The brains behind clinical 7T MRI

7-tesla magnetic resonance imaging has been around for more than 20 years. Our experts explain how artificial intelligence and advanced innovations are helping to fully exploit its potential in clinical use as well.
Felix Michelfeit and Doris Pischitz
Published on 15. April 2024

While the technology started as a pure research tool, thanks to ongoing development, smart inventions, and brilliant minds, it is now ready for clinical routine.

<p>7-tesla (7T) magnetic resonance imaging (MRI) was initially used above all in the field of neuroscience to study the composition and function of the brain. Thanks to ultra-high resolution and brilliant contrast, scientists can visualize details that they could not see before. As the technology became more widely available, it did not take long for clinicians to recognize the advantages for clinical use. In neurology, for example, physicians can use 7T MRI to detect lesions in the brains of patients and plan subsequent treatment. In musculoskeletal imaging, it can pick up the smallest details in cartilage and the meniscus and thereby support physicians in their treatment decisions.</p>
However, an image that is great for research might not be sufficient for clinical diagnosis, due to limited coverage, image inhomogeneities, or simply because the acquisition takes too long. A team at Siemens Healthineers set out to solve these challenges.
<p>The main challenge at higher field strengths like 7T is to reduce inhomogeneity in the MR image. The higher the field strength of the superconducting magnet, the more signal dropouts are likely to occur. It is like waves in a lake: the higher the frequency of these waves, the more often they will hit each other and cancel each other out. With 7T being the highest field strength available for clinical use, despite great contrast and resolution, the images can be attenuated at the edges.</p>
<p>The solution: Usually, only one or two transmit channels are used for the excitation of the MR signal. For <a href="" target="_blank">MAGNETOM Terra.X</a>, the team created a novel technology, called Dynamic pTx, with eight transmit channels that work in parallel and are perfectly synchronized. This is like using multiple light sources from different angles to avoid the occurrence of shadows—or inhomogeneities. An extremely high level of precision is needed all the way from the amplifier to the coil to provide homogenous images suitable for more clinical applications.</p>
However, it does not only take hardware to make homogenous images at 7T a reality. There are now several transmit channels, instead of a single one, that need to be coordinated, without compromising <a href="patient safety">patient safety</a>. The software is the glue that holds everything together. It coordinates the eight transmit channels, ensures good performance, and at the same time addresses patient safety.
In MRI, the transmit power is constantly monitored. This is straightforward for a single transmit channel, but far more challenging for eight independent channels. To this end, a new supervision model was developed to help ensure safe operation while delivering maximum performance.
All of this is embedded into a common intuitive software platform, which enables technicians to easily operate this highly complex scanner, thereby improving image quality without adding complexity.

Clinical image of a head shows signal inhomogeneities at the edges.
Clinical image of the head without signal inhomogeneities at the edges.

7T MRI enables high-resolution acquisitions with unique contrast. However, signal inhomogeneities can result, as shown in the image on the left. MAGNETOM Terra.X introduces Dynamic pTx to address this challenge, leading to improved homogeneity and coverage when compared to conventional 7T MRI.

While Dynamic pTx also addresses signal and contrast variations by optimizing the radiofrequency pulse on the transmitter side for each patient, the receiver side is just as important. Here, artificial intelligence (AI) comes into play: The deep receive enhancer (Deep RxE) utilizes its power to improve image homogeneity even more. In the end, the high image quality can only be achieved by combining both technologies, Dynamic pTx and Deep RxE.
<p>There is, however, a downside to high resolution: The thinner the slices, the more slices need to be acquired, and the longer the scan takes. Again, AI helps: AI-powered image reconstruction can drastically reduce scan times. <a href="" target="_blank">Deep Resolve</a>, which has already proven its value at lower field strengths, has now been trained with dedicated data from 7T. By including this technology in the image reconstruction pathway, acquisition time is no longer an obstacle for 7T MRI in clinical routine.</p>

By Felix Michelfeit and Doris Pischitz

Felix Michelfeit is a writer working for the diagnostic imaging business of Siemens Healthineers. He has held various positions in executive communications, media, and PR.
Doris Pischitz is an editor in corporate communications at Siemens Healthineers. The team specializes in topics related to healthcare, medical technology, disease areas, and digitalization.