Thoracic aortic aneurysms (TAA) are pathological diseases whose biomechanical behavior is often studied through complex computational models to improve clinical diagnosis and decision-making. We explore an approach based on the use of MRI imaging data that enables the implementation of wall displacement, thereby allowing us to propose a patient-specific model while limiting the computational cost of fluid-structure interaction modeling. To this end, i) the displacement of TAA walls is determined using magnetic resonance imaging (MRI) with the appropriate spatio-temporal resolution; ii) this is then implemented in an advanced numerical model; and iii) quantitative velocity comparisons are performed against MRI data. The results show that the 3D displacement of a pathological aorta can be captured within the limits of the best available spatial and temporal resolutions of medical images. Quantitative comparisons on velocity exhibit a mean error deviation that ranges from 7% to 21% for a transverse plane and 26% to 46% for a pseudosagittal plane. Thus using imposed displacements as boundary conditions enables heterogeneity in aortic displacements and root movements to be accounted for the first time in the literature, while reducing computational time compared to fluid-structure interaction modeling and leading to a biomimetic patient-specific model.

PURPOSE:To develop an improved post-processing pipeline for noise-robust accelerated phase-cycled Cartesian Single (SQ) and Triple Quantum (TQ) sodium (23Na) Magnetic Resonance Imaging (MRI) of in vivo human brain at 7 T. THEORY AND METHODS:Our pipeline aims to tackle the challenges of 23Na Multi-Quantum Coherences (MQC) MRI including low Signal-to-Noise Ratio (SNR) and time-consuming Radiofrequency (RF) phase-cycling. Our method combines low-rank k-space denoising for SNR enhancement with Dynamic Mode Decomposition (DMD) to robustly separate SQ and TQ signal components. This separation is crucial for computing the TQ/SQ ratio, a key parameter of 23Na MQC MRI. We validated our pipeline in silico, in vitro and in vivo in healthy volunteers, comparing it with conventional denoising and Fourier transform (FT) methods. Additionally, we assessed its robustness through ablation experiments simulating a corrupted RF phase-cycle step. RESULTS:Our denoising algorithm doubled SNR compared to non-denoised images and enhanced SNR by up to 29% compared to Wavelet denoising. The low-rank approach produced high-quality images even at later echo times, allowing reduced signal averaging. DMD effectively separated the SQ and TQ signals, even with missing RF phase cycle steps, resulting in superior Structural Similarity (SSIM) of 0.89±0.024 and lower Root Mean Squared Error (RMSE) of 0.055±0.008 compared to conventional FT methods (SSIM=0.71±0.061, RMSE=0.144±0.036). This pipeline enabled high-quality 8x8x15mm3 in vivo 23Na MQC MRI, with a reduction in acquisition time from 48 to 10 min at 7 T. CONCLUSION:The proposed pipeline improves robustness in 23Na MQC MRI by exploiting low-rank properties to denoise signals and DMD to effectively separate SQ and TQ signals. This approach ensures high-quality MR images of both SQ and TQ components, even in accelerated and incomplete RF phase-cycling cases.

Introduction: In sodium (23Na) magnetic resonance imaging (MRI), partial volume effects (PVE) are one of the most common causes of errors in the in vivo quantification of tissue sodium concentration (TSC). Advanced image reconstruction algorithms, such as compressed sensing (CS), have the potential to reduce PVE. Therefore, we investigated the feasibility of using CS-based methods to improve image quality and TSC quantification accuracy in patients with breast cancer. Subjects and methods: In this study, three healthy participants and 12 female participants with breast cancer were examined on a 7T MRI scanner. 23Na-MRI images were reconstructed using weighted total variation (wTV), directional total variation (dTV), anatomically guided total variation (AG-TV) and adaptive combine (ADC) methods. The consistency of tumor volume delineations based on sodium data was assessed using the Dice score, and TSC quantification was performed for various image reconstruction methods. Pearsons correlation coefficients were calculated to assess the relationships between wTV, dTV, AG-TV, and ADC values. Results: All methods provided breast MRI images with well-preserved sodium signal and tissue structures. The mean Dice scores for wTV, dTV, and AG-TV were 65

PURPOSE:To introduce Double Inversion Recovery (DIR) preparations for myocardial Arterial Spin Labeling (myoASL) for mitigation of heart rate (HR) variability induced physiological noise (PN). METHODS:DIR-labeling was implemented for double ECG-gated myoASL-sequences and compared with conventional Flow-sensitive Alternating Inversion Recovery (FAIR) labeling using single inversions. In DIR-preparations, the FAIR-inversion pulses were immediately followed by an identical reinversion pulse, applied either slice-selectively or nonselectively. Bloch-equation-based simulation and phantom experiments were performed to evaluate the PN and SNR across a range of HR variabilities. Data from six healthy subjects were acquired to evaluate myocardial blood flow (MBF), PN, and SNR in vivo. RESULTS:Simulation experiments showed that the average MBF values remained nearly constant across the range of HR variabilities and were comparable across all three sequences. However, DIR-labeling allowed for greater recovery of the myocardial background signal, which mitigates the sensitivity to HR-dependent changes in the inversion time. Consequently, PN in the presence of HR variability was substantially reduced with DIR-labeling. For HR variabilities corresponding to the mean value observed in vivo, this resulted in a simulated SNR gain of 1.79 ± $$ \pm $$ 0.90 for selective and 1.55 ± $$ \pm $$ 0.77 for nonselective DIR-labeling. In vivo, DIR-labeling showed reduced PN, with 53% ( p < 0 . 05 $$ p<0.05 $$ )/44% ( p = 0 . 16 $$ p=0.16 $$ ) less PN compared with conventional FAIR-myoASL, leading to an average SNR gain of 1.47 ± $$ \pm $$ 0.63 ( p = 0 . 09 $$ p=0.09 $$ )/1.32 ± $$ \pm $$ 0.57 ( p = 0 . 84 $$ p=0.84 $$ ) with selective/nonselective reinversions. CONCLUSION:The proposed DIR-preparations reduce sensitivity to HR variations and alleviate PN in double ECG-gated myoASL, improving the precision of myoASL-based perfusion quantification.

Introduction Les troubles de la statique pelvienne sont fréquents et leur prise en charge reste un sujet de controverse. Leur physiopathologie est mal connue [1]. L’observation tridimensionnelle des déplacements et déformations des organes pelviens en poussée pourrait aider à mieux les appréhender et les traiter [2], [3]. Méthodes Il s’agit d’une étude de faisabilité chez des volontaires saines. Une IRM dynamique en 3D dans cinq plans de l’espace avec 2 acquisitions par seconde a été réalisée chez chaque volontaire au repos et en poussée, avec balisage rectal et vaginal. Pour chaque volontaire, un modèle 3D spécifique a été élaboré par segmentation suivant une méthodologie éprouvée pour l’étude 3D de la vessie au cours d’une poussée abdominale [4]. Résultats Douze volontaires saines ont été incluses dans cette étude. Pour 100 % des volontaires, les viscères pelviens ont pu être segmentés en totalité, permettant une analyse dynamique dans les 3 plans de l’espace des déplacements et des déformations des organes pelviens. La durée moyenne de segmentation complète d’une poussée était de 153minutes. La limite supérieure du rectum et le plancher pelvien étaient les plus difficiles à identifier et à segmenter. Discussion Le caractère chronophage de cette technique est actuellement une limite pour son utilisation en pratique clinique de routine. Le recours au deep learning pourrait pallier cet écueil. Sa faisabilité chez des patientes présentant des troubles de la statique pelvienne reste à démontrer. Conclusion Cette étude est la première à démontrer la faisabilité de l’étude tridimensionnelle des déplacements et déformations des organes pelviens à partir d’une IRM pelvienne dynamique. La technique d’observation doit être éprouvée chez les patientes porteuses d’un trouble de la statique pelvienne et optimisée avant une implantation en pratique courante.

Purpose: To investigate and mitigate the influence of physiological and acquisition-related parameters on myocardial blood flow (MBF) measurements obtained with myocardial Arterial Spin Labeling (myoASL). Methods: A Flow-sensitive Alternating Inversion Recovery (FAIR) myoASL sequence with bSSFP and spoiled GRE (spGRE) readout is investigated for MBF quantification. Bloch-equation simulations and phantom experiments were performed to evaluate how variations in acquisition flip angle (FA), acquisition matrix size (AMS), heart rate (HR) and blood T-1 relaxation time (T-1,T-B) affect quantification of myoASL-MBF. In vivo myoASL-images were acquired in nine healthy subjects. A corrected MBF quantification approach was proposed based on subject-specific T-1,T-B values and, for spGRE imaging, subtracting an additional saturation-prepared baseline from the original baseline signal. Results: Simulated and phantom experiments showed a strong dependence on AMS and FA (R-2>0.73), which was eliminated in simulations and alleviated in phantom experiments using the proposed saturation-baseline correction in spGRE. Only a very mild HR dependence (R-2>0.59) was observed which was reduced when calculating MBF with individual T-1,T-B For corrected spGRE, in vivo mean global spGRE-MBF ranged from 0.54 to 2.59 mL/g/min and was in agreement with previously reported values. Compared to uncorrected spGRE, the intra-subject variability within a measurement (0.60 mL/g/min), between measurements (0.45 mL/g/min), as well as the inter-subject variability (1.29 mL/g/min) were improved by up to 40% and were comparable with conventional bSSFP.

Left ventricular (LV) diastolic dysfunction (DD) is an initially asymptomatic condition that can progress to heart failure, either with preserved or reduced ejection fraction. As such, DD is a growing public health problem. Impaired relaxation, the first stage of DD, is associated with altered LV filling. With progression, reducing LV compliance leads to restrictive cardiomyopathy. While cardiac magnetic resonance (CMR) imaging is the reference for LV systolic function assessment, transthoracic echocardiography (TTE) with Doppler flow measurements remains the standard for diastolic function assessment. Rather than simply replicating TTE measurements, CMR should complement and further advance TTE findings. We provide herein a step-by-step review of CMR findings in DD as well as imaging features which may help identify the underlying cause.

Multi-echo turbo-spin echo (ME-TSE) is a pulse sequence commonly used for T2 mapping in MRI. As compared to other pulse sequences such as MESE, ME-TSE is largely faster. It has been previously shown that dictionary-based T2-mapping can be used to provide accurate T2 values from MESE datasets but the corresponding accuracy on ME-TSE datasets has never been assessed. In the present study, we aimed to investigate the impact of combining effective echo signals in a ME-TSE pulse sequence on the accuracy of T2 mapping using a dictionary-based reconstruction method. We initially compared three different combinations of echo signals on phantom scans and identified the corresponding differences. We then determined the best combination among them. In the pulse sequence with an echo train length (ETL) of 3 and 3 contrasts, we found that the most accurate and homogeneous combination was achieved when the first echo was assigned to the center in the first contrast, the second echo in the second contrast, and the third echo in the third contrast. Next, we compared the use of dictionaries generated for a single slice versus multiple slices (N = 5) in the reconstruction process for this specific combination. The dictionaries were generated using a Bloch simulator, taking into account the saturation effect between slices during dictionary generation for the multi-slice case. Our results show that using single-slice dictionaries for reconstructing T2 phantom maps with no gap between slices can lead to variations in T2 values between slices. However, this variation can be reduced when using a multi-slice dictionary so that more accurate T2 values can be obtained.

Background: Metabolic diseases can negatively alter epicardial fat accumulation and composition, which can be probed using quantitative cardiac chemical shift encoded (CSE) cardiovascular magnetic resonance (CMR) by mapping proton-density fat fraction (PDFF). To obtain motion-resolved high-resolution PDFF maps, we proposed a free-running cardiac CSE-CMR framework at 3T. To employ faster bipolar readout gradients, a correction for gradient imperfections was added using the gradient impulse response function (GIRF) and evaluated on intermediate images and PDFF quantification. Methods: Ten minutes free-running cardiac 3D radial CSE-CMR acquisitions were compared in vitro and in vivo at 3T. Monopolar and bipolar readout gradient schemes provided 8 echoes (TE1/Delta TE = 1.16/1.96 ms) and 13 echoes (TE1/Delta TE = 1.12/1.07 ms), respectively. Bipolar-gradient free-running cardiac fat and water images and PDFF maps were reconstructed with or without GIRF correction. PDFF values were evaluated in silico, in vitro on a fat/water phantom, and in vivo in 10 healthy volunteers and 3 diabetic patients. Results: In monopolar mode, fat-water swaps were demonstrated in silico and confirmed in vitro. Using bipolar readout gradients, PDFF quantification was reliable and accurate with GIRF correction with a mean bias of 0.03% in silico and 0.36% in vitro while it suffered from artifacts without correction, leading to a PDFF bias of 4.9% in vitro and swaps in vivo. Using bipolar readout gradients, in vivo PDFF of epicardial adipose tissue was significantly lower compared to subcutaneous fat (80.4 +/- 7.1% vs 92.5 +/- 4.3%, P < 0.0001). Conclusions: Aiming for an accurate PDFF quantification, high-resolution free-running cardiac CSE-MRI imaging proved to benefit from bipolar echoes with k-space trajectory correction at 3T. This free-breathing acquisition framework enables to investigate epicardial adipose tissue PDFF in metabolic diseases.

Introduction and HypothesisFemale pelvic organ prolapses are common, but their treatment is challenging. Notably, diagnosis and understanding of these troubles remain incomplete. Tridimensional observations of displacement and deformation of the pelvic organs during a strain could support a better understanding and help to develop comprehensive tools for preoperative planning.MethodsThe present feasibility study evaluates tridimensional dynamic MRI in 12 healthy volunteers. Tridimensional acquisitions were approximated using five intersecting slices, each recorded twice per second. MRI was performed during rest and strain, with intrarectal and intravaginal contrast gel. Subject-specific dynamic 3D models were built for each volunteer through segmentation.ResultsFor each volunteer, pelvic organs could be segmented in three dimensions with a rate of acquisition of two cycles per second on five slices, allowing for a fluid observation of displacements and deformations during strain. Manual segmentation of a full strain required 2 h and 33 min on average. The upper limit of the rectum and the pelvic floor were the most difficult structures to identify. This technique is limited by its time-consuming manual segmentation, which impedes its implantation for routine clinical use. This method must be tried in patients with pelvic organ prolapse.ConclusionsThis multi-planar acquisition technique applied during a dynamic MRI allows for observation of displacement and deformations of pelvic organs during a strain.

PURPOSE:To develop a new sequence to simultaneously acquire Cartesian sodium (23Na) MRI and accelerated Cartesian single (SQ) and triple quantum (TQ) sodium MRI of in vivo human brain at 7 T by leveraging two dedicated low-rank reconstruction frameworks. THEORY AND METHODS:The Double Half-Echo technique enables short echo time Cartesian 23Na MRI and acquires two k-space halves, reconstructed by a low-rank coupling constraint. Additionally, three-dimensional (3D) 23Na Multi-Quantum Coherences (MQC) MRI requires multi-echo sampling paired with phase-cycling, exhibiting a redundant multidimensional space. Simultaneous Autocalibrating and k-Space Estimation (SAKE) were used to reconstruct highly undersampled 23Na MQC MRI. Reconstruction performance was assessed against five-dimensional (5D) CS, evaluating structural similarity index (SSIM), root mean squared error (RMSE), signal-to-noise ratio (SNR), and quantification of tissue sodium concentration and TQ/SQ ratio in silico, in vitro, and in vivo. RESULTS:The proposed sequence enabled the simultaneous acquisition of fully sampled 23Na MRI while leveraging prospective undersampling for 23Na MQC MRI. SAKE improved TQ image reconstruction regarding SSIM by 6% and reduced RMSE by 35% compared to 5D CS in vivo. Thanks to prospective undersampling, the spatial resolution of 23Na MQC MRI was enhanced from 8 × 8 × 15 $$ 8\times 8\times 15 $$ mm3 to 8 × 8 × 8 $$ 8\times 8\times 8 $$ mm3 while reducing acquisition time from 2 × 31 $$ 2\times 31 $$ min to 2 × 23 $$ 2\times 23 $$ min. CONCLUSION:The proposed sequence, coupled with low-rank reconstructions, provides an efficient framework for comprehensive whole-brain sodium MRI, combining TSC, T2*, and TQ/SQ ratio estimations. Additionally, low-rank matrix completion enables the reconstruction of highly undersampled 23Na MQC MRI, allowing for accelerated acquisition or enhanced spatial resolution.

Background and Objective: Pelvic floor disorders are prevalent diseases and patient care remains difficult as the dynamics of the pelvic floor remains poorly known. So far, only 2D dynamic observations of straining exercises at excretion are available in the clinics and the understanding of three-dimensional pelvic organs mechanical defects is not yet achievable. In this context, we proposed a complete methodology for the 3D representation of the non-reversible bladder deformations during exercises, directly combined with synthesized 3D representation of the location of the highest strain areas on the organ surface. Methods: Novel image segmentation and registration approaches have been combined with three geometrical configurations of up-to-date rapid dynamic multi-slices MRI acquisition for the reconstruction of real-time dynamic bladder volumes. Results: For the first time, we proposed real-time 3D deformation fields of the bladder under strain from in-bore forced breathing exercises. The potential of our method was assessed on eight control subjects undergoing forced breathing exercises. We obtained average volume deviation of the reconstructed dynamic volume of bladders around 2.5\% and high registration accuracy with mean distance values of 0.4 $\pm$ 0.3 mm and Hausdorff distance values of 2.2 $\pm$ 1.1 mm. Conclusions: Immediately transferable to the clinics with rapid acquisitions, the proposed framework represents a real advance in the field of pelvic floor disorders as it provides, for the first time, a proper 3D+t spatial tracking of bladder non-reversible deformations. This work is intended to be extended to patients with cavities filling and excretion to better characterize the degree of severity of pelvic floor pathologies for diagnostic assistance or in preoperative surgical planning.