Myocardial T1 mapping using an instantaneous signal loss simulation modeling and a Bayesian estimation method: A robust T1 extraction method free of tuning parameters.

The Instantaneous Signal Loss Simulation (InSiL) model is a promising alternative to the classical mono-exponential fitting of the Modified Look-Locker Inversion-recovery (MOLLI) sequence in cardiac T1 mapping applications, which achieves better accuracy and is less sensitive to heart rate (HR) variations. Classical non-linear least squares (NLLS) estimation methods require some parameters of the model to be fixed a priori in order to give reliable T1 estimations and avoid outliers. This introduces further bias in the estimation, reducing the advantages provided by the InSiL model. In this paper, a novel Bayesian estimation method using a hierarchical model is proposed to fit the parameters of the InSiL model. The hierarchical Bayesian modeling has a shrinkage effect that works as a regularizer for the estimated values, by pulling spurious estimated values toward the group-mean, hence reducing greatly the number of outliers. Simulations, physical phantoms, and in-vivo human cardiac data have been used to show that this approach estimates accurately all the InSiL parameters, and achieve high precision estimation of the T1 compared to the classical MOLLI model and NLLS InSiL estimation.

Alteration of skeletal muscle energy metabolism assessed by 31 P MRS in clinical routine: Part 2. Clinical application.

In this second part of a two-part paper, we intend to demonstrate the impact of the previously proposed advanced quality control pipeline. To understand its benefit and challenge the proposed methodology in a real scenario, we chose to compare the outcome when applying it to the analysis of two patient populations with significant but highly different types of fatigue: COVID-19 and multiple sclerosis (MS). 31 P-MRS was performed on a 3 T clinical MRI, in 19 COVID-19 patients, 38 MS patients, and 40 matched healthy controls. Dynamic acquisitions using an MR-compatible ergometer ran over a rest (40 s), exercise (2 min), and a recovery phase (6 min). Long and short TR acquisitions were also made at rest for T1 correction. The advanced data quality control pipeline presented in Part 1 is applied to the selected patient cohorts to investigate its impact on clinical outcomes. We first used power and sample size analysis to estimate objectively the impact of adding the quality control score (QCS). Then, comparisons between patients and healthy control groups using the validated QCS were performed using unpaired t tests or Mann-Whitney tests (p < 0.05). The application of the QCS resulted in increased statistical power, changed the values of several outcome measures, and reduced variability (standard deviation). A significant difference was found between the T1PCr and T1Pi values of MS patients and healthy controls. Furthermore, the use of a fixed correction factor led to systematically higher estimated concentrations of PCr and Pi than when using individually corrected factors. We observed significant differences between the two patient populations and healthy controls for resting [PCr]-MS only, [Pi ], [ADP], [H2 PO4 - ], and pH-COVID-19 only, and post-exercise [PCr], [Pi ], and [H2 PO4 - ]-MS only. The dynamic indicators τPCr , τPi , ViPCr , and Vmax were reduced for COVID-19 and MS patients compared with controls. Our results show that QCS in dynamic 31 P-MRS studies results in smaller data variability and therefore impacts study sample size and power. Although QCS resulted in discarded data and therefore reduced the acceptable data and subject numbers, this rigorous and unbiased approach allowed for proper assessment of muscle metabolites and metabolism in patient populations. The outcomes include an increased metabolite T1 , which directly affects the T1 correction factor applied to the amplitudes of the metabolite, and a prolonged τPCr , indicating reduced muscle oxidative capacity for patients with MS and COVID-19.

Alteration of skeletal muscle energy metabolism assessed by phosphorus-31 magnetic resonance spectroscopy in clinical routine, part 1: Advanced quality control pipeline.

Implementing a standardized phosphorus-31 magnetic resonance spectroscopy (31 P-MRS) dynamic acquisition protocol to evaluate skeletal muscle energy metabolism and monitor muscle fatigability, while being compatible with various longitudinal clinical studies on diversified patient cohorts, requires a high level of technicality and expertise. Furthermore, processing data to obtain reliable results also demands a great degree of expertise from the operator. In this two-part article, we present an advanced quality control approach for data acquired using a dynamic 31 P-MRS protocol. The aim is to provide decision support to the operator to assist in data processing and obtain reliable results based on objective criteria. We present here, in part 1, an advanced data quality control (QC) approach of a dynamic 31 P-MRS protocol. Part 2 is an impact study that will demonstrate the added value of the QC approach to explore data derived from two clinical populations that experience significant fatigue, patients with coronavirus disease 2019 and multiple sclerosis. In part 1, 31 P-MRS was performed using 3-T clinical MRI in 175 subjects from clinical and healthy control populations conducted in a University Hospital. An advanced data QC score (QCS) was developed using multiple objective criteria. The criteria were based on current recommendations from the literature enriched by new proposals based on clinical experience. The QCS was designed to indicate valid and corrupt data and guide necessary objective data editing to extract as much valid physiological data as possible. Dynamic acquisitions using an MR-compatible ergometer ran over a rest (40 s), exercise (2 min), and a recovery phase (6 min). Using QCS enabled rapid identification of subjects with data anomalies, allowing the user to correct the data series or reject them partially or entirely, as well as identify fully valid datasets. Overall, the use of the QCS resulted in the automatic classification of 45% of the subjects, including 58 participants who had data with no criterion violation and 21 participants with violations that resulted in the rejection of all dynamic data. The remaining datasets were inspected manually with guidance, allowing acceptance of full datasets from an additional 80 participants and recovery phase data from an additional 16 subjects. Overall, more anomalies occurred with patient data (35% of datasets) compared with healthy controls (15% of datasets). In conclusion, the QCS ensures a standardized data rejection procedure and rigorous objective analysis of dynamic 31 P-MRS data obtained from patients. This methodology contributes to efforts made to standardize 31 P-MRS practices that have been underway for a decade, with the goal of making it an empowered tool for clinical research.

Pixel-wise statistical analysis of myocardial injury in STEMI patients with delayed enhancement MRI.

Objectives: Myocardial injury assessment from delayed enhancement magnetic resonance images is routinely limited to global descriptors such as size and transmurality. Statistical tools from computational anatomy can drastically improve this characterization, and refine the assessment of therapeutic procedures aiming at infarct size reduction. Based on these techniques, we propose a new characterization of myocardial injury up to the pixel resolution. We demonstrate it on the imaging data from the Minimalist Immediate Mechanical Intervention randomized clinical trial (MIMI: NCT01360242), which aimed at comparing immediate and delayed stenting in acute ST-Elevation Myocardial Infarction (STEMI) patients. Methods: We analyzed 123 patients from the MIMI trial (62 ± 12 years, 98 male, 65 immediate 58 delayed stenting). Early and late enhancement images were transported onto a common geometry using techniques inspired by statistical atlases, allowing pixel-wise comparisons across population subgroups. A practical visualization of lesion patterns against specific clinical and therapeutic characteristics was also proposed using state-of-the-art dimensionality reduction. Results: Infarct patterns were roughly comparable between the two treatments across the whole myocardium. Subtle but significant local differences were observed for the LCX and RCA territories with higher transmurality for delayed stenting at lateral and inferior/inferoseptal locations, respectively (15% and 23% of myocardial locations with a p-value <0.05, mainly in these regions). In contrast, global measurements were comparable for all territories (no statistically significant differences for all-except-one measurements before standardization / for all after standardization), although immediate stenting resulted in more subjects without reperfusion injury. Conclusion: Our approach substantially empowers the analysis of lesion patterns with standardized comparisons up to the pixel resolution, and may reveal subtle differences not accessible with global observations. On the MIMI trial data as illustrative case, it confirmed its general conclusions regarding the lack of benefit of delayed stenting, but revealed subgroups differences thanks to the standardized and finer analysis scale.

StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE.

Purpose: To develop a three-dimensional (two dimensions + time) convolutional neural network trained with displacement encoding with stimulated echoes (DENSE) data for displacement and strain analysis of cine MRI. Materials and Methods: In this retrospective multicenter study, a deep learning model (StrainNet) was developed to predict intramyocardial displacement from contour motion. Patients with various heart diseases and healthy controls underwent cardiac MRI examinations with DENSE between August 2008 and January 2022. Network training inputs were a time series of myocardial contours from DENSE magnitude images, and ground truth data were DENSE displacement measurements. Model performance was evaluated using pixelwise end-point error (EPE). For testing, StrainNet was applied to contour motion from cine MRI. Global and segmental circumferential strain (Ecc) derived from commercial feature tracking (FT), StrainNet, and DENSE (reference) were compared using intraclass correlation coefficients (ICCs), Pearson correlations, Bland-Altman analyses, paired t tests, and linear mixed-effects models. Results: The study included 161 patients (110 men; mean age, 61 years ± 14 [SD]), 99 healthy adults (44 men; mean age, 35 years ± 15), and 45 healthy children and adolescents (21 males; mean age, 12 years ± 3). StrainNet showed good agreement with DENSE for intramyocardial displacement, with an average EPE of 0.75 mm ± 0.35. The ICCs between StrainNet and DENSE and FT and DENSE were 0.87 and 0.72, respectively, for global Ecc and 0.75 and 0.48, respectively, for segmental Ecc. Bland-Altman analysis showed that StrainNet had better agreement than FT with DENSE for global and segmental Ecc. Conclusion: StrainNet outperformed FT for global and segmental Ecc analysis of cine MRI.Keywords: Image Postprocessing, MR Imaging, Cardiac, Heart, Pediatrics, Technical Aspects, Technology Assessment, Strain, Deep Learning, DENSE Supplemental material is available for this article. © RSNA, 2023.

Cardioprotective effects of shock wave therapy: A cardiac magnetic resonance imaging study on acute ischemia-reperfusion injury.

Introduction: Cardioprotection strategies remain a new frontier in treating acute myocardial infarction (AMI), aiming at further protect the myocardium from the ischemia-reperfusion damage. Therefore, we aimed at investigating the mechano-transduction effects induced by shock waves (SW) therapy at time of the ischemia reperfusion as a non-invasive cardioprotective innovative approach to trigger healing molecular mechanisms. Methods: We evaluated the SW therapy effects in an open-chest pig ischemia-reperfusion (IR) model, with quantitative cardiac Magnetic Resonance (MR) imaging performed along the experiments at multiple time points (baseline (B), during ischemia (I), at early reperfusion (ER) (∼15 min), and late reperfusion (LR) (3 h)). AMI was obtained by a left anterior artery temporary occlusion (50 min) in 18 pigs (32 ± 1.9 kg) randomized into SW therapy and control groups. In the SW therapy group, treatment was started at the end of the ischemia period and extended during early reperfusion (600 + 1,200 shots @0.09 J/mm2, f = 5 Hz). The MR protocol included at all time points LV global function assessment, regional strain quantification, native T1 and T2 parametric mapping. Then, after contrast injection (gadolinium), we obtained late gadolinium imaging and extra-cellular volume (ECV) mapping. Before animal sacrifice, Evans blue dye was administrated after re-occlusion for area-at-risk sizing. Results: During ischemia, LVEF decreased in both groups (25 ± 4.8% in controls (p = 0.031), 31.6 ± 3.2% in SW (p = 0.02). After reperfusion, left ventricular ejection fraction (LVEF) remained significantly decreased in controls (39.9 ± 4% at LR vs. 60 ± 5% at baseline (p = 0.02). In the SW group, LVEF increased quickly ER (43.7 ± 11.4% vs. 52.4 ± 8.2%), and further improved at LR (49.4 ± 10.1) (ER vs. LR p = 0.05), close to baseline reference (LR vs. B p = 0.92). Furthermore, there was no significant difference in myocardial relaxation time (i.e. edema) after reperfusion in the intervention group compared to the control group: ΔT1 (MI vs. remote) was increased by 23.2±% for SW vs. +25.2% for the controls, while ΔT2 (MI vs. remote) increased by +24.9% for SW vs. +21.7% for the control group. Discussion: In conclusion, we showed in an ischemia-reperfusion open-chest swine model that SW therapy, when applied near the relief of 50' LAD occlusion, led to a nearly immediate cardioprotective effect translating to a reduction in the acute ischemia-reperfusion lesion size and to a significant LV function improvement. These new and promising results related to the multi-targeted effects of SW therapy in IR injury need to be confirmed by further in-vivo studies in close chest models with longitudinal follow-up.

Long-term fasting: Multi-system adaptations in humans (GENESIS) study-A single-arm interventional trial.

Fasting provokes fundamental changes in the activation of metabolic and signaling pathways leading to longer and healthier lifespans in animal models. Although the involvement of different metabolites in fueling human fasting metabolism is well known, the contribution of tissues and organs to their supply remains partly unclear. Also, changes in organ volume and composition remain relatively unexplored. Thus, processes involved in remodeling tissues during fasting and food reintroduction need to be better understood. Therefore, this study will apply state-of-the-art techniques to investigate the effects of long-term fasting (LF) and food reintroduction in humans by a multi-systemic approach focusing on changes in body composition, organ and tissue volume, lipid transport and storage, sources of protein utilization, blood metabolites, and gut microbiome profiles in a single cohort. This is a prospective, single-arm, monocentric trial. One hundred subjects will be recruited and undergo 9 ± 3 day-long fasting periods (250 kcal/day). We will assess changes in the composition of organs, bones and blood lipid profiles before and after fasting, as well as high-density lipoprotein (HDL) transport and storage, untargeted metabolomics of peripheral blood mononuclear cells (PBMCs), protein persulfidation and shotgun metagenomics of the gut microbiome. The first 32 subjects, fasting for 12 days, will be examined in more detail by magnetic resonance imaging (MRI) and spectroscopy to provide quantitative information on changes in organ volume and function, followed by an additional follow-up examination after 1 and 4 months. The study protocol was approved by the ethics board of the State Medical Chamber of Baden-Württemberg on 26.07.2021 and registered at ClinicalTrials.gov (NCT05031598). The results will be disseminated through peer-reviewed publications, international conferences and social media. Clinical trial registration: [ClinicalTrials.gov], identifier [NCT05031598].

CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images.

In the last decade, a large number of clinical trials have been deployed using Cardiac Magnetic Resonance (CMR) to evaluate cardioprotective strategies aiming at reducing the irreversible myocardial damage at the time of reperfusion. In these studies, segmentation and quantification of myocardial infarct lesion are often performed with a commercial software or an in-house closed-source code development thus creating a barrier for reproducible research. This paper introduces CMRSegTools: an open-source application software designed for the segmentation and quantification of myocardial infarct lesion enabling full access to state-of-the-art segmentation methods and parameters, easy integration of new algorithms and standardised results sharing. This post-processing tool has been implemented as a plug-in for the OsiriX/Horos DICOM viewer leveraging its database management functionalities and user interaction features to provide a bespoke tool for the analysis of cardiac MR images on large clinical cohorts. CMRSegTools includes, among others, user-assisted segmentation of the left-ventricle, semi- and automatic lesion segmentation methods, advanced statistical analysis and visualisation based on the American Heart Association 17-segment model. New segmentation methods can be integrated into the plug-in by developing components based on image processing and visualisation libraries such as ITK and VTK in C++ programming language. CMRSegTools allows the creation of training and testing data sets (labeled features such as lesion, microvascular obstruction and remote ROI) for supervised Machine Learning methods, and enables the comparative assessment of lesion segmentation methods via a single and integrated platform. The plug-in has been successfully used by several CMR imaging studies.

Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease.

BACKGROUND: While multiple cardiovascular magnetic resonance (CMR) methods provide excellent reproducibility of global circumferential and global longitudinal strain, achieving highly reproducible segmental strain is more challenging. Previous single-center studies have demonstrated excellent reproducibility of displacement encoding with stimulated echoes (DENSE) segmental circumferential strain. The present study evaluated the reproducibility of DENSE for measurement of whole-slice or global circumferential (Ecc), longitudinal (Ell) and radial (Err) strain, torsion, and segmental Ecc at multiple centers. METHODS: Six centers participated and a total of 81 subjects were studied, including 60 healthy subjects and 21 patients with various types of heart disease. CMR utilized 3 T scanners, and cine DENSE images were acquired in three short-axis planes and in the four-chamber long-axis view. During one imaging session, each subject underwent two separate DENSE scans to assess inter-scan reproducibility. Each subject was taken out of the scanner and repositioned between the scans. Intra-user, inter-user-same-site, inter-user-different-site, and inter-user-Human-Deep-Learning (DL) comparisons assessed the reproducibility of different users analyzing the same data. Inter-scan comparisons assessed the reproducibility of DENSE from scan to scan. The reproducibility of whole-slice or global Ecc, Ell and Err, torsion, and segmental Ecc were quantified using Bland-Altman analysis, the coefficient of variation (CV), and the intraclass correlation coefficient (ICC). CV was considered excellent for CV ≤ 10%, good for 10% < CV ≤ 20%, fair for 20% < CV ≤ 40%, and poor for CV > 40. ICC values were considered excellent for ICC > 0.74, good for ICC 0.6 < ICC ≤ 0.74, fair for ICC 0.4 < ICC ≤ 0.59, poor for ICC < 0.4. RESULTS: Based on CV and ICC, segmental Ecc provided excellent intra-user, inter-user-same-site, inter-user-different-site, inter-user-Human-DL reproducibility and good-excellent inter-scan reproducibility. Whole-slice Ecc and global Ell provided excellent intra-user, inter-user-same-site, inter-user-different-site, inter-user-Human-DL and inter-scan reproducibility. The reproducibility of torsion was good-excellent for all comparisons. For whole-slice Err, CV was in the fair-good range, and ICC was in the good-excellent range. CONCLUSIONS: Multicenter data show that 3 T CMR DENSE provides highly reproducible whole-slice and segmental Ecc, global Ell, and torsion measurements in healthy subjects and heart disease patients.

Kinetics of Cardiac Remodeling and Fibrosis Biomarkers During an Extreme Mountain Ultramarathon.

Objectives: The effects of ultra-distance on cardiac remodeling and fibrosis are unclear. Moreover, there are no data reporting the kinetics of cardiac alterations throughout the event and during recovery. Our aim was to investigate the kinetics of biological markers including new cardiac fibrosis biomarkers suppression of tumorigenicity 2 (ST2) and galectin-3 (Gal-3) during and after an extreme mountain ultramarathon. Methods: Fifty experienced runners participating in one of the most challenging mountain ultramarathons (330 km, D+ 25,000 m) were enrolled in our study. Blood samples were collected at four time points: before (Pre-), at 148 km (Mid-), at the finish line (Post-), and 3 days after the recovery period (Recov-). Results: The cardiac fibrosis biomarkers (ST2 and Gal-3) increased from Pre- to Mid-. During the second half, ST2 remained higher than pre-values as opposed to Gal-3. Necrosis, ischemia, and myocyte injury biomarkers increased until Mid- then decreased but remained higher at Recov- than Pre-values. Oxidative stress appeared at Mid-. Lipid peroxides remained higher at Recov- compared to Pre-. The maximal value in most of these biomarkers was observed at Mid- and not at Post-. Conclusions: The present study supports biphasic kinetics of cardiac fibrosis biomarkers, with a relative recovery during the second half of the event that seems specific to this extreme event. Overall, performing at such an extreme ultramarathon seems less deleterious for the heart than shorter events.

Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1-9 days later, and the data were analysed centrally. The average mean diffusivities (MDs) in 0% PVP were (1.124, 1.130, 1.113) x 10-3  mm2 /s for PGSE, SE and STEAM, respectively, and accurate to within 1.5% of reference data from the literature. The coefficients of variation in MDs across sites were 2.6%, 3.1% and 2.1% for PGSE, SE and STEAM, respectively, and were similar to previous studies using only PGSE. Reproducibility in MD was excellent, with mean differences in PGSE, SE and STEAM of (0.3 ± 2.3, 0.24 ± 0.95, 0.52 ± 0.58) x 10-5  mm2 /s (mean ± 1.96 SD). We show that custom sequences for cardiac DTI provide accurate, precise, repeatable and reproducible measurements. Further work in anisotropic and/or deforming phantoms is warranted.

Coupling hemodynamics with mechanobiology in patient-specific computational models of ascending thoracic aortic aneurysms.

BACKGROUND AND OBJECTIVE: The prevention of ascending thoracic aortic aneurysms (ATAAs), which affect thousands of persons every year worldwide, remains a major issue. ATAAs may be caused by anything that weakens the aortic wall. Altered hemodynamics, which concerns a majority of patients with bicuspid aortic valves, has been shown to be related to such weakening and to contribute to ATAA development and progression. However the underlying mechanisms remain unclear and computational modeling in this field could help significantly to elucidate how hemodynamics and mechanobiology interact in ATAAs. METHODS: Accordingly, we propose a numerical framework combining computational fluid dynamics and 4D flow magnetic resonance imaging (MRI) coupled with finite element (FE) analyses to simulate growth and remodeling (G&R) occurring in patient-specific aortas in relation with altered hemodynamics. The geometries and the blood velocities obtained from 4D flow MRI are used as boundary conditions for CFD simulations. CFD simulations provide an estimation of the wall shear stress (WSS) and relative residence time (RRT) distribution across the luminal surface of the wall. An initial insult is then applied to the FE model of the aortic wall, assuming that the magnitude of the insult correlates spatially with the normalized RRT distribution obtained from CFD simulations. G&R simulations are then performed. The material behavior of each Gauss point in these FE models is evolved continuously to compensate for the deviation of the actual wall stress distribution from the homeostatic state after the initial insult. The whole approach is illustrated on two healthy and two diseased subjects. The G&R parameters are calibrated against previously established statistical models of ATAA growth rates. RESULTS: Among the variety of results provided by G&R simulations, the analysis focused especially on the evolution of the wall stiffness, which was shown to be a major risk factor for ATAAs. It was shown that the G&R parameters, such as for instance the rate of collagen production or cell mechanosensitivity, play a critical role in ATAA progression and remodeling. CONCLUSIONS: These preliminary findings show that patient-specific computational modeling coupling hemodynamics with mechanobiology is a promising approach to explore aneurysm progression.

Direct Comparison of Bayesian and Fermi Deconvolution Approaches for Myocardial Blood Flow Quantification: In silico and Clinical Validations.

Cardiac magnetic resonance myocardial perfusion imaging can detect coronary artery disease and is an alternative to single-photon emission computed tomography or positron emission tomography. However, the complex, non-linear MR signal and the lack of robust quantification of myocardial blood flow have hindered its widespread clinical application thus far. Recently, a new Bayesian approach was developed for brain imaging and evaluation of perfusion indexes (Kudo et al., 2014). In addition to providing accurate perfusion measurements, this probabilistic approach appears more robust than previous approaches, particularly due to its insensitivity to bolus arrival delays. We assessed the performance of this approach against a well-known and commonly deployed model-independent method based on the Fermi function for cardiac magnetic resonance myocardial perfusion imaging. The methods were first evaluated for accuracy and precision using a digital phantom to test them against the ground truth; next, they were applied in a group of coronary artery disease patients. The Bayesian method can be considered an appropriate model-independent method with which to estimate myocardial blood flow and delays. The digital phantom comprised a set of synthetic time-concentration curve combinations generated with a 2-compartment exchange model and a realistic combination of perfusion indexes, arterial input dynamics, noise and delays collected from the clinical dataset. The myocardial blood flow values estimated with the two methods showed an excellent correlation coefficient (r 2 > 0.9) under all noise and delay conditions. The Bayesian approach showed excellent robustness to bolus arrival delays, with a similar performance to Fermi modeling when delays were considered. Delays were better estimated with the Bayesian approach than with Fermi modeling. An in vivo analysis of coronary artery disease patients revealed that the Bayesian approach had an excellent ability to distinguish between abnormal and normal myocardium. The Bayesian approach was able to discriminate not only flows but also delays with increased sensitivity by offering a clearly enlarged range of distribution for the physiologic parameters.

Myofiber strain in healthy humans using DENSE and cDTI.

PURPOSE: Myofiber strain, Eff , is a mechanistically relevant metric of cardiac cell shortening and is expected to be spatially uniform in healthy populations, making it a prime candidate for the evaluation of local cardiomyocyte contractility. In this study, a new, efficient pipeline was proposed to combine microstructural cDTI and functional DENSE data in order to estimate Eff in vivo. METHODS: Thirty healthy volunteers were scanned with three long-axis (LA) and three short-axis (SA) DENSE slices using 2D displacement encoding and one SA slice of cDTI. The total acquisition time was 11 minutes ± 3 minutes across volunteers. The pipeline first generates 3D SA displacements from all DENSE slices which are then combined with cDTI data to generate a cine of myofiber orientations and compute Eff . The precision of the post-processing pipeline was assessed using a computational phantom study. Transmural myofiber strain was compared to circumferential strain, Ecc , in healthy volunteers using a Wilcoxon sign rank test. RESULTS: In vivo, computed Eff was found uniform transmurally compared to Ecc (-0.14[-0.15, -0.12] vs -0.18 [-0.20, -0.16], P < .001, -0.14 [-0.16, -0.12] vs -0.16 [-0.17, -0.13], P < .001 and -0.14 [-0.16, -0.12] vs Ecc_C = -0.14 [-0.15, -0.11], P = .002, Eff_C vs Ecc_C in the endo, mid, and epi layers, respectively). CONCLUSION: We demonstrate that it is possible to measure in vivo myofiber strain in a healthy human population in 10 minutes per subject. Myofiber strain was observed to be spatially uniform in healthy volunteers making it a potential biomarker for the evaluation of local cardiomyocyte contractility in assessing cardiovascular dysfunction.

Significance of Hemodynamics Biomarkers, Tissue Biomechanics and Numerical Simulations in the Pathogenesis of Ascending Thoracic Aortic Aneurysms.

Guidelines for the treatment of aortic wall diseases are based on measurements of maximum aortic diameter. However, aortic rupture or dissections do occur for small aortic diameters. Growing scientific evidence underlines the importance of biomechanics and hemodynamics in aortic disease development and progression. Wall shear stress (WWS) is an important hemodynamics marker that depends on aortic wall morphology and on the aortic valve function. WSS could be helpful to interpret aortic wall remodeling and define personalized risk criteria. The complementarity of Computational Fluid Dynamics and 4D Magnetic Resonance Imaging as tools for WSS assessment is a promising reality. The potentiality of these innovative technologies will provide maps or atlases of hemodynamics biomarkers to predict aortic tissue dysfunction. Ongoing efforts should focus on the correlation between these non-invasive imaging biomarkers and clinico-pathologic situations for the implementation of personalized medicine in current clinical practice.

Imaging Interstitial Fibrosis, Left Ventricular Remodeling, and Function in Stage A and B Heart Failure.

Myocardial interstitial fibrosis is part of the advanced disease stage of most cardiovascular pathologies. It has been characterized histologically in various disease settings from hypertensive heart disease and diabetic cardiomyopathy to severe aortic stenosis. It is also involved in the process of aging. In cardiovascular medicine, myocardial interstitial fibrosis is associated with several adverse outcomes, especially heart failure (HF) and sudden cardiac death. Until recently, clinical measures of interstitial fibrosis could only be made by invasive myocardial biopsy. The availability of cardiac magnetic resonance (CMR) T1 mapping techniques allows for the indirect measurement of interstitial space characteristics and extracellular volume size, which is closely correlated with collagen content and interstitial infiltration by amyloid and other molecules. There has been significant improvement in the accuracy and reproducibility of T1 acquisition sequences in the last decade; however, the correct use of this technique requires a solid CMR expertise in daily imaging practice. CMR has become the gold standard to assess left ventricular (LV) remodeling and functional features associated with interstitial fibrosis. These features can be detected in the early stages of HF. The main objective of this paper is to review the relevant results of preclinical and clinical observational studies that demonstrate the prognostic impact of interstitial fibrosis assessed by T1 mapping, as well as adverse left ventricular remodeling, as determinants of HF. Therefore, this review focuses on the pathological mechanisms underlying LV remodeling and interstitial fibrosis, in addition to the technical considerations involved in the assessment of interstitial LV fibrosis by CMR. It provides a thorough review of clinical evidence that demonstrates the association of interstitial fibrosis and other-CMR derived LV phenotypes with Stages A and B HF.

Comparison of 2D simultaneous multi-slice and 3D GRASE readout schemes for pseudo-continuous arterial spin labeling of cerebral perfusion at 3 T.

OBJECTIVE: In this perfusion magnetic resonance imaging study, the performances of different pseudo-continuous arterial spin labeling (PCASL) sequences were compared: two-dimensional (2D) single-shot readout with simultaneous multislice (SMS), 2D single-shot echo-planar imaging (EPI) and multishot three-dimensional (3D) gradient and spin echo (GRASE) sequences combined with a background-suppression (BS) module. MATERIALS AND METHODS: Whole-brain PCASL images were acquired from seven healthy volunteers. The performance of each protocol was evaluated by extracting regional cerebral blood flow (rCBF) measures using an inline morphometric segmentation prototype. Image data postprocessing and subsequent statistical analyses enabled comparisons at the regional and sub-regional levels. RESULTS: The main findings were as follows: (i) Mean global CBF obtained across methods was were highly correlated, and these correlations were significantly higher among the same readout sequences. (ii) Temporal signal-to-noise ratio and gray-matter-to-white-matter CBF ratio were found to be equivalent for all 2D variants but lower than those of 3D-GRASE. DISCUSSION: Our study demonstrates that the accelerated SMS readout can provide increased acquisition efficiency and/or a higher temporal resolution than conventional 2D and 3D readout sequences. Among all of the methods, 3D-GRASE showed the lowest variability in CBF measurements and thus highest robustness against noise.

Quantitative Magnetic Resonance Imaging Assessment of the Quadriceps Changes during an Extreme Mountain Ultramarathon.

INTRODUCTION/PURPOSE: Extreme ultra-endurance races are growing in popularity, but their effects on skeletal muscles remain mostly unexplored. This longitudinal study explores physiological changes in mountain ultramarathon athletes' quadriceps using quantitative magnetic resonance imaging (MRI) coupled with serological biomarkers. The study aimed to monitor the longitudinal effect of the race and recovery and to identify local inflammatory and metabolic muscle responses by codetection of biological markers. METHODS: An automatic image processing framework was designed to extract imaging-based biomarkers from quantitative MRI acquisitions of the upper legs of 20 finishers at three time points. The longitudinal effect of the race was demonstrated by analyzing the image markers with dedicated biostatistical analysis. RESULTS: Our framework allows for a reliable calculation of statistical data not only inside the whole quadriceps volume but also within each individual muscle head. Local changes in MRI parameters extracted from quantitative maps were described and found to be significantly correlated with principal serological biomarkers of interest. A decrease in the PDFF after the race and a stable paramagnetic susceptibility value were found. Pairwise post hoc tests suggested that the recovery process differs among the muscle heads. CONCLUSIONS: This longitudinal study conducted during a prolonged and extreme mechanical stress showed that quantitative MRI-based markers of inflammation and metabolic response can detect local changes related to the prolonged exercise, with differentiated involvement of each head of the quadriceps muscle as expected in such eccentric load. Consistent and efficient extraction of the local biomarkers enables to highlight the interplay/interactions between blood and MRI biomarkers. This work indeed proposes an automatized analytic framework to tackle the time-consuming and mentally exhausting segmentation task of muscle heads in large multi-time-point cohorts.