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Early invasive cervical cancer: tumor delineation by magnetic resonance imaging, computed tomography, and clinical examination, verified by pathologic results, in the ACRIN 6651/GOG 183 Intergroup Study.早期浸润性宫颈癌:在ACRIN 6651/GOG 183协作组研究中,通过磁共振成像、计算机断层扫描和临床检查进行肿瘤勾画,并经病理结果验证。
J Clin Oncol. 2006 Dec 20;24(36):5687-94. doi: 10.1200/JCO.2006.07.4799.
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Automatic contour propagation in cine cardiac magnetic resonance images.电影式心脏磁共振图像中的自动轮廓传播
IEEE Trans Med Imaging. 2006 Nov;25(11):1472-82. doi: 10.1109/TMI.2006.882124.
3
Inter- and intraobserver variability in the evaluation of dynamic breast cancer MRI.动态乳腺癌MRI评估中的观察者间和观察者内变异性。
J Magn Reson Imaging. 2006 Dec;24(6):1316-25. doi: 10.1002/jmri.20768.
4
Interobserver variation in cervical cancer tumor delineation for image-based radiotherapy planning among and within different specialties.不同专业之间及专业内部在基于图像的宫颈癌放疗计划肿瘤勾画中的观察者间差异。
J Appl Clin Med Phys. 2005 Fall;6(4):106-10. doi: 10.1120/jacmp.v6i4.2117. Epub 2005 Nov 21.
5
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Med Image Anal. 2006 Apr;10(2):215-33. doi: 10.1016/j.media.2005.09.002. Epub 2005 Nov 28.
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A knowledge-guided active contour method of segmentation of cerebella on MR images of pediatric patients with medulloblastoma.
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Merging parametric active contours within homogeneous image regions for MRI-based lung segmentation.在基于MRI的肺部分割中,在均匀图像区域内合并参数化活动轮廓。
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On the design of active contours for medical image segmentation. A Scheme for Classification and construction.关于医学图像分割的活动轮廓设计。一种分类与构建方案。
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用于肿瘤轮廓描绘的迭代主动变形方法:跨放射治疗阶段和体积的评估

Iterative active deformational methodology for tumor delineation: Evaluation across radiation treatment stage and volume.

作者信息

Wu D H, Shaffer A D, Thompson D M, Yang Z, Magnotta V A, Alam R, Suri J, Yuh W T C, Mayr N A

机构信息

Department of Radiological Sciences, Oklahoma University Health Science Center, Oklahoma City, Oklahoma 73104, USA.

出版信息

J Magn Reson Imaging. 2008 Nov;28(5):1188-94. doi: 10.1002/jmri.21500.

DOI:10.1002/jmri.21500
PMID:18972365
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2720022/
Abstract

PURPOSE

To introduce, implement, and assess an iterative modification to the active deformational image segmentation method as applied to cervical cancer tumors.

MATERIALS AND METHODS

A comparison by Jaccard similarity (JS) between this active deformational method and manual segmentation was performed on tumors of various sizes across preradiation, 3 weeks postradiation, and 6 weeks postradiation using a General Linear Mixed Model across 121 studies from 52 patients with Stage IIB-IV cervical cancers.

RESULTS

The deformable segmentation method produced promising levels of agreement including JS factors of 0.71+/-0.11 in the preradiation studies. The analysis illustrated a rate of improvement in JS with increasing tumor volume that differed between the preradiation and 6 weeks postradiation stage (P=0.0474). In the large preradiated tumors each additional cm3 of volume was associated with an increase or improvement in JS of 0.0008 (95% confidence interval [CI]: 0.0003, 0.0014). In the smaller postradiation tumors, each additional cm3 of volume was associated with a more robust improvement in JS of 0.0046 (95% CI: 0.0009, 0.0082).

CONCLUSION

Agreement was strongly affected by tumor volume, and its performance was most impacted across volume in the later stages of radiation therapy. The deformation-based segmentation method appears to demonstrate utility for delineating cervical cancer tumors, particularly in the earliest stages of radiation treatment, where agreement is greatest.

摘要

目的

介绍、实施并评估对主动变形图像分割方法进行的迭代修改,该方法应用于宫颈癌肿瘤。

材料与方法

采用通用线性混合模型,对52例IIB-IV期宫颈癌患者的121项研究中的不同大小肿瘤,在放疗前、放疗后3周和放疗后6周,通过杰卡德相似度(JS)比较这种主动变形方法与手动分割的结果。

结果

可变形分割方法产生了令人满意的一致性水平,在放疗前研究中JS系数为0.71±0.11。分析表明,放疗前和放疗后6周阶段,JS随肿瘤体积增加的改善率有所不同(P=0.0474)。在放疗前的大肿瘤中,每增加1cm³体积,JS增加或改善0.0008(95%置信区间[CI]:0.0003,0.0014)。在放疗后的较小肿瘤中,每增加1cm³体积,JS更显著地改善0.0046(95%CI:0.0009,0.0082)。

结论

一致性受肿瘤体积的强烈影响,其性能在放疗后期受体积影响最大。基于变形的分割方法似乎在勾画宫颈癌肿瘤方面具有实用性,特别是在放疗最早阶段,此时一致性最佳。