Integration of big-data analytics in safety assessment of patients with medical implants during MRI exposure

摘要

The RF-induced heating of the patient with implant under MR exposure is a complex function of multi-factors, e.g., implant characteristic, patient anatomy, imaging position, RF coil, etc. A comprehensive safety assessment cannot be derived from limited clinical scenarios and in silico trials are usually required to assist the evaluation process. To address further needs for in silico trials, we have established a safety assessment workflow comprises a data library and toolset to perform a comprehensive evaluation in a timely and traceable manner. We demonstrate the proposed workflow through an evaluation of RF-induced heating of a spinal cord stimulator. More than 39 million unique clinical scenarios were emulated in silico.