MR Temperature Measurements in Fat During MR-Guided HIFU Treatments

描述（由申请人提供）：该项目的目标是克服目前尚未解决的使用磁共振成像（MRI）测量脂肪组织温度变化的问题。热疗法采用微创和非侵入性技术，如射频电流、微波或高强度聚焦超声（HIFU），有可能彻底改变肿瘤消融和药物输送程序。由于这些技术的微创性，需要持续监测能量沉积和温度变化，以确保治疗效果和患者安全。许多研究人员选择在MRI指导下进行这些手术，因为MRI可以提高软组织成像的对比度，消除电离辐射，并且能够测量水基组织的实时温度变化。然而，在脂肪组织中使用MRI进行快速、准确和可靠的温度测量的能力仍然是一个未解决的问题。这一限制是在热能可能沉积在脂肪组织的部位实施非侵入性热疗法的一大障碍。基于水质子共振频率（PRF）温度依赖性的磁共振测温技术已经建立并广泛应用于水基组织，但该方法在脂肪基组织中是无效的。为了测量脂肪的温度变化，研究人员转向了纵向松弛时间T1，这对水基和脂肪基组织都是温度依赖的。不幸的是，在水基组织中，基于T1的温度测量的准确性和稳定性明显低于PRF温度测量。鉴于这些挑战，我们正在采取双管齐下的方法来解决脂肪中的MR温度测量问题。首先，设计MR序列以同时获取PRF和T1信息。这将允许在所有水基组织中进行PRF温度测量，并在所有脂肪组织中进行T1温度测量。其次，为了提高脂肪组织T1温度测量的准确性，热模型的预测将被纳入该过程。该项目将分四个步骤进行。首先，我们将研究T1在各种组织类型中作为温度函数的行为。其次，我们将开发和优化PRF/T1杂交序列。第三，我们开发了非均匀组织的热建模技术。第四，我们将测试和优化MR温度测量与热模型温度预测相结合的方法。

DESCRIPTION (provided by applicant): The goal of this project is to overcome the currently unsolved problem of using magnetic resonance imaging (MRI) to measure temperature changes in fat-based tissues. Thermal therapies that use minimally invasive and non-invasive techniques such as radio frequency currents, microwaves, or high intensity focused ultrasound (HIFU) have the potential to revolutionize tumor ablation and drug delivery procedures. Due to the minimally invasive nature of these techniques, constant monitoring of energy deposition and temperature changes are required to ensure treatment efficacy and patient safety. Many investigators have chosen to perform these procedures under MRI guidance because of the improved contrast in soft tissue imaging, the elimination of ionizing radiation, and the ability to measure real time temperature changes in water-based tissues. However, the ability to use MRI for fast, accurate, and robust temperature measurements in fat-based tissues remains an unsolved problem. This limitation represents a large obstacle to the implementation of non- invasive thermal therapies in sites where thermal energy may be deposited in fatty tissue. MR thermometry techniques based on the temperature dependence of the water proton resonant frequency (PRF) are well established and in wide use for water-based tissues, however the method is ineffective in fat- based tissues. To measure temperature changes in fat, investigators have turned to the longitudinal relaxation time, T1, which is temperature dependent for both water- and fat-based tissues. Unfortunately, T1 based temperature measurements are significantly less accurate and stable than PRF temperature measurements in water-based tissues. In light of these challenges, we are taking a two pronged approach to solving the problem of MR temperature measurements in fat. First, the MR sequence will be designed to simultaneously acquire PRF and T1 information. This will allow PRF temperature measurements to be made in all water-based tissues, and T1 temperature measurements to be made in al fat-based tissues. Second, predictions from a thermal model will be incorporated into the process in order to improve the accuracy of the T1 temperature measurements in fat-based tissues. The project will be carried out in four steps. First, we will study the behavior of T1 as a function of temperature in a variety of tissue types. Second, we will develop and optimize the hybrid PRF/T1 sequence. Third, we develop thermal modeling techniques for inhomogeneous tissues. Fourth, we will test and optimize methods for combining the MR temperature measurements with the thermal model temperature predictions.