Publications by authors named "I Graesslin"

Purpose: The goal of this study is to increase patient safety in parallel transmission (pTx) MRI systems. A major concern in these systems is radiofrequency-induced tissue heating, which can be avoided by specific absorption rate (SAR) prediction and SAR monitoring before and during the scan.

Methods: In this novel comprehensive safety concept, the SAR is predicted prior to the scan based on precalculated fields obtained from electromagnetic simulations on different body models.

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Purpose: The permanent presence of devices (pacemakers) inside a patient, or the need to use other devices (catheters), for diagnosis and treatment, usually represents a contraindication for a magnetic resonance examination. To help overcome this problem, a novel and noninvasive magnetic resonance system-based concept is proposed to detect potentially unsafe radio frequency (RF) conditions of such devices to ensure patient safety.

Methods: This concept makes use of parallel transmit technology by monitoring currents in individual RF transmit coil elements during RF transmission using suitable current sensors.

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The specific absorption rate (SAR) is a limiting factor in high-field MR. SAR estimation is typically performed by numerical simulations using generic human body models. However, SAR concepts for single-channel radiofrequency transmission cannot be directly applied to multichannel systems.

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Object: Parallel transmission facilitates a relatively direct control of the RF transmit field. This is usually applied to improve the RF field homogeneity but might also allow a reduction of the specific absorption rate (SAR) to increase freedom in sequence design for high-field MRI. However, predicting the local SAR is challenging as it depends not only on the multi-channel drive but also on the individual patient.

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The specific absorption rate (SAR) is a limiting constraint in sequence design for high-field MRI. SAR estimation is typically performed by numerical simulations using generic human body models. This entails an intrinsic uncertainty in present SAR prediction.

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