Jasmine Vu1,2, Bhumi Bhusal2, and Laleh Golestanirad1,2
1Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States, 2Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
Synopsis
Keywords: Safety, Modelling, Medical Implants, Transfer Function, ISO/TS 10974
Motivation: Radiofrequency (RF) tissue heating is a known safety risk for patients with cardiac implantable electronic devices (CIEDs), especially children with epicardial systems.
Goal(s): We present the first cumulative transfer function based on the guidelines in ISO/TS 10974 to evaluate the RF heating of a CIED with a bipolar epicardial lead.
Approach: We measured, calibrated, and validated cumulative transfer functions for predicting RF heating through in vitro experiments and electromagnetic simulations.
Results: Our cumulative transfer functions accurately predicted RF heating around the electrode ends for 48 unique lead trajectories (r=0.90-0.97, p<0.05).
Impact: We introduce a
high-fidelity cumulative transfer function model of a CIED with a bipolar
epicardial lead to enable the evaluation of RF heating of bifurcating leads
during MRI.
Introduction
Radiofrequency (RF) tissue heating around
medical implants is a prominent safety risk, restricting accessibility to MRI1,2.
Currently, there are no MR-conditional epicardial cardiac implantable
electronic devices (CIEDs), which disproportionally affects the pediatric
population who are the main recipients of epicardial CIEDs. Current methods for
predicting RF heating of active devices outlined in ISO/TS 10974, particularly
the transfer function (TF) method, do not specify the approach for bipolar
epicardial leads which include lead bifurcation3. Recent studies
have developed TF methods for parallel wires, but bifurcating leads have yet to
be studied4,5. Here, we present the first successful application of
the TF concept for evaluating RF heating of a CIED with a bipolar epicardial
lead.Methods
The
TF concept was used to model a 35-cm bipolar epicardial lead (Medtronic CapSure® EPI 4968)
connected to a Medtronic Azure™ XT DR MRI SureScan implantable pulse generator
(IPG). We measured, calibrated, and validated the TFs following Clause 8 of ISO/TS
109743 and determined them based on the reciprocity method6.
The transmit probe was constructed using a rg402 semirigid coaxial cable to
create a monopole antenna that excited the electrode (Figure 1A)7.
The receive probe was constructed from a rg402 semirigid coaxial cable wound
around a 4C65 ferrite torus. The probes were connected to a two-port vector
network analyzer (VNA 5063, Keysight Technologies) where the complex
S-parameter S21 was measured at 5 mm intervals along the lead while submerged in a boxed phantom filled with
saline (σ=0.5 S/m, 𝜀r=80).
Cumulative transfer function: During excitation of the cathode, the cumulative
TF, TFC,total, was measured by adding two terms. First, the transfer
function TFC was measured as S21 as the receive probe moved
along the lead from the proximal end to the branch leading to the cathode
(Figure 1B). Then, the coupling effect due to the presence of the anodal branch
was measured as S21 when the receive probe moved along the anodal
branch while still exciting the cathode (TFCA).
The
total temperature increase (ΔT) at the cathode was estimated using the
following equation:
$$\triangle T_{C,total} = C \vert \int_{0}^{z=L} TF_{C}(z) E_{tan,C}(z)dz + \int_{z_{1, bifurcation}}^{z_{1}=L} TF_{CA}(z_{1}) E_{tan,CA}(z_{1})dz_{1}\mid^{2}$$
To
assess the effect of coupling, this process was repeated three times with different
separation distances between the two electrodes: 35, 65, and 90 mm (Figure 1C). The
reciprocal was performed during excitation of the anode resulting in 6 total TFs.
Validation:
To calibrate and validate the cumulative TFs, we performed experiments with the
CIED in a phantom filled with polyacrylic acid (PAA) gel representing average
tissue (σ=0.50 S/m, 𝜀r=88.96). The CIED lead was routed along 24 different configurations
amounting to 48 total trajectories (Figure 2). The ΔT was measured in the PAA
around the electrodes using fiber optic probes (Osensa) (Figure 3A-C). All
experiments were performed in a 1.5T Siemens Aera MRI scanner with RF exposure
from a T1-TSE sequence (TE/TR=7.3/897 ms, TA=280 s, FA=133o,
B1+rms=4.1µT). Electromagnetic simulations (ANSYS
Electronic Desktop 2021 R1 HFSS) were performed to determine the incident
electric field distribution inside the phantom (Figure 3D). The complex
tangential component of the incident electric field (Etan) was
calculated along each trajectory and its corresponding opposing branch. For
each TF, the calibration factor, C, was calculated based on the temperature
measurement of one arbitrary trajectory. Following calibration, we applied the
calibrated TFs to predict RF heating for the remaining trajectories. Results
Figure
4 shows the magnitude and phase of the TFs. Figure 5 shows the measured and TF-predicted
ΔT at the anode and cathode. The cumulative TFs demonstrated high fidelity in
predicting ΔT at both the anode and cathode across separation distances
(correlation coefficient, r=0.90-0.97, p<0.05 for all cases). Interestingly,
the anodal and cathodal TFs were asymmetrical, indicating the need to measure
at least two cumulative TFs to predict RF heating at both electrode ends of a
bipolar lead.Discussion
We
presented the first results of measured, calibrated, and validated cumulative TFs
for predicting RF heating of a CIED with a bipolar epicardial lead. Our results
show that the TFs are asymmetrical for predicting RF heating at the anode
versus the cathode. There is also a coupling effect between the conductor
branches which necessitates the cumulative TF model as the induced current
along one branch may be coupled to the other branch as previous studies have
suggested4,5. Our results demonstrate good agreement between the
experimentally measured and the TF-predicted ΔT across 48 trajectories. Future
work includes further investigation of the effect of other separation distances
and applying the TFs for predicting RF heating of clinically relevant trajectories
in heterogeneous human body models.Acknowledgements
This work was
supported by NIH grant R01EB034377.References
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