May/June 2026 Issue
Whole-Body Makeover
By Jessica Zimmer
Radiology Today
Vol. 27 No. 3 P. 16
Advances in ultrahigh gradient whole-body MRI show potential for improving care, reducing invasiveness, and reshaping predictive medicine.
Ultrahigh gradient (UHG) whole-body MRI technologies may be the next step in noninvasive diagnosis and therapy guidance, a shift that could improve clinical outcomes for everything from prostate cancer to neurodegeneration. In March, Texas A&M University held the first international meeting on UHG whole-body MRI at the School of Engineering Medicine. The International Society for Magnetic Resonance in Medicine (ISMRM) endorsed the event, and the National Academy of Engineering featured it on its website. Presentation topics included eliminating biopsies, potentially avoiding chemotherapy for breast cancer patients, and advancing neuroimaging capabilities.
“Ultrahigh gradient whole-body MRI, with greater resolution and sensitivity to the motion of water molecules, potentially offers an improvement in diagnostic information for the entire body, from head to toe. The intent of this conference was to gather people from around the world working in clinical settings with, conducting research related to, or developing MRI scanners that have ultrahigh magnetic field gradients,” says Roderic Pettigrew, MD, PhD. Pettigrew, who organized the conference, is the Robert A. Welch Professor of Medicine, former system vice chancellor for health and strategic initiatives, and inaugural dean of the School of Engineering Medicine at Texas A&M University.
In the body, ultrahigh magnetic field gradients have a strength of 200 milliT per meter (mT/m) with a slew rate of 200 T per meter per second (T/m/s). In the head, the strength and slew rate can be two to three times stronger and faster. For comparison, conventional systems use gradients that have a maximum strength of 40 to 80 mT/m.
“At the conference, we worked together to understand the boundaries of these systems,” Pettigrew says. “The goal was to determine how we can use and refine such machines to do even more, technically and diagnostically.”
UHG whole-body MRI is currently in use in clinical settings. Concerns include safety issues, such as acoustic noise and peripheral nerve stimulation. The latter can manifest as a tingling sensation in the extremities during prolonged imaging. Still, clinical scanners are engineered to comply with FDA guidelines. From an engineering standpoint, the two core problems are delivering higher power to the more powerful MRI system and dissipating increased heat.
“Whole-body imaging, typically done in a larger bore, necessarily requires more power than head-only imaging. This is because of the larger bore size of the scanner. Ultrahigh gradient MRI equipment also requires more power than standard gradient systems,” says Katie Grant, vice president of MR for Siemens Healthineers North America.
Cost-effectiveness is another issue. UHG systems are significantly more expensive than low-gradient systems. One path forward is to deploy high-end gradient systems at leading institutions. Then researchers could study how the technologies can be integrated into routine clinical practice, including in less affluent or remote settings. These efforts could help establish a framework for broader accessibility.
“The knowledge gained from the deployment of advanced gradient systems from leading institutions can guide the design of affordable systems that deliver comparable performance,” says Raja Muthupillai, PhD. “This is an area where judicious injection of AI into the imaging process, informed by the knowledge gained from these initial deployments, can help build low-cost MRI scanners to bridge the health care gap.” Muthupillai is the chief technology officer of Live Healthy Imaging, a specialized radiology imaging center in Houston. He is also a research professor at the School of Engineering Medicine at Texas A&M University.
The Connection to UHF
Ultrahigh field (UHF) MRI is a form of medical imaging that uses scanners with a main magnetic field strength of 7 T or greater. With increasing field strength, there is a proportional increase in signal-to-noise ratio, which can be used to increase the spatial and/or spectral resolution of MRI. In contrast, UHG MRI opens new windows to probe water’s molecular motion within organ systems with exquisite sensitivity.
One area in which the combination of UHF MRI and UHG MRI is valuable is assessing tissue stiffness through magnetic resonance elastography (MRE). MRE emphasizes understanding the body as an integrated system.
“Ultrahigh gradients offer exceptional sensitivity to water molecular motion within the body’s organs,” Muthupillai says. “For instance, measuring microscopic incoherent motion—movement lacking orderly direction—provides insights into tissue microstructure and microcirculation. Enhanced sensitivity to coherent, harmonic motion—synchronized and predictable motion—on the scale of a few micrometers, reveals organ stiffness. With the advent of ultrahigh gradient whole-body systems, we can now study organ systems.”
An example is the evaluation of the cardio-hepatic circuits, to explore the relationship between the heart and liver. It is easy to understand how a decrease in blood flow from the heart can result in reduced blood flow in the liver. A combination of UHF whole-body MRI and UHG whole-body MRI could show, in greater detail, the dynamic interplay between cardiovascular and hepatic dysfunction.
“The idea is to analyze complex situations sensitively, accurately, noninvasively, and expeditiously. We want to address issues we see now and prevent disease years from now,” Pettigrew says. He adds that UHG MRI has developed over the past decade for neuroimaging.
It has developed within the last two to three years for whole-body applications below the neck and in the rest of the body. “That recent shift in being able to implement the power of this technological advance throughout the whole body was core among the drivers for organizing this meeting,” Pettigrew says.
AI Assistance
Every effort in engineering builds on lessons learned in previous models. “What we learned from designing the Magnetom Cima.X, which has a 3 T field strength, helped us design the Magnetom Terra.X, which has a 7 T field strength. We put work into understanding the coil array design, the coil windings. This helped us get better coil stability and linearity, the ratio between a coil’s input and output. That, in turn, improved electronic control and fidelity, accurately producing the signal,” Grant says.
When it comes to incorporating AI into the equipment, Siemens Healthineers is looking for ways to make image acquisition and resolution enhancement as automated and user-friendly as possible. “For example, can I make a push-button exam that’ll accomplish the goal? We’ve had numerous conversations with clinicians over the past decade about how hard we can push the gradient and how easy we can make the technology,” Grant says.
Bryan Mock, general manager of premium segment MR at GE HealthCare, says AI is increasingly foundational, rather than an add-on. “We’re embedding AI-driven workflow and deep learning applications to help streamline the exam from planning to scan and beyond,” Mock says. “The goal is improving consistency for technologists while maintaining diagnostic confidence. In parallel, deep learning reconstruction and acceleration approaches are becoming a practical way to reduce scan times. They also preserve image quality, which is especially important as sites manage rising demand and staffing constraints.”
Mock says clinician feedback on GE HealthCare’s technologies informs which performance features are emphasized, ultimately shaping medical practice. “We use that input to prioritize capabilities that make a difference in real workflows—reducing setup variability, supporting consistent image quality, and enabling advanced studies in a way that’s repeatable across sites,” he says. “More broadly, our goal is to deliver ‘everyday’ improvements in efficiency and confidence.”
Jeffrey Bundy, CEO of United Imaging North America, says anticipating clinician needs is a complex and demanding process. He adds that United Imaging engineers are also working on understanding how to handle flow artifacts. Flow artifacts are image distortions or signal losses caused by the movement of fluids like blood and cerebrospinal fluid (CSF).
“We see flow artifacts display in many settings and clinicians will find these flow artifacts unhelpful. But sometimes the presence of flow motion is useful,” Bundy says. “For example, a flow artifact in the brain may be caused by CSF flow around the site of a brain tumor. A flow artifact in the bowels may be caused by the movement of digestive fluid in a patient with Crohn’s disease. You want to reduce or eliminate flow artifacts in some instances and be able to see them in others.”
Bundy says AI is an essential part of producing multiple images during the process. “The AI helps the technology generate different images of an area in the body, at distinct points in time,” he says. “Then the AI presents the clinician with those frames. It allows them to pick the best one, to see the concern clearly. Think of it like an iPhone capturing one image, and AI software for the photo program allowing you to recreate multiple images from that one shot.”
It is not easy to explain to patients and their families what UHG whole-body MRI coupled with AI can achieve. Siemens Healthineers North America is currently partnering with large nonprofits like the American Heart Association and the Alzheimer’s Association. These organizations then relay to patients what new MRI hardware and software can accomplish.
“It’s in their wheelhouse to get this information out, through events like walks, runs, fundraising campaigns, and advertisements in different publications,” Grant says. “At the same time, we also have a responsibility not to share [research developments] too widely with the lay population before we know the capabilities.”
Next Steps
Pettigrew is already considering holding a 2027 conference on UHG whole-body MRI. He says the 2026 conference was a remarkable success, with 175 registrants and many enthusiastic spoken and written reviews. This is despite the recent meeting being organized in just a few months. The list of speakers at the 2026 conference included six past ISMRM presidents, six gold medalists, and multiple past scientific program chairs, with attendees from six countries.
“I heard from many that they left highly energized and stimulated,” Pettigrew says. “A number of experienced attendees called it the best conference of this type they had attended. They were motivated because they interacted with a range of cutting-edge leaders in the field, gained new insights, and saw the potential to expand the impact in clinical practice.”
As Pettigrew looks back on what clinicians and manufacturers shared, he is assessing what the physics and engineering of MRI systems will allow. He is also considering how diagnosis and treatment delivery may change. For example, what would care look like, beyond an absence of biopsies and chemotherapy, for issues other than cancer?
A glimpse at research on cardiac imaging provides a clue. At the conference, Andrew Scott, PhD, discussed emerging cardiac applications using high-performance gradients. Scott is an associate professor in cardiovascular magnetic resonance physics at Royal Brompton Hospital in London.
One of the topics that Scott researches is cardiac diffusion tensor imaging (cDTI), a noninvasive MRI technique used to map the microstructure of the heart muscle in living subjects. cDTI looks at the diffusion of water molecules in heart tissue to understand patterns in the organization and orientation of heart muscle cells. cDTI is useful for identifying and monitoring conditions such as scarring and deficient blood supply. One concern has been that there are significant variations in in vivo cDTI results, due to differences in imaging sites, scanners, acquisition protocols, and postprocessing methods.
Sharing information across international borders, between equipment manufacturers, and between clinicians creates an opportunity to identify the sources of these discrepancies. In turn, stakeholders could contribute insights and practical techniques to reduce variability. Also, the greater fidelity of UHG imaging may help provide measurement consistency. That could lead to fewer discrepancies, better protocols, and more standardized interpretations of imaging data.
“Other innovations that are enhanced by UHG are also progressing in the brain and may offer predictive insights and guide therapies by assessing the response to interventions,” Pettigrew says. “Susie Huang, MD, PhD, of the Martinos Center at Harvard University, highlighted the potential to directly quantify neuroaxonal damage in multiple sclerosis. This could provide an objective metric for therapeutic efficacy. Richard Ehman, MD, of the Mayo Clinic and primary inventor of MRE, showed preliminary data that indicates quantitative brain stiffness measurements may be predictive of cognitive decline in Alzheimer’s. This is highly important as medical therapies to reduce this decline in early-stage Alzheimer’s have started to emerge.”
Pettigrew adds that Texas A&M University invited a substantial number of medical students and engineering students from the university, and many attended the conference. Some invited speakers also brought trainees from their labs.
“We want those students to understand that this is just the beginning,” Pettigrew says. “They have the chance to make ultrahigh gradient whole-body MRI and other emerging technologies better than they are now, as well as invent entirely new technologies. The convergence between the life sciences and engineering, or ‘physicianeering,’ is what we are all about. We’re not done yet.”
— Jessica Zimmer is a freelance writer living in northern California. She specializes in covering AI and legal matters.
