• 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

使用CT到CBCT可变形图像配准(DIR)评估宫颈癌患者外照射放疗的累积剂量分布。

Evaluation of cumulative dose distributions from external beam radiation therapy using CT-to-CBCT deformable image registration (DIR) for cervical cancer patients.

作者信息

Eckrich Carolyn, Lee Brandon, Wang Chunhao, Light Kim, Chino Junzo, Rodrigues Anna, Craciunescu Oana

机构信息

Duke University Medical Center, Department of Radiation Oncology, Durham, North Carolina, USA.

MIM Software, Cleveland, Ohio, USA.

出版信息

J Appl Clin Med Phys. 2025 Jan;26(1):e14538. doi: 10.1002/acm2.14538. Epub 2024 Oct 4.

DOI:10.1002/acm2.14538
PMID:39365744
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11713260/
Abstract

PURPOSE

To investigate dose differences between the planning CT (pCT) and dose calculated on pre-treatment verification CBCTs using DIR and dose summation for cervical cancer patients.

METHODS

Cervical cancer patients treated at our institution with 45 Gy EBRT undergo a pCT and 5 CBCTs, once every five fractions of treatment. A free-form intensity-based DIR in MIM was performed between the pCT and each CBCT using the "Merged CBCT" feature to generate an extended FOV-CBCT (mCBCT). DIR-generated bladder and rectum contours were adjusted by a physician, and dice similarity coefficients (DSC) were calculated. After deformation, the investigated doses were (1) recalculated in Eclipse using original plan parameters (ecD), and (2) deformed from planning dose (pD) using the deformation matrix in MIM (mdD). Dose summation was performed to the first week's mCBCT. Dose distributions were compared for the bladder, rectum, and PTV in terms of percent dose difference, dose volume histograms (DVHs), and gamma analysis between the calculated doses.

RESULTS

For the 20 patients, the mean DSC was 0.68 ± 0.17 for bladder and 0.79 ± 0.09 for rectum. Most patients were within 5% of pD for D2cc (19/20), Dmax (17/20), and Dmean (16/20). All patients demonstrated a percent difference > 5% for bladder V45 due to variations in bladder volume from the pCT. D90 showed fewer differences with 19/20 patients within 2% of pD. Gamma rates between pD and ecD averaged 94% for bladder and 94% for rectum, while pD and mdD exhibited slightly better performance for bladder (93%) and lower for rectum (85%).

CONCLUSION

Using DIR with weekly CBCT images, the MIM deformed dose (mdD) was found to be in close agreement with the Eclipse calculated dose (ecD). The proposed workflow should be used on a case-by-case basis when the weekly CBCT shows marked difference in organs-at-risk from the planning CT.

摘要

目的

研究宫颈癌患者计划CT(pCT)与使用DIR和剂量求和在治疗前验证CBCT上计算的剂量之间的差异。

方法

在我们机构接受45 Gy EBRT治疗的宫颈癌患者进行一次pCT和5次CBCT,每五分次治疗进行一次。使用MIM中基于自由形式强度的DIR,通过“合并CBCT”功能在pCT和每次CBCT之间进行操作,以生成扩展视野CBCT(mCBCT)。由医生调整DIR生成的膀胱和直肠轮廓,并计算骰子相似系数(DSC)。变形后,所研究的剂量为:(1)在Eclipse中使用原始计划参数重新计算(ecD),以及(2)使用MIM中的变形矩阵从计划剂量(pD)变形得到(mdD)。对第一周的mCBCT进行剂量求和。比较膀胱、直肠和PTV的剂量分布,包括剂量百分比差异、剂量体积直方图(DVH)以及计算剂量之间的伽马分析。

结果

对于20例患者,膀胱的平均DSC为0.68±0.17,直肠为0.79±0.09。大多数患者的D2cc(19/20)、Dmax(17/20)和Dmean(16/20)在pD的5%以内。由于膀胱体积与pCT存在差异,所有患者的膀胱V45百分比差异>5%。D90差异较少,19/20的患者在pD的2%以内。pD与ecD之间的伽马通过率膀胱平均为94% , 直肠为94%,而pD与mdD相比,膀胱表现稍好(93%),直肠较低(85%)。

结论

使用DIR和每周的CBCT图像,发现MIM变形剂量(mdD)与Eclipse计算剂量(ecD)密切一致。当每周的CBCT显示危及器官与计划CT有明显差异时,建议的工作流程应逐案使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/8ad54fcb9ae9/ACM2-26-e14538-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/acb3e3af9ec8/ACM2-26-e14538-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/4f7132aabb23/ACM2-26-e14538-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/353455ab1674/ACM2-26-e14538-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/cf47f169fe57/ACM2-26-e14538-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/3fd4676e1585/ACM2-26-e14538-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/7aedc6221d9f/ACM2-26-e14538-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/202df8523bd2/ACM2-26-e14538-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/a65642a3c97c/ACM2-26-e14538-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/5dbaafccac19/ACM2-26-e14538-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/77ceeb26ca3c/ACM2-26-e14538-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/dca7a1168f1e/ACM2-26-e14538-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/8905332a1e2c/ACM2-26-e14538-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/1c3e8b3fc606/ACM2-26-e14538-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/02612febd158/ACM2-26-e14538-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/8ad54fcb9ae9/ACM2-26-e14538-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/acb3e3af9ec8/ACM2-26-e14538-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/4f7132aabb23/ACM2-26-e14538-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/353455ab1674/ACM2-26-e14538-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/cf47f169fe57/ACM2-26-e14538-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/3fd4676e1585/ACM2-26-e14538-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/7aedc6221d9f/ACM2-26-e14538-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/202df8523bd2/ACM2-26-e14538-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/a65642a3c97c/ACM2-26-e14538-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/5dbaafccac19/ACM2-26-e14538-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/77ceeb26ca3c/ACM2-26-e14538-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/dca7a1168f1e/ACM2-26-e14538-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/8905332a1e2c/ACM2-26-e14538-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/1c3e8b3fc606/ACM2-26-e14538-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/02612febd158/ACM2-26-e14538-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89c0/11713260/8ad54fcb9ae9/ACM2-26-e14538-g004.jpg

相似文献

1
Evaluation of cumulative dose distributions from external beam radiation therapy using CT-to-CBCT deformable image registration (DIR) for cervical cancer patients.使用CT到CBCT可变形图像配准(DIR)评估宫颈癌患者外照射放疗的累积剂量分布。
J Appl Clin Med Phys. 2025 Jan;26(1):e14538. doi: 10.1002/acm2.14538. Epub 2024 Oct 4.
2
Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy.基于锥形束 CT 图像的形变图像配准和合成 CT 生成在宫颈癌放疗中对危及器官的剂量学比较。
Radiat Oncol. 2023 Jan 5;18(1):3. doi: 10.1186/s13014-022-02191-3.
3
Evaluation of on-board kV cone beam computed tomography-based dose calculation with deformable image registration using Hounsfield unit modifications.基于 Hounsfield 单位修正的变形图像配准的机载千伏锥形束 CT 剂量计算评估。
Int J Radiat Oncol Biol Phys. 2014 Jun 1;89(2):416-23. doi: 10.1016/j.ijrobp.2014.02.007. Epub 2014 Mar 28.
4
Evaluation of a commercial DIR platform for contour propagation in prostate cancer patients treated with IMRT/VMAT.评价一个商业的 DIR 平台在接受调强放疗/VMAT 治疗的前列腺癌患者中的靶区勾画。
J Appl Clin Med Phys. 2020 Feb;21(2):14-25. doi: 10.1002/acm2.12787.
5
Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation.研究用于头颈部质子治疗的CT到CBCT图像配准,作为每日剂量重新计算的工具。
Med Phys. 2015 Mar;42(3):1354-66. doi: 10.1118/1.4908223.
6
Quantifying the accuracy of deformable image registration for cone-beam computed tomography with a physical phantom.使用物理体模定量评估锥形束 CT 中的形变图像配准精度。
J Appl Clin Med Phys. 2019 Oct;20(10):92-100. doi: 10.1002/acm2.12717. Epub 2019 Sep 21.
7
Usefulness of hybrid deformable image registration algorithms in prostate radiation therapy.混合可变形图像配准算法在前列腺放射治疗中的应用价值。
J Appl Clin Med Phys. 2019 Jan;20(1):229-236. doi: 10.1002/acm2.12515. Epub 2018 Dec 27.
8
Assessing cumulative dose distributions in combined radiotherapy for cervical cancer using deformable image registration with pre-imaging preparations.使用可变形图像配准和成像前准备评估宫颈癌联合放疗中的累积剂量分布。
Radiat Oncol. 2014 Dec 20;9:293. doi: 10.1186/s13014-014-0293-4.
9
Investigation of dosimetric variations of liver radiotherapy using deformable registration of planning CT and cone-beam CT.利用计划CT与锥形束CT的可变形配准研究肝脏放射治疗的剂量学变化
J Appl Clin Med Phys. 2017 Jan;18(1):66-75. doi: 10.1002/acm2.12008. Epub 2016 Dec 5.
10
Evaluation of the geometric and dosimetric accuracies of deformable image registration of targets and critical organs in prostate CBCT-guided adaptive radiotherapy.评估前列腺锥形束 CT 引导自适应放疗中靶区和关键器官的形变图像配准的几何和剂量学准确性。
J Appl Clin Med Phys. 2024 Nov;25(11):e14490. doi: 10.1002/acm2.14490. Epub 2024 Sep 13.

引用本文的文献

1
Single-Center Preliminary Experience Treating Endometrial Cancer Patients with Fiducial Markers.使用基准标记物治疗子宫内膜癌患者的单中心初步经验
Life (Basel). 2025 Aug 1;15(8):1218. doi: 10.3390/life15081218.

本文引用的文献

1
Advances in External Beam Radiation Therapy and Brachytherapy for Cervical Cancer.宫颈癌外照射放疗和近距离放疗的进展。
Clin Oncol (R Coll Radiol). 2021 Sep;33(9):567-578. doi: 10.1016/j.clon.2021.06.012. Epub 2021 Jul 12.
2
Dose Summation Strategies for External Beam Radiation Therapy and Brachytherapy in Gynecologic Malignancy: A Review from the NRG Oncology and NCTN Medical Physics Subcommittees.妇科恶性肿瘤外照射放疗和近距离放疗的剂量叠加策略:NRG 肿瘤学和 NCTN 医学物理小组委员会的综述。
Int J Radiat Oncol Biol Phys. 2021 Nov 15;111(4):999-1010. doi: 10.1016/j.ijrobp.2021.06.019. Epub 2021 Jun 17.
3
Dosimetric impact of variable bladder filling on IMRT planning for locally advanced carcinoma cervix.
可变膀胱充盈对局部晚期宫颈癌调强放疗计划的剂量学影响。
J Egypt Natl Canc Inst. 2020 Jul 31;32(1):31. doi: 10.1186/s43046-020-00033-5.
4
Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.头颈部癌放疗中基于CBCT的剂量计算方法比较:从亨氏单位到密度校准曲线再到深度学习
Med Phys. 2020 Oct;47(10):4683-4693. doi: 10.1002/mp.14387. Epub 2020 Aug 11.
5
Radiation Therapy for Cervical Cancer: Executive Summary of an ASTRO Clinical Practice Guideline.宫颈癌放射治疗:ASTRO 临床实践指南摘要。
Pract Radiat Oncol. 2020 Jul-Aug;10(4):220-234. doi: 10.1016/j.prro.2020.04.002. Epub 2020 May 18.
6
"Dose of the day" based on cone beam computed tomography and deformable image registration for lung cancer radiotherapy.基于锥形束计算机断层扫描和形变图像配准的肺癌放疗日剂量。
J Appl Clin Med Phys. 2020 Jan;21(1):88-94. doi: 10.1002/acm2.12793. Epub 2019 Dec 9.
7
Clinical Outcomes of Volumetric Modulated Arc Therapy Following Intracavitary/Interstitial Brachytherapy in Cervical Cancer: A Single Institution Retrospective Experience.宫颈癌腔内/组织间近距离放疗后容积调强弧形放疗的临床结果:单机构回顾性经验
Front Oncol. 2019 Aug 16;9:760. doi: 10.3389/fonc.2019.00760. eCollection 2019.
8
Deformable Registration for Dose Accumulation.用于剂量累加的可变形配准。
Semin Radiat Oncol. 2019 Jul;29(3):198-208. doi: 10.1016/j.semradonc.2019.02.002.
9
An evaluation of techniques for dose calculation on cone beam computed tomography.锥形束计算机断层扫描剂量计算技术的评估
Br J Radiol. 2019 Apr;92(1096):20180383. doi: 10.1259/bjr.20180383. Epub 2019 Feb 26.
10
Practical quantification of image registration accuracy following the AAPM TG-132 report framework.按照美国医学物理学家协会(AAPM)TG-132报告框架对图像配准精度进行实际量化。
J Appl Clin Med Phys. 2018 Jul;19(4):125-133. doi: 10.1002/acm2.12348. Epub 2018 Jun 7.