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Toward precision radiotherapy: Physiological modeling of respiratory motion based on ultra-quality 4D-MRI

Toward precision radiotherapy: Physiological modeling of respiratory motion based on ultra-quality 4D-MRI
迈向精准放疗:基于超高质量 4D-MRI 的呼吸运动生理模型
批准号:
10653082
负责人:
Jing Cai
金额:
$41.67万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-18 至 2024-06-30

项目摘要

项目成果

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中文摘要
翻译
摘要 尽管在过去的十年里,放射治疗取得了许多进展,有效地增强了局部或局部的放射性。 尽管对于许多患者局部区域肿瘤的控制,仍有很大的改进空间。一个令人信服 在当今精确放射治疗的时代,需要进一步拓宽治疗窗口, 通过技术改进,如先进的成像技术, 引导和运动管理。四维(4D)成像和可变形图像配准 是最近许多放射治疗进展背后的两个最重要的工具,但两者都面临着重大的挑战。 随着对精度要求的提高,当前4D成像技术的主要局限性包括 时间/空间分辨率低,图像采集时间长,肿瘤对比度不佳,以及对 不规则呼吸引起的伪影与此同时,目前的聚类技术主要关注形态相似性, 不能对生理变形进行调节,导致在各种应用中产生不切实际的效果。 这些局限性严重阻碍了精确放射治疗的发展。我们的长期目标 是通过开发和临床实施先进的影像技术, 导航和运动管理技术。这个应用程序的总体目标是开发,跨- 施肥,并评估两种技术:(a)超高质量的4D-MRI和(B)基于生理学的运动建模, 用于精确的放射治疗应用。目的1是发展和优化4D-MRI成像技术 以超高的时空分辨率在胸部和腹部进行呼吸运动。目标二是发展一个 用于呼吸运动估计的基于生理学的运动建模方法。目的3是评价超 在患者研究中进行高质量4D-MRI和生理运动建模。目的4是构建生理现实的 4D数字体模用于未来精确放射治疗应用的发展。成功完成 这些目标将产生用于精确放射治疗的强大的图像引导和运动管理工具。等 通过显著提高辐射剂量,这些改进将把精确放射治疗提高到一个全新的水平 整合和打开大门,以生物为基础的治疗适应更有效的个性化 治疗该研究将对放射治疗和医学成像领域产生重大影响。 它将引发一系列新的和现有应用的广泛研究,如4D放射治疗, 放射组学、人体数字体模、基于功能的剂量绘制、自适应计划等。最重要的是,它将 通过提高我们精确提供放射治疗的能力, 并减轻对正常组织的辐射诱导损伤。
英文摘要
ABSTRACT Despite numerous advances in radiotherapy in the past decade, which have effectively enhanced local or locoregional tumor control for many patients, there remains substantial room for improvement. A compelling need in today's era of precision radiotherapy is to further widen the therapeutic window and improve radiation dose conformity to the defined target volume, through technological improvements such as advanced image guidance and motion management. Four-dimensional (4D) imaging and deformable image registration (DIR) are two of the most important tools behind many recent radiotherapy advances, but both are facing significant challenges as the requirement for precision increases. Major limitations of current 4D imaging technology include low temporal/spatial resolution, long image acquisition time, suboptimal tumor contrast, and susceptibility to artifacts caused by irregular breathing. Meanwhile, current DIR techniques focus on morphological similarity but not on the physiological plausibility of the deformation, leading to unrealistic results in various applications. These limitations have significantly hampered the advancement of precision radiotherapy. Our long-term goal is to enhance precision radiotherapy through the development and clinical implementation of advanced image guidance and motion management techniques. The overall objective of this application is to develop, cross-- fertilize, and evaluate two techniques: (a) ultra-quality 4D-MRI and (b) physiologically-based motion modeling, for precision radiotherapy applications. Aim 1 is to develop and optimize a 4D-MRI technique for imaging respiratory motion in the thorax and abdomen at ultra-high spatiotemporal resolution. Aim 2 is to develop a physiologically-based motion modeling method for respiratory motion estimation. Aim 3 is to evaluate ultra- quality 4D-MRI and physiological motion modeling in a patient study. Aim 4 is to construct physiologically realistic 4D digital phantoms for future development of precision radiotherapy applications. Successful completion of these aims will yield powerful image guidance and motion management tools for precision radiotherapy. Such improvements will take precision radiotherapy to a whole new level, by significantly improving radiation dose conformity and opening doors for biological-based treatment adaptation for more effective personalized treatment. The proposed research will have a high impact to the fields of both radiotherapy and medical imaging. It will trigger a wave of extensive studies on a number of new and existing applications such as 4D radiotherapy, radiomics, human digital phantom, function-based dose painting, adaptive planning, etc. Most importantly, it will ultimately improve outcomes for cancer patients by improving our ability to precisely deliver radiation treatment to the target and mitigate radiation-induced injury to normal tissues.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1088/1361-6560/ac232e
发表时间: 2021-10-05
期刊: Physics in medicine and biology
影响因子: 3.5
作者: [Huang B, Xiao H, Liu W, Zhang Y, Wu H, Wang W, Yang Y, Yang Y, Miller GW, Li T, Cai J]
通讯作者: Cai J
DOI: 10.1002/pro6.1167
发表时间: 2022-09
期刊: Precision radiation oncology
影响因子: --
作者: []
通讯作者:
DOI: 10.1016/j.radmp.2020.01.003
发表时间: 2020-03
期刊: Radiation medicine and protection
影响因子: --
作者: [Yang, Zi, Ren, Lei, Yin, Fang-Fang, Liang, Xiao, Cai, Jing]
通讯作者: Cai, Jing
DOI: 10.1002/mp.15542
发表时间: 2022-05
期刊: MEDICAL PHYSICS
影响因子: 3.8
作者: [Xiao, Haonan, Ni, Ruiyan, Zhi, Shaohua, Li, Wen, Liu, Chenyang, Ren, Ge, Teng, Xinzhi, Liu, Weiwei, Wang, Weihu, Zhang, Yibao, Wu, Hao, Lee, Ho-Fun Victor, Cheung, Lai-Yin Andy, Chang, Hing-Chiu Charles, Li, Tian, Cai, Jing]
通讯作者: Cai, Jing
Toward precision radiotherapy: Physiological modeling of respiratory motion based on ultra-quality 4D-MRI
  • 批准号:
    9980333
  • 项目类别:
  • 资助金额:
    $36.49万
  • 财政年份:
    2019
  • 负责人:
    Jing Cai
  • 依托单位:
Toward precision radiotherapy: Physiological modeling of respiratory motion based on ultra-quality 4D-MRI
  • 批准号:
    10204956
  • 项目类别:
  • 资助金额:
    $52.32万
  • 财政年份:
    2019
  • 负责人:
    Jing Cai
  • 依托单位:
Toward precision radiotherapy: Physiological modeling of respiratory motion based on ultra-quality 4D-MRI
  • 批准号:
    10413106
  • 项目类别:
  • 资助金额:
    $43.5万
  • 财政年份:
    2019
  • 负责人:
    Jing Cai
  • 依托单位:
Image-guided Dosimetry for Injectable Brachytherapy based on Elastin-like Polypeptide Nanoparticles
  • 批准号:
    9530607
  • 项目类别:
  • 资助金额:
    $16.53万
  • 财政年份:
    2017
  • 负责人:
    Jing Cai
  • 依托单位:
海外基金