A machine learning-derived risk score to predict left ventricular diastolic dysfunction from clinical cardiovascular magnetic resonance imaging.

Introduction: The evaluation of left ventricular diastolic dysfunction (LVDD) by clinical cardiac magnetic resonance (CMR) remains a challenge. We aimed to train and evaluate a machine-learning (ML) algorithm for the assessment of LVDD by clinical CMR variables and to investigate its prognostic value for predicting hospitalized heart failure and all-cause mortality. Methods: LVDD was characterized by echocardiography following the ASE guidelines. Eight demographic and nineteen common clinical CMR variables including delayed enhancement were used to train Random Forest models with a Bayesian optimizer. The model was evaluated using bootstrap and five-fold cross-validation. Area under the ROC curve (AUC) was utilized to evaluate the model performance. An ML risk score was used to stratify the risk of heart failure hospitalization and all-cause mortality. Results: A total of 606 consecutive patients underwent CMR and echocardiography within 7 days for cardiovascular disease evaluation. LVDD was present in 303 subjects by echocardiography. The performance of the ML algorithm was good using the CMR variables alone with an AUC of 0.868 (95% CI: 0.811-0.917), which was improved by combining with demographic data yielding an AUC 0.895 (95% CI: 0.845-0.939). The algorithm performed well in an independent validation cohort with AUC 0.810 (0.731-0.874). Subjects with higher ML scores (>0.4121) were associated with increased adjusted hazard ratio for a composite outcome than subjects with lower ML scores (1.72, 95% confidence interval 1.09-2.71). Discussion: An ML algorithm using variables derived from clinical CMR is effective in identifying patients with LVDD and providing prognostication for adverse clinical outcomes.

Inversion recovery and saturation recovery pulmonary vein MR angiography using an image based navigator fluoro trigger and variable-density 3D cartesian sampling with spiral-like order.

Contrast enhanced pulmonary vein magnetic resonance angiography (PV CE-MRA) has value in atrial ablation pre-procedural planning. We aimed to provide high fidelity, ECG gated PV CE-MRA accelerated by variable density Cartesian sampling (VD-CASPR) with image navigator (iNAV) respiratory motion correction acquired in under 4 min. We describe its use in part during the global iodinated contrast shortage. VD-CASPR/iNAV framework was applied to ECG-gated inversion and saturation recovery gradient recalled echo PV CE-MRA in 65 patients (66 exams) using .15 mmol/kg Gadobutrol. Image quality was assessed by three physicians, and anatomical segmentation quality by two technologists. Left atrial SNR and left atrial/myocardial CNR were measured. 12 patients had CTA within 6 months of MRA. Two readers assessed PV ostial measurements versus CTA for intermodality/interobserver agreement. Inter-rater/intermodality reliability, reproducibility of ostial measurements, SNR/CNR, image, and anatomical segmentation quality was compared. The mean acquisition time was 3.58 ± 0.60 min. Of 35 PV pre-ablation datasets (34 patients), mean anatomical segmentation quality score was 3.66 ± 0.54 and 3.63 ± 0.55 as rated by technologists 1 and 2, respectively (p = 0.7113). Good/excellent anatomical segmentation quality (grade 3/4) was seen in 97% of exams. Each rated one exam as moderate quality (grade 2). 95% received a majority image quality score of good/excellent by three physicians. Ostial PV measurements correlated moderate to excellently with CTA (ICCs range 0.52-0.86). No difference in SNR was observed between IR and SR. High quality PV CE-MRA is possible in under 4 min using iNAV bolus timing/motion correction and VD-CASPR.

Comparison between compressed sensing and segmented cine cardiac magnetic resonance: a meta-analysis.

PURPOSE: Highly accelerated compressed sensing cine has allowed for quantification of ventricular function in a single breath hold. However, compared to segmented breath hold techniques, there may be underestimation or overestimation of LV volumes. Furthermore, a heterogeneous sample of techniques have been used in volunteers and patients for pre-clinical and clinical use. This can complicate individual comparisons where small, but statistically significant differences exist in left ventricular morphological and/or functional parameters. This meta-analysis aims to provide a comparison of conventional cine versus compressed sensing based reconstruction techniques in patients and volunteers. METHODS: Two investigators performed systematic searches for eligible studies using PubMed/MEDLINE and Web of Science to identify studies published 1/1/2010-3/1/2021. Ultimately, 15 studies were included for comparison between compressed sensing cine and conventional imaging. RESULTS: Compared to conventional cine, there were small, statistically significant overestimation of LV mass, underestimation of stroke volume and LV end diastolic volume (mean difference 2.65 g [CL 0.57-4.73], 2.52 mL [CL 0.73-4.31], and 2.39 mL [CL 0.07-4.70], respectively). Attenuated differences persisted across studies using prospective gating (underestimated stroke volume) and non-prospective gating (underestimation of stroke volume, overestimation of mass). There were no significant differences in LV volumes or LV mass with high or low acceleration subgroups in reference to conventional cine except slight underestimation of ejection fraction among high acceleration studies. Reduction in breath hold acquisition time ranged from 33 to 64%, while reduction in total scan duration ranged from 43 to 97%. CONCLUSION: LV volume and mass assessment using compressed sensing CMR is accurate compared to conventional parallel imaging cine.

Left Ventricular Mass, Myocardial Structure, and Function in Severe Aortic Stenosis: an Echocardiographic and Cardiac Magnetic Resonance Imaging Study.

In severe aortic stenosis (AS), there are conflicting data on the prognostic implications of left ventricular (LV) hypertrophy (LVH). We aimed to characterize the LV geometry, myocardial matrix structural changes, and prognostic stratification using cardiac magnetic resonance imaging (CMR) and echocardiography in subjects with severe AS with and without LVH. Consecutive patients who had severe isolated AS and sufficient quality echocardiography and CMR within 6 months of each other were evaluated for LVH, cardiac structure, morphology, and late gadolinium-enhancement imaging. Kaplan-Meier curves, linear models, and proportional hazards models were used for prognostic stratification. There were 93 patients enrolled (mean age 74 ± 11 years, 48% female), of whom 38 (41%) had a normal LV mass index (LVMI), 41 (44%) had LVH defined at CMR by LVMI >2 SD higher than normal, and 14 (15% of the total) with >4 SD higher than the reference LVMI (severely elevated). The Society of Thoracic Surgeons scores were similar among the LVMI groups. Compared with those with normal LVMI, patients with LVH had higher LV end-diastolic and end-systolic volumes, increased late gadolinium-enhancement burden, and lower LV ejection fraction. Most notably, CMR feature-tracking global radial strain, 2-dimensional speckle-tracking echocardiography global longitudinal strain, and left atrial reservoir function were significantly worse. On the survival analyses, LVMI was not associated with a composite of all-cause mortality and/or heart failure hospitalization. In conclusion, compared with normal LVMI, elevated LVMI was not associated with a higher risk of adverse outcomes.

Myocardial Injury on CMR in Patients With COVID-19 and Suspected Cardiac Involvement.

BACKGROUND: Myocardial injury in patients with COVID-19 and suspected cardiac involvement is not well understood. OBJECTIVES: The purpose of this study was to characterize myocardial injury in a multicenter cohort of patients with COVID-19 and suspected cardiac involvement referred for cardiac magnetic resonance (CMR). METHODS: This retrospective study consisted of 1,047 patients from 18 international sites with polymerase chain reaction-confirmed COVID-19 infection who underwent CMR. Myocardial injury was characterized as acute myocarditis, nonacute/nonischemic, acute ischemic, and nonacute/ischemic patterns on CMR. RESULTS: In this cohort, 20.9% of patients had nonischemic injury patterns (acute myocarditis: 7.9%; nonacute/nonischemic: 13.0%), and 6.7% of patients had ischemic injury patterns (acute ischemic: 1.9%; nonacute/ischemic: 4.8%). In a univariate analysis, variables associated with acute myocarditis patterns included chest discomfort (OR: 2.00; 95% CI: 1.17-3.40, P = 0.01), abnormal electrocardiogram (ECG) (OR: 1.90; 95% CI: 1.12-3.23; P = 0.02), natriuretic peptide elevation (OR: 2.99; 95% CI: 1.60-5.58; P = 0.0006), and troponin elevation (OR: 4.21; 95% CI: 2.41-7.36; P < 0.0001). Variables associated with acute ischemic patterns included chest discomfort (OR: 3.14; 95% CI: 1.04-9.49; P = 0.04), abnormal ECG (OR: 4.06; 95% CI: 1.10-14.92; P = 0.04), known coronary disease (OR: 33.30; 95% CI: 4.04-274.53; P = 0.001), hospitalization (OR: 4.98; 95% CI: 1.55-16.05; P = 0.007), natriuretic peptide elevation (OR: 4.19; 95% CI: 1.30-13.51; P = 0.02), and troponin elevation (OR: 25.27; 95% CI: 5.55-115.03; P < 0.0001). In a multivariate analysis, troponin elevation was strongly associated with acute myocarditis patterns (OR: 4.98; 95% CI: 1.76-14.05; P = 0.003). CONCLUSIONS: In this multicenter study of patients with COVID-19 with clinical suspicion for cardiac involvement referred for CMR, nonischemic and ischemic patterns were frequent when cardiac symptoms, ECG abnormalities, and cardiac biomarker elevations were present.

Left Ventricle Wall Motion Analysis with Real-Time MRI Feature Tracking in Heart Failure Patients: A Pilot Study.

Volumetric measurements with cardiac magnetic resonance imaging (MRI) are effective for evaluating heart failure (HF) with systolic dysfunction that typically induces a lower ejection fraction (EF) than normal (<50%) while they are not sensitive to diastolic dysfunction in HF patients with preserved EF (≥50%). This work is to investigate whether HF evaluation with cardiac MRI can be improved with real-time MRI feature tracking. In a cardiac MRI study, we recruited 16 healthy volunteers, 8 HF patients with EF < 50% and 10 HF patients with preserved EF. Using real-time feature tracking, a cardiac MRI index, torsion correlation, was calculated which evaluated the correlation of torsional and radial wall motion in the left ventricle (LV) over a series of sequential cardiac cycles. The HF patients with preserved EF and the healthy volunteers presented significant difference in torsion correlation (one-way ANOVA, p < 0.001). In the scatter plots of EF against torsion correlation, the HF patients with EF < 50%, the HF patients with preserved EF and the healthy volunteers were well differentiated, indicating that real-time MRI feature tracking provided LV function assessment complementary to volumetric measurements. This study demonstrated the potential of cardiac MRI for evaluating both systolic and diastolic dysfunction in HF patients.

Society for Cardiovascular Magnetic Resonance 2021 cases of SCMR and COVID-19 case collection series.

The Society for Cardiovascular Magnetic Resonance (SCMR) is an international society focused on the research, education, and clinical application of cardiovascular magnetic resonance (CMR). "Cases of SCMR" is a case series hosted on the SCMR website ( https://www.scmr.org ) that demonstrates the utility and importance of CMR in the clinical diagnosis and management of cardiovascular disease. The COVID-19 Case Collection highlights the impact of coronavirus disease 2019 (COVID-19) on the heart as demonstrated on CMR. Each case in series consists of the clinical presentation and the role of CMR in diagnosis and guiding clinical management. The cases are all instructive and helpful in the approach to patient management. We present a digital archive of the 2021 Cases of SCMR and the 2020 and 2021 COVID-19 Case Collection series of nine cases as a means of further enhancing the education of those interested in CMR and as a means of more readily identifying these cases using a PubMed or similar literature search engine.

Temporospatial characterization of ventricular wall motion with real-time cardiac magnetic resonance imaging in health and disease.

Cardiac magnetic resonance imaging (MRI) has been largely dependent on retrospective cine for data acquisition. Real-time imaging, although inferior in image quality to retrospective cine, is more informative about motion dynamics. We herein developed a real-time cardiac MRI approach to temporospatial characterization of left ventricle (LV) and right ventricle (RV) wall motion. This approach provided two temporospatial indices, temporal periodicity and spatial coherence, for quantitative assessment of ventricular function. In a cardiac MRI study, we prospectively investigated temporospatial characterization in reference to standard volumetric measurements with retrospective cine. The temporospatial indices were found to be effective for evaluating the difference of ventricular performance between the healthy volunteers and the heart failure (HF) patients (LV temporal periodicity 0.24 ± 0.037 vs. 0.14 ± 0.021; RV temporal periodicity 0.18 ± 0.030 vs. 0.10 ± 0.014; LV spatial coherence 0.52 ± 0.039 vs. 0.38 ± 0.040; RV spatial coherence 0.50 ± 0.036 vs. 0.35 ± 0.035; all in arbitrary unit). The HF patients and healthy volunteers were well differentiated in the scatter plots of spatial coherence and temporal periodicity while they were mixed in those of end-systolic volume (ESV) and ejection fraction (EF) from volumetric measurements. This study demonstrated the potential of real-time cardiac MRI for intricate analysis of ventricular function beyond retrospective cine.

Optical Flow Analysis of Left Ventricle Wall Motion with Real-Time Cardiac Magnetic Resonance Imaging in Healthy Subjects and Heart Failure Patients.

In cardiology, magnetic resonance imaging (MRI) provides a clinical standard for measuring ventricular volumes. Owing to their reliability, volumetric measurements with cardiac MRI have become an essential tool for quantitative assessment of ventricular function. However, as volumetric indices are indirectly related to myocardial motion that drives ventricular filling and ejection, cardiac MRI cannot provide comprehensive evaluation of ventricular performance. To overcome this limitation, the presented work sought to measure ventricular wall motion directly with optical flow analysis of real-time cardiac MRI. By modeling left ventricle (LV) walls in real-time images based on myocardial architecture, we developed an optical flow approach to analyzing LV radial and circumferential wall motion for improved quantitative assessment of ventricular function. For proof-of-concept, a cardiac MRI study was conducted with healthy volunteers and heart failure (HF) patients. It was found that, as real-time images provided sufficient temporal information for correlation analysis between different LV wall motion velocity components, optical flow assessment detected the difference of ventricular performance between the HF patients and the healthy volunteers more effectively than volumetric measurements. We expect that this model-based optical flow assessment with real-time cardiac MRI would offer intricate analysis of ventricular function beyond conventional volumetric measurements.

Society for Cardiovascular Magnetic Resonance 2020 Case of the Week series.

The Society for Cardiovascular Magnetic Resonance (SCMR) is an international society focused on the research, education, and clinical application of cardiovascular magnetic resonance (CMR). Case of the week is a case series hosted on the SCMR website ( https://www.scmr.org ) that demonstrates the utility and importance of CMR in the clinical diagnosis and management of cardiovascular disease. Each case consists of the clinical presentation and a discussion of the condition and the role of CMR in diagnosis and guiding clinical management. The cases are all instructive and helpful in the approach to patient management. We present a digital archive of the 2020 Case of the Week series of 11 cases as a means of further enhancing the education of those interested in CMR and as a means of more readily identifying these cases using a PubMed or similar search engine.

How to do left atrial late gadolinium enhancement: a review.

BACKGROUND: Quantification of left atrial late gadolinium enhancement is a powerful clinical and research tool. Fibrosis burden has been shown to predict the success of pulmonary vein isolation, post-ablation reoccurrence, and major adverse cardiovascular events such as stroke. OVERVIEW: The standardized cardiovascular magnetic resonance imaging protocols 2020 update describes the key components of the examination. This review is a more in-depth guide, geared toward building left atrial late gadolinium enhancement imaging from the ground up. The standard protocol consists of the following: localization, pulmonary vein magnetic resonance angiography, cardiac cines, left ventricular, and atrial late gadolinium enhancement. We also review typical segmentation and post-processing techniques, as well as discuss pitfalls, limitations, and potential future innovations in this area. CONCLUSIONS: With sufficient experience and optimized protocols, left atrial late gadolinium enhancement imaging is a strong addition to the cardiac magnetic resonance imaging repertoire.

ACR Appropriateness Criteria® Nontraumatic Aortic Disease.

Nontraumatic aortic disease can be caused by a wide variety of disorders including congenital, inflammatory, infectious, metabolic, neoplastic, and degenerative processes. Imaging examinations such as radiography, ultrasound, echocardiography, catheter-based angiography, CT, MRI, and nuclear medicine examinations are essential for diagnosis, treatment planning, and assessment of therapeutic response. Depending upon the clinical scenario, each of these modalities has strengths and weaknesses. Whenever possible, the selection of a diagnostic imaging examination should be based upon the best available evidence. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment. The purpose of this document is to assist physicians select the most appropriate diagnostic imaging examination for nontraumatic aortic diseases.

A Technique for Endoscopic in Situ Repair of Undersurface Hip Abductor Tears.

Endoscopic repair of hip abductor tendons has been shown to have equivalent outcomes and lower complication rates compared with open repair. First reported in 2007, endoscopic repair has become more frequent, with multiple techniques previously described. Frequently, hip abductor tears involve a partial-thickness undersurface component that has been previously addressed endoscopically by making a longitudinal split in the tendon to access the diseased tissue. However, we present a technique for addressing these undersurface tears in situ, accessing the undersurface of the tear by coming under the distal anterior edge of the gluteus medius tendon.

Reduced cardiac function is associated with cardiac injury and mortality risk in hospitalized COVID-19 Patients.

BACKGROUND: Cardiac injury is common in COVID-19 patients and is associated with increased mortality. However, it remains unclear if reduced cardiac function is associated with cardiac injury, and additionally if mortality risk is increased among those with reduced cardiac function in COVID-19 patients. HYPOTHESIS: The aim of this study was to assess cardiac function among COVID-19 patients with and without biomarkers of cardiac injury and to determine the mortality risk associated with reduced cardiac function. METHODS/RESULTS: This retrospective cohort study analyzed 143 consecutive COVID-19 patients who had an echocardiogram during hospitalization between March 1, 2020 and May 5, 2020. The mean age was 67 ± 16 years. Cardiac troponin-I was available in 131 patients and an increased value (>0.03 ng/dL) was found in 59 patients (45%). Reduced cardiac function, which included reduced left or right ventricular systolic function, was found in 40 patients (28%). Reduced cardiac function was found in 18% of patients without troponin-I elevation, 42% with mild troponin increase (0.04-5.00 ng/dL) and 67% with significant troponin increase (>5 ng/dL). Reduced cardiac function was also present in more than half of the patients on mechanical ventilation or those deceased. The in-hospital mortality of this cohort was 28% (N = 40). Using logistic regression analysis, we found that reduced cardiac function was associated with increased mortality with adjusted odds ratio (95% confidence interval) of 2.65 (1.18 to 5.96). CONCLUSIONS: Reduced cardiac function is highly prevalent among hospitalized COVID-19 patients with biomarkers of myocardial injury and is independently associated with mortality.

Patient-Adaptive Magnetic Resonance Oximetry: Comparison With Invasive Catheter Measurement of Blood Oxygen Saturation in Patients With Cardiovascular Disease.

BACKGROUND: The current standard method to measure intracardiac oxygen (O2 ) saturation is by invasive catheterization. Accurate noninvasive blood O2 saturation by MRI could potentially reduce the duration and risk of invasive diagnostic procedures. PURPOSE: To noninvasively determine blood oxygen saturation in the heart with MRI and compare the accuracy with catheter measurements. STUDY TYPE: Prospective. SUBJECTS: Thirty-two patients referred for right heart catheterization (RHC) and five healthy subjects. FIELD STRENGTH/SEQUENCE: T2-prepared single-shot balanced steady-state free-precession at 1.5T. ASSESSMENT: MR signals in venous and arterial blood, hematocrit, and arterial O2 saturation from a pulse oximeter were jointly processed to fit the Luz-Meiboom model and estimate blood O2 saturation in the right heart. Interstudy reproducibility was evaluated in volunteers and patients. Interobserver reproducibility among three readers was assessed using data from volunteers and 10 patients. Accuracy of MR oximetry was compared to RHC in all patients. STATISTICAL TESTS: Coefficient of variation, intraclass correlation coefficient, Bland-Altman analysis, Pearson's correlation. RESULTS: The coefficient of variation for interstudy reproducibility of O2 saturation was 2.6% on average in volunteers and 3.2% in patients. Interobserver reproducibility among three observers yielded intraclass correlation coefficients of 0.81 and 0.87 respectively for RV and MPA O2 saturation. O2 saturation (y = 0.85x + 0.13, R = 0.78) and (a-v)O2 difference (y = 0.71x + 0.90, R = 0.69) by MR and RHC were significantly correlated (N = 32, P < 0.05 in both cases) in patients. MR slightly overestimated O2 saturation compared to RHC with 2% ± 5% bias and limits of agreement between -7% and 12%. DATA CONCLUSION: MR oximetry is repeatable and reproducible. Good agreement was shown between MR and catheter venous O2 saturation and (a-v)O2 difference in a cohort whose venous O2 ranged from abnormally low to high levels, with most values in the normal physiological range. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2.

Assessment of cardiac function, blood flow and myocardial tissue relaxation parameters at 0.35 T.

A low field strength (B0) system could increase cardiac MRI availability for patients otherwise contraindicated at higher field. Lower equipment costs could also broaden cardiac MR accessibility. The current study investigated the feasibility of cardiac function with steady-state free precession and flow assessment with phase contrast (PC) cine images at 0.35 T, and evaluated differences in myocardial relaxation times using quantitative T1, T2 and T2* maps by comparison with 1.5 and 3 T results in a small cohort of six healthy volunteers. Signal-to-noise ratio (SNR) differences across systems were characterized with proton density-weighted spin echo phantom data. SNR at 0.35 T was lower by factors of 5.5 and 15.0 compared with the 1.5 and 3 T systems used in this study. All cine images at 0.35 T scored 3 or greater on a five-point image quality scale. Normalized blood-myocardium contrast in cine images, left ventricular volumes (end diastolic volume, end systolic volume) and function (ejection fraction and stroke volume) measures at 0.35 T matched 1.5 and 3 T results. Phase-to-noise ratio in 0.35 T PC images (11.7 ± 1.9) was lower than 1.5 T (18.7 ± 5.2) and 3 T (44.9 ± 16.5). Peak velocity and stroke volume determined from PC images were similar across systems. Myocardial T1 increased (564 ± 13 ms at 0.35 T, 955 ± 19 ms at 1.5 T and 1200 ± 35 ms at 3 T) while T2 (59 ± 4 ms at 0.35 T, 49 ± 3 ms at 1.5 T and 40 ± 2 ms at 3 T) and T2* (42 ± 8 ms at 0.35 T, 33 ± 6 ms at 1.5 T and 24 ± 3 ms at 3 T) decreased with increasing B0. Despite SNR deficits, cardiovascular function, flow assessment and myocardial relaxation parameter mapping is feasible at 0.35 T using standard cardiovascular imaging sequences.

Water-fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network.

BACKGROUND: Water-fat separation is a postprocessing technique most commonly applied to multiple-gradient-echo magnetic resonance (MR) images to identify fat, provide images with fat suppression, and to measure fat tissue concentration. Recently, Numerous advancements have been reported. In contrast to early methods, the process of water-fat separation has become complicated due to multiparametric analytic models, optimization methods, and the absence of a unified framework for diverse source data. PURPOSE: To determine the feasibility and performance of MRI water-fat separation and parametric mapping via deep learning (DL) with a range of inputs. STUDY TYPE: Retrospective data usage. POPULATION/SUBJECTS: Ninety cardiac MR examinations from normal control, acute, subacute, and chronic myocardial infarction subjects were obtained, providing 1200 multiple gradient-echo acquisitions. FIELD STRENGTH/SEQUENCE: 1.5 T/2D multiple gradient-echo pulse sequence ASSESSMENT: Ground-truth training and validation water-fat separation were obtained using a graph cut method with R2 *, off-resonance correction, and a multipeak fat spectrum. U-Net DL training with single and multiecho, complex, and magnitude inputs were compared using quantitative and three-observer subjective analysis. STATISTICAL TESTS: DL methods' image structural similarity, and quantitative proton density fat fraction (PDFF), R2 *, and off-resonance quantitative values were statistically compared with the GraphCut reference standard using Student's t-test and Pearson's correlation. RESULTS: Myocardial fat deposition in chronic myocardial infarction and intramyocardial hemorrhage in acute myocardial infarction were well visualized in the DL results. Predicted values for R2 *, off-resonance, water, and fat signal intensities were well correlated with a conventional model-based water fat separation (R2 ≥ 0.97, P < 0.001) with appropriate inputs. DL parameter maps had a 14% higher signal-to-noise ratio (P < 0.001) when compared with a conventional method. DATA CONCLUSION: DL water-fat separation is feasible with a wide range of inputs, while R2 * and off-resonance mapping requires multiple echoes and complex images. With appropriate inputs, DL provides quantitative and subjective results comparable to conventional model-based methods. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:655-665.

Sparsity adaptive reconstruction for highly accelerated cardiac MRI.

PURPOSE: To enable parameter-free, accelerated cardiovascular magnetic resonance (CMR). METHODS: Regularized reconstruction methods, such as compressed sensing (CS), can significantly accelerate MRI data acquisition but require tuning of regularization weights. In this work, a technique, called Sparsity adaptive Composite Recovery (SCoRe) that exploits sparsity in multiple, disparate sparsifying transforms is presented. A data-driven adjustment of the relative contributions of different transforms yields a parameter-free CS recovery process. SCoRe is validated in a dynamic digital phantom as well as in retrospectively and prospectively undersampled cine CMR data. RESULTS: The results from simulation and 6 retrospectively undersampled datasets indicate that SCoRe with auto-tuned regularization weights yields lower root-mean-square error (RMSE) and higher structural similarity index (SSIM) compared to state-of-the-art CS methods. In 45 prospectively undersampled datasets acquired from 15 volunteers, the image quality was scored by 2 expert reviewers, with SCoRe receiving a higher average score (p  <  0.01) compared to other CS methods. CONCLUSIONS: SCoRe enables accelerated cine CMR from highly undersampled data. In contrast to other acceleration techniques, SCoRe adapts regularization weights based on noise power and level of sparsity in each transform, yielding superior performance without admitting any free parameters.

Fast implementation for compressive recovery of highly accelerated cardiac cine MRI using the balanced sparse model.

PURPOSE: Sparsity-promoting regularizers can enable stable recovery of highly undersampled magnetic resonance imaging (MRI), promising to improve the clinical utility of challenging applications. However, lengthy computation time limits the clinical use of these methods, especially for dynamic MRI with its large corpus of spatiotemporal data. Here, we present a holistic framework that utilizes the balanced sparse model for compressive sensing and parallel computing to reduce the computation time of cardiac MRI recovery methods. THEORY AND METHODS: We propose a fast, iterative soft-thresholding method to solve the resulting ℓ1-regularized least squares problem. In addition, our approach utilizes a parallel computing environment that is fully integrated with the MRI acquisition software. The methodology is applied to two formulations of the multichannel MRI problem: image-based recovery and k-space-based recovery. RESULTS: Using measured MRI data, we show that, for a 224 × 144 image series with 48 frames, the proposed k-space-based approach achieves a mean reconstruction time of 2.35 min, a 24-fold improvement compared a reconstruction time of 55.5 min for the nonlinear conjugate gradient method, and the proposed image-based approach achieves a mean reconstruction time of 13.8 s. CONCLUSION: Our approach can be utilized to achieve fast reconstruction of large MRI datasets, thereby increasing the clinical utility of reconstruction techniques based on compressed sensing. Magn Reson Med 77:1505-1515, 2017. © 2016 International Society for Magnetic Resonance in Medicine.