Abstract： Objective To investigate the time efficiency and accuracy of atlas-based auto-segmentation (ABAS) software with different atlas template numbers and layers of computed tomography(CT) scans in delineation of the target tissues of cervical cancer patients receiving radiotherapy. Methods The CT images from 20, 40, 60, 80, 100, and 120 patients with cervical cancer were separately selected as atlas templates for MIM auto-segmentation software, and the CT-based tumor volumes of another 20 patients with cervical cancer were manually contoured by physicians. The quality of contours obtained automatically from the software and manual contouring was compared by one-way analysis of variance (ANOVA), randomized block ANOVA, and least significant difference t test. The impact of atlas template numbers and layers of CT scans on the accuracy and time efficiency of MIM software was analyzed based on the time spent in delineation, dice similarity coefficient, and overlap index. Results Taking manual contouring as the reference, no significant differences were observed in the accuracy and time efficiency of auto-contouring when atlas template numbers ranged from 20 to 120(all P>0.05). The ABAS auto-contouring significantly shortened the time for target contours when the layers of CT scans were less than 65(all P>0.05), but reduced the accuracy of rectal contours (P=0.000), while CT scans with 67 layers achieved the highest accuracy of rectal contours (P=0.037). Conclusions The ABAS software shows an advantage in delineation of the target tissues of cervical cancer patients receiving radiotherapy, and 20 templates are suggested to construct this atlas. The CT scans with 65 layers are recommended for patients when target tissues include the bladder, femur, and spinal cord, and CT scans with 67 layers are recommended for patients when target tissues include the rectum.
Sun Yuchen,Zhang Xiaozhi,Li Yi. Clinical feasibility of atlas-based auto-segmentation software in radiotherapy for cervical cancer[J]. Chinese Journal of Radiation Oncology, 2017, 26(10): 1167-1172.
[1] Kokka F,Bryant A,Brockbank E,et al. Hysterectomy with radiotherapy or chemotherapy or both for women with locally advanced cervical cancer[J].Cochrane Database Syst Rev,2015(4):CD010260.DOI:10.1002/14651858.CD010260.pub2. [2] Young AV,Wortham A,Wernick I,et al. Atlas-based segmentation improves consistency and decreases time required for contouring postoperative endometrial cancer nodal volumes[J].Int J Radiat Oncol Biol Phys,2011,79(3):943-947.DOI:10.1016/j.ijrobp.2010.04.063. [3] Teguh DN,Levendag PC,Voet PWJ,et al. Clinical validation of atlas-based auto-segmentation of multiple target volumes and normal tissue (swallowing/mastication) structures in the head and neck[J].Int J Radiat Oncol Biol Phys,2011,81(4):950-957.DOI:10.1016/j.ijrobp.2010.07.009. [4] Langmack KA,Perry C,Sinstead C,et al. The utility of atlas-assisted segmentation in the male pelvis is dependent on the interobserver agreement of the structures segmented[J].Br J Radiol,2014,87(1043):20140299.DOI:10.1259/bjr.20140299. [5] Gambacorta MA,Valentini C,Dinapoli N,et al. Clinical validation of atlas-based auto-segmentation of pelvic volumes and normal tissue in rectal tumors using auto-segmentation computed system[J].Acta Oncol,2013,52(8):1676-1681.DOI:10.3109/0284186X.2012.754989. [6] Tao CJ,Yi JL,Chen NY,et al. Multi-subject atlas-based auto-segmentation reduces interobserver variation and improves dosimetric parameter consistency for organs at risk in nasopharyngeal carcinoma:a multi-institution clinical study[J].Radiother Oncol,2015,115(3):407-411.DOI:10.1016/j.radonc.2015.05.012. [7] Han X,Hoogeman MS,Levendag PC,et al. Atlas-based auto-segmentation of head and neck CT images[A]//Proceedings of the 11th international conference on medical image computing and computer-assisted intervention-MICCAI 2008[C].Berlin Heidelberg:Springer,2008:434-441.DOI:10.1007/978-3-540-85990-1_52. [8] Sims R,Isambert A,Grégoire V,et al. A pre-clinical assessment of an atlas-based automatic segmentation tool for the head and neck[J].Radiother Oncol,2009,93(3):474-478.DOI:10.1016/j.radonc.2009.08.013. [9] Hwee J,Louie AV,Gaede S,et al. Technology assessment of automated atlas based segmentation in prostate bed contouring[J].Radiat Oncol,2011,6(1):110.DOI:10.1186/1748-717X-6-110. [10] Anders LC,Stieler F,Siebenlist K,et al. Performance of an atlas-based autosegmentation software for delineation of target volumes for radiotherapy of breast and anorectal cancer[J].Radiother Oncol,2012,102(1):68-73.DOI:10.1016/j.radonc.2011.08.043. [11] 杜国波,蒋利华,郭飞,等.ABAS软件自动勾画技术在鼻咽癌调强放疗中的应用研究[J].中华放射肿瘤学杂志,2014,23(1):63-64.DOI:10.3760/cma.j.issn.1004-4221.2014.01.018. Du GB,Jiang LH,Guo F,et al. Application of ABAS software automatic mapping technique in intensity modulated radiotherapy for nasopharyngeal carcinoma[J].Chin J Radiat Oncol,2014,23(1):63-64.DOI:10.3760/cma.j.issn.1004-4221.2014.01.018. [12] 张秀春,胡彩容,陈传本,等.基于参考图像的ABAS软件自动勾画技术在头颈部肿瘤中的应用研究[J].中华放射肿瘤学杂志,2011,20(6):510-512.DOI:10.3760/cma.j.issn.1004-4221.2011.06.018. Zhang XC,Hu CR,Chen CB,et al. Evaluation of atlas-based autosegmentation with ABAS software for head-and-neck cancer[J].Chin J Radiat Oncol,2011,20(6):510-512.DOI:10.3760/cma.j.issn.1004-4221.2011.06.018. [13] 蒋晓芹,段宝风,艾平,等.基于图谱库的自动轮廓勾画软件(ABAS)在鼻咽癌调强放疗中的应用[J].中国医学物理学杂志,2013,30(2):3997-4000,4035.DOI:10.3969/j.issn.1005-202X.2013.02.008. Jiang XQ,Duan BF,Ai P,et al. Clinical evaluation of atlas-based autosegementation (ABAS) in NPC intensity-modulated radiotherapy[J].Chin J Med Phys,2013,30(2):3997-4000,4035.DOI:10.3969/j.issn.1005-202X.2013.02.008. [14] 陈开强,陈文娟,倪晓雷,等.基于图谱库的自动轮廓勾画软件在宫颈癌自适应放疗中的应用[J].中华放射医学与防护杂志,2015,35(2):111-113.DOI:10.3760/cma.j.issn.0254-5098.2015.02.008. Chen KQ,Chen WJ,Ni XL,et al. Systematic evaluation of atlas-based autosegmentation (ABAS) software for adaptive radiation therapy in cervical cancer[J].Chin J Radiol Med Prot,2015,35(2):111-113.DOI:10.3760/cma.j.issn.0254-5098.2015.02.008. [15] 单书灿,邱杰,全红,等.自动勾画软件对鼻咽癌靶区和OAR勾画结果对比分析[J].中国医学装备,2015,12(7):33-36.DOI:10.3969/J.ISSN.1672-8270.2015.07.012. Shan SC,Qiu J,Quan H,et al. Comparison of the two softwares for ABAS in NPC[J].China Med Equip,2015,12(7):33-36.DOI:10.3969/J.ISSN.1672-8270.2015.07.012. [16] 张艺宝,吴昊,李莎,等.临床前验证与几何对比分析基于图谱库的OAR自动勾画[J].中国医学物理学杂志,2015,32(6):761-767.DOI:10.3969/j.issn.1005-202X.2015.06.001. Zhang YB,Wu H,Li S,et al. Pre-clinical verification and geometric comparative analysis of atlas-based automatic delineation for organs at risk[J].Chin J Med Phys,2015,32(6):761-767.DOI:10.3969/j.issn.1005-202X.2015.06.001. [17] Jones D.ICRU report 50-prescribing,recording and reporting photon beam therapy[J].Med Phys,1994, 21(6):833-834. [18] LandbergT. ICRU report 62:prescribing,recording and reporting photon beam therapy (Supplement to ICRU report 50)[J].Oxford J,1999,32. [19] Zijdenbos AP,Dawant BM,Margolin RA,et al. Morphometric analysis of white matter lesions in MR images:method and validation[J].IEEE Trans Med Imag,1994,13(4):716-724.DOI:10.1109/42.363096. [20] La Macchia M,Fellin F,Amichetti M,et al. Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck,prostate and pleural cancer[J].Radiat Oncol,2012,7(1):160.DOI:10.1186/1748-717X-7-160.
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