Volume 21 Issue 8
Aug.  2023
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Article Navigation >  Chinese Journal of General Practice  > 2023  >  21(8): 1315-1318
ZHANG Mengyu, DUAN Shimiao, WU Ye, GUO Ziwen, LI Wei, JIANG Hao. Study on differences in target delineation methods for lung tumors using on four-dimensional CT[J]. Chinese Journal of General Practice, 2023, 21(8): 1315-1318. doi: 10.16766/j.cnki.issn.1674-4152.003111
Citation: ZHANG Mengyu, DUAN Shimiao, WU Ye, GUO Ziwen, LI Wei, JIANG Hao. Study on differences in target delineation methods for lung tumors using on four-dimensional CT[J]. Chinese Journal of General Practice, 2023, 21(8): 1315-1318. doi: 10.16766/j.cnki.issn.1674-4152.003111
shu

Study on differences in target delineation methods for lung tumors using on four-dimensional CT

doi: 10.16766/j.cnki.issn.1674-4152.003111
  • 1.

    Department of Radiotherapy, the First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui 233004, China

Funds:

 2020b07030008

 BYKY2019077ZD

  • Received Date: 2023-01-11
    Available Online: 2023-09-13
    Abstract
  •   Objective  Based on four dimensional CT (4DCT) images of patients with lung tumors in different parts, the study compares which target delineation method is more efficient.  Methods  A total of 130 patients with lung tumors, who underwent 4DCT simulation scans at the First Affiliated Hospital of Bengbu Medical College from October 2019 to December 2021 were selected. The doctor delineated the gross tumor volume (GTV) targets in 10 phases of 4DCT, and IGTV10 was obtained by fusion. IGTVMIP, IGTVAIP and IGTV2 were obtained based on maximum density projection (MIP), average density projection (AIP) images, 0% and 50% time-phase of 4DCT. The above delineation methods were compared in terms of volume and centroid displacement.  Results  The ratios of IGTVMIP, IGTVAIP and IGTV2 to IGTV10 in the upper lobe group were 1.00, 0.98 and 0.99, respectively (P=0.143, < 0.001, < 0.001). The ratios for the middle and lower lobe groups were 0.99, 0.96 and 0.98, respectively (P=0.603, < 0.001, < 0.001). There was no significant difference in the degree of mutual inclusion between IGTV10 and IGTVMIP in the upper lung lobe group (P>0.05), while there was a significant difference in the degree of mutual inclusion between IGTV10, IGTVAIP and IGTV2 in the upper lung lobe group (all P < 0.05). The degree of mutual inclusion of IGTV10, IGTVMIP, IGTVAIP and IGTV2 in the middle and lower lung lobe group was significantly different (all P < 0.05).  Conclusion  The motion information contained in the 10 time-fused images is significantly greater than that of the AIP images and the 0%+50% fused images, but close to that of the MIP images. The location of the tumor should also be considered when using MIP images to delineate the target area.

     

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    • References(23)
  • [1]
    周珊, 温莹浩, 朱泽文, 等. 三维适形放疗与静态调强放疗治疗局部晚期非小细胞肺癌的临床疗效和剂量学参数及对免疫功能的影响[J]. 癌症进展, 2020, 18(23): 2421-2423. https://www.cnki.com.cn/Article/CJFDTOTAL-AZJZ202023012.htm

    ZHOU S, WEN Y H, ZHU Z W, et al. Efficacy, dosimetric parameters and effect on immune function of 3-dimensional conformal radiatherapy and intensity modulated radiotherapy in locally advanced non-small cell lung cancer[J]. Oncology Progress, 2020, 18(23): 2421-2423. https://www.cnki.com.cn/Article/CJFDTOTAL-AZJZ202023012.htm
    [2]
    LI W Q, YE X J, HUANG Y W, et al. An integrated ultrasound imaging and abdominal compression device for respiratory motion management in radiation therapy[J]. Med Phys, 2022, 49(10): 6334-6345. doi: 10.1002/mp.15928
    [3]
    BURTON A, BEVERIDGE S, HARDCASTLE N, et al. Adoption of respiratory motion management in radiation therapy[J]. Phys Imaging in Radiat Oncol, 2022, 24: 21-29. doi: 10.1016/j.phro.2022.09.003
    [4]
    WANG Y, LIU T, CHEN H, et al. Comparison of internal target volumes defined by three-dimensional, four-dimensional, and cone-beam computed tomography images of a motion phantom[J]. Ann Transl Med, 2020, 8(22): 1488. doi: 10.21037/atm-20-6246
    [5]
    REHAILIA BLANCHARD A, DE OLIVEIRA DUARTE S, BAURY M, et al. Use of 4D-CT: main technical aspects and clinical benefits[J]. Cancer Radiother, 2019, 23(4): 334-341. doi: 10.1016/j.canrad.2018.07.143
    [6]
    KOKSAL C, DONMEZ KESEN N, OKUTAN M, et al. Investigation of approaches for internal target volume definition using 4-dimensional computed tomography in stereotactic body radiotherapy of lung cancer[J]. Med Dosim, 2021, 46(2): 136-142. doi: 10.1016/j.meddos.2020.10.004
    [7]
    吴雅楠, 齐守良, 庞浩文, 等. 基于肺区CT图像最大密度投影与深度卷积网络的慢阻肺识别模型的构建及意义[J]. 中华健康管理学杂志, 2022, 16(7): 457-463. doi: 10.3760/cma.j.cn115624-20220403-00245

    WU Y N, QI S L, PANG H W, et al. COPD identification using maximum intensity projection of lung field CT images and deep convolution neural network[J]. Chinese Journal of Health Management, 2022, 16(7): 457-463. doi: 10.3760/cma.j.cn115624-20220403-00245
    [8]
    PENG J, GONG J, WANG X Y, et al. 4-Dimensional computed tomography analysis of clinical target volume displacement in adjuvant radiation of patients with gastric cancer and its implication on radiotherapy[J]. Oncol Lett, 2019, 17(4): 3641-3648.
    [9]
    王雪, 王玮, 李建彬, 等. 内乳淋巴结清扫术后患者内乳靶区不同勾画方法比较研究[J]. 中华放射肿瘤学杂志, 2021, 30(11): 1136-1141. doi: 10.3760/cma.j.cn113030-20210204-00062

    WANG X, WANG W, LI J B, et al. Comparison of different delineation methods of clinical target volume of internal mammary lymph node for patients after internal mammary lymph node dissection[J]. Chinese Journal of Radiation Oncology, 2021, 30(11): 1136-1141. doi: 10.3760/cma.j.cn113030-20210204-00062
    [10]
    DUMAS M, LAUGEMAN E, SEVAK P, et al. Technical note: comparison of the internal target volume (ITV) contours and dose calculations on 4DCT, average CBCT, and 4DCBCT imaging for lung stereotactic body radiation therapy (SBRT)[J]. J Appl Clin Med Phys, 2020, 21(11): 288-294. doi: 10.1002/acm2.13041
    [11]
    NARDONE V, GIUGLIANO F M, REGINELLI A, et al. 4D CT analysis of organs at risk (OARs) in stereotactic radiotherapy[J]. Radiother Oncol, 2020, 151: 10-14. doi: 10.1016/j.radonc.2020.06.048
    [12]
    顾玉炎, 杨思雨, 沈小英, 等. 中文版厌食/恶液质量表-12在肺癌放疗患者中的应用[J]. 中华全科医学, 2021, 19(9): 1589-1592. doi: 10.16766/j.cnki.issn.1674-4152.002118

    GU Y Y, YANG S Y, SHEN X Y, et al. Verification of Chinese version of anorexia/cachexia subscale-12 in patients who undergo lung cancer radiotherapy[J]. Chinese Journal of General Practice, 2021, 19(9): 1589-1592. doi: 10.16766/j.cnki.issn.1674-4152.002118
    [13]
    RICH B J, SPIELER B O, YANG Y, et al. Erring characteristics of deformable image registration-based auto-propagation for internal target volume in radiotherapy of locally advanced non-small cell lung cancer[J]. Front Oncol, 2022, 12: 929727. DOI: 10.3389/fonc.2022.929727.
    [14]
    ZENG L, WANG X, ZHOU J D, et al. Analysis of the amplitude changes and baseline shifts of respiratory motion using intra-fractional CBCT in liver stereotactic body radiation therapy[J]. Phys Med, 2022, 93: 52-58. doi: 10.1016/j.ejmp.2021.12.007
    [15]
    ZHANG Y L, LI X F, HU L J. Consideration of the target area of radiotherapy for lung cancer with 4DPET[J]. Precision Radiation Oncology, 2021, 5(3): 191-196. doi: 10.1002/pro6.1131
    [16]
    ADAMCZYK M, KONKOL M, MATECKA-NOWAK M, et al. 4DCT-based evaluation of lung tumor motion during the breathing cycle[J]. Neoplasma, 2020, 67(1): 193-202. doi: 10.4149/neo_2019_190309N206
    [17]
    LI F X, ZHANG T T, SUN X, et al. Evaluation of lung tumor target volume in a large sample: target and clinical factors influencing the volume derived from four-dimensional CT and cone beam CT[J]. Front Oncol, 2022, 11: 717984. DOI: 10.3389/fonc.2021.717984.
    [18]
    LI X D, CHEN E L, GUO B N, et al. The impact of respiratory motion and CT pitch on the robustness of radiomics feature extraction in 4DCT lung imaging[J]. Comput Methods Programs Biomed, 2020, 197: 105719. DOI: 10.1016/j.cmpb.2020.105719.
    [19]
    BORM K J, OECHSNER M, WIEGANDT M, et al. Moving targets in 4D-CTs versus MIP and AIP: comparison of patients data to phantom data[J]. BMC Cancer, 2018, 18(1): 760. doi: 10.1186/s12885-018-4647-4
    [20]
    WANG G, ZHU X, ZHANG F, et al. Applied research of a four-dimensional CT localization technique in radiotherapy and treatment planning for early lung cancer[J]. Transl Cancer Res, 2020, 9(11): 7227-7235. doi: 10.21037/tcr-20-2800
    [21]
    宋孟孟, 王运来, 黄祥, 等. 肺部肿瘤基于最大密度投影图像和四维CT勾画的内靶区差异性分析[J]. 中国医学物理学杂志, 2018, 35(2): 135-140. https://www.cnki.com.cn/Article/CJFDTOTAL-YXWZ201802003.htm

    SONG M M, WANG Y L, HUANG X, et al. Differences of internal target areas delineated from maximum intensity projection image versus four-dimensional computed tomography image of lung tumor[J]. Chinese Journal of Medical Physics, 2018, 35(2): 135-140. https://www.cnki.com.cn/Article/CJFDTOTAL-YXWZ201802003.htm
    [22]
    TIBDEWAL A, BUSHRA S, MUMMUDI N, et al. Is maximum intensity projection an optimal approach for internal target volume delineation in lung cancer?[J]. J Med Phys, 2021, 46(2): 59-65. doi: 10.4103/jmp.JMP_65_20
    [23]
    黄玉玲, 潘纯国, 袁星星, 等. 4D-CT在肺转移瘤个体化精准放疗中的研究[J]. 实用癌症杂志, 2021, 36(12): 2007-2010. doi: 10.3969/j.issn.1001-5930.2021.12.026

    HUANG Y L, PAN C G, YUAN X X, et al. Internal Target Volume Determined with 4D-CT in Lung Metastases[J]. The Practical Journal of Cancer, 2021, 36(12): 2007-2010. doi: 10.3969/j.issn.1001-5930.2021.12.026
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