Siemens Healthineers Unveils Industry-First Ultra-High Gradient MRI Scanner at CIIE, Enabling Precise Navigation for Brain-Computer Interfaces

Deep News11-07

At the 9th China International Import Expo, Siemens Healthineers presented nearly 20 innovative products, cutting-edge disease solutions, and achievements in ecosystem collaboration and value co-creation.

The company showcased its mesoscopic MRI system, MAGNETOM Cima.X, which achieves micron-level ultra-high-resolution imaging through its 200/200 ultra-strong gradient, precisely and delicately capturing microscopic structural details within tissues. This opens new possibilities for clinical research and applications in frontier fields such as brain-computer interfaces, neurodegenerative disease research, precision tumor staging, and myocardial fiber visualization.

Sun Jiayin from Siemens Healthineers' MRI division told reporters that the device, with its ultra-high gradient characteristics, is "particularly suited for ultra-high-resolution imaging." He further explained that this ultra-high resolution applies "not only to anatomical imaging but also to functional and metabolic levels; not only to spatial resolution but also to temporal resolution," thereby enhancing imaging capabilities across different dimensions.

Regarding the device's integration with brain-computer interfaces, Sun Jiayin stated that its core value lies in "being able to very precisely locate brain regions, especially the activation of functional brain areas, which can be displayed with great precision, thereby helping brain-computer interface implants find suitable positions." He used a vivid analogy: "So it is like a map, or like a compass, helping brain-computer interfaces more accurately find the position where they should be placed."

When discussing what specific problems the device can solve for doctors and patients, Sun Jiayin outlined three stages based on brain-computer interface application scenarios: determining the placement location before surgery, navigating and positioning during surgery, and evaluating after surgery whether the position has shifted and how neurological function has improved. He said, "Before brain-computer interface surgery, there is a need to evaluate the patient's brain function, including neurological function. This machine can perform this kind of assessment and diagnosis very well. After placement, beyond whether the brain-computer interface chip itself has been well positioned, there is also a need to evaluate how the patient's nervous system function has improved across various aspects, and this improvement also requires relatively precise imaging-based evaluation."

In Sun Jiayin's view, brain-computer interfaces are "not as far from daily life as one might imagine." He noted that in a narrow sense, this refers to the invasive brain-computer interfaces pioneered by Musk's Neuralink, but in reality there are many broad-sense brain-computer interfaces that actually fit the definition of brain-computer systems. "In fact, broad-sense brain-computer interfaces have already been applied in daily life, such as transcranial magnetic and transcranial electrical stimulation devices used for post-stroke rehabilitation. With just a slight upgrade, they could become broad-sense brain-computer interfaces." He also mentioned, "Currently, invasive brain-computer interface technology has entered early clinical trials at hospitals including Xuanwu Hospital and Tiantan Hospital in Beijing, and Zhongshan Hospital and Huashan Hospital in Shanghai, and has already helped some patients with conditions such as paralysis, aphasia, and behavioral disorders after stroke to improve their living conditions. In the treatment and intervention of psychiatric disorders such as depression and schizophrenia, it has also begun to be applied in treatment processes."

"So from an industry perspective, I remain fairly optimistic about this matter," Sun Jiayin said. "I think it won't be too long before it truly begins to make people aware and starts to affect people's lives. In the next one to three years, we may see many real-world applications in this area."

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