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How do you know how a medical implant will behave before it's manufactured?

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IT'IS has risen to the challenge of modelling the human body's complexity, from tissue anatomy to nervous system physiology. Credit: IT'IS Foundation Skull Bones Anatomy

How do you know how a medical implant will behave before it's manufactured?

Not all technical advances can be safely tested in the field. “The aerospace industry was one of the first to use technical computer-aided models to investigate and optimize aircraft design four decades ago,” says Niels Kuster, director of the Zurich-based Foundation for Research on Information Technologies in Society (IT’IS). “We had the ambitious goal of bringing the same disruptive technology to the field of medicine.”

Modelling tools for medicine are much more complex than those for the aerospace or automotive industries, Kuster explains, as they must simulate not only the physics of a medical device, but also its interactions with human anatomy and the resulting physiological responses.

Recognizing the importance of simulations to the research community, the US National Institutes of Health selected IT’IS to develop its technology to enable collaborative, reproducible and open computational research — to bring these complex simulations to the cloud without sacrificing performance.

IT’IS has two online platforms that provide modelling and simulation tools to researchers and product developers: the open o2S2PARC platform, for collaborative (neuro)sciences; and the commercial life sciences platform Sim4Life. “These platforms cover everything from basic research all the way to translational science and in silico trial methodologies,” says Esra Neufeld, head of Computational Life Sciences at IT’IS.

Neufeld’s group spearheads the development of these platforms. His team also frequently collaborates with researchers working at the forefront of medical technology. Their contributions include improving the stimulation of spinal nerves in paralysed patients to restore mobility, creating new technologies to selectively activate deep brain structures, and assessing the safety of implantable devices.

IT’IS’ experience and expertise has established it as a vital player in a growing network of international collaborators collectively advancing medical physics.

Founded in 1999, IT’IS started by investigating how environmental electromagnetic fields affect humans.

The work required detailed computational models “because electromagnetic absorption depends on anatomical details”, says Kuster. And it soon became clear that such sophisticated models had broader applicability. For instance, companies developing implantable medical devices could use the models to determine whether a patient fitted with their device could safely undergo an MRI scan — where exposure to massive magnetic fields could lead to device-related heating.

IT'IS developed its software into a tool for manufacturers to test their designs in silico — rather than in animal experiments — considering variables such as scanner type, a person’s BMI and posture, and the anatomy of the scanned body part. “It's not just a matter of accelerating development,” Neufeld says. “It's also a matter of improving safety because you cover many more configurations and conditions.”

In 2019, the FDA approved the software as a medical device development tool. Today, numerous manufacturers use it to establish the MRI-compatibility of new products and to gain regulatory approval.

Restoring movement and function in people with spinal injuries is a longstanding project, and showcases how modelling can contribute to all stages of research.

Optimising spine stimulation using personalised modelling to restore lower limb function in paraplegic patients: (top) tissue anatomy from MRI data is reconstructed in Sim4Life to build a subject-specific spinal cord model; (middle) various configurations of electromagnetic pulses delivered to the spinal cord model are simulated in the cloud on o2S2PARC; (bottom) the simulation results are used to determine the best electrode position and excitation for triggering natural movement. Credit: IT'IS Foundation

Today, IT’IS works closely with Grégoire Courtine and Jocelyne Bloch at the Centre for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), whose implanted devices have enabled paralysed people to walk, cycle and swim1.

Much of their successful early proof-of-concept work had used rodents, where researchers directly stimulated nerves innervating the muscles. But size differences between rodents and humans meant the results didn’t scale up, and early translational results were disappointing.

To improve outcomes, Neufeld’s team helped develop a model of human spinal anatomy and function to decipher how the stimulation affected the nervous system.

“The modelling was key to understanding that the target was actually not the spinal cord,” says Neufeld. “It was the spinal roots and the proprioceptive inputs.”

Proprioceptive inputs are signals from musculoskeletal sensors that inform the nervous system about self-movement and body position. Electrical stimulation to the spinal roots therefore suggests ongoing motion, and activates neural circuits that trigger movement patterns2.

The team was also able to account for the large anatomical variability between individuals, such as the differing vertebral levels of neural centres that control complex leg movements. “There is a need to create not only a single reference model, but also personalized models for each subject, especially for designing safer and more effective spinal root stimulators,” Neufeld says.

IT’IS’ tools are also empowering a new research field around a novel form of brain stimulation called temporal interference.

Electrically stimulating a brain region to increase or decrease its activity can ameliorate the symptoms of neurological and psychiatric disorders.

Neurons respond most powerfully to electrical stimulation at frequencies below 150 Hz. However, because fields decay as they pass through tissues, it is not possible to reach deep structures without perturbing overlying ones. Therefore, to selectively target deep brain regions, practitioners typically resort to surgically implanted electrodes, limiting both research and clinical uptake.

Around a decade ago, MIT’s Nir Grossman and Ed Boyden had a breakthrough idea for modulating deep brain structures from outside the skull. Their concept used two sources of high-frequency currents with a small frequency difference (say 10,000 and 10,020 Hz). Such high-frequency stimulation is ineffective at modulating neuronal activity. Where these currents overlap, however, they produce a low-frequency modulation field (in this example, 20 Hz), which brain cells can track. By selecting the location and amount of applied current, it is possible to elicit a neural response only within targeted brain regions.

IT’IS helped refine Grossman and Boyden’s idea. To achieve targeted stimulation, the team needed tooling for high-precision current delivery, as well as detailed anatomical models and tissue property maps, which they built from patient-specific medical imaging data. Working with partners, IT’IS has developed a high-end stimulator and a dedicated personalized planning tool to support temporal interference research.

Two papers published in late 2023 demonstrated selective brain activity modulation in humans using temporal interference. One, targeting the hippocampus3, found that stimulation boosted volunteers’ memories. In the other, stimulating the striatum4 helped volunteers learn a movement task more rapidly.

“Targeting so many different brain structures that previously you wouldn't have been able to reach has big therapeutic potential,” says Neufeld, though he stresses that this new technology requires additional research to reach its full potential.

For Kuster, the benefit of IT’IS’ tools is clear: “They help accelerate basic research and the time-to-market for novel, more effective, and safer therapies.”

To learn more about the medical physics capabilities of IT’IS, explore its tools and systems.

Wagner, F. B. et al. Nature 563, 65–71 (2018).

Rowald, A. et al. Nature Medicine 28, 260–271 (2022).

Violante, IR et al.Nature Neuroscience 26, 1994–2004 (2023).

How do you know how a medical implant will behave before it's manufactured?

Skeleton Anatomy Model Wessel, M. J. et al. Nature Neuroscience 26, 2005–2016 (2023).