MIM软件的图像形变配准可靠性研究
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摘要
目的评价MIM软件对CT图像的形变配准精度。方法选取4个金属点及3个印模膏捏制的具有一定形状的物体置于琼脂糖形成的凝胶中作为弹性模体。采用CT对弹性模体形变前后进行扫描重建,然后再分别导入MIM软件中进行图像配准。利用形变配准前后弹性模体内金属点矩心在X、Y、Z轴方向上的平移距离以及印模膏的Dice系数、Hausdorff距离、Jaccard系数对MIM软件CT图像形变配准精度进行评价。结果金属点矩心在X、Y、Z轴方向上的偏移均小于1.1 mm。印模膏的相似度验证中,3个印模膏的Dice系数均在0.9以上,Hausdorff距离均在2.1 mm以内,Jaccard系数均在0.85以上。结论 MIM软件对CT图像的形变配准精度能够满足临床要求,可为多模态图像在放疗计划设计中的应用提供可靠的依据。
Objective To evaluate the image registration accuracy of CT images by MIM software. Methods Four metallic dots and three shaped impression compounds were implanted in an elastic phantom made by agarose. The phantom was scanned and reconstructed using CT before and after deformation. The images were then imported into the MIM software for image registration. The metallic dot centroid distance in X, Y and Z directions between before and after deformation, the Dice coefficient, the Hausdorff distance, and the Jaccard coefficient of the impression compounds were used to evaluate the image deformation registration reliability of MIM software. Results The offsets of the metallic dot centroids were less than 1.1 mm in the X, Y, and Z directions. The Dice coefficients of the three impression compounds were all above 0.9. The Hausdorff distances were all within 2.1 mm. The Jaccard coefficients were all above 0.85. Conclusion The accuracy of deformation registration of CT images by MIM software can meet the clinical requirements, and it can provide a reliable basis for the application of multi-modal images in the design of radiotherapy plans.
Objective To evaluate the image registration accuracy of CT images by MIM software. Methods Four metallic dots and three shaped impression compounds were implanted in an elastic phantom made by agarose. The phantom was scanned and reconstructed using CT before and after deformation. The images were then imported into the MIM software for image registration. The metallic dot centroid distance in X, Y and Z directions between before and after deformation, the Dice coefficient, the Hausdorff distance, and the Jaccard coefficient of the impression compounds were used to evaluate the image deformation registration reliability of MIM software. Results The offsets of the metallic dot centroids were less than 1.1 mm in the X, Y, and Z directions. The Dice coefficients of the three impression compounds were all above 0.9. The Hausdorff distances were all within 2.1 mm. The Jaccard coefficients were all above 0.85. Conclusion The accuracy of deformation registration of CT images by MIM software can meet the clinical requirements, and it can provide a reliable basis for the application of multi-modal images in the design of radiotherapy plans.
引文
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[16]石慧烽,涂文勇,孔月虹,等.颈椎形变配准与剂量叠加M I M软件临床应用可靠性研究[J].中华肿瘤防治杂志,2018,25(5):365-369.
[17]宋恒利,鞠忠建,王金媛,等.MIM软件CT图像自动刚性配准的准确性研究[J].中国医学装备,2016,13(8):17-20.
[2]俞鹏陶,恒陆进,陈士文,等.解剖图像与功能图像配准技术研究进展[J].四川解剖学杂志,2016,24(3):40-41.
[3]龙腾飞,王凡,孔令玲,等.In Room CT与电子射野影像系统在头颈部肿瘤图像引导放射治疗中配准的对比研究[J].安徽医药,2016,(2):279-282.
[4]巩贯忠,王刚,尹勇,等.形变配准技术分析呼吸运动对肝癌患者正常肝脏及其鞍区形态影响[J].中华肿瘤防治杂志,2015,22(1):54-58.
[5]胡逸民.肿瘤放射物理学[M].北京:原子能出版社,2003:328.
[6] Zarepisheh M,Long T,Li N,et al.A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning[J].Med Phy,2014,41(6):061711.
[7] Yu G,Liang Y,Yang G,et al.Accelerated gradient-based free form deformable registration for online adaptive radiotherapy[J].Phy Med Biol,2015,60(7):2765-2783.
[8] Usui K,Ichimaru Y,Okumura Y,et al.Dose calculation with a cone beam CT image in image-guided radiation therapy[J].Radiol Phys Technol,2013,6(1):107-114.
[9] Bonner J A,Harari P M,Giralt J,et al.Radiotherapy plus cetuximab for locoregionaly advanced head and neck cancer:5-year survival data from a phase 3 randomised trial,and relation between cetuximabinduced rash and survival[J].Lancet Oncol,2010,11(1):21-28.
[10]Gleason JF Jr,Kudrimoti M,Van Meter EM,et al.Low-dose fractionated radiation with induction chemotherapy for locally advanced head and neck cancer:5 year results of a prospective phase II trial[J].J Radiat Oncol,2013,2(1):35-42.
[11] Njeh CF.Tumor delineation:the weakest link in the search for accuracy in radiotherapy[J].J Med Phys,2008,33(4):136-140.
[12] Rasch CR,Steenbakkers RJ,Fitton I,et al.Decreased 3D observer variation with matched CT-MRI for target delineation in Nasopharynx cancer[J].Radiat Oncol,2010,5(1):21.
[13]Rasch C,Steenbakkers R,Herk MV.Target definition in prostate,head,and neck[J].Semin Radiat Oncol,2005,15(3):136-145.
[14] Peters LJ,O'Sullivan B,Giralt J,et al.Critical impact of radiotherapy protocol compliance and quality in the treatment of advanced head and neck cancer:results from TROG 02.02[J].J Clin Oncol,2010,28(18):2996-3001.
[15]袁奉金,刘翠英,李洪升.鼻咽癌在线图像引导放疗摆位校正残余误差分析及计划靶区的确定[J].山东医药,2014,54(41):62-64.
[16]石慧烽,涂文勇,孔月虹,等.颈椎形变配准与剂量叠加M I M软件临床应用可靠性研究[J].中华肿瘤防治杂志,2018,25(5):365-369.
[17]宋恒利,鞠忠建,王金媛,等.MIM软件CT图像自动刚性配准的准确性研究[J].中国医学装备,2016,13(8):17-20.