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: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-18 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10653082
• 关键词: 3-Dimensional; 4D Imaging; 4D MRI; Abdomen; Algorithms; Biological; Biomechanics; Breathing; Cancer Patient; Chest; Communities; Data; Development; Dose; Four-dimensional; Future; Goals; Human; Hybrids; Image; Imaging Techniques; Imaging technology; Liver; Lung; Magnetic Resonance Imaging; Malignant Neoplasms; Measurement; Measures; Medical Imaging; Medicine; Methods; Modeling; Modernization; Morphologic artifacts; Morphology; Motion; Normal tissue morphology; Paint; Patients; Phase; Physiological; Predisposition; Process; Prospective Studies; Radiation Dose Unit; Radiation therapy; Research; Resolution; Sampling; Scheme; Techniques; Technology; Therapeutic; Time; Trees; Walking; cancer radiation therapy; clinical implementation; digital; image guided; image registration; improved; improved outcome; multimodality; novel; personalized medicine; physiologic model; public health relevance; radiation mitigation; radiation-induced injury; radiomics; respiratory; respiratory imaging; spatiotemporal; therapy development; tool; tumor

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.

抽象的 尽管过去十年在放疗方面取得了许多进步，这些疗法有效地增强了本地或 许多患者的局部肿瘤控制，仍然有很大的改善空间。引人注目的 在当今的精确放疗时代的需求是进一步扩大治疗窗口并改善辐射 通过技术改进（例如高级图像），剂量符合定义的目标体积 指导和运动管理。四维（4D）成像和可变形图像登记（DIR） 这是许多最近放疗的两种最重要的工具，但两者都面临着重要的 挑战随着精确的要求而增加。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，次优肿瘤对比度以及对 由不规则呼吸引起的伪影。同时，当前的DIR技术集中于形态相似性，但 并非关于变形的生理合理性，导致各种应用中的不切实际结果。 这些局限性严重阻碍了精度放疗的进步。我们的长期目标 是通过开发和临床实施高级图像来增强精度放疗 指导和运动管理技术。该应用程序的总体目的是开发，交叉 - 施肥并评估两种技术：（a）超质量的4D-MRI和（b）基于生理的运动建模， 用于精确放疗应用。 AIM 1是开发和优化4D-MRI成像技术 超高时空分辨率下胸腔和腹部的呼吸运动。目标2是开发一个 基于生理的运动建模方法用于呼吸运动估计。目标3是评估超级 在患者研究中，质量4D-MRI和生理运动建模。目标4是构建生理上现实的 4D数字幻象，用于未来开发精确放疗应用。成功完成 这些目标将产生强大的图像指导和运动管理工具，以进行精确放疗。这样的 通过显着改善辐射剂量，改进将使精确放疗达到一个全新的水平 以生物为基础治疗适应​​的合规性和开门门，以更有效的个性化 治疗。拟议的研究将对放射疗法和医学成像的领域产生高影响。 它将引发一波关于许多新应用和现有应用，例如4D放射疗法的广泛研究， 放射学，人类数字幻影，基于功能的剂量绘画，自适应计划等。最重要的是，它将 最终通过提高我们精确提供辐射治疗的能力来改善癌症患者的预后 到目标并减轻辐射引起的正常组织损伤。

项目成果

MRI super-resolution via realistic downsampling with adversarial learning.

• 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

Improving liver tumor image contrast and synthesizing novel tissue contrasts by adaptive multiparametric MRI fusion.

• DOI: 10.1002/pro6.1167
• 发表时间: 2022-09
• 期刊: Precision radiation oncology

A dual-supervised deformation estimation model (DDEM) for constructing ultra-quality 4D-MRI based on a commercial low-quality 4D-MRI for liver cancer radiation therapy.

• 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

Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study.

• DOI: 10.1016/j.radmp.2020.01.003
• 发表时间: 2020-03
• 期刊: Radiation medicine and protection
• 作者: Yang, Zi;Ren, Lei;Yin, Fang-Fang;Liang, Xiao;Cai, Jing
• 通讯作者: Cai, Jing