Thermal Heating of Human Tissue Induced by Electro-Magnetic Fields of Magnetic Resonance Imaging

Thiele, Jens; Golombeck, M.-A.; Dössel, Olaf

doi:10.1515/bmte.2002.47.s1b.743

Cited by 8 publications

(6 citation statements)

References 1 publication

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“…The interest in magnetic resonance imaging (MRI)‐guided endoscopic examinations in interventional medicine is growing (1–4). At clinical field strength, imaging of small regions of interest obtained from endoluminal coils exhibits a higher signal‐to‐noise ratio than with external coils (5).…”

Section: Introductionmentioning

confidence: 99%

Assessment of radiofrequency self‐heating around a metallic wire with MR T1‐based thermometry

Detti¹,

Grenier²,

Perrin³

et al. 2011

Magnetic Resonance in Med

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Heat produced by a magnetic resonance (MR) imaging sequence in the vicinity of a conductive wire (pacemaker, electrodes, or catheter), is a subject of interest for the assessment of patient safety during imaging. For this purpose, the measurement of temperature rises during an MR imaging sequence using MR T 1 -based thermometry provides several advantages, mainly in its ability to retrieve in situ realtime thermal maps. Recent studies investigated the heat produced by an independent radiofrequency pulse, assessing MR imaging sequence heating using a specific MR thermometry sequence. This study focuses on self-heating for which the radiofrequency pulses used for measuring temperature create the heat. An experimental design was set up to evaluate T 1 -based thermometry self-heating using a coupled/decoupled wire and to compare it with a reference temperature gathered by an optical fiber device. For the tested experimental set up, T 1 -based thermometry is in fairly good agreement with optical fiber reference temperature. Magn Reson Med 66:448-455,

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Section: Introductionmentioning

confidence: 99%

Assessment of radiofrequency self‐heating around a metallic wire with MR T1‐based thermometry

Detti¹,

Grenier²,

Perrin³

et al. 2011

Magnetic Resonance in Med

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“…Thermal simulations are based on the resolution of the Pennes bio heat equation with nodal finite element. We performed a comparative study with a sphere of diameter 200 mm for which we know the analytical formulation for the for the calculation of temperature rise caused by heat convection [22]. With AMIRA, we generated two meshes S 1 and S 2 , the first mesh is built from an isosurface and the second from the input voxels.…”

Section: Resultsmentioning

confidence: 99%

Variational tetrahedral mesh generation from discrete volume data

et al. 2009

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In this paper, we propose a novel tetrahedral mesh generation algorithm, which takes volumic data (voxels) as an input. Our algorithm performs a clustering of the original voxels within a variational framework. A vertex replaces each cluster and the set of created vertices is triangulated in order to obtain a tetrahedral mesh, taking into account both the accuracy of the representation and the elements quality. The resulting meshes exhibit good elements quality with respect to minimal dihedral angle and tetrahedra form factor. Experimental results show that the generated meshes are well suited for Finite Element Simulations.

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“…Previous works have shown that wireless electromagnetic energy transfer through induction, radio frequency waves, or resonant evanescent coupling results in thermal effects on tissues [ 8 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. The temperature of a wireless power receiver will rise as the energy is being transferred.…”

Section: Motivation and Problem Statementmentioning

confidence: 99%

“…Wireless charging can result in more serious thermal effects [ 26 , 27 , 28 ]. Wireless energy transfer can result in thermal effects on tissues is stated in many works [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 29 ]. The temperature of a wireless power receiver will rise as the energy is being transferred.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Data Transmission for Sensors with Wireless Charging

Fang

Luo

et al. 2018

Sensors

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This paper studies the problem of maximizing the energy utilization for data transmission in sensors with periodical wireless charging process while taking into account the thermal effect. Two classes of problems are analyzed: one is the case that wireless charging can process for only a limited period of time, and the other is the case that wireless charging can process for a long enough time. Algorithms are proposed to solve the problems and analysis of these algorithms are also provided. For the first problem, three subproblems are studied, and, for the general problem, we give an algorithm that can derive a performance bound of (1−12m)(OPT−E) compared to an optimal solution. In addition, for the second problem, we provide an algorithm with 2m2m−1OPT+1 performance bound for the general problem. Simulations confirm the analysis of the algorithms.

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Thermal Heating of Human Tissue Induced by Electro-Magnetic Fields of Magnetic Resonance Imaging

Cited by 8 publications

References 1 publication

Assessment of radiofrequency self‐heating around a metallic wire with MR T1‐based thermometry

Assessment of radiofrequency self‐heating around a metallic wire with MR T1‐based thermometry

Variational tetrahedral mesh generation from discrete volume data

Energy Efficient Data Transmission for Sensors with Wireless Charging

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