Acoustic Modeling of skull bone for improved transcranial MR-guided focused ultrasound therapy

项目概要/摘要（限30行） 该提案旨在改善患者特异性计算机断层扫描（CT）衍生的建模， 通过比较声学和热模拟与水听器扫描， 原发性震颤（ET）的切除颅骨瓣和临床磁共振测温（MRTI） 丘脑切开术治疗磁共振引导经颅聚焦超声（tMRgFUS）是一种非 用于治疗多种神经系统疾病侵入性治疗方式。tMRgFUS紧密依赖于 聚焦超声波束穿过不均匀的人类头骨。一个根本的挑战是准确地 确定颅骨的声学特性以相位补偿不均匀性。此外，委员会认为， 诸如声速C和衰减α的声学参数可以随着温度的升高而改变， 导致进一步散焦。不准确的声学参数可能导致偏离目标的加热，治疗时间延长 治疗失败的次数。 该项目将通过准确确定人类头骨的超声聚焦， 个体颅骨声学参数。本文介绍了混合角谱（HAS）光束模拟方法， Pennes生物热方程可以通过映射声学和热学来模拟压力场和温升 CT Hounsfield单位这些模拟的结果可以与实验数据进行比较， 确定tFUS声学和热建模的准确性。反过来应用此方法， 优化算法，它擅长于黑箱昂贵的优化问题，将被用来迭代 使用成本函数调整模拟参数以拟合实验数据。目的我将决定关系 骨的声学特性与CT亨氏单位的关系。优化算法将迭代地调整 声学参数映射，使得比较模拟的和测量的传输声学参数的成本函数 压力被最小化。由此产生的最佳声学参数准确地模拟经颅声学 传输目的II将确定在高声功率下治疗效率降低的原因， tMRgFUS。优化算法将迭代地调整声学和热参数以最小化 比较模拟与临床ET丘脑切开术患者的MRI数据的成本函数。 这项工作将通过人类头骨改进声学建模，这是改进的第一步。 经颅聚焦超声治疗根据聚焦超声基金会，tMRgFUS可以 应用于至少34种神经系统疾病。因此，这项工作可能会产生放大效应， 降低神经病学领域的发病率和死亡率。

Project Summary/Abstract (Limit 30 lines) This proposal aims to improve the patient-specific Computed Tomography (CT)-derived modeling of transcranial focused ultrasound by comparing acoustic and thermal simulations to hydrophone scans of excised skull flaps and clinical magnetic resonance thermometry (MRTI) from Essential Tremor (ET) thalamotomy treatments. Magnetic resonance-guided transcranial focused ultrasound (tMRgFUS) is a non- invasive therapeutic modality used to treat a wide variety of neurological disorders. tMRgFUS relies on tightly focusing the ultrasound beam through the inhomogeneous human skull. A fundamental challenge is accurately determining the acoustic properties of the skull to phase-compensate for the inhomogeneities. Furthermore, acoustic parameters such as speed of sound c and attenuation α may change with increased temperature, causing further defocusing. Inaccurate acoustic parameters can result in off-target heating, longer treatment times, and failed treatments. This project will improve the focusing of ultrasound through the human skull by accurately determining individual skull acoustic parameters. The Hybrid Angular Spectrum (HAS) beam simulation method and the Pennes bioheat equation can simulate pressure fields and thermal rises by mapping acoustic and thermal parameters to CT Hounsfield Units. The results of these simulations may be compared to experimental data to determine the accuracy of tFUS acoustic and thermal modeling. Applying this method in reverse, a surrogate optimization algorithm, which excels at black-box expensive optimization problems, will be used to iteratively adjust simulation parameters to fit experimental data using a cost function. Aim I will determine the relationship of the acoustic properties of bone to CT Hounsfield Units. An optimization algorithm will iteratively adjust the acoustic parameter mapping such that a cost function comparing simulated and measured transmitted acoustic pressures is minimized. The resulting optimal acoustic parameters accurately model transcranial acoustic transmission. Aim II will determine the cause of reduced treatment efficiency with high acoustic powers during tMRgFUS. An optimization algorithm will iteratively adjust the acoustic and thermal parameters to minimize a cost function comparing simulation to MRTI data from clinical ET Thalamotomy patients. This work will improve acoustic modeling through the human skull, which is the first step in improving transcranial focused ultrasound therapy. According to the Focused Ultrasound Foundation, tMRgFUS could be applied to at least 34 neurological disorders. Thus, this work could have a magnified effect, significantly reducing morbidity and mortality across the field of neurology.