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. 2025 Dec;42(1):2452927.
doi: 10.1080/02656736.2025.2452927. Epub 2025 Jan 22.

Computational predictions of magnetic resonance acoustic radiation force imaging for breast cancer focused ultrasound therapy

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Computational predictions of magnetic resonance acoustic radiation force imaging for breast cancer focused ultrasound therapy

Chloe K Nelson et al. Int J Hyperthermia. 2025 Dec.

Abstract

Purpose: In magnetic resonance-guided focused ultrasound (MRgFUS) breast therapies, the focal location must be characterized to guide successful treatment. Focal characterization is difficult because heterogeneous breast tissues introduce phase aberrations that blur and shift the focus and traditional guidance methods do not work in adipose tissues. The purpose of this work is to evaluate numerical simulations of MRgFUS that predict the focal location. Those simulations are compared to clinical magnetic resonance acoustic radiation force imaging (MR-ARFI) data collected during in vivo treatment of breast tumors.

Methods: The focal location was evaluated before MRgFUS treatment with MR-ARFI in five patients. The hybrid angular spectrum method (HAS) was applied to simulate pressure fields which were converted to forces, then convolved with a 3D Green's function (with time-of-arrival weighting) to produce a simulation of the MR-ARFI tissue displacement.

Results: The focal locations found by the simulations and the MR-ARFI measurements were on average separated by 3.7 mm (SD: 0.9 mm). Characterization of the focal zone spatial distributions had a normalized root mean squared difference of 8.1% (SD: 2.5%). The displacement magnitudes of the simulations underestimated the MR-ARFI measurements by 82% (SD: 5.6%).

Conclusions: The agreement between MR-ARFI measurements and simulations demonstrates that HAS can predict the in vivo focal location in heterogeneous tissues, though accurate patient-specific properties are needed to improve predictions of tissue displacement magnitude. Tools developed in this study could be used to streamline MRgFUS treatment planning and optimization, for biomechanical property estimation, and in developing phase aberration correction techniques.

Keywords: Breast cancer; MR-ARFI; MRgFUS; acoustic modeling; focused ultrasound.

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Conflict of interest statement

Declaration of Interest Statement

Dr. Allison Payne has intellectual property in the MRgFUS technology that was used to acquire the experimental data.

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