• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

一种用于在放射治疗期间跟踪胸部肿瘤位置的患者特异性对应模型。

A Patient-Specific correspondence model to track tumor location in thorax during radiation therapy.

作者信息

Fakhraei Sharareh, Ehler Eric, Sterling David, Chinsoo Cho L, Alaei Parham

机构信息

Department of Radiation Oncology, University of Minnesota, Minneapolis, MN, 55455, USA.

Department of Radiation Oncology, University of Minnesota, Minneapolis, MN, 55455, USA.

出版信息

Phys Med. 2023 Dec;116:103167. doi: 10.1016/j.ejmp.2023.103167. Epub 2023 Nov 15.

DOI:10.1016/j.ejmp.2023.103167
PMID:37972484
Abstract

PURPOSE

We present a patient-specific model to estimate tumor location in the thorax during radiation therapy using chest surface displacement as the surrogate signal.

METHODS

Two types of data are used for model construction: Four-dimensional computed tomography (4D-CT) images of the patient and the displacement of two points on the patient's skin on the thoracic area. Principal component analysis is used to fit the correspondence model. This model incorporates the recorded surrogate signals during radiation delivery as input and delivers the 3D trajectory of the tumor as output. We evaluated the accuracy of the proposed model on a respiratory phantom and five lung cancer patients.

RESULTS

For the respiratory phantom, the location of the center of the sphere during treatment was calculated in three directions: Left-Right (LR), Anterior-Posterior (AP) and, Superior-Inferior (SI). The error of localization was less than 1 mm in the LR and AP directions and less than 2 mm in the SI direction. The location of the tumor center for two of the patients, and the location of the apex of the diaphragm for the other three, was calculated in three directions. For all patients, the localization error in the LR and AP directions was less than 1.1 mm for two fractions and the maximum localization error in the SI direction was 6.4 mm.

CONCLUSIONS

This work presents a feasibility study of utilizing surface displacement data to locate the tumor in the thorax during radiation treatment. Future work will validate the model on a larger patient population.

摘要

目的

我们提出一种针对患者的模型,以利用胸部表面位移作为替代信号来估计放射治疗期间胸部肿瘤的位置。

方法

使用两种类型的数据进行模型构建:患者的四维计算机断层扫描(4D-CT)图像以及患者胸部区域皮肤上两点的位移。主成分分析用于拟合对应模型。该模型将放射治疗期间记录的替代信号作为输入,并输出肿瘤的三维轨迹。我们在呼吸体模和五名肺癌患者身上评估了所提出模型的准确性。

结果

对于呼吸体模,在三个方向上计算了治疗期间球体中心的位置:左右(LR)、前后(AP)和上下(SI)。在LR和AP方向上的定位误差小于1毫米,在SI方向上小于2毫米。计算了两名患者肿瘤中心的位置以及另外三名患者膈肌顶点的位置,均在三个方向上进行。对于所有患者,在LR和AP方向上两个分次的定位误差均小于1.1毫米,在SI方向上的最大定位误差为6.4毫米。

结论

这项工作展示了利用表面位移数据在放射治疗期间定位胸部肿瘤的可行性研究。未来的工作将在更大的患者群体中验证该模型。

相似文献

1
A Patient-Specific correspondence model to track tumor location in thorax during radiation therapy.一种用于在放射治疗期间跟踪胸部肿瘤位置的患者特异性对应模型。
Phys Med. 2023 Dec;116:103167. doi: 10.1016/j.ejmp.2023.103167. Epub 2023 Nov 15.
2
A new method for assessing lung tumor motion in radiotherapy using dynamic chest radiography.使用动态胸部 X 光摄影评估放疗中肺肿瘤运动的新方法。
J Appl Clin Med Phys. 2022 Oct;23(10):e13736. doi: 10.1002/acm2.13736. Epub 2022 Aug 5.
3
A 4D global respiratory motion model of the thorax based on CT images: A proof of concept.基于 CT 图像的胸部 4D 全局呼吸运动模型:概念验证。
Med Phys. 2018 Jul;45(7):3043-3051. doi: 10.1002/mp.12982. Epub 2018 Jun 3.
4
Real-time direct diaphragm tracking using kV imaging on a standard linear accelerator.使用标准直线加速器的千伏成像进行实时直接膈膜跟踪。
Med Phys. 2019 Oct;46(10):4481-4489. doi: 10.1002/mp.13738. Epub 2019 Aug 13.
5
Evaluation of the four-dimensional motion of lung tumors during end-exhalation breath-hold conditions using volumetric cine computed tomography images.使用容积电影 CT 图像评价肺肿瘤在呼气末屏气状态下的四维运动。
Radiother Oncol. 2023 May;182:109573. doi: 10.1016/j.radonc.2023.109573. Epub 2023 Feb 21.
6
Measurement of intra-fraction displacement of the mediastinal metastatic lymph nodes using four-dimensional CT in non-small cell lung cancer.使用 4DCT 测量非小细胞肺癌纵隔转移性淋巴结的分次内位移。
Korean J Radiol. 2012 Jul-Aug;13(4):417-24. doi: 10.3348/kjr.2012.13.4.417. Epub 2012 Jun 18.
7
Systematic evaluation of lung tumor motion using four-dimensional computed tomography.使用四维计算机断层扫描对肺肿瘤运动进行系统评估。
Acta Oncol. 2017 Apr;56(4):525-530. doi: 10.1080/0284186X.2016.1274049. Epub 2017 Jan 11.
8
Comparison of setup error using different reference images: a phantom and lung cancer patients study.使用不同参考图像的摆位误差比较:模体与肺癌患者研究
Med Dosim. 2012 Spring;37(1):47-52. doi: 10.1016/j.meddos.2011.01.001. Epub 2011 Jul 8.
9
Four-dimensional computed tomography prediction of inter- and intrafractional upper gastrointestinal tumor motion during fractionated stereotactic body radiation therapy.分次立体定向体部放射治疗期间上消化道肿瘤分次间及分次内运动的四维计算机断层扫描预测
Pract Radiat Oncol. 2016 May-Jun;6(3):176-182. doi: 10.1016/j.prro.2015.10.006. Epub 2015 Oct 22.
10
On the evaluation of mobile target trajectory between four-dimensional computer tomography and four-dimensional cone-beam computer tomography.在四维计算机断层扫描和四维锥形束计算机断层扫描中对移动目标轨迹的评估。
J Appl Clin Med Phys. 2021 Jul;22(7):198-207. doi: 10.1002/acm2.13310. Epub 2021 Jun 3.

引用本文的文献

1
A study on indirect tumor localization using lung phantom during radiation therapy.一项关于在放射治疗期间使用肺部体模进行间接肿瘤定位的研究。
Quant Imaging Med Surg. 2025 Apr 1;15(4):3248-3262. doi: 10.21037/qims-24-1777. Epub 2025 Mar 28.
2
Deep learning-based estimation of respiration-induced deformation from surface motion: A proof-of-concept study on 4D thoracic image synthesis.基于深度学习从表面运动估计呼吸引起的变形:关于四维胸部图像合成的概念验证研究
Med Phys. 2025 Jul;52(7):e17804. doi: 10.1002/mp.17804. Epub 2025 Apr 5.