Designing AIMDs for full-body MRI compatibility
Most patients with implanted medical devices will require at least one MRI scan within the lifetime of their implant. As a result, active implantable medical device (AIMD) manufacturers are increasingly compelled to develop devices that are MRI-compatible and move beyond the restrictive “MRI-conditional” labelling, which can limit scan access and compromise diagnostic value, toward enabling full-body MRI use.
Achieving MRI labelling for an AIMD requires demonstrating acceptable risk levels across several hazards, including implant displacement due to static magnetic field, image artefacts, and potential damage to implant electronics. For devices with long leads, such as pacemakers and neuromodulation implants, another key risk arises from RF fields inducing currents in the lead, which can cause localised tissue heating at the electrode-tissue interfaces.
ISO 10974 and the Tier 3 Approach
How can engineering teams effectively assess the impact of lead design upon MRI compatibility?
ISO 10974 (Assessment of the safety of magnetic resonance imaging for patients with an active implantable medical device) defines a tiered framework for evaluating RF-induced heating in AIMDs, with the applicable tier depending on the length of the implant’s conductive components. The most comprehensive Tier 4 requires full-system electromagnetic simulation across device, tissue, and MRI scanner scales. In practice, this is computationally prohibitive.
Tier 3 is, however, a standard approach accepted by industry and regulators. It separates RF exposure modelling from lead characterisation using the transfer function(TF), which describes how RF fields couple into the lead and generate induced currents. Combined with RF field distributions from MRI simulations derived from body-scale simulations, it enables assessment of tissue heating at the electrode-tissue interface.
Thus, Tier 3 provides a practical route for evaluating and comparing lead designs.
Addressing the burden of prototyping
Tier 3 reduces the computational burden by separating global RF exposure from local lead behaviour. However, it raises a key question: how is the transfer function determined?
ISO 10974 does not prescribe a single method, but many groups still derive transfer functions experimentally. This requires physical lead prototypes, which becomes costly and time-consuming when designs require multiple iterations, in particular when the root cause of underperformance is not immediately clear.
An alternative is to determine the transfer computationally. Advances in commercial modelling software, combined with stronger understanding of the underlying physics, now enable efficient and reliable models of transfer functions. These models can guide design decisions and reduce reliance on physical prototyping.
Streamlined determination of transfer function
We describe an efficient computational approach to rapid modelling of TF within the Tier 3 framework of ISO 10974. This has several implications for development workflow:
- Faster design iteration - Allows design changes to be evaluated in minutes rather than weeks, accelerating optimisation and improving scalability.
- Earlier design insight - Transfer functions can be estimated early in development, enabling informed decisions before other design elements are fixed and increasing the likelihood of first-pass success.
- Targeted validation - Experimental testing can focus on confirmatory validation rather than exploratory iteration, reducing demand on laboratory resources.
- Earlier risk identification - Potential compliance issues can be identified sooner, supporting a more predictable regulatory pathway.
- Reduced MRI restrictions - Improved understanding of lead behaviour makes it easier to minimise MRI constraints and, where required, support full-body MRI compatibility.
Discover more about the approach with the e-Book
To read more about this approach, download our free e-book: A smarter way to design MRI-safe implants.
