The number of patients with a cardiovascular implanted electronic device (CIED) is rapidly and constantly growing, now comprising several million patients worldwide. It is estimated that up to 75% of all patients with CIED will have the future need for a magnetic resonance imaging (MRI) investigation due to the high probability of comorbidities such as stroke, lumbar disease, arthritis, or cancer in this patient population. A few studies have assessed the safety of endocardial leads connected to working devices, but many patients require additional procedures which lead to ?lead extraction?, leaving fractions of the device left in situ, in which case the original safety studies of the device/lead combination are not applicable. Magnetic resonance imaging (MRI) is considered the imaging tool of choice in a wide range of diagnostic tasks, however, MRI is currently a contraindication for patients with abandoned or retained cardiac leads. This is particularly alarming, considering that 50% of patients undergoing heart transplantation who significantly benefit from MRI in assessment of rejection and ventricular function have already abandoned or retained leads from a previously implanted CIED. The major safety concern is due to the so-called ?antenna effect?, where the electric field of the MRI transmit coil couples with conductive implanted leads and amplifies energy deposition in the tissue which leads to excessive heating and potential tissue damage. Phantom experiments have highlighted the significant effect of lead geometry, location, and trajectory on MR-induced RF heating, yet almost nothing is known about the actual temperature rise in the tissue in a realistic patient population. A significant challenge is that the problem has a very large parameter space with many interacting factors that preclude the application of a systematic experimental approach to estimate heating in the worst case scenario. This proposal aims to develop, optimize, and validate computational methodologies that consistently and reliably predict tissue heating in patients with retained leads during high-field MRI. As a first step, we will complete development of a repository of 30 patient-derived realistic models of abandoned/retained leads that incorporate detailed features of the lead structure and trajectory, co-registered in high-resolution anatomically detailed models of human body. We will then use these patient-derived lead and body models along with experimentally validated models of MRI transmit coils and perform full-wave electromagnetic simulations to calculate tissue heating during MRI at both 1.5 T and 3.0 T. Dependency and sensitivity of results on parameters such as RF coil?s frequency (64 MHz, vs. 127 MHz), mode of operation (linear vs. quadrature), body model characteristics (size, number of tissues, electric and thermal properties), and lead trajectory will be examined. Finally, we will use this information to devise an evidence-based, patient-specific, and easy-to-use clinical guideline to help clinicians better assess risks and benefits of performing MRI on these patients based on the particular imaging landmark and the pulse sequence in use.
This project aims to develop computational methodologies that assess, for the first time, the heating of tissue during magnetic resonance imaging of patients with retained cardiac leads using patient-derived computational models. Results will produce data that will help to determine the safe range of imaging parameters, optimize clinical protocols, and support the development of standards and imaging guidelines that bring MRI accessible to these patients.
