Estimates of Peak Electric Fields Induced by Transcranial Magnetic Stimulation in Pregnant Women as Patients or Operators Using an FEM Full-Body Model

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Abstract

Transcranial magnetic stimulation (TMS) is increasingly used as a diagnostic and therapeutic tool for neuropsychiatric disorders. TMS for treatment of depression during pregnancy is an appealing alternative to fetus-threatening drugs. However, there are no studies to date that evaluate the safety of TMS for a pregnant mother and her fetus. Two scenarios are possible in practice: (i) pregnant woman as a patient and (ii) pregnant woman as an operator. The goal of the present study is to estimate maximum field exposures for the fetus in both scenarios. A full-body finite element method (FEM) compatible model of a pregnant woman with about 100 tissue parts has been developed for the present study. This model allows detailed computations of induced current/electric field in every tissue given different locations of a figure-eight coil, a biphasic pulse, common TMS pulse durations, and using different values of the TMS intensity measured in standard motor threshold (SMT) units. Along with the numerical simulations, we use a simple analytical estimation model; both approaches confirm and augment each other. Our simulation/analytical results estimate the maximum peak values of the electric field in the fetal area and beyond in 48 (operator/patient) representative cases, for every fetal tissue separately and for a TMS intensity of one SMT unit. This study provides the first detailed data on risk to fetal exposure to induced fields by TMS in pregnant patients and pregnant operators. It is expandable to any patient/operator configuration by applying a simple analytical upper estimate of field strength/eddy current density.

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Yanamadala, J., Borwankar, R., Makarov, S., & Pascual-Leone, A. (2019). Estimates of Peak Electric Fields Induced by Transcranial Magnetic Stimulation in Pregnant Women as Patients or Operators Using an FEM Full-Body Model. In Brain and Human Body Modeling: Computational Human Modeling at EMBC 2018 (pp. 49–73). Springer International Publishing. https://doi.org/10.1007/978-3-030-21293-3_3

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