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The study of articulatory gestures has a wide spectrum of applications, notably in speech production and recognition. Sets of phonemes, as well as their articulation, are language-specific; however, existing MRI databases mostly include English speakers. In our present work, we introduce a dataset acquired with MRI from 10 healthy native French speakers. A corpus consisting of synthetic sentences was used to ensure a good coverage of the French phonetic context. A real-time MRI technology with temporal resolution of 20 ms was used to acquire vocal tract images of the participants speaking. The sound was recorded simultaneously with MRI, denoised and temporally aligned with the images. The speech was transcribed to obtain phoneme-wise segmentation of sound. We also acquired static 3D MR images for a wide list of French phonemes. In addition, we include annotations of spontaneous swallowing., Measurement(s)Vocal tract images • SpeechTechnology Type(s)Magnetic Resonance Imaging • Microphone DeviceSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16404453

A Magnetic Resonance Imaging (MRI) scanner uses three different electromagnetic fields (EMF) to produce body images: a static permanent magnetic field (MF), several pulsed magnetic gradients, and a radiofrequency pulse. As a result, any occupation that includes an MRI exposes workers to a strong MF. The World Health Organization has now given the monitoring of occupational EMF exposure a high priority. One design for a low-cost, compact MF exposure monitor (« MR exposimeter ») uses a set of three orthogonally assembled Hall sensors. However, at such a strong EMF exposure intensity, the non-linearity and non-orthogonality (misalignment between the three Hall sensors) have an impact on the accuracy of EMF measurement. Therefore, a sensor characterization was performed in order to link Hall-effect output voltage to MF intensity. The sensor was then calibrated using an orthogonalization matrix and an offset vector. For each sensor configuration, the matrix and vector parameters were optimized with a calibration set generated by the movement of a three-axis sensor inside homogeneous MF areas. Once calibrated, the sensor was tested at different MF intensities and returned accuracy improvements. This calibration procedure was tested on synthetic data and performed on experimental data. The calibration parameters can be easily reused by the user, and their stability could be used as a quality control sensor. Finally, real-time monitoring test for static MF exposure was completed and validated on an MRI worker during a typical working day. Bioelectromagnetics. 39:108-119, 2018. © 2018 Wiley Periodicals, Inc.

Sorti le 3 aout 2016 et applicable au premier janvier 2017, le decret 2016–1074 etablit des regles et recommandations a suivre pour proteger les travailleurs face aux risques dus aux champs electromagnetiques. Transposant la directive europeenne 2013/35/UE, il concerne tout employeur et impose au minimum l'etablissement d'une evaluation des risques. Les unites, clinique ou de recherche, utilisant des dispositifs d'imagerie par resonance magnetique (IRM) sont particulierement concernees. En effet, cette modalite d'imagerie emet des champs electromagnetiques susceptibles d'engendrer des niveaux d'exposition des travailleurs depassant les valeurs declenchant l'action et les valeurs limites d'exposition definies par la directive et le decret. Une section de ce dernier lui est d'ailleurs entierement consacree. Le present document propose, en premier lieu, une analyse detaillee du decret 2016–1074 et des obligations de l'employeur. Il propose, dans un second temps, une analyse concernant la mise en application de cette directive et du decret associe pour le dispositif particulier qu'est l'IRM.

International audience; Worker exposure to electromagnetic fields (EMF) is a growing concern of international commissions. A European directive from 2013 (2013/35/EU) recommend to estimate or measure EMF exposure of all exposed workers. Magnetic resonance imaging (MRI) workers are specially concerned by this point because they work all day long in the vicinity of a very strong magnet (generally 1.5 or 3 T), which cannot be turned off. Setting up a magnetic field monitoring device on these workers would therefore be a good way to ensure their security. European directive threshold adequacy could then be verified. But this verification does not ensure a complete analysis of the worker exposure. Such an analysis based on quality control charts and exposure time's metrics has been described in this paper. The proposed magnetic field exposure analysis has additionally been tested on a long-term exposure follow-up of 18 MRI workers during 2 months.

International audience; We present an algorithm for augmenting the shape of the vocal tract using 3D static and 2D dynamic speech MRI data. While static 3D images have better resolution and provide spatial information, 2D dynamic images capture the transitions. The aim of this work is to combine strong points of these two types of data to obtain better image quality of 2D dynamic images and extend the 2D dynamic images to the 3D domain. To produce a 3D dynamic consonant-vowel (CV) sequence, our algorithm takes as input the 2D CV transition and the static 3D targets for C and V. To obtain the enhanced sequence of images , the first step is to find a transformation between the 2D images and the mid-sagittal slice of the acoustically corresponding 3D image stack, and then find a transformation between neighbouring sagittal slices in the 3D static image stack. Combination of these transformations allows producing the final set of images. In the present study we first examined the transformation from the 3D mid-sagittal frame to the 2D video in order to improve image quality and then we examined the extension of the 2D video to the 3rd dimension with the aim to enrich spatial information.

International audience; Objective: Despite being routinely acquired during MRI examinations for triggering or monitoring purposes, electrocardiogram (ECG) signal recording and analysis remain challenging due to the inherent magnetic environment of an MRI scanner. The ECG signals are particularly distorted by the induction of electrical fields in the body by the MRI gradients. In this study, we propose a new hardware and software solution for the acquisition of ECG signal during MRI up to 3 T.Approach: Instead of restricting the sensor bandwidth to limit these gradient artifacts, the new sensor architecture has a higher bandwidth, higher sampling frequency and larger input dynamics, in order to acquire the ECG signals and the gradient artifacts more precisely. Signal processing based on a novel detection algorithm and blanking are then applied for improved artifact suppression.Main results: The proposed sensor allows the gradient artifacts to be acquired more precisely, and these artifacts are recorded with peak-to-peak amplitudes two orders of magnitude larger than for QRS complexes. The proposed method outperforms a state-of-the-art approach both in terms of signal quality (+9% 'SNR') and accuracy of QRS detection (+11%).Significance: The proposed hardware and software solutions open the way for the acquisition of high-quality of ECG gating in MRI, and improved diagnostic quality of ECG signals in MRI.

Exploiting redundancies between multiple images of an MRI examination can be formalized as the joint reconstruction of these images. The anatomy is preserved indeed so that specific constraints can be implemented (e.g. most of the features or spatial gradients should be in the same place in all these images) and only the contrast changes from one image to another need to be encoded. The application of this concept is particularly challenging in cardiovascular and body imaging due to the complex organ deformations, especially with the patient breathing. In this study a joint optimization framework is proposed for reconstructing multiple MR images together with a nonrigid motion model. The motion model takes into account both intra-image and inter-image motion and therefore can correct for most ghosting/blurring artifacts and misregistration between images. The framework was validated with free-breathing myocardial ${\rm T}_{2}$ mapping experiments from nine heart transplant patients at 1.5 T. Results showed improved image quality and excellent image alignment with the multi-image reconstruction compared to the independent reconstruction of each image. Segment-wise myocardial ${\rm T}_{2}$ values were in good agreement with the reference values obtained from multiple breath-holds (62.5 $\pm$ 11.1 ms against 62.2 $\pm$ 11.2 ms which was not significant with ${\rm p}=0.49$ ).

International audience; Purpose: Segmentation of cardiac cine MRI data is routinely used for the volumetric analysis of cardiac function. Conventionally, 2D contours are drawn on short-axis (SAX) image stacks with relatively thick slices (typically 8 mm). Here, an acquisition/reconstruction strategy is used for obtaining isotropic 3D cine datasets; reformatted slices are then used to optimize the manual segmentation workflow.Methods: Isotropic 3D cine datasets were obtained from multiple 2D cine stacks (acquired during free-breathing in SAX and long-axis (LAX) orientations) using nonrigid motion correction (cine-GRICS method) and super-resolution. Several manual segmentation strategies were then compared, including conventional SAX segmentation, LAX segmentation in three views only, and combinations of SAX and LAX slices. An implicit B-spline surface reconstruction algorithm is proposed to reconstruct the left ventricular cavity surface from the sparse set of 2D contours.Results: All tested sparse segmentation strategies were in good agreement, with Dice scores above 0.9 despite using fewer slices (3-6 sparse slices instead of 8-10 contiguous SAX slices). When compared to independent phase-contrast flow measurements, stroke volumes computed from four or six sparse slices had slightly higher precision than conventional SAX segmentation (error standard deviation of 5.4 mL against 6.1 mL) at the cost of slightly lower accuracy (bias of -1.2 mL against 0.2 mL). Functional parameters also showed a trend to improved precision, including end-diastolic volumes, end-systolic volumes, and ejection fractions).Conclusion: The postprocessing workflow of 3D isotropic cardiac imaging strategies can be optimized using sparse segmentation and 3D surface reconstruction. Magn Reson Med 79:2665-2675, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

International audience; The paper presents a method to acquire articulatory data from a sequence of MRI images at a high framerate. The acquisition rate is enhanced by partially collecting data in the kt-space. The combination of compressed sensing technique, along with homodyne reconstruction, enables the missing data to be recovered. The good reconstruction is guaranteed by an appropriate design of the sampling pattern. It is based on a pseudo-random Cartesian scheme, where each line is partially acquired for use of the homodyne reconstruction, and where the lines are pseudo-randomly sampled: central lines are constantly acquired and the sampling density decreases as the lines are far from the center. Application on real speech data show that the framework enables dynamic sequences of vocal tract images to be recovered at a framerate higher than 30 frames per second and with a spatial resolution of 1 mm. A method to extract articulatory data from contour identification is presented. It is intended, in fine, to be used for the creation of a large database of articulatory data.

Purpose: To assess cardiac function by means of a novel free-breathing cardiac magnetic resonance imaging (MRI) strategy. Materials and Methods: A stack of ungated 2D steady-state free precession (SSFP) slices was acquired during free breathing and reconstructed as cardiac cine imaging based on the generalized reconstruction by inversion of coupled systems (GRICS). A motion-compensated sliding window approach allows reconstructing cine movies with most motion artifacts cancelled. The proposed reconstruction uses prior knowledge from respiratory belts and electrocardiogram recordings and features a piecewise linear model that relates the electrocardiogram signal to cardiac displacements. The free-breathing protocol was validated in six subjects against a standard breath-held protocol. Results: Image sharpness, as assessed by the image gradient entropy, was comparable to that of breath-held images and significantly better than in uncorrected images. Volumetric parameters of cardiac function in the left ventricle (LV) and right ventricle (RV) were similar, including end-systolic volumes, end-diastolic volumes and mass, stroke volumes, and ejection fractions (with differences of 3% ± 2.4 in the LV and 2.9% ± 4.4 in the RV). The duration of the free-breathing protocol was nearly the same as the breath-held protocol. Conclusion: Free-breathing cine-GRICS enables accurate assessment of volumetric parameters of cardiac function with efficient correction of motion. J. Magn. Reson. Imaging 2012;340-351. © 2011 Wiley Periodicals, Inc.

Black Blood Fast Spin Echo imaging of the heart is usually performed during mid-diastolic rest. This is a direct consequence of the long inversion time required to suppress the blood signal, which is constrained by the T(1) of the blood, and of the heart rate. To overcome these constraints, and to acquire black blood images in the end-systolic rest period, a new approach is introduced aiming at adaptively predicting the best time to prepare and acquire MR signals. It is based on a RR interval prediction algorithm and on a cardiac cycle model. The proposed method was applied to 14 healthy volunteers and is compared to a simple alternative method using a fixed delay and to the standard black blood imaging method for imaging in the mid-diastolic rest period. Results show that the proposed method offers an increased robustness in terms of trigger delay error and image quality compared to the tested simple alternative. Also, it has been shown by qualitative analysis done by an experienced observer that the right ventricle, especially the thin right ventricle free wall, is better depicted with our method than with the standard mid-diastolic rest acquisition.

This paper describes a rigorous framework for reconstructing MR images of the heart, acquired continuously over the cardiac and respiratory cycle. The framework generalizes existing techniques, commonly referred to as retrospective gating, and is based on the properties of reproducing kernel Hilbert spaces. The reconstruction problem is formulated as a moment problem in a multidimensional reproducing kernel Hilbert spaces (a two-dimensional space for cardiac and respiratory resolved imaging). Several reproducing kernel Hilbert spaces were tested and compared, including those corresponding to commonly used interpolation techniques (sinc-based and splines kernels) and a more specific kernel allowed by the framework (based on a first-order Sobolev RKHS). The Sobolev reproducing kernel Hilbert spaces was shown to allow improved reconstructions in both simulated and real data from healthy volunteers, acquired in free breathing.

A reconstruction strategy is proposed for physiological motion correction, which overcomes many limitations of existing techniques. The method is based on a general framework allowing correction for arbitrary motion–nonrigid or affine, making it suitable for cardiac or abdominal imaging, in the context of multiple coil, arbitrarily sampled acquisition. A model is required to predict motion in the field of view at each sample time point, based on prior knowledge provided by external sensors. A theoretical study is carried out to analyze the influence of motion prediction errors. Small errors are shown to propagate linearly in that reconstruction algorithm, and thus induce a reconstruction residue that is bounded (stability). Furthermore, optimization of the motion model is proposed in order to minimize this residue. This leads to reformulating reconstruction as two inverse problems which are coupled: motion-compensated reconstruction (known motion) and model optimization (known image). A fixed-point multiresolution scheme is described for inverting these two coupled systems. This framework is shown to allow fully autocalibrated reconstructions, as coil sensitivities and motion model coefficients are determined directly from the corrupted raw data. The theory is validated with real cardiac and abdominal data from healthy volunteers, acquired in free-breathing. Magn Reson Med 60:146–157, 2008. © 2008 Wiley-Liss, Inc.

Background During pediatric cardiac Cine-MRI, data acquired during cycles of different lengths must be combined. Feinstein’s model is used to project multiple cardiac cycles of variable lengths into a mean cycle. Methods 1/The temporal errors during Feinstein’s projection were computed in 306 cardiac cycles fully characterized by tissue Doppler imaging with 6-phase analysis (from a population of 7 children and young adults). 2/The effects of these temporal errors on tissue velocities were assessed by simulating a typical tissue phase mapping acquisition and reconstruction. 3/Myocardial velocities curves, extracted from high-resolution phase-contrast cine images, were compared for the 6 volunteers with lowest and highest heart rate variability, within a population of 36young adults. Results 1/The mean of temporal misalignments was 30ms over the cardiac cycle but reached 60ms during early diastole. 2/During phase contrast MRI simulation, early diastole velocity peaks were diminished by 5cm/s leading to virtual disappearance of isovolumic relaxation peaks. 3/The smoothing and erasing of isovolumic relaxation peaks was confirmed on tissue phase mapping velocity curves, between subjects with low and high heart rate variability (p=0.05). Conclusions Feinstein cardiac model creates temporal misalignments that impair high temporal resolution (notably for phase contrast cine imaging) in a population of high heart rate variations such as in paediatry (figure next page). Download : Download high-res image (187KB) Download : Download full-size image Abstract 0217 – Figure: Velocity curves with/without heart rate variation

Exploiting redundancies between multiple images of an MRI examination can be formalized as the joint reconstruction of these images. The anatomy is preserved indeed so that specific constraints can be implemented (e.g. most of the features or spatial gradients should be in the same place in all these images) and only the contrast changes from one image to another need to be encoded. The application of this concept is particularly challenging in cardiovascular and body imaging due to the complex organ deformations, especially with the patient breathing. In this study a joint optimization framework is proposed for reconstructing multiple MR images together with a nonrigid motion model. The motion model takes into account both intra-image and inter-image motion and therefore can correct for most ghosting/blurring artifacts and misregistration between images. The framework was validated with free-breathing myocardial T2 mapping experiments from nine heart transplant patients at 1.5 T. Results showed improved image quality and excellent image alignment with the multi-image reconstruction compared to the independent reconstruction of each image. Segment-wise myocardial T2 values were in good agreement with the reference values obtained from multiple breath-holds (62.5 ± 11.1 ms against 62.2 ± 11.2 ms which was not significant with p=0.49).

Introduction MRI is nowadays an indispensable technique with its excellent resolution achieved without ionizing radiations. Active implantable medical devices exist (such as pacemakers) which are MRI-compatible and do not show any hazardous local heating when interacting with the MRI machine radiofrequency, but multiple devices, as when two leads are side by side, were studied [1] , [2] but are not know enough to allow the implanted patients in these cases to undergo an MRI scan. The work presented here focuses on the coupling effects and the resulting heating between two leads, by simulation and experiments. Material and methods An ASTM [3] phantom inside a radiofrequency “birdcage” antenna was modeled with the CST Microwave Studio software (CST GmbH, Darmstadt, Germany). Two simples metallic cables, isolated and 5 mm bare at one tip were inserted in the phantom, spaced with 2.5 mm. One of them was also isolated at the upper extremity (referred to as “capped”) while the other one had its two tips bare (referred to as “uncapped”). An electromagnetic simulation was made and its results were used to launch a thermal simulation. With the latter, the temperature variations versus time were collected at both cables’ tips. The same process was repeated for each cable alone. Corresponding experiment were made with a Signa HDx 1.5 T MRI machine (GE Healthcare Technologies, Milwaukee, WI), an ASTM phantom filled with gel and cables made to match the simulations. An FSE sequence was used, generating high radiofrequency heating measured by optical temperature probes. Results Simulations and experiments show a coupling between the two cables: it is indeed observed that the “capped” cable heating is halved in presence of the “uncapped” cable. It is also observed that alone, the “capped” cable heats more that the “uncapped” one, but once together the higher heating is at the “uncapped” cable’s tip (see the appendix for the curves). Conclusion This study highlights the existence of lead coupling, such as it could occur in a patient’s body. This coupling could be explained by a theoretical model of two antennas subjected to radiofrequency, including mutual inductance and capacitance between the cables. Moreover, experiments on implant leads such as pacemaker leads could allow concluding on the occurrence of the phenomenon in more concrete cases. In the end, understanding this kind of interactions will allow a evolution in the design of medical devices, for each patient to be allowed to undergo an MRI scan safely, whatever his or her implants. Acknowledgement The authors thank the Region Lorraine and FEDER for financial support. Download : Download high-res image (188KB) Download : Download full-size image

International audience; Non-invasive quantitative assessment of articular cartilage integrity is essential for early detection and evaluation of osteoarthritis (OA) and for the follow-up of stem-cell-driven cartilage engineering. In this study, we investigated the feasibility of exploiting diffusion tensor imaging (DTI) on porcine knee joints with a clinical magnetic resonance (MR) scanner to extract micro-structural information in order to complement biochemical information quantified by T2 maps. We propose an MR protocol for quantifying T2 and cartilage microstructure with diffusion MR on a clinical scanner. Preliminary results were obtained on four pig knee joints using a 3 T GE clinical MRI scanner and an 8-channel knee coil array. The measured cartilage volume, T2 values, apparent diffusion coefficient and fractional anisotropy (FA) of femoral and tibial cartilage were respectively 9.8/2.3 mm2, 67.0/56.1 ms, 1.3/1.3×10-3 mm2/s and 0.4/0.3. This new protocol has the potential to be combined in vivo with quantitative assessment of both cartilage degradation and restoration in osteoarthritis.

Magnetic resonance images are affected by motion artefacts due to breathing and cardiac beating that occur during the acquisition. Methods for joint reconstruction of image and motion have been proposed recently. Such optimization problems are ill-conditioned, therefore regularization methods are required such as motion smoothness constraints using the Tikhonov method. However with Tikhonov methods the solution often relies on a good choice of the regularization parameter micron, especially in large parameter search spaces (e.g., in 3D reconstructions). In this paper, we propose an adaptive, implicit regularization method which results in subject-specific, spatially varying smoothness constraints on the motion model. It is based on the idea of solving for motion only in certain key points that form a mesh. A practical algorithm is proposed for generating this mesh automatically. The proposed method is shown to have a better convergence rate than the Tikhonov method, both in silico and in vivo. The accuracy of the reconstructed image and motion is also improved.

Object Quantitative T 2 measurement is applied in cardiac Magnetic Resonance Imaging (MRI) for the diagnosis and follow-up of myocardial pathologies. Standard Electrocardiogram (ECG)-gated fast spin echo pulse sequences can be used clinically for T 2 assessment, with multiple breath-holds. However, heart rate is subject to physiological variability, which causes repetition time variations and affects the recovery of longitudinal magnetization between TR periods. Materials and methods The bias caused by heart rate variability on quantitative T 2 measurements is evaluated for fast spin echo pulse sequence. Its retrospective correction based on an effective TR is proposed. Heart rate variations during breath-holds are provided by the ECG recordings from healthy volunteers. T 2 measurements were performed on a phantom with known T 2 values, by synchronizing the sequence with the recorded ECG. Cardiac T 2 measurements were performed twice on six volunteers. The impact of T 1 on T 2 is also studied. Results Maximum error in T 2 is 26% for phantoms and 18% for myocardial measurement. It is reduced by the proposed compensation method to 20% for phantoms and 10% for in vivo measurements. Only approximate knowledge of T 1 is needed for T 2 correction. Conclusion Heart rate variability may cause a bias in T2 measurement with ECG-gated FSE. It needs to be taken into account to avoid a misleading diagnosis from the measurements.

Summary This study demonstrates the feasibility of free-breathing phase-contrast CINE MRI without averaging. A new version of the CINE GRICS algorithm[1] was used to correct for motion. Background Phase-contrast MRI encodes speed and direction of moving spins by means of toggling a bipolar gradient. It is a valuable tool for assessing conditions affecting the vascular system by measuring the velocity of flowing blood[2]. Clinically, this sequence is performed in breath-hold or in free breathing but, in the latter case, using signal averaging. We propose to demonstrate the feasibility of free-breathing phase-contrast CINE MRI without averaging exploiting the acquisition redundancy by applying a new version of the CINE GRICS algorithm[1] to correct for motion. Methods Cardiac examination (approved by our local ethics committee) was performed on one normal volunteer during which three 2D phase-contrast CINE MRI sequences (common parameters: 256x128 acquisition matrix, 6 views per segment (vps), 32 reconstructed cardiac phases, 150 cm/sec VENC, slice direction velocity encoding, 5 mm slice thickness, 44 cm FOV, 62.5 kHz bandwidth, 3.05/8.08 ms TE/TR, 15° flip angle) were acquired on a 3T scanner (Signa HDxt, GE Healthcare, Milwaukee, WI) with a 8-element cardiac coil : (1) breath-held (2) averaged (3 NEX) in free breathing (3) in free breathing storing the raw data of 3 NEX to an external computer for offline processing. Signals from a respiratory belt were carried by a custom Maglife patient monitoring system (Schiller Medical, France) and recorded with a dedicated home-made hardware. Offline processing consisted of splitting the raw data from the 2 velocity encoding steps thus giving 2 sets of

Magnetic resonance images are affected by motion artefacts due to breathing and cardiac beating that occur during the acquisition. Methods for joint reconstruction of image and motion have been proposed recently. Such optimization problems are ill-conditioned, therefore regularization methods are required such as motion smoothness constraints using the Tikhonov method. However with Tikhonov methods the solution often relies on a good choice of the regularization parameter μ, especially in large parameter search spaces (e.g. in 3D reconstructions). In this paper, we propose an adaptive, implicit regularization method which results in subject-specific, spatially varying smoothness constraints on the motion model. It is based on the idea of solving for motion only in certain key points that form a mesh. A practical algorithm is proposed for generating this mesh automatically. The proposed method is shown to have a better convergence rate than the Tikhonov method, both in silico and in vivo. The accuracy of the reconstructed image and motion is also improved.

International audience; Reproducibility of the manual assessment of right ventricle volumes by short-axis cine-MRI remains low and is often attributed to the difficulty in separating the right atrium from the ventricle. This study was designed to evaluate the regional interobserver variability of the right ventricle volume assessment to identify segmentation zones with the highest interobserver variability. Short-axis views of 90 right ventricles (30 hypertrophic, 30 dilated, and 30 normal) were acquired with 2D steady-state free precession sequences at 1.5 T and were manually segmented by two observers. The two segmentations were compared and the variations were quantified with a variation score based on the Hausdorff distance between the two segmentations and the interobserver 95% limits of concordance of the global volumes. The right ventricles were semiautomatically split into four subregions: apex, mid-ventricle, tricuspid zone, and infundibulum. These four subregions represented 11%, 34%, 36%, and 19% of the volume but, respectively, yielded variation scores of 8%, 16%, 42%, and 34%. The infundibulum yielded the highest interobserver regional variability although its variation score remained comparable to the tricuspid zone due to its lower volume. These results emphasize the importance of standardizing the segmentation of the infundibulum and the tricuspid zone to improve reproducibility.

This paper presents a framework allowing parallel MRI to be optimized. Parallel imaging relies on good coil sensitivity map estimates. As these sensitivities are determined experimentally, errors may occur during their assessment, whether using prior calibration (due to patient motion between calibration and actual scan), or autocalibration (due to lower resolution, suboptimal estimates). Here we reformulate reconstruction as a coupled inverse problem, consisting of simultaneously solving the parallel imaging problem, based on SENSE algorithm, and minimizing the propagation of sensitivity map errors in that reconstruction. The problem is practically solved using a multiresolution fixed-point iterative method, producing both the reconstructed image and optimized sensitivity maps. The method was validated by comparing sensitivity maps and reconstructed images obtained by standard SENSE reconstruction, based on a reduced number of autocalibration signal (ACS) data, to those obtained by the proposed method, starting from the same ACS data as initial guess.

A multimodality platform (CT, PET, Radiotherapy) has been developed in order to move phantoms (maximum weight: 70kg). This allows the study of the influence of motion on image quality. The translation system (160 mm in the z axis, maximal speed of 50 mm × s -1 ) was controlled by a computer via a NI Motion Controller PCI 7344 (National Instrument, TX, USA). As an initial experiment, an anthropomorphic cardiac CT phantom (QRM, Moehrendorf, Germany) was moved linearly with speeds of 5, 10 and 20 mm × s -1 . Acquisitions were done on a Siemens Somatom Volume Zoom CT Scanner. To compare dynamic and static images, mutual information, correlation coefficient, standard deviation, volume computation and radiologist scoring were conducted. The mean position error of the platform was 0.1mm ± 0.04. Automatic evaluation of the image quality and/or the blurring is not easy. As predicted, we found an increase in artifacts with the speed of the phantom. The platform allows us to simulate physiological motions (respiratory and cardiac) in order to study their real influence on image quality and to correct them. We can already produce z axis physiological motion with the platform. More degrees of freedom (y and z rotations, x and y translations) will be added to improve the simulation of physiological motions.

International audience; Double Inversion Recovery Fast Spin Echo (DIR-FSE) sequences, resulting in black-blood images, are widespread in cardiac exams [1] as high resolution and great contrast between heart cavities and walls are achieved. For these sequences, DIR pulses are generally played on the R wave and the inversion time (TI) needed to cancel blood signal (~500ms) only allows diastolic view of the heart. Cardiac contraction is complete at end systole so myocardium can be better observed during this short phase. To perform systolic acquisitions, DIR pulses have to be placed before the R wave in the previous heart cycle and RR interval prediction is mandatory. Moreover, as systole is generally shorter than diastole, shorter echo trains are desirable, resulting in longer acquisition time incompatible with breath hold. A method which combines (i) heart rate prediction [2], (ii) respiratory motion estimation [3] and (iii )motion compensated construction [4] is presented. It allows free breathing black-blood systolic imaging and has been tested on five subjects.

International audience; Cardiac MRI is still challenging due to the perpetual heart motion. In order to avoid cardiac motion artifacts, acquisitions are synchronized with heart activity, generally by triggering on R-waves of the Electrocardiogram (ECG). Double Inversion Recovery Fast Spin Echo (DIR-FSE) sequences, resulting in black-blood images, require furthermore specific timing. For such acquisitions, inversion time (TI) is needed to cancel blood signals (~500ms) [1], making acquisitions in the first 500ms of the cardiac cycle impossible. Black-blood imaging allows then only diastolic view of the heart. Moreover heart rate (HR) variability has been shown to be important during breath-holds [2] making cardiac synchronization even more complicated. In this paper, a RR interval prediction method has been implemented, which permits to launch DIR pulses before R waves and thus enables black blood systolic imaging.

International audience

Methods Eighteen healthy volunteers underwent cardiac MRI examination on a Signa HDxt 3T scanner (General Electric, Waukesha). A phase contrast sequence modified to acquire only the central k-space line was used in a midventricular small axis scan plane with through-plane velocity encoding during 128 heartbeats. The frequency encoding direction was angulated to encompass the projection of the left ventricular outflow tract plane (Figure 1). Relevant parameters were: 256-point frequency k-space size, 35 cm FOV, 1 view per segment, 150 cm/s velocity encoding and 7 ms TR. Data were Fourier transformed into 1D+t image space, subjected to SVD decomposition for automatic spatial segmentation and finally automatic temporal domain peak detection. This process lead to the measurement of four durations for each heartbeat (RR): IsoVolumic Contraction (IVC), Systolic Ejection (SE), IsoVolumic Relaxation (IVR), and Diastolic Diastasis (DD). For every cardiac cycle, the results of the automatic detection were quality controlled by a physician who could either discard the data, correct or accept it. Myocardiac Performance Index (MPI) [4] was computed as (IVC+IVR)/SE as well as normalized systole duration (IVC+SE)/RR and normalized diastasis duration DD/RR. These values were checked

National audience; L'imagerie par résonance magnétique (IRM) du coeur reste difficile. Les solutions retenues dans la pratique clinique pour limiter les problèmes liées aux mouvements sont l'apnée et la synchronisation cardiaque. En imagerie cardiaque, la séquence Double Inversion Récupération Fast Spin Echo (DIR- FSE) est couramment utilisée [1]. Cependant, cette séquence, synchronisée avec l'activité cardiaque, nécessite un temps de préparation long (TI) ce qui contraint le temps entre l'onde R et l'acquisition (TD) à être long. Par conséquent, cette séquence n'est utilisée qu'en diastole. De plus, les variations de rythme cardiaque instantané (temps entre 2 ondes R consécutives) ne sont pas prises en compte (Figure 1-A et 1-B). Afin de passer outre ces limitations, nous désirons mettre en oeuvre une technique adaptative pour utiliser les séquences DIR-FSE en systole (volume cardiaque minimum et constant). Ceci a deux buts : 1. étudier et diagnostiquer certaines maladies en systole et 2. étudier les propriétés magnétiques du coeur en systole et diastole.