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

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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.