New medical advances thanks to digital twins

The idea of treating certain conditions with electrical currents is not new. However, the results that can be achieved by combining physical and medical expertise with modern medical engineering are impressive. You only have to look at the research carried out by Dr. Andreas Rowald and his team at the Chair of Digital Health at FAU. They are developing personalised treatments and ways to make living with their condition easier for patients with neurological conditions such as Parkinson's disease, stroke-induced damage or spinal cord injuries.

Electrotherapy can have eye-opening results in a number of different conditions, for example mitigating the effect of neurodegenerative diseases in which important nerve cells within the body cease to function over time. It is possible for injured nerve cells and nerve cords to be reactivated. A weak electric current can also be used to switch off certain bodily functions, such as pain. In the best case scenario, treating a patient in this way would make medication superfluous, and side effects are very rare.

However, 'one of medicine's mysteries is that we often fail to really understand how a certain treatment actually works,' explains Dr. Andreas Rowald, head of the working group 'ProModel: Interactive creation and simulation of prognostic, personalised digital patient models.' 'We only know that they are successful in treating patients, but the same means can have different effects in different people. We have seen this to be the case with both medicine and treatment using electrical currents.'

Rowald, who is a physicist, now hopes to gain a better understanding of the mechanisms behind electrotherapy. The first step involves getting to know the patient as well as possible, literally inside out. He is using modern imaging methods such as MRI or CT together with portable sensors to gather important data on factors such as the properties of fat and bones, the strength and size of muscles, connections between nerves, and the electrical resistance of tissue in the patient's body, to name just a few. Rowald uses these data to construct a digital twin of the patient on the computer and can then run simulations of what would happen when an electrical current is applied to various areas of the body.

'Once we understand the processes within the body, then we can take the next step and explore the most promising treatment options for individual patients,' explains Rowald. Andreas Rowald and his team are using complex physical calculations to determine where it would be most beneficial to place electrodes. They calculate the optimal voltage and strength of the electric current, and test whether it would be more effective to provide the electrical current constantly or in pulses.

'Of course, therapists also change the type of simulation they use in traditional scenarios where treatments are not specifically tailored to suit the individual in question. However, experience has shown that treatment then lasts far longer and demands far more patience on the part of patients and therapists than our method, with our personalised electrostimulation often proving successful to a greater or lesser extent from the very first session,' explains Rowald.

One aim of the research conducted by Andreas Rowald and his team is to develop computer models for personalising treatments that are customised to suit the patient as well as possible whilst using data that is easier to collect. At the Chair of Digital Health (Prof. Dr. Oliver Amft), computer models and digital twins are being developed and analysed for a wide range of medical applications.

The ProModel team is always looking for patients with neurological diseases to take part in clinical studies. The ProModel team is also keen to hear from young researchers who are interested in investigating how digital twins can be used to treat neurological conditions.

The latest paper from the working group has been published in Nature Medicine: https://rdcu.be/cGwVp

Contact for the press:

Dr. Andreas Rowald

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