Adaptive Positioning and Targeting Optimization in Transcranial Focused Ultrasound (tFUS): A Numerical Study

Transcranial focused ultrasound (tFUS) has garnered significant attention owing to its capacity for precise depth penetration and high spatial resolution within tissues. However, the pronounced heterogeneity of the skull presents substantial challenges to precise targeting, limiting optimal therapeutic efficacy. Precise positioning is urgently needed.

A homogeneous spherical model was employed as the attenuation reference. In the skull model, the transducer operating matrix was determined using a radius positioning method, and an acceleration factor was introduced to exclude invalid candidate locations within the matrix. Subsequently, pseudospectral method was applied to compute and identify peak acoustic pressure points, which served as positioning points.

The effect of the stimulation modality perpendicular to the target region, which was widely employed in previous studies, was found to be less than 70% of our effect. The results in both 2D and 3D scenarios exhibited similarities in a homogeneous medium, permitting the prediction of 3D outcomes from 2D data. In a heterogeneous skull model of one patient, the mean attenuation across all parameters (transducer diameter and ultrasound frequency) was 81.92% ± 6.56%, compared with 68.82% ± 7.22% in homogeneous medium. Larger transducers exhibited greater acoustic beam attenuation and increased heat generation. The proposed k-space-based radius positioning (k-RP) optimization framework improved computational efficiency by approximately 40%.

The k-RP framework proposed in this study improves the efficiency of computational resource utilization and enables parameter-driven adaptive probe positioning, thereby overcoming the limitations of traditional empirically based modulation strategies. This framework provides important methodological guidance for neuromodulation research in complex environments.