Comparison between MR and CT imaging used to correct for skull-induced phase aberrations during transcranial focused ultrasound

Abstract

Transcranial focused ultrasound with the InSightec Exablate system uses thermal ablation for the treatment of movement and mood disorders and blood brain barrier disruption for tumor therapy. The system uses computed tomography (CT) images to calculate phase corrections that account for aberrations caused by the human skull. This work investigates whether magnetic resonance (MR) images can be used as an alternative to CT images to calculate phase corrections. Phase corrections were calculated using the gold standard hydrophone method and the standard of care InSightec ray tracing method. MR binary image mask, MR-simulated-CT (MRsimCT), and CT images of three ex vivo human skulls were supplied as inputs to the InSightec ray tracing method. The degassed ex vivo human skulls were sonicated with a 670 kHz hemispherical phased array transducer (InSightec Exablate 4000). 3D raster scans of the beam profiles were acquired using a hydrophone mounted on a 3-axis positioner system. Focal spots were evaluated using six metrics: pressure at the target, peak pressure, intensity at the target, peak intensity, positioning error, and focal spot volume. Targets at the geometric focus and 5 mm lateral to the geometric focus were investigated. There was no statistical difference between any of the metrics at either target using either MRsimCT or CT for phase aberration correction. As opposed to the MRsimCT, the use of CT images for aberration correction requires registration to the treatment day MR images; CT misregistration within a range of ± 2 degrees of rotation error along three dimensions was shown to reduce focal spot intensity by up to 9.4%. MRsimCT images used for phase aberration correction for the skull produce similar results as CT-based correction, while avoiding both CT to MR registration errors and unnecessary patient exposure to ionizing radiation.

Evaluation of synthetically generated computed tomography for use in transcranial focused ultrasound procedures

“…44 Most recently, Leung et al generated skulls from UTE images and calculated phases from the Insightec system but applied phases in a water bath setup, measuring the pressure field behind a skull using a hydrophone; they reported comparable beam profile results when compared with rCTs. 45 Regarding peak intracranial pressure differences observed between rCT and sCT, the mean difference computed in our study falls within an expected range of variability of 10% that was observed through an intercomparison study across 11 simulation tools. 46 Because the modeled array was large, the grid size necessary to fit all elements would be ðNx; Ny; NzÞ ¼ ð960; 960; 540Þ to maintain >6 PPW in water at 650 kHz and satisfy 3D convergence testing requirements to avoid simulation instabilities.…”

“…5 Similar work has evaluated the skull correction performance capabilities of artificial skulls and applied the phases in an experimental context beyond modeling and simulations. 4,44,45 One study reconstructed a virtual CT from a T1-weighted MR image and compared calculated phases from Insightec's ExAblate system, resulting in an average phase difference between the real and MR-generated CT of <1 radians, and application of the phases was successfully demonstrated in thermal experiments using head phantoms. 4 A study using the same transducer as Wintermark et al compared UTE-derived MR images with rCT images of head phantoms and found no statistical difference between peak temperatures achieved for thermal experiments.…”

BabelBrain: An Open-Source Application for Prospective Modeling of Transcranial Focused Ultrasound for Neuromodulation Applications

“…72(±18)%, followed by the transcranial modeling with 24(±16)% and thermal modeling with 4(±5)%. While some tasks in the domain generation are GPU-accelerated, such as voxelization and median filters, functions for bias correction, coregistration, and upscaling [36], Fry [38], Gimeno [34], Leung [33], Marsac…”

“…A pressure transmission coefficient T S was calculated with T S = √ E L . The values of T S calculated with each of the different mapping approaches were compared against experimental values of sub-MHz pressure transmission (T E ) from literature reports on pressure [18,29,[32][33][34][35][36] and energy [28,37,38] transmission. For the latter, T E was approximated by the square root of the reported energy transmission.…”

“…The colored areas indicate the spread of prediction of T S across all datasets with different SDR values. T E values from the literature are shown by Alkins ∆ [37], Chen[36], Fry[38], Gimeno[34], Leung[33], Marsac…”