Personalized dosimetry for liver cancer radioembolization using fluid dynamics simulation

项目摘要/摘要 肝癌是癌症死亡的主要原因之一，在美国和世界各地的发病率都在上升。 ~(90)Y微球放射栓塞术，或选择性内放射治疗(SIRT)，是一种治疗 插入患者肝动脉的导管将放射性90Y微球输送到肝脏。它 越来越多地被用于治疗二线或三线不能切除的肝肿瘤患者，但其一些 提高总体存活率的潜力仍未被挖掘。提高SIRT效率的主要障碍是 治疗计划。它包括根据对肿瘤的估计剂量来选择要注射的90Y活度 以及处于危险中的器官。问题是，剂量计算非常不可靠，不包括 重要参数，如众所周知的不均匀或喷射点。因此，医生们 经常选择非常保守的剂量来限制毒性，而牺牲了肿瘤(S)的剂量，这大大地 降低SIRT疗效。 该项目的目标是为SIRT计划开发准确的患者特定剂量学。我们建议 结合计算流体力学(CFD)的90Y微球三维模拟新方法 分布和90年物理模型预测吸收剂量。中心和新颖的方法是 对每个患者的肝动脉树进行CFD模拟，以达到高准确度和精确度， 因为决定微球分布的解剖特征在不同的 患者群体，并禁止使用仿制药。这种新的基于CFD的剂量测量将是第一个 集成(1)从患者护理标准中提取的肝动脉树的综合工具 血管造影术，(2)在该肝动脉树中进行CFD模拟，以预测和优化微球分布， (3)用90Y物理模型计算吸收剂量。我们的长期目标是开发一种工具 可集成到临床工作流程中，以优化90Y微球的数量和注射点 Sirt计划。为此，我们将追求两个具体目标。(1)开发CFD模型和剂量 使用PIG模型进行计算以进行验证；(2)我们将开发深度学习方法，以同时 从标准护理患者的血管造影中分割肝动脉并进行形态计量研究 对得到的肝动脉树进行识别，找出影响模型的主要参数。 如果成功，该项目将为SIRT产生可靠的、患者特定的剂量测定，提供 综合计算单个病变以及健康肝脏的吸收剂量。这将是 实现高精度的治疗计划，以更好地治疗肿瘤的剂量绘制方法和 最终改善患者的长期预后。

Project Summary/ Abstract Liver cancer is one of the leading causes of cancer deaths with rising incidence in the U.S and worldwide. Yttrium-90 microspheres radioembolization, or Selective Internal Radiation Therapy (SIRT), is a treatment in which a catheter inserted in the patient's hepatic artery delivers radioactive 90Y microspheres to the liver. It is increasingly utilized to treat patients with unresectable liver tumors in second or third line, but some of its potential to improve overall survival is still untapped. The major obstacle in making SIRT more efficient is the treatment planning. It consists in selecting the 90Y activity to inject based on the estimated dose to the tumor and organs-at-risk. The problem is that the dose calculation is highly unreliable and does not include important parameters, such as well-known non-uniformities or the injection point. As a result, physicians often choose very conservative dosage to limit toxicity at the expense of the tumor(s) dose, which drastically reduces SIRT efficacy. The objective of this project is to develop accurate patient-specific dosimetry for SIRT planning. We propose a novel method combining computational fluid dynamics (CFD) to simulate the 90Y microsphere 3D distribution and 90Y physics modeling to predict the absorbed dose. The central and novel approach is to carry out the CFD simulations for each patient's hepatic arterial tree to achieve high accuracy and precision, because anatomical features determining the microsphere distribution present wide variations across the patient population and prohibit the use of generic models. This novel CFD-based dosimetry will be the first comprehensive tool to integrate (1) the hepatic arterial tree extracted from the patient's standard-of-care angiogram, (2) CFD simulation in this hepatic arterial tree to predict and optimize the microsphere distribution, (3) calculation of the absorbed dose with 90Y physics modeling. Our long-term goal is developing a tool that can be integrated in clinical workflow to optimize the quantity and injection point of 90Y microspheres during SIRT planning. To this end, we will pursue two specific aims. (1) We will develop the CFD model and dose calculation using a pig model for validation; (2) we will develop a deep learning approach to simultaneously segment the hepatic artery from the standard-of-care patient angiograms and conduct a morphometric study of the obtained hepatic arterial trees to identify the principal parameters affecting the model. If successful, this project will generate a reliable, patient-specific dosimetry for SIRT providing a comprehensive calculation of the absorbed dose in individual lesions as well as in the healthy liver. This will enable high precision treatment planning to better treat the tumors with a “dose-painting” approach and ultimately improve long-term patient outcome.