Artificial intelligence: Artificial intelligence reduces obstacles in ultrasonic brain treatment
Sejong: Using ultrasound energy to target specific millimeters of the brain, including deep areas, focused ultrasound technology is a non-invasive therapeutic approach that treats neurological disorders without the need to open the skull.
Because it does not damage surrounding healthy tissue and has minimal side effects such as infections and seizures, it has been used to treat many resistant brain disorders, including depression and Alzheimer’s disease.
Nevertheless, its use has been restricted, as it is challenging to reflect in real time the distortion of ultrasonic waves caused by the different sizes of patients’ skulls.
An acoustic simulation technique based on generative AI has been developed by a research team led by Dr. Kim, Heungmin of the Bionics Research Center of the Korea Institute of Science and Technology (KIST).
This technology can be used to predict and correct the distortion of ultrasound focus position caused by the skull during focused ultrasound therapy in real time. So far, there has been no confirmation of the clinical utility of AI simulation models in the field of non-invasive focused ultrasound therapy technologies.
However, its application is limited so far because it is difficult to reflect the deformability of ultrasound waves generated by different sizes of patients’ skulls in real time.
A research team led by Dr. Kim, Heungmin of the Bionics Research Center of the Korea Institute of Science and Technology (KIST) developed a real-time acoustic simulation technique based on generative AI to predict and correct the distortion of ultrasound focus position. Has Developed. Due to the scalp in real time during focused ultrasound therapy.
So far, the clinical applicability of AI simulation models in the field of non-invasive 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 used, 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 This becomes difficult to implement in actual clinical practice. ,
The research team developed a real-time focused ultrasound simulation technology through an artificial intelligence model based on Generative Adversarial Neural Network (GAN), 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 seconds, while showing an average maximum acoustic pressure error of less than 7 percent and a focal position error of less than 6 mm, Both of which are within the error limits of existing simulation technologies, thereby increasing the possibility of clinical application.
The research team has also developed a medical image-based navigation system to verify the performance of the developed technology so that it can be rapidly deployed in real-world clinical practice.
The system can provide real-time acoustic simulation at a rate of 5 Hz depending on the position of the ultrasound transducer, and has been successful in predicting ultrasound energy and focus position 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 at a pre-planned location in order to use the simulation results.
However, with the newly developed simulation-guided navigation system, it is now possible to adjust the ultrasound focus based on acoustic simulation results obtained in real time.
In the future, this is expected to provide safer treatments for patients by improving the accuracy of focused ultrasound and being able to react quickly to unexpected situations that may occur during the treatment process.
“As the accuracy and safety of focused ultrasound brain disease treatment improves through this research, more clinical applications will emerge,” said Dr. Kim Hyungmin of KIST.
“For practical use, we plan to validate the system by diversifying ultrasound sonication environments such as multi-array ultrasound transducers.”
