Comprehensive left atrial flow component analysis reveals abnormal flow patterns in paroxysmal atrial fibrillation.

Left atrial (LA) blood flow plays an important role in diseases such as atrial fibrillation (AF) and atrial cardiomyopathy since alterations in the blood flow might lead to thrombus formation and stroke. Using traditional techniques, such as echocardiography, atrial flow velocities can be measured at the pulmonary veins and the mitral valve, but a comprehensive understanding of the three-dimensional atrial flow field is missing. Previously, ventricular flow has been analyzed using flow component analysis, revealing new insights into ventricular flow and function. Thus, the aim of this project was to develop a comprehensive flow component analysis method for the LA and explore its utility in 21 patients with paroxysmal atrial fibrillation compared with a control group of 8 participants. The flow field was derived from time-resolved CT acquired during sinus rhythm using computational fluid dynamics. Flow components were computed from particle tracking. We identified six atrial flow components: conduit, reservoir, delayed ejection, retained inflow, residual volume, and pulmonary vein backflow. It was shown that conduit flow, defined as blood entering and leaving the LA within the same diastolic phase, exists in most subjects. Although the volume of conduit and reservoir is similar in patients with paroxysmal AF in sinus rhythm and controls, the volume of the other components is increased in paroxysmal AF. Comprehensive quantification of LA flow using flow component analysis makes atrial blood flow quantifiable, thus facilitating investigation of mechanisms underlying atrial dysfunction and can increase understanding of atrial blood flow in disease progression and stroke risk.NEW & NOTEWORTHY We developed a new comprehensive approach to atrial blood component analysis that includes both conduit flow and residual volume and compared the flow components of atrial fibrillation (AF) patients in sinus rhythm with controls. Conduit and reservoir flow were similar between the groups, whereas components with longer residence time in the left atrium were increased in the AF group. This could add to the pathophysiological understanding of atrial diseases and possibly clinical management.

Liver fibrosis is associated with left ventricular remodeling: insight into the liver-heart axis.

OBJECTIVE: In nonalcoholic fatty liver disease (NAFLD), liver fibrosis is the strongest predictor of adverse outcomes. We sought to investigate the relationship between liver fibrosis and cardiac remodeling in participants from the general population using magnetic resonance imaging (MRI), as well as explore potential mechanistic pathways by analyzing circulating cardiovascular biomarkers. METHODS: In this cross-sectional study, we prospectively included participants with type 2 diabetes and individually matched controls from the SCAPIS (Swedish CArdioPulmonary bioImage Study) cohort in Linköping, Sweden. Between November 2017 and July 2018, participants underwent MRI at 1.5 Tesla for quantification of liver proton density fat fraction (spectroscopy), liver fibrosis (stiffness from elastography), left ventricular (LV) structure and function, as well as myocardial native T1 mapping. We analyzed 278 circulating cardiovascular biomarkers using a Bayesian statistical approach. RESULTS: In total, 92 participants were enrolled (mean age 59.5 ± 4.6 years, 32 women). The mean liver stiffness was 2.1 ± 0.4 kPa. 53 participants displayed hepatic steatosis. LV concentricity increased across quartiles of liver stiffness. Neither liver fat nor liver stiffness displayed any relationships to myocardial tissue characteristics (native T1). In a regression analysis, liver stiffness was related to increased LV concentricity. This association was independent of diabetes and liver fat (Beta = 0.26, p = 0.0053), but was attenuated (Beta = 0.17, p = 0.077) when also adjusting for circulating levels of interleukin-1 receptor type 2. CONCLUSION: MRI reveals that liver fibrosis is associated to structural LV remodeling, in terms of increased concentricity, in participants from the general population. This relationship could involve the interleukin-1 signaling. CLINICAL RELEVANCE STATEMENT: Liver fibrosis may be considered a cardiovascular risk factor in patients without cirrhosis. Further research on the mechanisms that link liver fibrosis to left ventricular concentricity may reveal potential therapeutic targets in patients with non-alcoholic fatty liver disease (NAFLD). KEY POINTS: Previously, studies on liver fibrosis and cardiac remodeling have focused on advanced stages of liver fibrosis. Liver fibrosis is associated with left ventricular (LV) concentricity and may relate to interleukin-1 receptor type 2. Interleukin-1 signaling is a potential mechanistic interlink between early liver fibrosis and LV remodeling.

Regional and Global Aortic Pulse Wave Velocity in Patients with Abdominal Aortic Aneurysm.

OBJECTIVE: Abdominal aortic aneurysm (AAA) is commonly defined as localised aortic dilatation with a diameter > 30 mm. The pathophysiology of AAA includes chronic inflammation and enzymatic degradation of elastin, possibly increasing aortic wall stiffness and pulse wave velocity (PWV). Whether aortic stiffness is more prominent in the abdominal aorta at the aneurysm site is not elucidated. The aim of this study was to evaluate global and regional aortic PWV in patients with AAA. METHODS: Experimental study of local PWV in the thoracic descending and abdominal aorta in patients with AAA and matched controls. The study cohort comprised 25 patients with an AAA > 30 mm (range 36 - 70 mm, all male, age range 65 - 76 years) and 27 age and sex matched controls free of AAA. PWV was measured with applanation tonometry (carotid-femoral PWV, cfPWV) as well as a 4D flow MRI technique, assessing regional aortic PWV. Blood pressure and anthropometrics were measured. RESULTS: Global aortic PWV was greater in men with an AAA than controls, both by MRI (AAA 8.9 ± 2.4 m/s vs. controls 7.1 ± 1.5 m/s; p = .007) and cfPWV (AAA 11.0 ± 2.1 m/s vs. controls 9.3 ± 2.3 m/s; p = .007). Regionally, PWV was greater in the abdominal aorta in the AAA group (AAA 7.0 ± 1.8 m/s vs. controls 5.8 ± 1.0 m/s; p = .022), but similar in the thoracic descending aorta (AAA 8.7 ± 3.2 m/s vs. controls 8.2 ± 2.4 m/s; p = .59). Furthermore, PWV was positively associated with indices of central adiposity both in men with AAA and controls. CONCLUSION: PWV is higher in men with AAA compared with matched controls in the abdominal but not the thoracic descending aorta. Furthermore, aortic stiffness was linked with central fat deposition. It remains to be seen whether there is a causal link between AAA and increased regional aortic stiffness.

Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and the peak late (A) transmitral flow velocity, is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography (echo) is the preferred imaging technique for diastolic function assessment, while cardiovascular magnetic resonance (CMR) is less established as a method. Previous four-dimensional (4D) Flow-based studies have looked at the E/A ratio proximal to the mitral valve, requiring manual interaction. In this study, we compare an automated, deep learning-based and two semi-automated approaches for 4D Flow CMR-based E/A ratio assessment to conventional, gold-standard echo-based methods. METHODS: Ninety-seven subjects with chronic ischemic heart disease underwent a cardiac echo followed by CMR investigation. 4D Flow-based E/A ratio values were computed using three different approaches; two semi-automated, assessing the E/A ratio by measuring the inflow velocity (MVvel) and the inflow volume (MVflow) at the mitral valve plane, and one fully automated, creating a full LV segmentation using a deep learning-based method with which the E/A ratio could be assessed without constraint to the mitral plane (LVvel). RESULTS: MVvel, MVflow, and LVvel E/A ratios were strongly associated with echocardiographically derived E/A ratio (R2 = 0.60, 0.58, 0.72). LVvel peak E and A showed moderate association to Echo peak E and A, while MVvel values were weakly associated. MVvel and MVflow EA ratios were very strongly associated with LVvel (R2 = 0.84, 0.86). MVvel peak E was moderately associated with LVvel, while peak A showed a strong association (R2 = 0.26, 0.57). CONCLUSION: Peak E, peak A, and E/A ratio are integral to the assessment of diastolic dysfunction and may expand the utility of CMR studies in patients with cardiovascular disease. While underestimation of absolute peak E and A velocities was noted, the E/A ratio measured with all three 4D Flow methods was strongly associated with the gold standard Doppler echocardiography. The automatic, deep learning-based method performed best, with the most favorable runtime of ∼40 seconds. As both semi-automatic methods associated very strongly to LVvel, they could be employed as an alternative for estimation of E/A ratio.

Optimization of photon counting CT for cardiac imaging in patients with left ventricular assist devices: An in-depth assessment of metal artifacts.

PURPOSE: Photon counting CT (PCCT) holds promise for mitigating metal artifacts and can produce virtual mono-energetic images (VMI), while maintaining temporal resolution, making it a valuable tool for characterizing the heart. This study aimed to evaluate and optimize PCCT for cardiac imaging in patients during left ventricular assistance device (LVAD) therapy by conducting an in-depth objective assessment of metal artifacts and visual grading. METHODS: Various scan and reconstruction settings were tested on a phantom and further evaluated on a patient acquisition to identify the optimal protocol settings. The phantom comprised an empty thoracic cavity, supplemented with heart and lungs from a cadaveric lamb. The heart was implanted with an LVAD (HeartMate 3) and iodine contrast. Scans were performed on a PCCT (NAEOTOM Alpha, Siemens Healthcare). Metal artifacts were assessed by three objective methods: Hounsfield units (HU)/SD measurements (DiffHU and SDARTIFACT), Fourier analysis (AmplitudeLowFreq), and depicted LVAD volume in the images (BloomVol). Radiologists graded metal artifacts and the diagnostic interpretability in the LVAD lumen, cardiac tissue, lung tissue, and spinal cord using a 5-point rating scale. Regression and correlation analysis were conducted to determine the assessment method most closely associated with acquisition and reconstruction parameters, as well as the objective method demonstrating the highest correlation with visual grading. RESULTS: Due to blooming artifacts, the LVAD volume fluctuated between 27.0 and 92.7 cm3. This variance was primarily influenced by kVp, kernel, keV, and iMAR (R2 = 0.989). Radiologists favored pacemaker iMAR, 3 mm slice thickness, and T3D keV and kernel Bv56f for minimal metal artifacts in cardiac tissue assessment, and 110 keV and Qr40f for lung tissue interpretation. The model adequacy for DiffHU SDARTIFACT, AmplitueLowFreq, and BloomVol was 0.28, 0.76, 0.29, and 0.99 respectively for phantom data, and 0.95, 0.98, 1.00, and 0.99 for in-vivo data. For in-vivo data, the correlation between visual grading (VGSUM) and DiffHU SDARTIFACT, AmplitueLowFreq, and BloomVol was -0.16, -0.01, -0.48, and -0.40 respectively. CONCLUSION: We found that optimal scan settings for LVAD imaging involved using 120 kVp and IQ level 80. Employing T3D with pacemaker iMAR, the sharpest allowed vascular kernel (Bv56f), and VMI at 110 keV with kernel Qr40 yields images suitable for cardiac imaging during LVAD-therapy. Volumetric measurements of the LVAD for determination of the extent of blooming artifacts was shown to be the best objective method to assess metal artifacts.

Haemodynamic effects of hypertension and type 2 diabetes: Insights from a 4D flow MRI-based personalized cardiovascular mathematical model.

Type 2 diabetes (T2D) and hypertension increase the risk of cardiovascular diseases mediated by whole-body changes to metabolism, cardiovascular structure and haemodynamics. The haemodynamic changes related to hypertension and T2D are complex and subject-specific, however, and not fully understood. We aimed to investigate the haemodynamic mechanisms in T2D and hypertension by comparing the haemodynamics between healthy controls and subjects with T2D, hypertension, or both. For all subjects, we combined 4D flow magnetic resonance imaging data, brachial blood pressure and a cardiovascular mathematical model to create a comprehensive subject-specific analysis of central haemodynamics. When comparing the subject-specific haemodynamic parameters between the four groups, the predominant haemodynamic difference is impaired left ventricular relaxation in subjects with both T2D and hypertension compared to subjects with only T2D, only hypertension and controls. The impaired relaxation indicates that, in this cohort, the long-term changes in haemodynamic load of co-existing T2D and hypertension cause diastolic dysfunction demonstrable at rest, whereas either disease on its own does not. However, through subject-specific predictions of impaired relaxation, we show that altered relaxation alone is not enough to explain the subject-specific and group-related differences; instead, a combination of parameters is affected in T2D and hypertension. These results confirm previous studies that reported more adverse effects from the combination of T2D and hypertension compared to either disease on its own. Furthermore, this shows the potential of personalized cardiovascular models in providing haemodynamic mechanistic insights and subject-specific predictions that could aid in the understanding and treatment planning of patients with T2D and hypertension. KEY POINTS: The combination of 4D flow magnetic resonance imaging data and a cardiovascular mathematical model allows for a comprehensive analysis of subject-specific haemodynamic parameters that otherwise cannot be derived non-invasively. Using this combination, we show that diastolic dysfunction in subjects with both type 2 diabetes (T2D) and hypertension is the main group-level difference between controls, subjects with T2D, subjects with hypertension, and subjects with both T2D and hypertension. These results suggest that, in this relatively healthy population, the additional load of both hypertension and T2D affects the haemodynamic function of the left ventricle, whereas each disease on its own is not enough to cause significant effects under resting conditions. Finally, using the subject-specific model, we show that the haemodynamic effects of diastolic dysfunction alone are not sufficient to explain all the observed haemodynamic differences. Instead, additional subject-specific variations in cardiac and vascular function combine to explain the complex haemodynamics of subjects affected by hypertension and/or T2D.

Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning.

BACKGROUND: Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue. PURPOSE: To develop and evaluate a deep learning-based segmentation method to automatically segment the cardiac chambers and great thoracic vessels from 4D flow MRI. STUDY TYPE: Retrospective. SUBJECTS: A total of 205 subjects, including 40 healthy volunteers and 165 patients with a variety of cardiac disorders were included. Data were randomly divided into training (n = 144), validation (n = 20), and testing (n = 41) sets. FIELD STRENGTH/SEQUENCE: A 3 T/time-resolved velocity encoded 3D gradient echo sequence (4D flow MRI). ASSESSMENT: A 3D neural network based on the U-net architecture was trained to segment the four cardiac chambers, aorta, and pulmonary artery. The segmentations generated were compared to manually corrected atlas-based segmentations. End-diastolic (ED) and end-systolic (ES) volumes of the four cardiac chambers were calculated for both segmentations. STATISTICAL TESTS: Dice score, Hausdorff distance, average surface distance, sensitivity, precision, and miss rate were used to measure segmentation accuracy. Bland-Altman analysis was used to evaluate agreement between volumetric parameters. RESULTS: The following evaluation metrics were computed: mean Dice score (0.908 ± 0.023) (mean ± SD), Hausdorff distance (1.253 ± 0.293 mm), average surface distance (0.466 ± 0.136 mm), sensitivity (0.907 ± 0.032), precision (0.913 ± 0.028), and miss rate (0.093 ± 0.032). Bland-Altman analyses showed good agreement between volumetric parameters for all chambers. Limits of agreement as percentage of mean chamber volume (LoA%), left ventricular: 9.3%, 13.5%, left atrial: 12.4%, 16.9%, right ventricular: 9.9%, 15.6%, and right atrial: 18.7%, 14.4%; for ED and ES, respectively. DATA CONCLUSION: The addition of this technique to the 4D flow MRI assessment pipeline could expedite and improve the utility of this type of acquisition in the clinical setting. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Non-invasive cardiovascular magnetic resonance assessment of pressure recovery distance after aortic valve stenosis.

BACKGROUND: Decisions in the management of aortic stenosis are based on the peak pressure drop, captured by Doppler echocardiography, whereas gold standard catheterization measurements assess the net pressure drop but are limited by associated risks. The relationship between these two measurements, peak and net pressure drop, is dictated by the pressure recovery along the ascending aorta which is mainly caused by turbulence energy dissipation. Currently, pressure recovery is considered to occur within the first 40-50 mm distally from the aortic valve, albeit there is inconsistency across interventionist centers on where/how to position the catheter to capture the net pressure drop. METHODS: We developed a non-invasive method to assess the pressure recovery distance based on blood flow momentum via 4D Flow cardiovascular magnetic resonance (CMR). Multi-center acquisitions included physical flow phantoms with different stenotic valve configurations to validate this method, first against reference measurements and then against turbulent energy dissipation (respectively n = 8 and n = 28 acquisitions) and to investigate the relationship between peak and net pressure drops. Finally, we explored the potential errors of cardiac catheterisation pressure recordings as a result of neglecting the pressure recovery distance in a clinical bicuspid aortic valve (BAV) cohort of n = 32 patients. RESULTS: In-vitro assessment of pressure recovery distance based on flow momentum achieved an average error of 1.8 ± 8.4 mm when compared to reference pressure sensors in the first phantom workbench. The momentum pressure recovery distance and the turbulent energy dissipation distance showed no statistical difference (mean difference of 2.8 ± 5.4 mm, R2 = 0.93) in the second phantom workbench. A linear correlation was observed between peak and net pressure drops, however, with strong dependences on the valvular morphology. Finally, in the BAV cohort the pressure recovery distance was 78.8 ± 34.3 mm from vena contracta, which is significantly longer than currently accepted in clinical practise (40-50 mm), and 37.5% of patients displayed a pressure recovery distance beyond the end of the ascending aorta. CONCLUSION: The non-invasive assessment of the distance to pressure recovery is possible by tracking momentum via 4D Flow CMR. Recovery is not always complete at the ascending aorta, and catheterised recordings will overestimate the net pressure drop in those situations. There is a need to re-evaluate the methods that characterise the haemodynamic burden caused by aortic stenosis as currently clinically accepted pressure recovery distance is an underestimation.

4D Flow cardiovascular magnetic resonance consensus statement: 2023 update.

Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.

Enhancing students' understanding of cardiac physiology by using 4D visualization.

Difficulties in achieving knowledge about physiology and anatomy of the beating heart highlight the challenges with more traditional pedagogical methods. Recent research regarding anatomy education has mainly focused on digital three-dimensional models. However, these pedagogical improvements may not be entirely applicable to cardiac anatomy and physiology due to the multidimensional complexity with moving anatomy and complex blood flow. The aim of this study was therefore to evaluate whether high quality time-resolved anatomical images combined with realistic blood flow simulations improve the understanding of cardiac structures and function. Three time-resolved datasets were acquired using time-resolved computed tomography and blood flow was computed using Computational Fluid Dynamics. The anatomical and blood flow information was combined and interactively visualized using volume rendering on an advanced stereo projection system. The setup was tested in interactive lectures for medical students. Ninety-seven students participated. Summative assessment of examinations showed significantly improved mean score (18.1 ± 4.5 vs 20.3 ± 4.9, p = 0.002). This improvement was driven by knowledge regarding myocardial hypertrophy and pressure-velocity differences over a stenotic valve. Additionally, a supplementary formative assessment showed significantly more agreeing answers than disagreeing answers (p < 0.001) when the participants subjectively evaluated the contribution of the visualizations to their education and knowledge. In conclusion, the use of simultaneous visualization of time-resolved anatomy data and simulated blood flow improved medical students' results, with a particular effect on understanding of cardiac physiology and these simulations may be useful educational tools for teaching complex anatomical and physiological concepts.

Wall shear stress and relative residence time as potential risk factors for abdominal aortic aneurysms in males: a 4D flow cardiovascular magnetic resonance case-control study.

BACKGROUND: Abdominal aortic aneurysms (AAA) can lead to catastrophic events such as dissection or rupture, and are an expression of general aortic disease. Low wall shear stress (WSS), high oscillatory shear index (OSI), and high relative residence time (RRT) have been correlated against increased uptake of inflammatory markers in the vessel wall and may improve risk stratification of AAA. We sought to obtain a comprehensive view of WSS, OSI, and RRT in the whole aorta for patients with AAA and age-matched elderly controls and young normal controls. METHODS: 4D Flow cardiovascular magnetic resonance images of the whole aorta were acquired in 18 AAA patients (70.8 ± 3.4 years), 22 age-matched controls (71.4 ± 3.4 years), and 23 young subjects (23.3 ± 3.1 years), all males. Three-dimensional segmentations of the whole aorta were created for all timeframes using a semi-automatic approach. The aorta was divided into five segments: ascending aorta, arch, descending aorta, suprarenal and infrarenal abdominal aorta. For each segment, average values of peak WSS, OSI, and RRT were computed. Student's t-tests were used to compare values between the three cohorts (AAA patients vs elderly controls, and elderly controls vs young controls) where the data were normally distributed, and the non-parametric Wilcoxon rank sum tests were used otherwise. RESULTS: AAA patients had lower peak WSS in the descending aorta as well as in the abdominal aorta compared to elderly controls (p ≤ 0.001), similar OSI, but higher RRT in the descending and abdominal aorta (p ≤ 0.001). Elderly controls had lower peak WSS compared to young controls throughout the aorta (p < 0.001), higher OSI in all segments except for the infrarenal aorta (p < 0.001), and higher RRT throughout the aorta, except the infrarenal aorta (p < 0.001). CONCLUSIONS: This study provides novel insights into WSS, OSI, and RRT in patients with AAA in relation to normal ageing, highlighting how AAA patients have markedly abnormal hemodynamic stresses not only in the infrarenal, but in the entire aorta. Moreover, we identified RRT as a marker for abnormal AAA hemodynamics. Further investigations are needed to explore if RRT or other measures of hemodynamics stresses best predict AAA growth and/or rupture.

Non-contrast myocardial perfusion in rest and exercise stress using systolic flow-sensitive alternating inversion recovery.

OBJECTIVE: To evaluate systolic flow-sensitive alternating inversion recovery (FAIR) during rest and exercise stress using 2RR (two cardiac cycles) or 1RR intervals between inversion pulse and imaging. MATERIALS AND METHODS: 1RR and 2RR FAIR was implemented on a 3T scanner. Ten healthy subjects were scanned during rest and stress. Stress was performed using an in-bore ergometer. Heart rate, mean myocardial blood flow (MBF) and temporal signal-to-noise ratio (TSNR) were compared using paired t tests. RESULTS: Mean heart rate during stress was higher than rest for 1RR FAIR (85.8 ± 13.7 bpm vs 63.3 ± 11.1 bpm; p < 0.01) and 2RR FAIR (83.8 ± 14.2 bpm vs 63.1 ± 10.6 bpm; p < 0.01). Mean stress MBF was higher than rest for 1RR FAIR (2.97 ± 0.76 ml/g/min vs 1.43 ± 0.6 ml/g/min; p < 0.01) and 2RR FAIR (2.8 ± 0.96 ml/g/min vs 1.22 ± 0.59 ml/g/min; p < 0.01). Resting mean MBF was higher for 1RR FAIR than 2RR FAIR (p < 0.05), but not during stress. TSNR was lower for stress compared to rest for 1RR FAIR (4.52 ± 2.54 vs 10.12 ± 3.69; p < 0.01) and 2RR FAIR (7.36 ± 3.78 vs 12.41 ± 5.12; p < 0.01). 2RR FAIR TSNR was higher than 1RR FAIR for rest (p < 0.05) and stress (p < 0.001). DISCUSSION: We have demonstrated feasibility of systolic FAIR in rest and exercise stress. 2RR delay systolic FAIR enables non-contrast perfusion assessment during stress with relatively high TSNR.

Using Deep Learning to Emulate the Use of an External Contrast Agent in Cardiovascular 4D Flow MRI.

BACKGROUND: Although contrast agents would be beneficial, they are seldom used in four-dimensional (4D) flow magnetic resonance imaging (MRI) due to potential side effects and contraindications. PURPOSE: To develop and evaluate a deep learning architecture to generate high blood-tissue contrast in noncontrast 4D flow MRI by emulating the use of an external contrast agent. STUDY TYPE: Retrospective. SUBJECTS: Of 222 data sets, 141 were used for neural network (NN) training (69 with and 72 without contrast agent). Evaluation was performed on the remaining 81 noncontrast data sets. FIELD STRENGTH/SEQUENCES: Gradient echo or echo-planar 4D flow MRI at 1.5 T and 3 T. ASSESSMENT: A cyclic generative adversarial NN was trained to perform image translation between noncontrast and contrast data. Evaluation was performed quantitatively using contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), structural similarity index (SSIM), mean squared error (MSE) of edges, and Dice coefficient of segmentations. Three observers performed a qualitative assessment of blood-tissue contrast, noise, presence of artifacts, and image structure visualization. STATISTICAL TESTS: The Wilcoxon rank-sum test evaluated statistical significance. Kendall's concordance coefficient assessed interobserver agreement. RESULTS: Contrast in the regions of interest (ROIs) in the NN enhanced images increased by 88%, CNR increased by 63%, and SNR improved by 48% (all P < 0.001). The SSIM was 0.82 ± 0.01, and the MSE of edges was 0.09 ± 0.01 (range [0,1]). Segmentations based on the generated images resulted in a Dice similarity increase of 15.25%. The observers managed to differentiate between contrast MR images and our results; however, they preferred the NN enhanced images in 76.7% of cases. This percentage increased to 93.3% for phase-contrast MR angiograms created from the NN enhanced data. Visual grading scores were blood-tissue contrast = 4.30 ± 0.74, noise = 3.12 ± 0.98, and presence of artifacts = 3.63 ± 0.76. Image structures within and without the ROIs resulted in scores of 3.42 ± 0.59 and 3.07 ± 0.71, respectively (P < 0.001). DATA CONCLUSION: The proposed approach improves blood-tissue contrast in MR images and could be used to improve data quality, visualization, and postprocessing of cardiovascular 4D flow data. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Evaluating the prevalence and severity of NAFLD in primary care: the EPSONIP study protocol.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 20-30% of the general adult population. NAFLD patients with type 2 diabetes mellitus (T2DM) are at an increased risk of advanced fibrosis, which puts them at risk of cardiovascular complications, hepatocellular carcinoma, or liver failure. Liver biopsy is the gold standard for assessing hepatic fibrosis. However, its utility is inherently limited. Consequently, the prevalence and characteristics of T2DM patients with advanced fibrosis are unknown. Therefore, the purpose of the current study is to evaluate the prevalence and severity of NAFLD in patients with T2DM by recruiting participants from primary care, using the latest imaging modalities, to collect a cohort of well phenotyped patients. METHODS: We will prospectively recruit 400 patients with T2DM using biomarkers to assess their status. Specifically, we will evaluate liver fat content using magnetic resonance imaging (MRI); hepatic fibrosis using MR elastography and vibration-controlled transient elastography; muscle composition and body fat distribution using water-fat separated whole body MRI; and cardiac function, structure, and tissue characteristics, using cardiovascular MRI. DISCUSSION: We expect that the study will uncover potential mechanisms of advanced hepatic fibrosis in NAFLD and T2DM and equip the clinician with better diagnostic tools for the care of T2DM patients with NAFLD. TRIAL REGISTRATION: Clinicaltrials.gov, identifier NCT03864510. Registered 6 March 2019, https://clinicaltrials.gov/ct2/show/NCT03864510 .

The transluminal attenuation gradient does not add diagnostic accuracy to coronary computed tomography.

BACKGROUND: A method for improving the accuracy of coronary computed tomography angiography (CCTA) is highly sought after as it would help to avoid unnecessary invasive coronary angiographies. Measurement of the transluminal attenuation gradient (TAG) has been proposed as an alternative to other existing methods, i.e. CT perfusion and CT fractional flow reserve (FFR). PURPOSE: To evaluate the incremental value of three types of TAG in high-pitch spiral CCTA with invasive FFR measurements as reference. MATERIAL AND METHODS: TAG was measured using two semi-automatic methods and one manual method. A receiver operating characteristic (ROC) analysis was made to determine the usefulness of TAG alone as well as TAG combined with CCTA for detection of significant coronary artery stenoses defined by an invasive FFR value ≤0.80. RESULTS: A total of 51 coronary vessels in 37 patients were included in this retrospective study. Hemodynamically significant stenoses were found in 13 vessels according to FFR. The ROC analysis TAG alone resulted in areas under the curve (AUCs) of 0.530 and 0.520 for the semi-automatic TAG and 0.557 for the manual TAG. TAG and CCTA combined resulted in AUCs of 0.567, 0.562 for semi-automatic TAG, and 0.569 for the manual TAG. CONCLUSION: The results from our study showed no incremental value of TAG measured in single heartbeat CCTA in determining the severity of coronary artery stenosis degrees.

Data Quality and Optimal Background Correction Order of Respiratory-Gated k-Space Segmented Spoiled Gradient Echo (SGRE) and Echo Planar Imaging (EPI)-Based 4D Flow MRI.

BACKGROUND: A reduction in scan time of 4D Flow MRI would facilitate clinical application. A recent study indicates that echo-planar imaging (EPI) 4D Flow MRI allows for a reduction in scan time and better data quality than the recommended k-space segmented spoiled gradient echo (SGRE) sequence. It was argued that the poor data quality of SGRE was related to the nonrecommended absence of respiratory motion compensation. However, data quality can also be affected by the background offset compensation. PURPOSE: To compare the data quality of respiratory motion-compensated SGRE and EPI 4D Flow MRI and their dependence on background correction (BC) order. STUDY TYPE: Retrospective. SUBJECTS: Eighteen healthy subjects (eight female, mean age 32 ± 5 years). FIELD STRENGTH AND SEQUENCE: 1.5 T. [Correction added on July 26, 2019, after first online publication: The preceding field strength was corrected.] SGRE and EPI-based 4D Flow MRI. ASSESSMENT: Data quality was investigated visually and by comparing flows through the cardiac valves and aorta. Measurements were obtained from transvalvular flow and pathline analysis. STATISTICAL TESTS: Linear regression and Bland-Altman analysis were used. Wilcoxon test was used for comparison of visual scoring. Student's t-test was used for comparison of flow volumes. RESULTS: No significant difference was found by visual inspection (P = 0.08). Left ventricular (LV) flows were strongly and very strongly associated with SGRE and EPI, respectively (R2 = 0.86-0.94 SGRE; 0.71-0.79 EPI, BC0-4). LV and right ventricular (RV) outflows and LV pathline flows were very strongly associated (R2 = 0.93-0.95 SGRE; 0.88-0.91 EPI, R2 = 0.91-0.95 SGRE; 0.91-0.93 EPI, BC1-4). EPI LV outflow was lower than the short-axis-based stroke volume. EPI RV outflow and proximal descending aortic flow were lower than SGREs. DATA CONCLUSION: Both sequences yielded good internal data consistency when an adequate background correction was applied. Second and first BC order were considered sufficient for transvalvular flow analysis in SGRE and EPI, respectively. Higher BC orders were preferred for particle tracing. Level of Evidence 4 Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2020;51:885-896.

Clinical validation of three cardiovascular magnetic resonance techniques to measure strain and torsion in patients with suspected coronary artery disease.

BACKGROUND: Several cardiovascular magnetic resonance (CMR) techniques can measure myocardial strain and torsion with high accuracy. The purpose of this study was to compare displacement encoding with stimulated echoes (DENSE), tagging and feature tracking (FT) for measuring circumferential and radial myocardial strain and myocardial torsion in order to assess myocardial function and infarct scar burden both at a global and at a segmental level. METHOD: 116 patients with a high likelihood of coronary artery disease (European SCORE > 15%) underwent CMR examination including cine images, tagging, DENSE and late gadolinium enhancement (LGE) in the short axis direction. In total, 97 patients had signs of myocardial disease and 19 had no abnormalities in terms of left ventricular (LV) wall mass index, LV ejection fraction, wall motion, LGE or a history of myocardial infarction. Thirty-four patients had myocardial infarct scar with a transmural LGE extent (transmurality) that exceeded 50% of the wall thickness in at least one segment. Global circumferential strain (GCS) and global radial strain (GRS) was analyzed using FT of cine loops, deformation of tag lines or DENSE displacement. RESULTS: DENSE and tagging both showed high sensitivity (82% and 71%) at a specificity of 80% for the detection of segments with > 50% LGE transmurality, and receiver operating characteristics (ROC) analysis showed significantly higher area under the curve-values (AUC) for DENSE (0.87) than for tagging (0.83, p < 0.001) and FT (0.66, p = 0.003). GCS correlated with global LGE when determined with DENSE (r = 0.41), tagging (r = 0.37) and FT (r = 0.15). GRS had a low but significant negative correlation with LGE; DENSE r = - 0.10, FT r = - 0.07 and tagging r = - 0.16. Torsion from DENSE and tagging had a weak correlation (- 0.20 and - 0.22 respectively) with global LGE. CONCLUSION: Circumferential strain from DENSE detected segments with > 50% scar with a higher AUC than strain determined from tagging and FT at a segmental level. GCS and torsion computed from DENSE and tagging showed similar correlation with global scar size, while when computed from FT, the correlation was lower.

Validation of pressure drop assessment using 4D flow MRI-based turbulence production in various shapes of aortic stenoses.

PURPOSE: To validate pressure drop measurements using 4D flow MRI-based turbulence production in various shapes of stenotic stenoses. METHODS: In vitro flow phantoms with seven different 3D-printed aortic valve geometries were constructed and scanned with 4D flow MRI with six-directional flow encoding (ICOSA6). The pressure drop through the valve was non-invasively predicted based on the simplified Bernoulli, the extended Bernoulli, the turbulence production, and the shear-scaling methods. Linear regression and agreement of the predictions with invasively measured pressure drop were analyzed. RESULTS: All pressure drop predictions using 4D Flow MRI were linearly correlated to the true pressure drop but resulted in different regression slopes. The regression slope and 95% limits of agreement for the simplified Bernoulli method were 1.35 and 11.99 ± 21.72 mm Hg. The regression slope and 95% limits of agreement for the extended Bernoulli method were 1.02 and 0.74 ± 8.48 mm Hg. The regression slope and 95% limits of agreement for the turbulence production method were 0.89 and 0.96 ± 8.01 mm Hg. The shear-scaling method presented good correlation with an invasively measured pressure drop, but the regression slope varied between 0.36 and 1.00 depending on the shear-scaling coefficient. CONCLUSION: The pressure drop assessment based on the turbulence production method agrees well with the extended Bernoulli method and invasively measured pressure drop in various shapes of the aortic valve. Turbulence-based pressure drop estimation can, as a complement to the conventional Bernoulli method, play a role in the assessment of valve diseases.

Intracardiac 4D Flow MRI in Congenital Heart Disease: Recommendations on Behalf of the ISMRM Flow & Motion Study Group.

LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:677-681.