MR-ARFI Forward Modeling for Transcranial Ultrasound Targeting
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Solution Overview
Problem
Current systems face challenges in accurately controlling and managing transcranial ultrasound stimulation (TUS) and focused ultrasound (FUS) due to skull attenuation and physiological factors like respiration, which complicate the targeting of deep brain regions and the ability to relate tissue displacement to acoustic intensity.
Innovation Solution
A method and system for estimating tissue mechanical and acoustic properties using MR-ARFI data, converting pressure fields to force, and employing finite element modeling to calculate dynamic tissue displacements, enabling improved control of TUS/FUS processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If transcranial ultrasound stimulation (TUS) or focused ultrasound (FUS) is used to target deep brain regions, then neuromodulation capability is improved, but skull attenuation and focus shifting make precise targeting difficult
Solution Approach 1:
The system uses MR-ARFI imaging to provide real-time feedback on the actual focus location and tissue displacement, which is then fed back to adjust transducer positioning and parameters to achieve the desired targeting accuracy despite skull attenuation
Solution Approach 2:
MR-ARFI imaging serves as an intermediary tool that bridges the gap between transducer control and actual focus location, providing visual feedback that enables precise targeting without requiring direct measurement of the ultrasound focus
2Measurement precision
If MR-ARFI is used to image tissue displacement for localization, then focus localization precision is improved, but respiration and gradient eddy currents obscure the focus
Solution Approach 1:
The system performs preliminary registration of anatomical images with the MR-ARFI displacement maps to establish a reference framework, and uses physiological monitoring to preemptively adjust for respiration and vascular pulsatility effects
Solution Approach 2:
Physiological monitoring provides feedback on respiration and vascular pulsatility, which is used to adjust the MR-ARFI imaging parameters and displacement analysis to compensate for these interfering factors
3Force
If highly focused transducers are used to produce larger displacements, then displacement magnitude is improved, but the ability to relate tissue displacement back to acoustic intensity becomes more difficult
Solution Approach 1:
The system performs preliminary finite element modeling to establish the relationship between acoustic intensity and tissue displacement for the specific transducer and tissue configuration, which is then used to interpret MR-ARFI measurements in terms of acoustic intensity
Solution Approach 2:
Finite element modeling serves as an intermediary that translates between the measurable quantity (tissue displacement from MR-ARFI) and the desired quantity (acoustic intensity), accounting for the complex nonlinear relationship
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the precision of TUS/FUS delivery by accounting for tissue aberrations and physiological factors, allowing for accurate targeting and dosimetry based on acoustic intensity calculations.
Implementation Method 1
the acoustic radiation force (ARF) applied by FUS causes neuromodulation in the brain, and the level and type of neuromodulatory effect changes depending on the pressure of the sound wave
Implementation Method 2
MR imaging gradient pulses, to encode in the MR image tissue displacement caused by the transference of momentum from the ultrasound pulse to the tissue
Data Source
AI summary
Systems and methods are provided for creating a magnetic resonance acoustic radiation force imaging (MR-ARFI) image from simulations or measurements of a pressure field of an ultrasound transducer. The method includes converting simulations or measurements of a pressure field for an ultrasound transducer to force, delivering the force to a finite element model to calculate dynamic tissue displacements in tissue, delivering the dynamic tissue displacement to control operation of an MR-ARFI process.