Pulmonary vascular disease in Veterans with post-deployment respiratory syndrome.

Exertional dyspnea has been documented in US military personnel after deployment to Iraq and Afghanistan. We studied whether continued exertional dyspnea in this patient population is associated with pulmonary vascular disease (PVD). We performed detailed histomorphometry of pulmonary vasculature in 52 Veterans with biopsy-proven post-deployment respiratory syndrome (PDRS) and then recruited five of these same Veterans with continued exertional dyspnea to undergo a follow-up clinical evaluation, including symptom questionnaire, pulmonary function testing, surface echocardiography, and right heart catheterization (RHC). Morphometric evaluation of pulmonary arteries showed significantly increased intima and media thicknesses, along with collagen deposition (fibrosis), in Veterans with PDRS compared to non-diseased (ND) controls. In addition, pulmonary veins in PDRS showed increased intima and adventitia thicknesses with prominent collagen deposition compared to controls. Of the five Veterans involved in our clinical follow-up study, three had borderline or overt right ventricle (RV) enlargement by echocardiography and evidence of pulmonary hypertension (PH) on RHC. Together, our studies suggest that PVD with predominant venular fibrosis is common in PDRS and development of PH may explain exertional dyspnea and exercise limitation in some Veterans with PDRS.

Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review.

Magnetic resonance imaging (MRI) stands as a vital medical imaging technique, renowned for its ability to offer high-resolution images of the human body with remarkable soft-tissue contrast. This enables healthcare professionals to gain valuable insights into various aspects of the human body, including morphology, structural integrity, and physiological processes. Quantitative imaging provides compositional measurements of the human body, but, currently, either it takes a long scan time or is limited to low spatial resolutions. Undersampled k-space data acquisitions have significantly helped to reduce MRI scan time, while compressed sensing (CS) and deep learning (DL) reconstructions have mitigated the associated undersampling artifacts. Alternatively, magnetic resonance fingerprinting (MRF) provides an efficient and versatile framework to acquire and quantify multiple tissue properties simultaneously from a single fast MRI scan. The MRF framework involves four key aspects: (1) pulse sequence design; (2) rapid (undersampled) data acquisition; (3) encoding of tissue properties in MR signal evolutions or fingerprints; and (4) simultaneous recovery of multiple quantitative spatial maps. This paper provides an extensive literature review of the MRF framework, addressing the trends associated with these four key aspects. There are specific challenges in MRF for all ranges of magnetic field strengths and all body parts, which can present opportunities for further investigation. We aim to review the best practices in each key aspect of MRF, as well as for different applications, such as cardiac, brain, and musculoskeletal imaging, among others. A comprehensive review of these applications will enable us to assess future trends and their implications for the translation of MRF into these biomedical imaging applications.

Associations of Sarcopenia and Body Composition Measures With Mortality After Transcatheter Aortic Valve Replacement.

BACKGROUND: Frailty associates with worse outcomes after transcatheter aortic valve replacement (TAVR). Sarcopenia underlies frailty, but the association between a comprehensive assessment of sarcopenia-muscle mass, strength, and performance-and outcomes after TAVR has not been examined. METHODS: From a multicenter prospective registry of patients with symptomatic severe aortic stenosis undergoing TAVR, 445 who had a preprocedure computed tomography and clinical assessment of frailty were included. Cross-sectional muscle (psoas and paraspinal) areas were measured on computed tomography and indexed to height. Gait speed and handgrip strength were obtained, and patients were dichotomized into fast versus slow; strong versus weak; and normal versus low muscle mass. As measures of body composition, cross-sectional fat (subcutaneous and visceral) was measured and indexed to height. RESULTS: The frequency of patients who were slow, weak, and had low muscle mass was 56%, 59%, and 42%, respectively. Among the 3 components of sarcopenia, only slower gait speed (muscle performance) was independently associated with increased post-TAVR mortality (adjusted hazard ratio, 1.12 per 0.1 m/s decrease [95% CI, 1.04-1.21]; P=0.004; adjusted hazard ratio, 1.38 per 1 SD decrease [95% CI, 1.11-1.72]; P=0.004). Meeting multiple sarcopenia criteria was not associated with higher mortality risk than fewer. Lower indexed visceral fat area (adjusted hazard ratio, 1.48 per 1 SD decrease [95% CI, 1.15-1.89]; P=0.002) was associated with mortality but indexed subcutaneous fat was not. Death occurred in 169 (38%) patients. CONCLUSIONS: Among patients with symptomatic severe aortic stenosis and comprehensive sarcopenia and body composition phenotyping, gait speed was the only sarcopenia measure associated with post-TAVR mortality. Lower visceral fat was also associated with increased risk pointing to an obesity paradox also observed in other patient populations. These findings reinforce the clinical utility of gait speed as a measure of risk and a potential target for adjunctive interventions alongside TAVR to optimize clinical outcomes.

Characterization of Age-Related and Sex-Related Differences of Relaxation Parameters in the Intervertebral Disc Using MR-Fingerprinting.

BACKGROUND: Multiparameter characterization using MR fingerprinting (MRF) can quantify multiple relaxation parameters of intervertebral disc (IVD) simultaneously. These parameters may vary by age and sex. PURPOSE: To investigate age- and sex-related differences in the relaxation parameters of the IVD of the lumbar spine using a multiparameter MRF technique. STUDY TYPE: Prospective. SUBJECTS: 17 healthy subjects (8 male; mean age = 34 ± 10 years, range 20-60 years). FIELD STRENGTH/SEQUENCE: 3D-MRF sequence for simultaneous acquisition of proton density, T1 , T2 , and T1ρ maps at 3.0T. ASSESSMENT: Global mean T1 , T2 , and T1ρ of all lumbar IVDs and mean T1 , T2 , and T1ρ of each individual IVD (L1-L5) were measured. Gray level co-occurrence matrix was used to quantify textural features (median, contrast, correlation, energy, and homogeneity) from T1 , T2 , and T1ρ maps. STATISTICAL TESTS: Spearman rank correlations (R) evaluated the association between age and T1 , T2 , and T1ρ of IVD. Mann-Whitney U-tests evaluated differences between males and females in T1 , T2 , and T1ρ of IVD. Statistical significance was defined as P-value <0.05. RESULTS: There was a significant negative correlation between age and global mean values of all IVDs for T1 (R = -0.637), T2 (R = -0.509), and T1ρ (R = -0.726). For individual IVDs, there was a significant negative correlation between age and mean T1 at all IVD segments (R range = -0.530 to -0.708), between age and mean T2 at L2-L3, L3-L4, and L4-L5 (R range = -0.493 to 0.640), and between age and mean T1ρ at all segments except L1-L2 (R range = -0.632 to -0.763). There were no significant differences between sexes in global mean T1 , T2, and T1ρ (P-value = 0.23-0.76) The texture features with the highest significant correlations with age for all IVDs were global T1ρ mean (R = -0.726), T1 energy (R = -0.681), and T1 contrast (R = 0.709). CONCLUSION: This study showed that the 3D-MRF technique has potential to characterize age-related differences in T1 , T2, or T1ρ of IVD in healthy subjects. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Repeatability of Quantitative Knee Cartilage T1 , T2 , and T1ρ Mapping With 3D-MRI Fingerprinting.

BACKGROUND: Three-dimensional MR fingerprinting (3D-MRF) techniques have been recently described for simultaneous multiparametric mapping of knee cartilage. However, investigation of repeatability remains limited. PURPOSE: To assess the intra-day and inter-day repeatabilities of knee cartilage T1 , T2 , and T1ρ maps using a 3D-MRF sequence for simultaneous measurement. STUDY TYPE: Prospective. SUBJECTS: Fourteen healthy subjects (35.4 ± 9.3 years, eight males), scanned on Day 1 and Day 7. FIELD STRENGTH/SEQUENCE: 3 T/3D-MRF, T1 , T2 , and T1ρ maps. ASSESSMENT: The acquisition of 3D-MRF cartilage (simultaneous acquisition of T1 , T2 , and T1ρ maps) were acquired using a dictionary pattern-matching approach. Conventional cartilage T1 , T2 , and T1ρ maps were acquired using variable flip angles and a modified 3D-Turbo-Flash sequence with different echo and spin-lock times, respectively, and were fitted using mono-exponential models. Each sequence was acquired on Day 1 and Day 7 with two scans on each day. STATISTICAL TESTS: The mean and SD for cartilage T1 , T2 , and T1ρ were calculated in five manually segmented regions of interest (ROIs), including lateral femur, lateral tibia, medial femur, medial tibia, and patella cartilages. Intra-subject and inter-subject repeatabilities were assessed using coefficient of variation (CV) and intra-class correlation coefficient (ICC), respectively, on the same day and among different days. Regression and Bland-Altman analysis were performed to compare maps between the conventional and 3D-MRF sequences. RESULTS: The CV in all ROIs was lower than 7.4%, 8.4%, and 7.5% and the ICC was higher than 0.56, 0.51, and 0.52 for cartilage T1 , T2 , and T1ρ , respectively. The MRF results had a good agreement with the conventional methods with a linear regression slope >0.61 and R2 > 0.59. CONCLUSION: The 3D-MRF sequence had high intra-subject and inter-subject repeatabilities for simultaneously measuring knee cartilage T1 , T2 , and T1ρ with good agreement with conventional sequences. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Emerging Trends in Fast MRI Using Deep-Learning Reconstruction on Undersampled k-Space Data: A Systematic Review.

Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides excellent soft-tissue contrast and high-resolution images of the human body, allowing us to understand detailed information on morphology, structural integrity, and physiologic processes. However, MRI exams usually require lengthy acquisition times. Methods such as parallel MRI and Compressive Sensing (CS) have significantly reduced the MRI acquisition time by acquiring less data through undersampling k-space. The state-of-the-art of fast MRI has recently been redefined by integrating Deep Learning (DL) models with these undersampled approaches. This Systematic Literature Review (SLR) comprehensively analyzes deep MRI reconstruction models, emphasizing the key elements of recently proposed methods and highlighting their strengths and weaknesses. This SLR involves searching and selecting relevant studies from various databases, including Web of Science and Scopus, followed by a rigorous screening and data extraction process using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. It focuses on various techniques, such as residual learning, image representation using encoders and decoders, data-consistency layers, unrolled networks, learned activations, attention modules, plug-and-play priors, diffusion models, and Bayesian methods. This SLR also discusses the use of loss functions and training with adversarial networks to enhance deep MRI reconstruction methods. Moreover, we explore various MRI reconstruction applications, including non-Cartesian reconstruction, super-resolution, dynamic MRI, joint learning of reconstruction with coil sensitivity and sampling, quantitative mapping, and MR fingerprinting. This paper also addresses research questions, provides insights for future directions, and emphasizes robust generalization and artifact handling. Therefore, this SLR serves as a valuable resource for advancing fast MRI, guiding research and development efforts of MRI reconstruction for better image quality and faster data acquisition.

SUMOylation of the cardiac sodium channel NaV1.5 modifies inward current and cardiac excitability.

BACKGROUND: Decreased peak sodium current (INa) and increased late sodium current (INa,L), through the cardiac sodium channel NaV1.5 encoded by SCN5A, cause arrhythmias. Many NaV1.5 posttranslational modifications have been reported. A recent report concluded that acute hypoxia increases INa,L by increasing a small ubiquitin-like modifier (SUMOylation) at K442-NaV1.5. OBJECTIVE: The purpose of this study was to determine whether and by what mechanisms SUMOylation alters INa, INa,L, and cardiac electrophysiology. METHODS: SUMOylation of NaV1.5 was detected by immunoprecipitation and immunoblotting. INa was measured by patch clamp with/without SUMO1 overexpression in HEK293 cells expressing wild-type (WT) or K442R-NaV1.5 and in neonatal rat cardiac myocytes (NRCMs). SUMOylation effects were studied in vivo by electrocardiograms and ambulatory telemetry using Scn5a heterozygous knockout (SCN5A+/-) mice and the de-SUMOylating protein SENP2 (AAV9-SENP2), AAV9-SUMO1, or the SUMOylation inhibitor anacardic acid. NaV1.5 trafficking was detected by immunofluorescence. RESULTS: NaV1.5 was SUMOylated in HEK293 cells, NRCMs, and human heart tissue. HyperSUMOylation at NaV1.5-K442 increased INa in NRCMs and in HEK cells overexpressing WT but not K442R-Nav1.5. SUMOylation did not alter other channel properties including INa,L. AAV9-SENP2 or anacardic acid decreased INa, prolonged QRS duration, and produced heart block and arrhythmias in SCN5A+/- mice, whereas AAV9-SUMO1 increased INa and shortened QRS duration. SUMO1 overexpression enhanced membrane localization of NaV1.5. CONCLUSION: SUMOylation of K442-Nav1.5 increases peak INa without changing INa,L, at least in part by altering membrane abundance. Our findings do not support SUMOylation as a mechanism for changes in INa,L. Nav1.5 SUMOylation may modify arrhythmic risk in disease states and represents a potential target for pharmacologic manipulation.

Age and gender differences in lumbar intervertebral disk strain using mechanical loading magnetic resonance imaging.

The objective of the current study was to investigate age- and gender-related differences in lumbar intervertebral disk (IVD) strain with the use of static mechanical loading and continuous three-dimensional (3D) golden-angle radial sparse parallel (GRASP) MRI. A continuous 3D-GRASP stack-of-stars trajectory of the lumbar spine was performed on a 3-T scanner with static mechanical loading. Compressed sensing reconstruction, motion deformation maps, and Lagrangian strain maps during loading and recovery in the X-, Y-, and Z-directions were calculated for segmented IVD segments from L1/L2 to L5/S1. Mean IVD height was measured at rest. Spearman coefficients were used to evaluate the associations between age and global IVD height and global IVD strain. Mann-Whitney tests were used to compare global IVD height and global IVD strain in males and females. The prospective study enrolled 20 healthy human volunteers (10 males, 10 females; age 34.6 ± 11.4 [mean ± SD], range 22-56 years). Significant increases in compressive strain were observed with age, as evidenced by negative correlations between age and global IVD strain during loading (ρ = -0.76, p = 0.0046) and recovery (ρ = -0.68, p = 0.0251) in the loading X-direction. There was no significant correlation between age and global IVD height, global IVD strain during loading and recovery in the Y-direction, and global IVD strain during loading and recovery in the Z-direction. There were no significant differences between males and females in global IVD height and global IVD strain during loading and recovery in the X-, Y-, and Z-directions. It was concluded that our study demonstrated the significant role aging plays in internal dynamic strains in the lumbar IVD during loading and recovery. Older healthy individuals have reduced IVD stiffness and greater IVD compression during static mechanical loading of the lumbar spine. The GRASP-MRI technique demonstrates the feasibility to identify changes in IVD mechanical properties with early IVD degeneration due to aging.

Optimizing variable flip angles in magnetization-prepared gradient-echo sequences for efficient 3D-T1ρ mapping.

PURPOSE: To optimize the choice of the flip angles of magnetization-prepared gradient-echo sequences for improved accuracy, precision, and speed of 3D-T1ρ mapping. METHODS: We propose a new optimization approach for finding variable flip-angle values that improve magnetization-prepared gradient-echo sequences used for 3D-T1ρ mapping. This new approach can improve the accuracy and SNR, while reducing filtering effects. We demonstrate the concept in the three different versions of the magnetization-prepared gradient-echo sequences that are typically used for 3D-T1ρ mapping and evaluate their performance in model agarose phantoms (n = 4) and healthy volunteers (n = 5) for knee joint imaging. We also tested the optimization with sequence parameters targeting faster acquisitions. RESULTS: Our results show that optimized variable flip angle can improve the accuracy and the precision of the sequences, seen as a reduction of the mean of normalized absolute difference from about 5%-6% to 3%-4% in model phantoms and from 15%-16% to 11%-13% in the knee joint, and improving SNR from about 12-28 to 22-32 in agarose phantoms and about 7-14 to 13-17 in healthy volunteers. The optimization can also compensate for the loss in quality caused by making the sequence faster. This results in sequence configurations that acquire more data per unit of time with SNR and mean of normalized absolute difference measurements close to its slower versions. CONCLUSION: The optimization of the variable flip angle can be used to increase accuracy and precision, and to improve the speed of the typical imaging sequences used for quantitative 3D-T1ρ mapping of the knee joint.

Metabolic Signatures of Cardiac Dysfunction, Multimorbidity, and Post-Transcatheter Aortic Valve Implantation Death.

Background Studies in mice and small patient subsets implicate metabolic dysfunction in cardiac remodeling in aortic stenosis, but no large comprehensive studies of human metabolism in aortic stenosis with long-term follow-up and characterization currently exist. Methods and Results Within a multicenter prospective cohort study, we used principal components analysis to summarize 12 echocardiographic measures of left ventricular structure and function pre-transcatheter aortic valve implantation in 519 subjects (derivation). We used least absolute shrinkage and selection operator regression across 221 metabolites to define metabolic signatures for each structural pattern and measured their relation to death and multimorbidity in the original cohort and up to 2 validation cohorts (N=543 for overall validation). In the derivation cohort (519 individuals; median age, 84 years, 45% women, 95% White individuals), we identified 3 axes of left ventricular remodeling, broadly specifying systolic function, diastolic function, and chamber volumes. Metabolite signatures of each axis specified both known and novel pathways in hypertrophy and cardiac dysfunction. Over a median of 3.1 years (205 deaths), a metabolite score for diastolic function was independently associated with post-transcatheter aortic valve implantation death (adjusted hazard ratio per 1 SD increase in score, 1.54 [95% CI, 1.25-1.90]; P<0.001), with similar effects in each validation cohort. This metabolite score of diastolic function was simultaneously associated with measures of multimorbidity, suggesting a metabolic link between cardiac and noncardiac state in aortic stenosis. Conclusions Metabolite profiles of cardiac structure identify individuals at high risk for death following transcatheter aortic valve implantation and concurrent multimorbidity. These results call for efforts to address potentially reversible metabolic biology associated with risk to optimize post-transcatheter aortic valve implantation recovery, rehabilitation, and survival.

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications.

Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely debilitating and causes significant socioeconomic burdens to society. Magnetic resonance imaging (MRI) is the preferred imaging modality for the morphological evaluation of cartilage due to its excellent soft tissue contrast and high spatial resolution. However, its utilization typically involves subjective qualitative assessment of cartilage. Compositional MRI, which refers to the quantitative characterization of cartilage using a variety of MRI methods, can provide important information regarding underlying compositional and ultrastructural changes that occur during early OA. Cartilage compositional MRI could serve as early imaging biomarkers for the objective evaluation of cartilage and help drive diagnostics, disease characterization, and response to novel therapies. This review will summarize current and ongoing state-of-the-art cartilage compositional MRI techniques and highlight emerging methods for cartilage compositional MRI including MR fingerprinting, compressed sensing, multiexponential relaxometry, improved and robust radio-frequency pulse sequences, and deep learning-based acquisition, reconstruction, and segmentation. The review will also briefly discuss the current challenges and future directions for adopting these emerging cartilage compositional MRI techniques for use in clinical practice and translational OA research studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Three-dimensional multi-parameter brain mapping using MR fingerprinting.

The purpose of this study was to develop and test a 3D multi-parameter MR fingerprinting (MRF) method for brain imaging applications. The subject cohort included 5 healthy volunteers, repeatability tests done on 2 healthy volunteers and tested on two multiple sclerosis (MS) patients. A 3D-MRF imaging technique capable of quantifying T1, T2 and T1ρ was used. The imaging sequence was tested in standardized phantoms and 3D-MRF brain imaging with multiple shots (1, 2 and 4) in healthy human volunteers and MS patients. Quantitative parametric maps for T1, T2, T1ρ, were generated. Mean gray matter (GM) and white matter (WM) ROIs were compared for each mapping technique, Bland-Altman plots and intra-class correlation coefficient (ICC) were used to assess repeatability and Student T-tests were used to compare results in MS patients. Standardized phantom studies demonstrated excellent agreement with reference T1/T2/T1ρ mapping techniques. This study demonstrates that the 3D-MRF technique is able to simultaneously quantify T1, T2 and T1ρ for tissue property characterization in a clinically feasible scan time. This multi-parametric approach offers increased potential to detect and differentiate brain lesions and to better test imaging biomarker hypotheses for several neurological diseases, including MS.

Data-driven optimization of sampling patterns for MR brain T1ρ mapping.

PURPOSE: The goal of this study was to apply a fast data-driven optimization algorithm, called bias-accelerated subset selection, for MR brain T1ρ mapping to generate optimized sampling patterns (SPs) for compressed sensing reconstruction of brain 3D-T1ρ MRI. METHODS: Five healthy volunteers were recruited, and fully sampled Cartesian 3D-T1ρ MRIs were obtained. Variable density (VD) and Poisson disc (PD) undersampling was used as the input to SP optimization process. The reconstruction used 3 compressed sensing methods: spatiotemporal finite differences, low-rank plus sparse with spatial finite differences, and low rank. The performance of images and T1ρ maps using PD-SP and VD-SP and their optimized sampling patterns (PD-OSP and VD-OSP) were compared to the fully sampled reference using normalized root mean square error (NRMSE). RESULTS: The VD-OSP with spatiotemporal finite differences reconstruction (NRMSE = 0.078) and the PD-OSP with spatiotemporal finite differences reconstruction (NRMSE = 0.079) at the highest acceleration factors (AF = 30) showed the largest improvement compared to the respective nonoptimized SPs (VD NRMSE = 0.087 and PD NRMSE = 0.149). Prospective undersampling was tested at AF = 4, with VD-OSP NRMSE = 0.057 versus PD-OSP NRMSE = 0.060, with optimized sampling performing better that input PD or VD sampling. For brain T1ρ mapping, the VD-OSP with low rank reconstruction for AFs <10 and VD-OSP with spatiotemporal finite differences for AFs >10 perform better. CONCLUSIONS: The study demonstrated that the appropriate use of data-driven optimized sampling and suitable compressed sensing reconstruction technique can be employed to potentially accelerate 3D T1ρ mapping for brain imaging applications.

Age-Dependent Changes in Knee Cartilage T1 , T2 , and T1p Simultaneously Measured Using MRI Fingerprinting.

BACKGROUND: Magnetic resonance fingerprinting (MRF) techniques have been recently described for simultaneous multiparameter cartilage mapping of the knee although investigation of their ability to detect early cartilage degeneration remains limited. PURPOSE: To investigate age-dependent changes in knee cartilage T1 , T2 , and T1p relaxation times measured using a three-dimensional (3D) MRF sequence in healthy volunteers. STUDY TYPE: Prospective. SUBJECTS: The study group consisted of 24 healthy asymptomatic human volunteers (15 males with mean age 34.9 ± 14.4 years and 9 females with mean age 44.5 ± 13.1 years). FIELD STRENGTH/SEQUENCE: A 3.0 T gradient-echo-based 3D-MRF sequence was used to simultaneously create proton density-weighted images and T1 , T2 , and T1p maps of knee cartilage. ASSESSMENT: Mean global cartilage and regional cartilage (lateral femur, lateral tibia, medial femur, medial tibia, and patella) T1 , T2 , and T1ρ relaxation times of the knee were measured. STATISTICAL TESTS: Kruskal-Wallis tests were used to compared cartilage T1 , T2 , and T1ρ relaxation times between different age groups, while Spearman correlation coefficients was used to determine the association between age and cartilage T1 , T2 , and T1ρ relaxation times. The value of P < 0.05 was considered statistically significant. RESULTS: Higher age groups showed higher global and regional cartilage T1 , T2 , and T1ρ . There was a significant difference between age groups in global cartilage T2 and T1ρ but no significant difference (P = 0.13) in global cartilage T1. Significant difference was also present between age groups in cartilage T2 and T1ρ for medial femur cartilage and medial tibia cartilage. There were significant moderate correlations between age and T2 and T1ρ for global cartilage (R2  = 0.63-0.64), medial femur cartilage (R2  = 0.50-0.56), and medial tibia cartilage (R2  = 0.54-0.66). CONCLUSION: Cartilage T2 and T1p relaxation times simultaneously measured using a 3D-MRF sequence in healthy volunteers showed age-dependent changes in knee cartilage, primarily within the medial compartment.

Optimization of spin-lock times for T1ρ mapping of human knee cartilage with bi- and stretched-exponential models.

Two optimization criteria based on Cramér-Rao Bounds are compared between each other and with non-optimized schedules for T1ρ mapping using synthetic data, model phantoms, and in-vivo knee cartilage. The curve fitting is done on complex-valued data using an iterative Nonlinear Least Squares (NLS) approach. The optimization criteria are compared based on the Mean Normalized Absolute Error (MNAE) and variance of the estimated parameters. The optimized spin-lock time (TSL) schedules provided improved results over the non-optimized schedules for all cases that were tested. The simulations showed that optimized schedules can reach the same precision and reduce acquisition times by 16.5 min (42%) for the bi-exponential model, and 6.6 min (22%) for the stretched-exponential model. In the model phantoms experiments, the bi-exponential MNAE was reduced from 0.47 to 0.36, while stretched-exponential from 0.28 to 0.20 with a Modified Cramér-Rao Lower Bound (MCRLB). In-vivo knee cartilage experiments show a reduction in bi-exponential MNAE from 0.47 to 0.31, and stretched-exponential from 0.047 to 0.039. The optimized spin-lock times criteria reduced the error in all cases, being more significant in the synthetic data and model phantoms. The optimized TSL schedules can be either used to improve the quality of parameter maps or reduce scan time.

Global Longitudinal Strain and Biomarkers of Cardiac Damage and Stress as Predictors of Outcomes After Transcatheter Aortic Valve Implantation.

Background Global longitudinal strain (GLS) is a sensitive measure of left ventricular function and a risk marker in severe aortic stenosis. We sought to determine whether biomarkers of cardiac damage (cardiac troponin) and stress (NT-proBNP [N-terminal pro-B-type natriuretic peptide]) could complement GLS to identify patients with severe aortic stenosis at highest risk. Methods and Results From a multicenter prospective cohort of patients with symptomatic severe aortic stenosis who underwent transcatheter aortic valve implantation, we measured absolute GLS (aGLS), cardiac troponin, and NT-proBNP at baseline in 499 patients. Left ventricular ejection fraction <50% was observed in 19% and impaired GLS (aGLS <15%) in 38%. Elevations in cardiac troponin and NT-proBNP were present in 79% and 89% of those with impaired GLS, respectively, as compared with 63% and 60% of those with normal GLS, respectively (P<0.001 for each). aGLS <15% was associated with increased mortality in univariable analysis (P=0.009), but, in a model with both biomarkers, aGLS, and clinical covariates included, aGLS was not associated with mortality; elevation in each biomarker was associated with an increased hazard of mortality (adjusted hazard ratio, >2; P≤0.002 for each) when the other biomarker was elevated, but not when the other biomarker was normal (interaction P=0.015). Conclusions Among patients with symptomatic severe aortic stenosis undergoing transcatheter aortic valve implantation, elevations in circulating cardiac troponin and NT-proBNP are more common as GLS worsens. Biomarkers of cardiac damage and stress are independently associated with mortality after transcatheter aortic valve implantation, whereas GLS is not. These findings may have implications for risk stratification of asymptomatic patients to determine optimal timing of valve replacement.

3D magnetic resonance fingerprinting for rapid simultaneous T1, T2, and T1ρ volumetric mapping of human articular cartilage at 3 T.

Quantitative MRI can detect early biochemical changes in cartilage; however, the conventional techniques only measure one parameter (e.g., T1 , T2 , and T1ρ ) at a time while also being comparatively slow. We implemented a 3D magnetic resonance fingerprinting (3D-MRF) technique for simultaneous, volumetric mapping of T1 , T2 , and T1ρ in knee articular cartilage in under 9 min. It is evaluated on 11 healthy volunteers (mean age: 53 ± 9 years), five mild knee osteoarthritis (OA) patients (Kellgren-Lawrence (KL) score: 2, mean age: 60 ± 4 years), and the National Institute of Standards and Technology (NIST)/International Society for Magnetic Resonance in Medicine (ISMRM) system phantom. Proton density image, and T1 , T2, T1ρ relaxation times, and B1 + were estimated in the NIST/ISMRM system phantom as well as in the human knee medial and lateral femur, medial and lateral tibia, and patellar cartilage. The repeatability and reproducibility of the proposed technique were assessed in the phantom using analysis of the Bland-Altman plots. The intrasubject repeatability was assessed with the coefficient of variation (CV) and root mean square CV (rmsCV). The Mann-Whitney U test was used to assess the difference between healthy subjects and mild knee OA patients. The Bland-Altman plots in the NIST/ISMRM phantom demonstrated an average difference of 0.001% ± 015%, 1.2% ± 7.1%, and 0.47% ± 3% between two scans from the same 3-T scanner (repeatability), and 0.002% ± 015%, 0.62% ± 10.5%, and 0.97% ± 14% between the scans acquired on two different 3-T scanners (reproducibility) for T1 , T2 , and T1ρ , respectively. The in vivo knee study showed excellent repeatability with rmsCV less than 1%, 2%, and 1% for T1 , T2 , and T1ρ , respectively. T1ρ relaxation time in the mild knee OA patients was significantly higher (p < 0.05) than in healthy subjects. The proposed 3D-MRF sequence is fast, reproducible, robust to B1 + inhomogeneity, and can simultaneously measure the T1 , T2 , T1ρ , and B1 + volumetric maps of the knee joint in a single scan within a clinically feasible scan time.

Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications.

This work proposes an alternating learning approach to learn the sampling pattern (SP) and the parameters of variational networks (VN) in accelerated parallel magnetic resonance imaging (MRI). We investigate four variations of the learning approach, that alternates between improving the SP, using bias-accelerated subset selection, and improving parameters of the VN, using ADAM. The variations include the use of monotone or non-monotone alternating steps and systematic reduction of learning rates. The algorithms learn an effective pair to be used in future scans, including an SP that captures fewer k-space samples in which the generated undersampling artifacts are removed by the VN reconstruction. The quality of the VNs and SPs obtained by the proposed approaches is compared against different methods, including other kinds of joint learning methods and state-of-art reconstructions, on two different datasets at various acceleration factors (AF). We observed improvements visually and in three different figures of merit commonly used in deep learning (RMSE, SSIM, and HFEN) on AFs from 2 to 20 with brain and knee joint datasets when compared to the other approaches. The improvements ranged from 1% to 62% over the next best approach tested with VNs. The proposed approach has shown stable performance, obtaining similar learned SPs under different initial training conditions. We observe that the improvement is not only due to the learned sampling density, it is also due to the learned position of samples in k-space. The proposed approach was able to learn effective pairs of SPs and reconstruction VNs, improving 3D Cartesian accelerated parallel MRI applications.

Left Ventricular Hypertrophy and Biomarkers of Cardiac Damage and Stress in Aortic Stenosis.

Background Left ventricular hypertrophy (LVH) is associated with increased mortality risk and rehospitalization after transcatheter aortic valve replacement among those with severe aortic stenosis. Whether cardiac troponin (cTnT) and NT-proBNP (N-terminal pro-B-type natriuretic peptide) risk stratify patients with aortic stenosis and without LVH is unknown. Methods and Results In a multicenter prospective registry of 923 patients with severe aortic stenosis undergoing transcatheter aortic valve replacement, we included 674 with core-laboratory-measured LV mass index, cTnT, and NT-proBNP. LVH was defined by sex-specific guideline cut-offs and elevated biomarker levels were based on age and sex cut-offs. Adjusted Cox proportional hazards models evaluated associations between LVH and biomarkers and all-cause death out to 5 years. Elevated cTnT and NT-proBNP were present in 82% and 86% of patients with moderate/severe LVH, respectively, as compared with 66% and 69% of patients with no/mild LVH, respectively (P<0.001 for each). After adjustment, compared with no/mild LVH, moderate/severe LVH was associated with an increased hazard of mortality (adjusted hazard ratio [aHR], 1.34; 95% CI 1.01-1.77, P=0.043). cTnT and NT-proBNP each risk stratified patients with moderate/severe LVH (P<0.05). In a model with both biomarkers and LVH included, elevated cTnT (aHR, 2.08; 95% CI 1.45-3.00, P<0.001) and elevated NT-proBNP (aHR, 1.46; 95% CI 1.00-2.11, P=0.049) were each associated with increased mortality risk, whereas moderate/severe LVH was not (P=0.15). Conclusions Elevations in circulating cTnT and NT-proBNP are more common as LVH becomes more pronounced but are also observed in those with no/minimal LVH. As measures of maladaptive remodeling and cardiac injury, cTnT and NT-proBNP predict post-transcatheter aortic valve replacement mortality better than LV mass index. These findings may have important implications for risk stratification and treatment of patients with aortic stenosis.

Unbound vitamin D concentrations are not decreased in critically ill patients.

BACKGROUND: Free concentrations of highly protein bound hormones, such as cortisol and thyroxine, are unchanged in critical illness despite substantial decreases in total concentration. Total 25-hydroxyvitamin D (25(OH)D) concentration is decreased in critical illness, but the free concentration of 25(OH)D has had less attention. AIM: To compare total and calculated free 25(OH)D concentrations in critically ill patients with healthy controls. METHODS: In this case-control study, 38 patients with critical illness were compared with 68 healthy controls; 25(OH)D was measured by liquid chromatography tandem mass spectrometry (LCMS/MS) and vitamin D binding protein (VDBP) by direct sandwich enzyme-linked immunosorbent assay. Total and calculated free 25(OH)D concentrations were compared using unpaired t-tests. RESULTS: Total 25(OH)D concentrations were significantly lower in critically ill patients than controls (37 (95% confidence interval 31-43) vs 57 (53-60) nmol/L). Calculated free concentrations of 25(OH)D were not lower in critically ill patients than healthy controls (26 (22-29) vs 19 (18-20) pmol/L). CONCLUSIONS: Calculated free 25(OH)D concentrations are not decreased in critical illness. Measuring total 25(OH)D concentrations in patients with critical illness potentially underestimates vitamin D and overestimates the number of patients who are deficient in vitamin D.