Evaluation of MRI RF electromagnetic field induced heating near leads of cochlear implants.
Abstract
A typical cochlear implant system under magnetic resonance imaging (MRI) procedures may couple with the radio frequency (RF) electromagnetic field (EMF) and results in an intensified electric field at the lead tip. As a result, the RF energy deposited in human tissues around the lead tip may induce heating and cause tissue damage concerns. The purpose of this work is to evaluate the RF-EMF-induced heating for cochlear implant system in 1.5 T MRI coil and highlight the factors that have significant effects on the heating. The potential factors involved in the RF-EMF-induced heating including the lead type, lead trajectory, human model and MRI landmark. In this paper, the RF-EMF-induced heating for three types of leads is evaluated in two virtual human models. A total of 24 lead trajectories and 23 anatomical landmark positions are studied using the transfer function method. The average temperature rise for all the studied cases in the human models is 0.79 °C, and the maximum value is 2.80 °C for a maximum whole-body average specific absorption rate of 2 W kg in an RF body coil. It is found that the lead trajectory and MRI landmark are two primary influencing factors. The maximum temperature rises for different lead trajectories can vary from 0.82 to 2.80 °C. A difference in heating of 2.80 °C is observed when the landmark changes from -100 to 700 mm. This work demonstrates that it is necessary to take these factors into account when evaluating the RF-EMF-induced heating for implanted medical devices.
AI evidence extraction
Main findings
Using a transfer function method in two virtual human models, average temperature rise across studied cases was 0.79 °C and the maximum was 2.80 °C at a maximum whole-body average SAR of 2 W/kg in an RF body coil. Lead trajectory and MRI landmark position were identified as primary factors influencing heating, with maximum temperature rise varying from 0.82 to 2.80 °C across trajectories and a 2.80 °C difference observed when landmark changed from -100 to 700 mm.
Outcomes measured
- RF-EMF-induced heating/temperature rise near cochlear implant lead tips during 1.5 T MRI
- Influence of lead type, lead trajectory, human model, and MRI landmark on heating
Limitations
- Simulation/virtual human models rather than measurements in patients
- Frequency and detailed MRI RF exposure parameters not specified in the abstract
- Sample size for modeled cases not fully specified beyond counts of trajectories/landmarks
Suggested hubs
- occupational-exposure (0)
View raw extracted JSON
{
"study_type": "engineering",
"exposure": {
"band": "RF",
"source": "MRI",
"frequency_mhz": null,
"sar_wkg": 2,
"duration": null
},
"population": "Virtual human models with cochlear implant leads (simulation)",
"sample_size": null,
"outcomes": [
"RF-EMF-induced heating/temperature rise near cochlear implant lead tips during 1.5 T MRI",
"Influence of lead type, lead trajectory, human model, and MRI landmark on heating"
],
"main_findings": "Using a transfer function method in two virtual human models, average temperature rise across studied cases was 0.79 °C and the maximum was 2.80 °C at a maximum whole-body average SAR of 2 W/kg in an RF body coil. Lead trajectory and MRI landmark position were identified as primary factors influencing heating, with maximum temperature rise varying from 0.82 to 2.80 °C across trajectories and a 2.80 °C difference observed when landmark changed from -100 to 700 mm.",
"effect_direction": "harm",
"limitations": [
"Simulation/virtual human models rather than measurements in patients",
"Frequency and detailed MRI RF exposure parameters not specified in the abstract",
"Sample size for modeled cases not fully specified beyond counts of trajectories/landmarks"
],
"evidence_strength": "low",
"confidence": 0.7399999999999999911182158029987476766109466552734375,
"peer_reviewed_likely": "yes",
"keywords": [
"MRI",
"RF electromagnetic field",
"cochlear implant",
"lead tip",
"heating",
"temperature rise",
"specific absorption rate",
"transfer function method",
"lead trajectory",
"anatomical landmark"
],
"suggested_hubs": [
{
"slug": "occupational-exposure",
"weight": 0,
"reason": null
}
]
}
AI can be wrong. Always verify against the paper.
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