Focused ultrasound technology is a noninvasive method that uses ultrasound to treat brain disorders like depression and Alzheimer’s disease by minimizing damage to healthy tissue and reducing complications without the need for surgery. However, its wider use is limited because it struggles to account for the varying shapes of patients’ skulls, which can distort the ultrasound waves in real-time.
A research team led by Hyungmin Kim, PhD, of the Bionics Research Center at the Korea Institute of Science and Technology (KIST) has developed a real-time acoustic simulation technology based on generative artificial intelligence to predict and correct the distortion of the ultrasound focus position caused by the skull in real-time during focused ultrasound therapy. Until now, the clinical applicability of AI simulation models in the field of noninvasive focused ultrasound therapy technology has not been validated.
To predict the location of the invisible acoustic focus, navigation systems based on medical images taken before treatment are currently utilized, which provide information about the relative position of the patient and the ultrasound transducer. However, they are limited by their inability to account for the distortion of ultrasound waves caused by the skull, and while various simulation techniques have been used to compensate for this, they still require significant computational time, making them difficult to apply in actual clinical practice.
The research team developed a real-time focused ultrasound simulation technology through an artificial intelligence model based on a generative adversarial neural network, a deep learning model widely used for image generation in the medical field. The technology reduces the update time of three-dimensional simulation information reflecting changes in ultrasound acoustic waves from 14 seconds to 0.1 second, while showing an average maximum acoustic pressure error of less than 7% and a focal position error of less than 6mm, both of which are within the error range of existing simulation technologies, increasing the possibility of clinical application.
The research team also developed a medical image-based navigation system to verify the performance of the developed technology to rapidly deploy it to real-world clinical practice. The system can provide real-time acoustic simulations at the rate of 5 Hz depending on the position of the ultrasound transducer and succeeded in predicting the position of the ultrasound energy and focus within the skull in real-time during focused ultrasound therapy.
Previously, due to the long calculation time, the ultrasound transducer had to be precisely positioned in a pre-planned location to utilize the simulation results. However, with the newly developed simulation-guided navigation system, it is now possible to adjust the ultrasound focus based on the acoustic simulation results obtained in real-time.
In the future, it is expected to improve the accuracy of focused ultrasound and provide safe treatment for patients by being able to quickly respond to unexpected situations that may occur during the treatment process.
“As the accuracy and safety of focused ultrasound brain disease treatment has been improved through this research, more clinical applications will emerge,” says Hyungmin. “For practical use, we plan to verify the system by diversifying the ultrasound sonication environment, such as multi-array ultrasound transducers.”
