Computational Investigation of the Factors That Affect Tangential Electric Fields along Cardiac Lead Paths inside MRI Birdcage Coils

Abstract

The medical imaging of a patient with a cardiac implantable electronic device (CIED) inside a magnetic resonance imaging (MRI) scanner carries the risk of tissue heating at the tip of the implant lead. In this work, we numerically assessed the impact of various factors, namely the resonant frequency, the imaging position, the implant position inside the human body and the coil configuration, on the induced tangential electric field along 10,080 cardiac lead paths at 1140 different scanning scenarios. During this comparative process, a function was considered based on the induced electrical potential at the tip of the lead. The input power of each coil was adjusted to generate constant B1+RMS at the iso-center or to limit the global SAR to the values provided in the safety guidelines IEC 60601-33. The values of the function were higher for higher static field and longer coil lengths when assessing the cases of a constrained B1+RMS, and the trend was reversed considering the limiting SAR values. Moreover, the electric field was higher as the imaging landmark approached the thorax and the neck. It was also shown that both the choice regarding the insertion vein of the lead and the positioning of the implantable pulse generator (IPG) affected the induced tangential electric field along the paths. In particular, when the CIED lead was inserted into the left axillary vein instead of entering into the right subclavian vein, the electrical potential at the tip could be on average lower by 1.6 dB and 2.1 dB at 1.5 T and 3 T, respectively.

Next Generation Clinical Trials: Embracing Virtual Methods

“…Integrating data from numerous sources to produce a 3D depiction of a person's anatomy and physiology is obligatory to create a human data-filled virtual body. This can be accomplished by making a virtual model of the human body using medical imaging methods like computed tomography (CT) scans or magnetic resonance imaging (MRI) [15] . Then, patient-specific data, including demographics, a patient's medical history, and the outcomes of laboratory tests, can be added to this virtual model.…”