The Novel Design of a Single-Sided MRI Probe for Assessing Burn Depth

He, Zhonghua; He, Wei; Wu, Jiamin; Xu, Zheng

doi:10.3390/s17030526

Cited by 17 publications

(7 citation statements)

References 33 publications

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“…Finally, the measurement can be performed in a few minutes suggesting potential for use as a real‐time measure of fluid volume status. Portable, single sided MR sensors have recently shown potential across a wide range of biomedical applications …”

Section: Discussionmentioning

confidence: 99%

Dehydration assessment via a portable, single sided magnetic resonance sensor

Bashyam

Frangieh

et al. 2019

Magnetic Resonance in Med

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Undiagnosed dehydration compromises health outcomes across many populations. Existing dehydration diagnostics require invasive bodily fluid sampling or are easily confounded by fluid and electrolyte intake, environment, and physical activity limiting widespread adoption. We present a portable MR sensor designed to measure intramuscular fluid shifts to identify volume depletion. Methods: Fluid loss is induced via a mouse model of thermal dehydration (37°C; 15-20% relative humidity). We demonstrate quantification of fluid loss induced by hyperosmotic dehydration with multicomponent T2 relaxometry using both a benchtop NMR system and MRI localized to skeletal muscle tissue. We then describe a miniaturized (~1000 cm 3) portable (~4 kg) MR sensor (0.28 T) designed to identify dehydration-induced fluid loss. T2 relaxometry measurements were performed using a Carr-Purcell-Meiboom-Gill pulse sequence in ~4 min. Results: T2 values from the portable MR sensor exhibited strong (R 2 = 0.996) agreement with benchtop NMR spectrometer. Thermal dehydration induced weight loss of 4 to 11% over 5 to 10 h. Fluid loss induced by thermal dehydration was accurately identified via whole-animal NMR and skeletal muscle. The portable MR sensor accurately identified dehydration via multicomponent T2 relaxometry. Conclusion: Performing multicomponent T2 relaxometry localized to the skeletal muscle with a miniaturized MR sensor provides a noninvasive, physiologically relevant measure of dehydration induced fluid loss in a mouse model. This approach offers sensor portability, reduced system complexity, fully automated operation, and low cost compared with MRI. This approach may serve as a versatile and portable point of care technique for dehydration monitoring.

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Section: Discussionmentioning

confidence: 99%

Dehydration assessment via a portable, single sided magnetic resonance sensor

Bashyam

Frangieh

et al. 2019

Magnetic Resonance in Med

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“…There are two broad classes of optimization target fields: one which consists of a linear static magnetic field gradient perpendicular to the surface of the magnet [ 28 , 32 , 33 , 35 , 41 , 45 , 49 ] or a localized ‘sweet spot’ consisting of a ROI in which the magnetic field is relatively homogeneous in all three dimensions [ 29 , 30 , 34 , 42 , 43 , 48 , 50 ]. In the next section we will use the EA model we developed to find an optimized magnet design solution by varying the relative positions of the individual permanent cubic magnets.…”

Section: Magnet Array Designmentioning

confidence: 99%

Deep neural-network based optimization for the design of a multi-element surface magnet for MRI applications

2022

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We present a combination of a CNN-based encoder with an analytical forward map for solving inverse problems. We call it an encoder-analytic (EA) hybrid model. It does not require a dedicated training dataset and can train itself from the connected forward map in a direct learning fashion. A separate regularization term is not required either, since the forward map also acts as a regularizer. As it is not a generalization model it does not suffer from overfitting. We further show that the model can be customized to either finding a specific target solution or one that follows a given heuristic. As an example, we apply this approach to the design of a multi-element surface magnet for low-field magnetic resonance imaging (MRI). We further show that the EA model can outperform the benchmark genetic algorithm model currently used for magnet design in MRI, obtaining almost 10 times better results.

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“…In the case of the open-air MRI device, a weak magnetic field (up to 0.2 T) is usually generated by a pair of permanent magnets. Between these magnets, the gradient system consisting of 2 Â 3 planar coils is situated together with the RF receiving/transmitting coils surrounding the tested object [1]. Slices of a tested object are selected in 3D coordinates by a gradient system consisting of planar coils parallel to the magnets.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Energy Relations between Noise and Vibration Produced by a Low-Field MRI Device

Přibil¹,

Přibilová²,

Frollo³

2019

Noise and Vibration Control - From Theory to Practice

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Magnetic resonance imaging (MRI) tomography is often used for noninvasive scanning of various parts of a human body without undesirable effects present in X-ray computed tomography. In MRI devices, slices of a tested subject are selected in 3D coordinates by a system of gradient coils. The current flowing through these coils changes rapidly, which results in mechanical vibration. This vibration is significant also in the equipment working with a low magnetic field, and it causes image blurring of thin layer samples and acoustic noise significantly degrading a speech signal recorded simultaneously during MR scanning of the vocal tract. There are always negative physiological and psychological effects on a person exposed to vibration and acoustic noise. In order to minimize these negative impacts depending on intensity and time duration of exposition, we mapped relationship between energy of vibration and noise signals measured in the MRI scanning area and its vicinity.

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The Novel Design of a Single-Sided MRI Probe for Assessing Burn Depth

Cited by 17 publications

References 33 publications

Dehydration assessment via a portable, single sided magnetic resonance sensor

Dehydration assessment via a portable, single sided magnetic resonance sensor

Deep neural-network based optimization for the design of a multi-element surface magnet for MRI applications

Analysis of Energy Relations between Noise and Vibration Produced by a Low-Field MRI Device

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