Applications » MRI Active Implant Safety

MRI Active Implant Safety

The Most Effective Way to
Demonstrating RF Active Implant Safety

 

Problem Description

Undesirable interactions of an active implanted medical device (AIMD) inside an MRI scanner.

 

Magnetic resonance imaging (MRI) is a medical imaging modality, which is indispensable in diagnosing several pathologies. Nevertheless, the presence of medical implants in some patients taking an MRI scan may lead to undesirable interactions of the implants with the radiofrequency (RF) radiation necessary for the operation of the scanner. Therefore, it is necessary to develop a comprehensive risk assessment methodology, in order to determine the specific conditions that would permit an MRI examination for implant-bearing patients.

 

 

Standards Addressed

The standard ISO/TS 10974 for assessment of the safety of magnetic resonance imaging for patients with an active implantable medical device.

 

The ISO/IEC Technical Specification 10974 (ISO/TS 10974) defines the procedures to assess the local power deposition (RF heating) at the electrodes and the voltage/current (EMC) at the device terminals of an active implanted medical device (AIMD). Vertical standards define the risk assessment procedures. Members of ZMT and the IT’IS Foundation have contributed in the development of the standards and have optimized a toolbox for demonstrating RF implant safety.

 

Methodology

1. Generation of the AIMD Response Model (piX System)

 

The piX system is used to validate numerical results for the transfer function.

 

In the Tier 3 approach described in TS 10974 the first step towards safety evaluation is to create a response model of the AIMD, namely to create a transfer function that allows the assessment of the power deposited at the distal end of the AIMD lead under known excitation. The AIMD model can be determined either experimentally with the use of the piX system and a physical sample of the device under test (DUT) or/and with the use of the Sim4Life electromagnetics solver and a CAD model of the DUT.

 

 

2. Validation of the AIMD Response Model for Power Deposition

 

The MITS 1.5/3.0 validates the power deposition distribution along a pacemaker lead.

 

Thereafter, the created model needs to be validated with a sufficient set of orthogonal test functions. This involves specific absorption (SAR) or temperature rise (ΔΤ) measurements with a medical implant test system (MITS). The latter allows for the fast evaluation of the AIMD model under worst-case incident fields of commercial scanners, but also for specific exposures such as constant amplitude and phase with the use of ELIT phantoms. The integration of the measurement and Sim4Life results is seamless for the user, facilitating comparison and sensitivity and/or uncertainty analysis. It should be noted here that the AIMD model can be established for each operating mode of the AIMD separately.

 

 

3. Validation of the AIMD Response Model for Induced Voltages or Current at the Device Terminals

 

RFoF1P: A miniature electrically fully isolated RF-over-Fiber (RFoF) transducer.

 

The EMC interaction models must also be validated by measuring the currents at the terminals or the induced voltages inside the device. This involves measurement of voltages without modifying the devices. The solution of miniaturized RF over fibers (RFoF) measurement heads in conjunction with the MITS systems fulfills all the demanding specifications.

 

 

4. Computation of the Incident Field Distributions for the Patient Population

 

ViP3.0 human models.

POSER tool in action.

Coil library includes E-fields of coils with varying length and diameter.

Evaluation and visualization of MRI-induced electrical fields along clinical paths for a cardiac pacemaker with the IMSFAFE tool.

 

The validated AIMD model is, subsequently, used for the estimation of the power delivered to the distal tip of the AIMD lead when the latter is implanted inside a human body (in vivo). The approach described in TS 10974 requires that the risk assessment of RF heating covers a wide range of the population. Currently, Sim4Life is the only software platform that is based on computable anatomical phantoms functionalized for morphing and posing, enabling the user to obtain a wide and representative patient population with realistic and clinically relevant postures. The choice is not limited to standard male and female subjects in child- or adulthood, but includes an elderly male and an obese one, the latter being most important for worst-case evaluations inside an MRI volume coil.

The calculation of the incident (tangential) electric fields along the lead of an AIMD in vivo for all the above computational models and for all the possible ways of clinical implantation in them would be a Herculean task in terms of human and computational resources without the tools of Sim4Life. Indeed, the fast design of birdcage coils tuned at the desired frequency, the effortless setting of the material and tissue physical properties, and the calculation of the electric fields inside the human body with the verified Huygens approach render the whole task affordable by commonly available computational power and a snap for the High Performance Computing (HPC) framework provided by ZMT. Instead of performing the calculations anew, the user has the option of acquiring a validated library of the electric field distributions in five human models placed at different imaging positions (according to TS 10974) inside various birdcage coils, which are carefully selected to represent the majority of commercially available ones.

However, safety evaluation would have never been so easy without the flexibility of the IMSAFE tool. It allows the user to create, within seconds, thousands of possible implant paths for the lead placement of an AIMD, using different exclusion rules (bending, intersection, etc.). The incident (tangential) electric fields along these paths are easily visualized or statistically processed with the tool for faster report generation. After being exported by the tool, the fields serve as the input for the AIMD models obtained in the beginning of the assessment process, thus resulting in the estimated power deposited at the tip of the AIMD lead for each operating mode, lead placement path, imaging position and human model.

 

 

5. Risk Assessment for RF Heating

 

Temperature rise at the tip of a cardiac pacemaker lead, simulated with Sim4Life.

The industry mainly applies two approaches to translate the power deposition into risk assessment. The first one is to use animal experiments by injecting the equivalent power to the electrodes and assessing the response (e.g., change in the pacing threshold) as a function of the deposited power. The other approach is to translate the power deposition into in vivo temperature rise inside the human tissues using the Sim4Life thermal solver, which has been validated both for local and locoregional RF heating in humans.

 

 

 

Procedure Overview

 

Products Involved

 
Sim4Life → Computable Human Phantoms → ViP3.0
Sim4Life → Physics Models → P-EM-FDTD
Sim4Life → Physics Models → P-THERMAL
Sim4Life → Modules → POSER
Sim4Life → Modules → BCAGE
Sim4Life → Modules → HUYGENS
Sim4Life → Modules → IMSAFE
Sim4Life → Framework → HPC
Validation Hardware → MITS Systems → MITS1.5/MITS3.0

Validation Hardware → MITS Systems → piX

 

 

Documentation

Publications

  1. Zastrow, E., Cabot, E., Kuster, N. Assessment of local RF-induced heating of AIMDs during MR exposure (2014) 2014 31th URSI General Assembly and Scientific Symposium, URSI GASS 2014, art. no. 6930111.
  2. Cabot, E., Lloyd, T., Christ, A., Kainz, W., Douglas, M., Stenzel, G., Wedan, S., Kuster, N. Evaluation of the RF heating of a generic deep brain stimulator exposed in 1.5T magnetic resonance scanners (2013) Bioelectromagnetics, 34 (2), pp. 104-113.
  3. Kyriakou, A., Christ, A., Neufeld, E., Kuster, N. Local tissue temperature increase of a generic implant compared to the basic restrictions defined in safety guidelines (2012) Bioelectromagnetics, 33 (5), pp. 366-374.
  4. Neufeld, E., Kühn, S., Szekely, G., Kuster, N. Measurement, simulation and uncertainty assessment of implant heating during MRI (2009) Physics in Medicine and Biology, 54 (13), pp. 4151-4169.
  5. Gosselin, M.-C., Neufeld, E., Moser, H., Huber, E., Farcito, S., Gerber, L., Jedensjo, M., Hilber, I., Gennaro, F.D., Lloyd, B., Cherubini, E., Szczerba, D., Kainz, W., Kuster, N. Development of a new generation of high-resolution anatomical models for medical device evaluation: The Virtual Population 3.0 (2014) Physics in Medicine and Biology, 59 (18), pp. 5287-5303.

 

Validation Reports, available upon request from our support team

  1. Population coverage of ViP3.0 phantoms
  2. Verification of P-EM-FDTD Module
  3. Verification of P-Thermal Module
  4. Validation of P-Thermal Module
  5. Validation of the POSER tool (incl. validation of model import/export)
  6. Validation of the IMSAFE tool (incl. validation of field extraction and post-processing)
  7. Validation of the Coil Library

 

 
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22/08/2017