.001 43.40
    (37.75,56.75)
    31.60
    (27.58,39.60)
    −3.920 < 0.001
    AI 262.19±67.91 232.25±64.56 6.904 40.94
    (36.03,48.62)
    27.64
    (22.87,33.97)
    −3.920
    iDose4-5 SD 243.36±60.97 215.43±57.18 5.884 < 0.001 40.10
    (33.55,50.18)
    28.65
    (23.15,35.65)
    −3.920 < 0.001
    AI 237.27±61.49 208.16±57.94 5.932 37.62
    (31.65,43.21)
    25.66
    (19.23,30.09)
    −3.920
    iDose4-6 SD 214.33±53.84 187.84±49.78 5.002 < 0.001 36.95
    (31.20,43.88)
    26.90
    (20.43,31.85)
    −3.920 < 0.001
    AI 208.82±54.36 181.09±50.49 5.075 33.71
    (29.73,39.55)
    22.17
    (16.32,26,54)
    −3.920
    iDose4-7 SD 180.81±46.48 155.63±41.40 4.139 < 0.001
    AI 176.04±47.03 149.52±42.04 4.234
    下载: 导出CSV

    表  2   骨算法评分值

    Table  2   Score of bone algorithm

    金属伪影 诊断信息
    医师1 医师2 医师1 医师2
    算法 使用O-MAR 不使用O-MAR 使用O-MAR 不使用O-MAR 使用O-MAR 不使用O-MAR 使用O-MAR 不使用O-MAR
    FBP 2(2,2) 1(1,1) 2(2,2) 1(1,1) 2(2,2) 1(1,1) 2(2,2) 1(1,1)
    iDose4-1 2(2,2) 1(1,1) 2(2,2) 1(1,1) 2(2,2) 1(1,1) 2(2,2) 1(1,1)
    iDose4-2 2(2,2) 1(1,1) 2(2,2) 1(1,1) 3(2,3) 1(1,1) 3(2,3) 1(1,1)
    iDose4-3 2(2,2) 1(1,1) 2(2,3) 1(1,1) 3(3,3) 1(1,1) 3(3,3) 1(1,1)
    iDose4-4 2(2,3) 1(1,1) 2(2,3) 1(1,1) 3(2,3) 1(1,1) 2(2.25,3) 1(1,1)
    iDose4-5 3(3,3) 1(1,2) 3(3,3) 1(1,2) 2(2,2) 1(1,1.75) 2(2,3) 1(1,2)
    iDose4-6 3(3,3) 2(1,2) 3(3,3) 2(1,2) 2(2,2) 1(1,2) 2(2,2) 1(1,2)
    iDose4-7 3(3,3) 2(1,2) 3(2.25,3) 2(1,2) 2(2,2) 1(1,1) 2(2,2) 1.5(1,2)
    Z −11.318 −11.208 −10.662 −10.008
    P < 0.001 < 0.001 < 0.001 < 0.001
    下载: 导出CSV

    表  3   软组织算法评分值

    Table  3   Score of soft tissue algorithm

    金属伪影 诊断信息
    医师1 医师2 医师1 医师2
    算法 使用O-MAR 不使用O-MAR 使用O-MAR 不使用O-MAR 使用O-MAR 不使用O-MAR 使用O-MAR 不使用O-MAR
    FBP 2(2,2) 1(1,2) 2(2,2) 1(1,2) 2(1,2) 2(2,2) 2(1,2) 2(2,2)
    iDose4-1 2(2,2) 1(1,2) 2(2,2) 1(1,2) 2(1,2) 2(2,2) 2(1,2) 2(2,2)
    iDose4-2 2(2,2) 1(1,2) 2(2,2) 1(1,2) 2(1,2) 2(2,2) 2(1,2) 2(2,2)
    iDose4-3 2(2,2) 1(1,2) 2(2,2) 1(1,2) 2(1,2) 2(2,2) 2(1,2) 2(2,2)
    iDose4-4 2(2,2) 1(1,2) 2(2,2) 1(1,2) 2(1,2) 2(1.25,2) 2(1,2) 2(2,2)
    iDose4-5 2(2,2) 1.5(1,2) 2(2,2) 1.5(1,2) 1(1,2) 1(1,2) 1(1,2) 2(1.25,2)
    iDose4-6 2(2,2) 2(1,2.75) 2(2,2) 2(1,2) 1(1,1) 1(1,1) 1(1,1.75) 2(1,2)
    Z −7.233 −6.794 4.989 6.057
    P < 0.001 < 0.001 < 0.001 < 0.001
    下载: 导出CSV
  • [1] 房加高, 邹月芬, 徐海, 等. O-MAR技术在去除腰椎金属植入物伪影中的应用价值[J]. 海南医学, 2018, 29(10): 1408-1410. DOI: 10.3969/j.issn.1003-6350.2018.10.023.

    FANG J G, ZOU Y F, XU H, et al. Value of O-MAR iterative algorithm in removing metal artifacts of lumbar implants[J]. Hainan Medical Journal, 2018, 29(10): 1408-1410. DOI: 10.3969/j.issn.1003-6350.2018.10.023. (in Chinese).

    [2]

    CHOO H J, LEE S J, KIM D W, et al. Comparison of the quality of various polychromatic and monochromatic dual-energy CT images with or without a metal Artifact reduction algorithm to evaluate total knee arthroplasty[J]. Korean Journal of Radiology, 2021, 22(8): 1341-1351. DOI: 10.3348/kjr.2020.0548.

    [3] 王平, 高玉颖, 卢再鸣, 等. 迭代重组IMR技术和iDose4技术在腹部低剂量CT扫描乏血供肝转移瘤中的图像质量[J]. 中华放射学杂志, 2015, 49(4): 283-287. DOI: 10.3760/cma.j.issn.1005-1201.2015.04.011.

    WANG P, GAO Y Y, LU Z M, et al. Iterative model reconstruction and hybrid iterative reconstruction techniques iDose4 in low-dose abdominal CT: Comparison of image quality in evaluation of hypovascular metastases of liver[J]. Chinese Journal of Radiology, 2015, 49(4): 283-287. DOI: 10.3760/cma.j.issn.1005-1201.2015.04.011. (in Chinese).

    [4]

    CHO Y J, SCHOEPF U J, SILVERMAN J R, et al. Iterative image reconstruction techniques: Cardiothoracic computed tomography applications[J]. Journal of Thoracic Imaging, 2014, 29(4): 198-208. DOI: 10.1097/RTI.0000000000000041.

    [5] 侯阳, 于兵, 郭启勇, 等. 迭代重建对前置门控冠状动脉CT图像质量及辐射剂量的影响[J]. 中华放射学杂志, 2013, 47(4): 305-309. DOI: 10.3760/cma.j.issn.1005-1201.2013.04.004.

    HOU Y, YU B, GUO Q Y, et al. Application of iterative reconstruction in prospective electrocardiography-triggered CT coronary angiography[J]. Chinese Journal of Radiology, 2013, 47(4): 305-309. DOI: 10.3760/cma.j.issn.1005-1201.2013.04.004. (in Chinese).

    [6] 李杰, 袁源, 王春杰, 等. 能谱CT去金属伪影(MAR)技术用于减低单髋关节置换物伪影[J]. 中国医学影像技术, 2021, 37(1): 131-135. DOI: 10.13929/j.issn.1003-3289.2021.01.032.

    LI J, YUAN Y, WANG C J, et al. Energy spectrum CT metal artifacts reduction (MAR) for reducing artifacts of unilateral hip arthroplasty[J]. Chinese Journal of Medical Imaging Technology, 2021, 37(1): 131-135. DOI: 10.13929/j.issn.1003-3289.2021.01.032. (in Chinese).

    [7]

    HU Y, PAN S, ZHAO X, et al. Value and clinical application of orthopedic metal artifact reduction algorithm in CT scans after orthopedic metal implantation[J]. Korean Journal of Radiology, 2017, 18(3): 526-535. DOI: 10.3348/kjr.2017.18.3.526.

    [8]

    GROßE H N, NEUHAUS V, ABDULLAYEV N, et al. Reduction of artifacts caused by orthopedic hardware in the spine in spectral detector CT examinations using virtual monoenergetic image reconstructions and metal-artifact-reduction algorithms[J]. Skeletal Radiology, 2018, 47(2): 195-201. DOI: 10.1007/s00256-017-2776-5.

    [9] 刘丹丹, 崔莹, 赵波, 等. 定位像扫描参数对胸部CT影像质量和辐射剂量影响的模体研究[J]. 中华放射医学与防护杂志, 2021, 41(3): 217-221. DOI: 10.3760/cma.j.issn.0254-5098.2021.03.011.

    LIU D D, CUI Y, ZHAO B, et al. The influence of scout scanning parameters on image quality and radiation dose of chest CT: A phantom study[J]. Chinese Journal of Radiological Medicine and Protection, 2021, 41(3): 217-221. DOI: 10.3760/cma.j.issn.0254-5098.2021.03.011. (in Chinese).

    [10] 李晓莉, 冯卫华, 董诚, 等. CT能谱成像技术减除金属植入物伪影的定量实验研究[J]. 中华放射学杂志, 2011, 45(8): 736-739. DOI: 10.3760/cma.j.issn.1005-1201.2011.08.007.

    LI X L, FENG W H, DONG C, et al. The experimental quantitative study of spectral CT imaging in reducing the metal artifacts[J]. Chinese Journal of Radiology, 2011, 45(8): 736-739. DOI: 10.3760/cma.j.issn.1005-1201.2011.08.007. (in Chinese).

    [11]

    HILGERS G, NUVER T, MINKEN A. The CT number accuracy of a novel commercial metal artifact reduction algorithm for large orthopedic implants[J]. Journal of Applied Clinical Medical Physics, 2014, 15(1): 4597. DOI: 10.1120/jacmp.v15i1.4597.

    [12] 吴志斌, 李剑, 郑敏文, 等. O-MAR技术在减少高浓度造影剂硬化伪影中的应用价值[J]. 中国医疗设备, 2019, 34(6): 9-11. DOI: 10.3969/j.issn.1674-1633.2019.06.003.

    WU Z B, LI J, ZHENG M W, et al. Application of O-MAR technology in reducing the artifacts of high concentration contrast medium[J]. China Medical Devices, 2019, 34(6): 9-11. DOI: 10.3969/j.issn.1674-1633.2019.06.003. (in Chinese).

    [13] 宋殿行, 郭鹏, 王玉琦, 等. O-MAR重组在减少颅内动脉瘤弹簧圈栓塞术后金属伪影的价值[J]. 临床放射学杂志, 2020, 39(3): 592-595. DOI: 10.13437/j.cnki.jcr.2020.03.037.

    SONG D X, GUO P, WANG Y Q, et al. Clinical evaluation of orthopedic metal artifact reduction (O-MAR) in reducing metallic artifacts in CT of intracranial aneurysms after endovascular coil treatment[J]. Journal of Clinical Radiology, 2020, 39(3): 592-595. DOI: 10.13437/j.cnki.jcr.2020.03.037. (in Chinese).

    [14] 王茹, 姜彦, 徐凯, 等. iDose4与O-MAR迭代算法对TACE术后CT成像质量和疗效评估的价值[J]. 中国医学计算机成像杂志, 2016, 22(5): 457-462. DOI: 10.3969/j.issn.1006-5741.2016.05.014.

    WANG R, JIANG Y, XU K, et al. Effect of iDose4 and O-MAR iterative algorithm on imaging quality of CT scan after TACE operation[J]. Chinese Computed Medical Imaging, 2016, 22(5): 457-462. DOI: 10.3969/j.issn.1006-5741.2016.05.014. (in Chinese).

    [15] 袁肖娜, 高知玲, 朱凯, 等. iDose迭代重建算法对上腹部CT图像质量的影响[J]. 实用放射学杂志, 2016, 32(1): 102-106. DOI: 10.3969/j.issn.1002-1671.2016.01.027.

    YUAN X N, GAO Z L, ZHU K, et al. The effect of iDose iterative reconstruction algorithm on the image quality of upper abdomen CT scan[J]. Journal of Practical Radiology, 2016, 32(1): 102-106. DOI: 10.3969/j.issn.1002-1671.2016.01.027. (in Chinese).

    [16]

    JOEMAI R M, GELEIJINS J, VELDKAMP W J. Development and validation of a low dose simulator for computed tomography[J]. European Radiology, 2010, 20(4): 958-966. DOI: 10.1007/s00330-009-1617-x.

    [17]

    NEUHAUS V, GROSSE H N, ZOPFS D, et al. Reducing artifacts from total hip replacements in dual layer detector CT: Combination of virtual monoenergetic images and orthopedic metal artifact reduction[J]. European Journal of Radiology, 2019, 111: 14-20. DOI: 10.1016/j.ejrad.2018.12.008.

    [18]

    AKDENIZ Y, YEGINGIL I, YEGINGIL Z. Effects of metal implants and a metal artifact reduction tool on calculation accuracy of AAA and acuros XB algorithms in small fields[J]. Medical Physics, 2019, 46(11): 5326-5335. DOI: 10.1002/mp.13819.

    [19] 李杰, 孙兴文, 欧阳汉强, 等. 能谱CT去金属伪影技术减低脊柱不同类型植入物伪影的体模研究[J]. 中华放射学杂志, 2021, 55(9): 910-916. DOI: 10.3760/cma.j.cn112149-20200914-01086.

    LI J, SUN X W, OUYANG H Q, et al. The experimental phantom study of spectral CT metal artifact reduction technique in reducing the artifacts of different types of spinal implants[J]. Chinese Journal of Radiology, 2021, 55(9): 910-916. DOI: 10.3760/cma.j.cn112149-20200914-01086. (in Chinese).

    [20]

    SELLES M, KORTE J H, BOELHOUWERS H J, et al. Metal artifact reduction in computed tomography: Is it of benefit in evaluating sacroiliac joint fusion?[J]. European Journal of Radiology, 2022, 148: 110159. DOI: 10.1016/j.ejrad.2022.110159.

    [21] 张青帝, 吴丽卓, 姜晓静, 等. 不同级别iDose4迭代重建技术在冠状动脉CT成像中的应用[J]. 中国实验诊断学, 2016, 20(5): 752-754.

    ZHANG Q D, WU L Z, JIANG X J, et al. Application of different level iDose4 iterative reconstruction technique in coronary computed tomography angiography[J]. Chinese Journal of Laboratory Diagnosis, 2016, 20(5): 752-754. (in Chinese).

    [22]

    BARRETO I, PEPIN E, DAVIS I, et al. Comparison of metal artifact reduction using single-energy CT and dual-energy CT with various metallic implants in cadavers[J]. European Journal of Radiology, 2020, 133: 109357. DOI: 10.1016/j.ejrad.2020.109357.

    [23]

    SUNWOO L, PARK S W, RHIM J H, et al. Metal artifact reduction for orthopedic implants: Brain CT angiography in patients with intracranial metallic implants[J]. Journal of Korean Medical Science, 2018, 33(21): e158. DOI: 10.3346/jkms.2018.33.e158.

图(4)  /  表(3)
计量
  • 文章访问数:  110
  • HTML全文浏览量:  31
  • PDF下载量:  32
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-06-15
  • 修回日期:  2024-08-12
  • 录用日期:  2024-09-03
  • 网络出版日期:  2024-10-29
  • 刊出日期:  2025-03-04

目录

    /

    返回文章
    返回
    x 关闭 永久关闭