Siemens Healthineers Silvia Arroyo Camejo is a Futureshaper

Siemens Healthineers Technical Lead, Silvia Arroyo Camejo, is part of the company's #Futureshaper series. Having become a scientific author when she was just a teenager, today she's a data scientist helping to make MRI scanners even smarter, powered by artificial intelligence.

Having completing her university doctoral degree in experimental physics, Sylvia Arroyo Camejo works as a data scientist in predevelopment of software for magnetic resonance imaging (MRI) at Siemens Healthineers. Here, she reiterates why she chose to work in the medical technology domain instead of research in physics and how her role helps her reach her full potential.

A passion for science and technology

Silvia was always passionate about scientific innovation right from her days as a teenager. When many in her age group were thumbing through teen fan magazines, she was poring over books on theoretical physics. Silvia was just 17 when she decided to write a book herself: on the cryptic world of quantum physics – the shear unintelligibility of which had captured her imagination.

"I had read so much on the subject that the idea of writing my own book just came naturally," explains Silvia. She continues that it was "mainly for herself" that she wanted to document her knowledge of the "completely crazy" quantum theory.

Silvia received various awards while still in secondary school, including recognition in 2005 from the German Physical Society (DPG) for outstanding achievements in the field of physics. Silvia's book Skurrile Quantenwelt (Crazy Quantum World), published in 2006, was translated from German into four other languages. She herself now has only one last copy of the book – in Japanese: "Over time I gave away the remaining copies to family and friends when they asked me," she explains.

That Silvia, after her long journey through theoretical physics, was then drawn to applied medical technology, was thanks in part to her father, a Spanish-born vascular surgeon.

"I want to use my abilities in ways that people actually benefit from directly. I can achieve significantly greater impact in medical technology than by pursuing basic research in physics," Silvia comments.

A giant playing field

Together with her 15-strong international team at Siemens Healthineers, Silvia is now working as Technical Lead on a smart scanning function for MRI scanners.

"In a nutshell, it's about digitalizing MRI scanners and taking them to a whole new level with the aid of artificial intelligence," Silvia explains.

Predevelopment work – as the term suggests – is a preparatory stage prior to plunging into actual product development. It's precisely the right place for Silvia, "It's like a giant playing field. We have diverse technological components that we have to correctly unite into a whole," she says.

Creating the right technical tools

Silvia creates cryptic-looking, multi-colored combinations of characters strung together on the computer screen as she codes using the Python programming language. Her task scope includes programming complex algorithms, as well as coordinating the technical collaboration among her team members.

Silvia says that an in-depth needs analysis was conducted by directly exchanging ideas and information with international customers before starting the predevelopment project. What do these various hospitals, clinics, practices, and practice chains need? What are they lacking? And what would be just the right technical tool to help them?

Skilled worker shortage

"Our customers report to us again and again about a general lack of highly qualified personnel," explains Silvia. These shortages are found among medical-technical radiology assistants (MTRA).

"There's high demand for medical scans. Yet, experienced 'techs' are hard for hospitals and clinics to come by. They're not as readily available as they're actually needed," Silvia explains.

Yet, experienced medical technicians – MTRAs – are absolutely essential to ensuring that the optimum image quality is generated with equipment as complex as MRI scanners, given the numerous setting variables.

The smart scanning function that Silvia and her team are researching aims to make MRI scans considerably less dependent on the level of experience of attending MTRAs, and to do so using artificial intelligence – on the basis of Deep Learning algorithms, for instance. "You can imagine it similarly to autonomous driving," explains Silvia. Various levels of automation are also at play here.

Working to simplify processes

Some MRI scanners from Siemens Healthineers already operate today using what are called Dot Engines which, in part, perform intelligent functions as part of scan preparation. For example, they can correctly document the anatomy of patients and, based on this log, automatically adjust initial scan parameters accordingly.

The smart scanning project that Silvia is pursuing aims to go one step further by significantly simplifying the operation of MRI scanners by increasing the level of automation.

"We seek to get as close as possible to autonomous driving, so to speak – while remaining fully aware that the MTRA always has the final say, and can intervene at any time," she says.

Making MRI scanners even smarter

Besides their programming work, the team agenda includes extensive trial testing series on MRI scanners. Silvia and two of her team colleagues, Solution Owner, Julian Wohlers, and Chief Developer, Dirk Franger, sit in the scanner control room.

They throw cryptic technical terms at each other via three computer monitors with MRI scans. Any outsider would hardly understand a single word. Yet, from their general mood it's evident that the team members understand each other well – and not just technically.

The new smart scanning function the team is working on could make it possible in future for image quality controls to be performed automatically: artificial intelligence could recommend, for example, whether scans need to be repeated, or what particular scan steps should come next in the sequence.

Precision medicine advancement

While it may sound contradictory at first, precisely this standardization of processes would mark another step towards precision medicine: there would be no "one size fits all", and all scanning steps could be individually adapted to the given patient.

"The scanner watches quasi continuously over the shoulder of the MTRA, as an assistant, noting to the MTRA for example, 'You know what? For this patient I'd recommend that we also run the tumor protocol, as there's something suspicious-looking there,'" says Silvia.

Images generated more precisely, which undergo automatic image quality control on the scanner, would ensure that fewer patients have to be called back in for repeat scans. The potentially life-saving "time to diagnosis" factor could be shortened. For hospitals and clinics, the process could substantially relieve the shortage of skilled personnel, enable workflows to be designed more efficiently, cut costs, and reduce the load on the healthcare system as a whole.

Each and every one of us is a #Futureshaper

Silvia knows that there's still a long way to go until any solution is implemented as finished software, as they're still in the predevelopment stage. The vision, however, is for this smart scanning function to be useable in future on MRI scanners across the broadest possible range of applications.

Regarding the future, does Silvia plan to author more books? "The idea does indeed tempt me," she says.

"Perhaps someday later I'll find the time again to do so. But it's also important to leave the computer behind now and then, right?"