In this paper, we demonstrate the use of a LiTaO 3 crystal associated with a typical nuclear magnetic resonant loop coil to perform an optically remote radio frequency magnetic-field characterization. The whole transduction scheme is theoretically and experimentally studied. The measurement dynamics reaches 60 dB. The minimum detectable magnetic field is lower than 1 nT, which corresponds to an induced inner crystal electric field as low as 30 mV/m. To evaluate the spatial potentialities of the sensor, a 1-D mapping of the field along an asymmetric butterfly-shaped loop coil is performed. The result is in good agreement with finite-difference time-domain simulations and demonstrates the vectorial behavior of the sensor device.

Low-field (LF) MRI research currently gains momentum from its potential to offer reduced costs and reduced footprints translating into wider accessibility. However, the impeded signal-to-noise ratio inherent to lower magnetic fields can have a significant impact on acquisition times that challenges LF clinical relevance. Undersampling is an effective way to speed up acquisitions in MRI, and recent work has shown encouraging results when combined with deep learning (DL). Yet, training DL models generally requires large databases that are not yet available at LF regimes. Here, we demonstrate the capability of Residual U-net combined with data augmentation to reconstruct magnitude and phase information of undersampled LF MRI scans at 0.1 T with a limited training dataset (n = 10). The model performance was first evaluated in a retrospective study for different acceleration rates and sampling patterns. Ultimately, the DL approach was validated on prospectively acquired, fivefold undersampled LF data. With varying performances associated to the adopted sampling scheme, our results show that the approach investigated can preserve the global structure and the details sharpness in the reconstructed magnitude and phase images. Overall, promising results could be obtained on acquired LF MR images that may bring this research closer to clinical implementation.

International audienceA pigtailed Ti:LiNbO3 waveguide is here associated to a specific nuclear magnetic resonant coil to perform a low invasive magnetic field measurement. The developed device exploits a passive electro-optic transduction between the measured magnetic field and polarization state modulation of a laser probe beam. Because of the use of integrated optics, the coil electromotive force induces a dramatically enhanced electric field, thus leading to sensitivity improvement. A minimum detectable magnetic field lower than 60 fT. Hz-1/2 is achieved at the resonant frequency of 128 MHz. A dynamic range exceeding 100 dB is experimentally demonstrated

In this paper we demonstrate the effectiveness of an active optical detuning circuit for magnetic resonance imaging (MRI) endoluminal receiver coil. Three endoluminal coils prototypes were built: a coil without any detuning circuit, a coil with a galvanic (classic) detuning circuit using a PIN diode, and a coil with an optical detuning circuit using two photodiodes in parallel with a PIN diode. These coils were built and characterized on a laboratory experimental bench. Then, an in vitro experiment was performed with a 3.0 T MR system to evaluate the impact of the endoluminal receiver coils in detuned phase on the image uniformity distribution measured using the body coil. Next, the endoluminal coil was used as a receiver coil to compare the signal-to-noise ratio (SNR) distribution based on iso-contour maps. On experimental bench, the results show an increase delay of the switching times (tuned-detuned or detuned-tuned) for optical-detuned coils of about 10 µs due to the electro-optical circuits, delay still compatible with requirements. When the body coil is used as a transceiver, the SNR uniformity is similar whether the galvanic or the optical detuning circuit is used. Finally, the SNR iso-contours of the different endoluminal coils prototypes are comparable.

International audienceNuclear Magnetic Resonance (NMR) spectroscopy on small volumes, either on microfluidic channelsor in vivo configuration, is a present challenge. We report here a high resolution NMR spectroscopyon micron scale performed with Giant Magnetic Resistance-based sensors placed in a static magnetic$B_0$ field of 0.3 T. The sensing volume of the order of several tens of pL opens the way to highresolution spectroscopy on volumes unreached so far. Published by AIP Publishing

International audienceAn electrooptic transduction is here used to perform a low invasive characterization of the magnetic field in the context of magnetic resonance imaging. A resonant coil is coupled to a passive electrooptic crystal and the electromotive force of the magnetic field sensor is converted into a polarization state modulation of a laser probe beam. The optical conversion is demonstrated and lead to a fiber remote measurement of the magnetic field. The setup sensitivity and dynamics are finally dramatically enhanced using a LiNbO3 integrated waveguide. The minimum detectable field is as low as 60 fT.Hz-1/2 and the dynamics exceeds 100 dB

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Low magnetic field (LF) MRI is gaining popularity as a flexible and cost-effective complement to conventional MRI. However, LF-MRI suffers from a low signal-to-noise ratio per unit time which calls for signal averaging and hence prolonged acquisition times, challenging the clinical value of LF MRI. In this study, we show that Deep Learning (DL) can reconstruct artifact-free heavily undersampled 2D LF MR images (34% sampling) with great success, both retrospectively and prospectively. Our results also highlight that a transfer learning approach combined with data augmentation improves the overall reconstruction performances, even when only small LF training datasets are available.