Effects of breast structure on high-intensity focused ultrasound focal error

Abstract

BackgroundThe development of imaging technologies and breast cancer screening allowed early detection of breast cancers. High-intensity focused ultrasound (HIFU) is a non-invasive cancer treatment, but the success of HIFU ablation was depending on the system type, imaging technique, ablation protocol, and patient selection. Therefore, we aimed to determine the relationship between breast tissue structure and focal error during breast cancer HIFU treatment.MethodsNumerical simulations of the breast cancer HIFU ablation were performed using digital breast phantoms constructed using the magnetic resonance imaging data obtained from 12 patients.ResultsThe focal shapes were distorted despite breast tissue representing soft tissue. Focal errors are caused by the complex distribution of fibroglandular tissue, and they depend on the target position and the arrangement of the transducer. We demonstrated that the focusing ratio increases with the decrease in the local acoustic inhomogeneity, implying that it may be used as an indicator to reduce the HIFU focal error depending on the breast structure.ConclusionsThe obtained results demonstrated that the focal error observed during the breast cancer HIFU treatment is highly dependent on the structure of fibroglandular tissue. The optimal arrangement of the transducer to the target can be obtained by minimizing the local acoustic inhomogeneity before the breast cancer HIFU treatment.

ESHO benchmarks for computational modeling and optimization in hyperthermia therapy

“…The provided benchmark makes no use of physical or electronic focus scanning and instead predicts the acoustic exposure and induced heating from a spherical transducer (geometric radius: 10 cm, aperture angle: 73.7 deg (10 cm), frequency: 1.6 MHz, pressure at the source: 16 kPa) placed vertically below the tumor center (assuming lying position), at a distance equal to the transducer curvature radius. Thermal simulations are performed according to Section 2.4 and the acoustic properties from [28] are used (tumor is treated as glandular breast tissue [88]). The shared reference solution has been generated using an FDTD acoustic solver (Sim4Life v5.2.2), a grid resolution of at least a tenth of a wavelength throughout (the provided reference solution used a grid resolution around 0.09 mm and 2.6 Billion voxels), perfectly matched layer boundary conditions, Dirichlet pressure sources, and a run-time of 200 periods.…”

“…The acoustic tissue properties of reference [28] should be used. For breast tumor, glandular breast tissue properties should be used [88]. In the context of HT, spatial scanning is necessary as a result of the high FUS focality to achieve an adequate temperature distributions Thermal simulations Unless the hypthermia therapy is applied in a dynamic fashion (e.g., time-modulated), thermal simulations shall be performed according to Section 2.4, i.e., Apply a steady-state formulation of the Pennes' bioheat equation for temperature optimization Computations are performed using static blood perfusion under heat stress (Table 3).…”

Effects of phase aberration on transabdominal focusing for a large aperture, low f-number histotripsy transducer

“…Simulation has been used extensively to study phase aberration of therapeutic ultrasound in the breast, abdomen, and pelvis (Liu et al 2005, Farrer et al 2016, Suomi et al 2016, Abbas et al 2018, Okita et al 2018, Bobina et al 2021. Simulation permits study of intact human tissues in their natural conformation and thus has some advantages over in vitro study.…”

Performance and accuracy analysis of nonlinear k-Wave simulations using local domain decomposition with an 8-GPU server

“…Large-scale nonlinear ultrasound simulations in heterogeneous media are particularly important for highintensity focused ultrasound (HIFU), for example, to aid with hardware design, patient selection, and treatment planning. 1 However, these are computationally demanding simulations due to the large size of the area of interest compared to the acoustic wavelength. Such simulations can be performed using the MPI version of k-Wave running on traditional CPU-based clusters.…”