Abstract

Transcranial focused ultrasound (FUS) ablation is an emerging incision-less treatment for neurological disorders. The factors affecting FUS treatment efficiency are not well understood. Kranion is open-source software that allows the user to simulate the planning stages of FUS treatment and to "replay" previous treatments for off-line analysis. This study aimed to investigate the relationship between skull parameters and treatment efficiency and to create a metric to estimate temperature rise during FUS. CT images from 28 patients were analyzed to validate the use of Kranion. For stereotactic targets within each patient, individual transducer element incident angles, skull density ratio, and skull thickness measurements were recorded. A penetration metric (the "beam index") was calculated by combining the energy loss from incident angles and the skull thickness. Kranion accurately estimated the patient's skull and treatment parameters. The authors observed significant changes in incident angles with different targets in the brain. Using the beam index as a predictor of temperature rise in a linear-mixed-effects model, they were able to predict the average temperature rise at the focal point during ablation with < 21% error (55°C ± 3.8°C) in 75% of sonications, and with < 44% (55°C ± 7.9°C) in 97% of sonications. This research suggests that the beam index can improve the prediction of temperature rise during FUS. Additional work is required to study the relationship between temperature rise and lesion shape and clinical outcomes.

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