Optimization and Evaluation of Anatomical Models of Liver Radiation Response

肝脏辐射反应解剖模型的优化与评估

• 批准号: 10443572
• 负责人: Kristy Brock
• 金额: $ 35.52万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-03 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10443572
• 关键词: Ablation; Anatomic Models; Anatomy; Area; Atrophic; Biomechanics; Chronic; Clinical; Clinical Research; Complex; Confidence Intervals; Data; Development; Diet; Disease; Disease-Free Survival; Dose; Enrollment; Ensure; Evaluation; Fibrosis; Functional Imaging; Funding; Hepatotoxicity; Hypertrophy; Image; Incidence; Investigation; Life Style; Link; Liver; Liver diseases; Liver neoplasms; Local Therapy; Magnetic Resonance Imaging; Malignant neoplasm of liver; Mechanics; Metastatic Neoplasm to the Liver; Methodology; Methods; Modeling; Necrosis; Normal tissue morphology; Oligonucleotides; Organ; Patients; Play; Primary carcinoma of the liver cells; Radiation; Radiation Toxicity; Radiation therapy; Recurrence; Registries; Research Priority; Retreatment; Risk; Role; Site; Sum; Technology; Time; Toxic effect; Translations; Transplantation; Treatment Protocols; Tumor Tissue; Uncertainty; Validation; Variant; Work; base; biomechanical model; convolutional neural network; design; early experience; experience; follow-up; improved; irradiation; liver function; liver transplantation; patient population; patient response; phase III trial; predictive modeling; prospective; radiation effect; radiation response; response; serial imaging; success; therapy design; tool; treatment response; tumor; working group

The full utilization of radiation for liver cancer is limited by uncertainty in the radiation toxicity risk for patients with underlying liver disease and the inability to compute aggregate dose in the re-treatment setting due to large anatomical changes in responses to therapy. The NCI hepatocellular cancer working group has stated that the use of radiation to downstage prior to liver transplant should be a clinical research priority. In this setting, it is essential to induce complete ablation of the macroscopic disease, which has been shown to correlate with increased disease free survival, while maintaining a low toxicity profile. Functional imaging is beginning to play a role in understanding the impact of radiation on liver function, however the translation of image-based assessments have been hampered by the inability to accurately link the serially acquired images indicating response over time with an accurate assessment of the therapy that was delivered. Early experience with dynamic multi-organ anatomical models demonstrated that deformation technologies can improve treatment design, delivery, and evaluation of the accumulated dose in both the tumor and normal tissues. However, it was noted in these investigations that currently available anatomical models were not sufficient to describe complex deformation due the therapeutic response, notably in the liver where hypertrophy is observed in areas receiving minimal dose and fibrosis/necrosis/atrophy occurs in higher dose regions. Currently, there is not a clear understanding of determinants of hypertrophy/atrophy and methods to optimize this effect. We hypothesize that the differential anatomical changes in otherwise normal liver in response to radiation therapy of liver tumors can be described via dose-driven expansions/contractions in biomechanical models. Our preliminary data shows that these initial models can predict, a priori, the induced hypertrophy and fibrosis/necrosis/atrophy rates to within a 95% confidence interval in 80% of the cases. The sensitivity of the models to the optimization parameters indicate that additional refinement of the models can further improve this accuracy. The combination of this dose-driven expansion/contraction component of the model with the overall biomechanics describing stiffness and deformation, can facilitate safe dose-escalation to the tumor either in the definitive setting or as a bridge to transplant, enable quantitative assessment of therapy response during therapy and throughout follow up via deformable dose summation of the treatment received, and allow accurate correlation between longitudinal imaging of functional response and the delivered radiation therapy dose. IMPACT: The successful completion of this work will develop metrics to aid in the safe utilization of radiotherapy for the liver, improve correlation of functional imaging with delivered therapy, and, where necessary, enable the safe treatment of subsequent tumors in the liver, should they arise.

肝癌放射治疗的充分利用受到以下患者辐射毒性风险的不确定性的限制 潜在的肝病和无法计算再治疗环境中的总剂量，因为 治疗反应的解剖学变化。NCI肝细胞癌工作组曾表示， 在肝移植前使用前台辐射应该是临床研究的重点。在这种情况下，它是 对于诱导完全消融宏观疾病是必不可少的，这已被证明与 提高无病存活率，同时保持低毒性。功能成像开始发挥作用 一种了解辐射对肝功能影响的作用，但以影像翻译为主 由于无法准确地将连续获取的图像联系起来，表明 随着时间的推移做出反应，对所提供的治疗进行准确的评估。早期的经验： 动态多器官解剖模型显示变形技术可以改善治疗 肿瘤和正常组织中累积剂量的设计、传递和评估。然而，它是 在这些研究中指出，目前可用的解剖模型不足以描述复杂的 由治疗反应引起的变形，特别是在肝脏，在接受治疗的区域观察到肥大 最小剂量和纤维化/坏死/萎缩发生在高剂量区域。目前，还没有一个明确的 了解肥大/萎缩的决定因素以及优化这种影响的方法。 我们假设，正常肝脏对辐射的反应中的不同解剖变化 在生物力学模型中，肝肿瘤的治疗可以通过剂量驱动的扩张/收缩来描述。我们的 初步数据显示，这些初始模型可以先验地预测诱导的肥厚和 在80%的病例中，纤维化/坏死/萎缩的比率在95%的可信区间内。它的敏感度 模型的优化参数表明，模型的进一步改进可以进一步改善这一点 精确度。该模型的剂量驱动的扩展/收缩组件与总体 描述僵硬和变形的生物力学，可以促进肿瘤的安全剂量升级 确定的环境或作为移植的桥梁，能够在治疗期间对治疗反应进行量化评估 并在整个随访过程中通过可变形的剂量总和接受治疗，并允许准确 功能反应的纵向成像与放射治疗剂量的相关性。 影响：这项工作的成功完成将制定有助于安全使用放射治疗的指标 对于肝脏，提高功能成像与所提供治疗的相关性，并在必要时使 肝脏后续肿瘤的安全治疗，如果它们出现的话。

项目成果

Automated Contouring of Contrast and Noncontrast Computed Tomography Liver Images With Fully Convolutional Networks.

• DOI: 10.1016/j.adro.2020.04.023
• 发表时间: 2021-01
• 期刊: Advances in radiation oncology
• 影响因子: 2.3
• 作者: Anderson BM;Lin EY;Cardenas CE;Gress DA;Erwin WD;Odisio BC;Koay EJ;Brock KK
• 通讯作者: Brock KK

Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement.

多能计算机断层扫描和材料量化：当前的障碍和进步机会。

• DOI: 10.1002/mp.14241
• 发表时间: 2020-08
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: Jacobsen MC;Thrower SL;Ger RB;Leng S;Court LE;Brock KK;Tamm EP;Cressman ENK;Cody DD;Layman RR
• 通讯作者: Layman RR

Simple Python Module for Conversions Between DICOM Images and Radiation Therapy Structures, Masks, and Prediction Arrays.

• DOI: 10.1016/j.prro.2021.02.003
• 发表时间: 2021-05
• 期刊: Practical radiation oncology
• 影响因子: 3.3
• 作者: Anderson BM;Wahid KA;Brock KK
• 通讯作者: Brock KK

A novel use of biomechanical model-based deformable image registration (DIR) for assessing colorectal liver metastases ablation outcomes.

• DOI: 10.1002/mp.15147
• 发表时间: 2021-10
• 期刊: Medical physics
• 影响因子: 3.8