Prognostic utility of exercise cardiovascular magnetic resonance in patients with systemic sclerosis-associated pulmonary arterial hypertension.

AIMS: Systemic sclerosis complicated by pulmonary arterial hypertension (SSc-PAH) is a rare condition with poor prognosis. The majority of patients are categorized as intermediate risk of mortality. Cardiovascular magnetic resonance (CMR) is well placed to reproducibly assess right heart size and function, but most patients with SSc-PAH have less overtly abnormal right ventricles than other forms of PAH. The aim of this study was to assess if exercise CMR measures of cardiac size and function could better predict outcome in patients with intermediate risk SSc-PAH compared with resting CMR. METHODS AND RESULTS: Fifty patients with SSc-PAH categorized as intermediate risk underwent CMR-augmented cardiopulmonary exercise testing. Most patients had normal CMR-defined resting measures of right ventricular (RV) size and function. Nine (18%) patients died during a median follow-up period of 2.1 years (range 0.1-4.6). Peak exercise RV indexed end-systolic volume (ESVi) was the only CMR metric to predict prognosis on stepwise Cox regression analysis, with an optimal threshold < 39 mL/m2 to predict favourable outcome. Intermediate-low risk patients with peak RVESVi < 39 mL/m2 had significantly better survival than all other combinations of intermediate-low/-high risk status and peak RVESVi< or ≥39 mL/m2. In our cohort, ventilatory efficiency and resting oxygen consumption (VO2) were predictive of mortality, but not peak VO2, peak cardiac output, or peak tissue oxygen extraction. CONCLUSION: Exercise CMR assessment of RV size and function may help identify SSc-PAH patients with poorer prognosis amongst intermediate risk cohorts, even when resting CMR appears reassuring, and could offer added value to clinical PH risk stratification.

Rapid 2D 23Na MRI of the calf using a denoising convolutional neural network.

PURPOSE: 23Na MRI can be used to quantify in-vivo tissue sodium concentration (TSC), but the inherently low 23Na signal leads to long scan times and/or noisy or low-resolution images. Reconstruction algorithms such as compressed sensing (CS) have been proposed to mitigate low signal-to-noise ratio (SNR); although, these can result in unnatural images, suboptimal denoising and long processing times. Recently, machine learning has been increasingly used to denoise 1H MRI acquisitions; however, this approach typically requires large volumes of high-quality training data, which is not readily available for 23Na MRI. Here, we propose using 1H data to train a denoising convolutional neural network (CNN), which we subsequently demonstrate on prospective 23Na images of the calf. METHODS: 1893 1H fat-saturated transverse slices of the knee from the open-source fastMRI dataset were used to train denoising CNNs for different levels of noise. Synthetic low SNR images were generated by adding gaussian noise to the high-quality 1H k-space data before reconstruction to create paired training data. For prospective testing, 23Na images of the calf were acquired in 10 healthy volunteers with a total of 150 averages over ten minutes, which were used as a reference throughout the study. From this data, images with fewer averages were retrospectively reconstructed using a non-uniform fast Fourier transform (NUFFT) as well as CS, with the NUFFT images subsequently denoised using the trained CNN. RESULTS: CNNs were successfully applied to 23Na images reconstructed with 50, 40 and 30 averages. Muscle and skin apparent TSC quantification from CNN-denoised images were equivalent to those from CS images, with <0.9 mM bias compared to reference values. Estimated SNR was significantly higher in CNN-denoised images compared to NUFFT, CS and reference images. Quantitative edge sharpness was equivalent for all images. For subjective image quality ranking, CNN-denoised images ranked equally best with reference images and significantly better than NUFFT and CS images. CONCLUSION: Denoising CNNs trained on 1H data can be successfully applied to 23Na images of the calf; thus, allowing scan time to be reduced from ten minutes to two minutes with little impact on image quality or apparent TSC quantification accuracy.

A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of patients with Fontan circulation (Fontan Outcomes Registry Using CMR Examinations [FORCE]). Materials and Methods This retrospective study used 250 cardiac MRI examinations (November 2007-December 2022) from 13 institutions for training, validation, and testing. The pipeline contained three DL models: a classifier to identify short-axis cine stacks and two U-Net 3+ models for image cropping and segmentation. The automated segmentations were evaluated on the test set (n = 50) by using the Dice score. Volumetric and functional metrics derived from DL and ground truth manual segmentations were compared using Bland-Altman and intraclass correlation analysis. The pipeline was further qualitatively evaluated on 475 unseen examinations. Results There were acceptable limits of agreement (LOA) and minimal biases between the ground truth and DL end-diastolic volume (EDV) (bias: -0.6 mL/m2, LOA: -20.6 to 19.5 mL/m2) and end-systolic volume (ESV) (bias: -1.1 mL/m2, LOA: -18.1 to 15.9 mL/m2), with high intraclass correlation coefficients (ICCs > 0.97) and Dice scores (EDV, 0.91 and ESV, 0.86). There was moderate agreement for ventricular mass (bias: -1.9 g/m2, LOA: -17.3 to 13.5 g/m2) and an ICC of 0.94. There was also acceptable agreement for stroke volume (bias: 0.6 mL/m2, LOA: -17.2 to 18.3 mL/m2) and ejection fraction (bias: 0.6%, LOA: -12.2% to 13.4%), with high ICCs (>0.81). The pipeline achieved satisfactory segmentation in 68% of the 475 unseen examinations, while 26% needed minor adjustments, 5% needed major adjustments, and in 0.4%, the cropping model failed. Conclusion The DL pipeline can provide fast standardized segmentation for patients with single ventricle physiology across multiple centers. This pipeline can be applied to all cardiac MRI examinations in the FORCE registry. Keywords: Cardiac, Adults and Pediatrics, MR Imaging, Congenital, Volume Analysis, Segmentation, Quantification Supplemental material is available for this article. © RSNA, 2023.

2D sodium MRI of the human calf using half-sinc excitation pulses and compressed sensing.

PURPOSE: Sodium MRI can be used to quantify tissue sodium concentration (TSC) in vivo; however, UTE sequences are required to capture the rapidly decaying signal. 2D MRI enables high in-plane resolution but typically has long TEs. Half-sinc excitation may enable UTE; however, twice as many readouts are necessary. Scan time can be minimized by reducing the number of signal averages (NSAs), but at a cost to SNR. We propose using compressed sensing (CS) to accelerate 2D half-sinc acquisitions while maintaining SNR and TSC. METHODS: Ex vivo and in vivo TSC were compared between 2D spiral sequences with full-sinc (TE = 0.73 ms, scan time ≈ 5 min) and half-sinc excitation (TE = 0.23 ms, scan time ≈ 10 min), with 150 NSAs. Ex vivo, these were compared to a reference 3D sequence (TE = 0.22 ms, scan time ≈ 24 min). To investigate shortening 2D scan times, half-sinc data was retrospectively reconstructed with fewer NSAs, comparing a nonuniform fast Fourier transform to CS. Resultant TSC and image quality were compared to reference 150 NSAs nonuniform fast Fourier transform images. RESULTS: TSC was significantly higher from half-sinc than from full-sinc acquisitions, ex vivo and in vivo. Ex vivo, half-sinc data more closely matched the reference 3D sequence, indicating improved accuracy. In silico modeling confirmed this was due to shorter TEs minimizing bias caused by relaxation differences between phantoms and tissue. CS was successfully applied to in vivo, half-sinc data, maintaining TSC and image quality (estimated SNR, edge sharpness, and qualitative metrics) with ≥50 NSAs. CONCLUSION: 2D sodium MRI with half-sinc excitation and CS was validated, enabling TSC quantification with 2.25 × 2.25 mm2 resolution and scan times of ≤5 mins.

Ongoing Exercise Intolerance Following COVID-19: A Magnetic Resonance-Augmented Cardiopulmonary Exercise Test Study.

Background Ongoing exercise intolerance of unclear cause following COVID-19 infection is well recognized but poorly understood. We investigated exercise capacity in patients previously hospitalized with COVID-19 with and without self-reported exercise intolerance using magnetic resonance-augmented cardiopulmonary exercise testing. Methods and Results Sixty subjects were enrolled in this single-center prospective observational case-control study, split into 3 equally sized groups: 2 groups of age-, sex-, and comorbidity-matched previously hospitalized patients following COVID-19 without clearly identifiable postviral complications and with either self-reported reduced (COVIDreduced) or fully recovered (COVIDnormal) exercise capacity; a group of age- and sex-matched healthy controls. The COVIDreducedgroup had the lowest peak workload (79W [Interquartile range (IQR), 65-100] versus controls 104W [IQR, 86-148]; P=0.01) and shortest exercise duration (13.3±2.8 minutes versus controls 16.6±3.5 minutes; P=0.008), with no differences in these parameters between COVIDnormal patients and controls. The COVIDreduced group had: (1) the lowest peak indexed oxygen uptake (14.9 mL/minper kg [IQR, 13.1-16.2]) versus controls (22.3 mL/min per kg [IQR, 16.9-27.6]; P=0.003) and COVIDnormal patients (19.1 mL/min per kg [IQR, 15.4-23.7]; P=0.04); (2) the lowest peak indexed cardiac output (4.7±1.2 L/min per m2) versus controls (6.0±1.2 L/min per m2; P=0.004) and COVIDnormal patients (5.7±1.5 L/min per m2; P=0.02), associated with lower indexed stroke volume (SVi:COVIDreduced 39±10 mL/min per m2 versus COVIDnormal 43±7 mL/min per m2 versus controls 48±10 mL/min per m2; P=0.02). There were no differences in peak tissue oxygen extraction or biventricular ejection fractions between groups. There were no associations between COVID-19 illness severity and peak magnetic resonance-augmented cardiopulmonary exercise testing metrics. Peak indexed oxygen uptake, indexed cardiac output, and indexed stroke volume all correlated with duration from discharge to magnetic resonance-augmented cardiopulmonary exercise testing (P<0.05). Conclusions Magnetic resonance-augmented cardiopulmonary exercise testing suggests failure to augment stroke volume as a potential mechanism of exercise intolerance in previously hospitalized patients with COVID-19. This is unrelated to disease severity and, reassuringly, improves with time from acute illness.

Reduced exercise capacity in patients with systemic sclerosis is associated with lower peak tissue oxygen extraction: a cardiovascular magnetic resonance-augmented cardiopulmonary exercise study.

BACKGROUND: Exercise intolerance in systemic sclerosis (SSc) is typically attributed to cardiopulmonary limitations. However, problems with skeletal muscle oxygen extraction have not been fully investigated. This study used cardiovascular magnetic resonance (CMR)-augmented cardiopulmonary exercise testing (CMR-CPET) to simultaneously measure oxygen consumption and cardiac output. This allowed calculation of arteriovenous oxygen content gradient, a recognized marker of oxygen extraction. We performed CMR-CPET in 4 groups: systemic sclerosis (SSc); systemic sclerosis-associated pulmonary arterial hypertension (SSc-PAH); non-connective tissue disease pulmonary hypertension (NC-PAH); and healthy controls. METHODS: We performed CMR-CPET in 60 subjects (15 in each group) using a supine ergometer following a ramped exercise protocol until exhaustion. Values for oxygen consumption, cardiac output and oxygen content gradient, as well as ventricular volumes, were obtained at rest and peak-exercise for all subjects. In addition, T1 and T2 maps were acquired at rest, and the most recent clinical measures (hemoglobin, lung function, 6-min walk, cardiac and catheterization) were collected. RESULTS: All patient groups had reduced peak oxygen consumption compared to healthy controls (p < 0.022). The SSc and SSc-PAH groups had reduced peak oxygen content gradient compared to healthy controls (p < 0.03). Conversely, the SSc-PAH and NC-PH patients had reduced peak cardiac output compared to healthy controls and SSc patients (p < 0.006). Higher hemoglobin was associated with higher peak oxygen content gradient (p = 0.025) and higher myocardial T1 was associated with lower peak stroke volume (p = 0.011). CONCLUSIONS: Reduced peak oxygen consumption in SSc patients is predominantly driven by reduced oxygen content gradient and in SSc-PAH patients this was amplified by reduced peak cardiac output. Trial registration The study is registered with ClinicalTrials.gov Protocol Registration and Results System (ClinicalTrials.gov ID: 100358).

Real-time deep artifact suppression using recurrent U-Nets for low-latency cardiac MRI.

PURPOSE: Real-time low latency MRI is performed to guide various cardiac interventions. Real-time acquisitions often require iterative image reconstruction strategies, which lead to long reconstruction times. In this study, we aim to reconstruct highly undersampled radial real-time data with low latency using deep learning. METHODS: A 2D U-Net with convolutional long short-term memory layers is proposed to exploit spatial and preceding temporal information to reconstruct highly accelerated tiny golden radial data with low latency. The network was trained using a dataset of breath-hold CINE data (including 770 time series from 7 different orientations). Synthetic paired data were created by retrospectively undersampling the magnitude images, and the network was trained to recover the target images. In the spirit of interventional imaging, the network was trained and tested for varying acceleration rates and orientations. Data were prospectively acquired and reconstructed in real time in 1 healthy subject interactively and in 3 patients who underwent catheterization. Images were visually compared to sliding window and compressed sensing reconstructions and a conventional Cartesian real-time sequence. RESULTS: The proposed network generalized well to different acceleration rates and unseen orientations for all considered metrics in simulated data (less than 4% reduction in structural similarity index compared to similar acceleration and orientation-specific networks). The proposed reconstruction was demonstrated interactively, successfully depicting catheters in vivo with low latency (39 ms, including 19 ms for deep artifact suppression) and an image quality comparing favorably to other reconstructions. CONCLUSION: Deep artifact suppression was successfully demonstrated in the time-critical application of non-Cartesian real-time interventional cardiac MR.

Reducing Contrast Agent Dose in Cardiovascular MR Angiography with Deep Learning.

BACKGROUND: Contrast-enhanced magnetic resonance angiography (MRA) is used to assess various cardiovascular conditions. However, gadolinium-based contrast agents (GBCAs) carry a risk of dose-related adverse effects. PURPOSE: To develop a deep learning method to reduce GBCA dose by 80%. STUDY TYPE: Retrospective and prospective. POPULATION: A total of 1157 retrospective and 40 prospective congenital heart disease patients for training/validation and testing, respectively. FIELD STRENGTH/SEQUENCE: A 1.5 T, T1-weighted three-dimensional (3D) gradient echo. ASSESSMENT: A neural network was trained to enhance low-dose (LD) 3D MRA using retrospective synthetic data and tested with prospective LD data. Image quality for LD (LD-MRA), enhanced LD (ELD-MRA), and high-dose (HD-MRA) was assessed in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and a quantitative measure of edge sharpness and scored for perceptual sharpness and contrast on a 1-5 scale. Diagnostic confidence was assessed on a 1-3 scale. LD- and ELD-MRA were assessed against HD-MRA for sensitivity/specificity and agreement of vessel diameter measurements (aorta and pulmonary arteries). STATISTICAL TESTS: SNR, CNR, edge sharpness, and vessel diameters were compared between LD-, ELD-, and HD-MRA using one-way repeated measures analysis of variance with post-hoc t-tests. Perceptual quality and diagnostic confidence were compared using Friedman's test with post-hoc Wilcoxon signed-rank tests. Sensitivity/specificity was compared using McNemar's test. Agreement of vessel diameters was assessed using Bland-Altman analysis. RESULTS: SNR, CNR, edge sharpness, perceptual sharpness, and perceptual contrast were lower (P < 0.05) for LD-MRA compared to ELD-MRA and HD-MRA. SNR, CNR, edge sharpness, and perceptual contrast were comparable between ELD and HD-MRA, but perceptual sharpness was significantly lower. Sensitivity/specificity was 0.824/0.921 for LD-MRA and 0.882/0.960 for ELD-MRA. Diagnostic confidence was 2.72, 2.85, and 2.92 for LD, ELD, and HD-MRA, respectively (PLD-ELD , PLD-HD  < 0.05). Vessel diameter measurements were comparable, with biases of 0.238 (LD-MRA) and 0.278 mm (ELD-MRA). DATA CONCLUSION: Deep learning can improve contrast in LD cardiovascular MRA. LEVEL OF EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Rapid whole-heart CMR with single volume super-resolution.

BACKGROUND: Three-dimensional, whole heart, balanced steady state free precession (WH-bSSFP) sequences provide delineation of intra-cardiac and vascular anatomy. However, they have long acquisition times. Here, we propose significant speed-ups using a deep-learning single volume super-resolution reconstruction, to recover high-resolution features from rapidly acquired low-resolution WH-bSSFP images. METHODS: A 3D residual U-Net was trained using synthetic data, created from a library of 500 high-resolution WH-bSSFP images by simulating 50% slice resolution and 50% phase resolution. The trained network was validated with 25 synthetic test data sets. Additionally, prospective low-resolution data and high-resolution data were acquired in 40 patients. In the prospective data, vessel diameters, quantitative and qualitative image quality, and diagnostic scoring was compared between the low-resolution, super-resolution and reference high-resolution WH-bSSFP data. RESULTS: The synthetic test data showed a significant increase in image quality of the low-resolution images after super-resolution reconstruction. Prospectively acquired low-resolution data was acquired ~× 3 faster than the prospective high-resolution data (173 s vs 488 s). Super-resolution reconstruction of the low-resolution data took < 1 s per volume. Qualitative image scores showed super-resolved images had better edge sharpness, fewer residual artefacts and less image distortion than low-resolution images, with similar scores to high-resolution data. Quantitative image scores showed super-resolved images had significantly better edge sharpness than low-resolution or high-resolution images, with significantly better signal-to-noise ratio than high-resolution data. Vessel diameters measurements showed over-estimation in the low-resolution measurements, compared to the high-resolution data. No significant differences and no bias was found in the super-resolution measurements in any of the great vessels. However, a small but significant for the underestimation was found in the proximal left coronary artery diameter measurement from super-resolution data. Diagnostic scoring showed that although super-resolution did not improve accuracy of diagnosis, it did improve diagnostic confidence compared to low-resolution imaging. CONCLUSION: This paper demonstrates the potential of using a residual U-Net for super-resolution reconstruction of rapidly acquired low-resolution whole heart bSSFP data within a clinical setting. We were able to train the network using synthetic training data from retrospective high-resolution whole heart data. The resulting network can be applied very quickly, making these techniques particularly appealing within busy clinical workflow. Thus, we believe that this technique may help speed up whole heart CMR in clinical practice.

Correction to: The aorta after coarctation repair - effects of calibre and curvature on arterial haemodynamics.

In the original version of this article [1], published on 11 April 2019, there is 1 error in the 'Conclusion' paragraph of the abstract.

The cardiovascular phenotype of childhood hypertension: a cardiac magnetic resonance study.

BACKGROUND: The cardiovascular phenotype is poorly characterized in treated pediatric hypertension. Cardiovascular magnetic resonance imaging (MRI) can be used to better characterize both cardiac and vascular phenotype in children with hypertension. OBJECTIVE: To use MRI to determine the cardiac and vascular phenotypes of different forms of treated hypertension and compare the results with those of healthy children. MATERIALS AND METHODS: Sixty children (15 with chronic renal disease with hypertension, 15 with renovascular hypertension, 15 with essential hypertension and 15 healthy subjects) underwent MRI with noninvasive blood pressure measurements. Cardiovascular parameters measured include systemic vascular resistance, total arterial compliance, left ventricular mass and volumetric data, ejection fraction and myocardial velocity. Between-group comparisons were used to investigate differences in the hypertension types. RESULTS: Renal hypertension was associated with elevated vascular resistance (P≤0.007) and normal arterial compliance. Conversely, children with essential hypertension had normal resistance but increased compliance (P=0.001). Renovascular hypertension was associated with both increased resistance and compliance (P≤0.03). There was no difference in ventricular volumes, mass or cardiac output between groups. Children with renal hypertension also had lower systolic and diastolic myocardial velocities. CONCLUSION: Cardiovascular MRI may identify distinct vascular and cardiac phenotypes in different forms of treated childhood hypertension. Future studies are needed to investigate how this may inform further optimisation of blood pressure treatment in different types of hypertension.

The aorta after coarctation repair - effects of calibre and curvature on arterial haemodynamics.

BACKGROUND: Aortic shape has been proposed as an important determinant of adverse haemodynamics following coarctation repair. However, previous studies have not demonstrated a consistent relationship between shape and vascular load. In this study, 3D aortic shape was evaluated using principal component analysis (PCA), allowing investigation of the relationship between 3D shape and haemodynamics. METHODS: Sixty subjects (38 male, 25.0 ± 7.8 years) with repaired coarctation were recruited. Central aortic haemodynamics including wave intensity analysis were measured noninvasively using a combination of blood pressure and phase contrast cardiovascular magnetic resonance (CMR). 3D curvature and radius data were derived from CMR angiograms. PCA was separately performed on 3D radius and curvature data to assess the role of arch geometry on haemodynamics. Clinical findings were corroborated using 1D vascular models. RESULTS: There were no independent associations between 3D curvature and any hemodynamic parameters. However, the magnitude of the backwards compression wave was related to the 1st (r = - 0.36, p = 0.005), 3rd (r = 0.27, p = 0.036) and 4th (r = - 0.31, p = 0.017) principle components of radius. The 4th principle componentof radius also correlated with central aortic systolic pressure. These aortas had larger aortic roots, more transverse arch hypoplasia and narrower aortic isthmuses. CONCLUSIONS: There are major modes of variation in 3D aortic shape after coarctation repair witha modest association between variation in aortic radius and pathological wave reflections, but not with 3D curvature. Taken together, these data suggest that shape is not the major determinant of vascular load following coarctation repair, and calibre is more important than curvature.

Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease.

PURPOSE: Real-time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability of CNNs to reconstruct highly accelerated radial real-time data in patients with congenital heart disease (CHD). METHODS: A 3D (2D plus time) CNN architecture was developed and trained using synthetic training data created from previously acquired breath hold cine images from 250 CHD patients. The trained CNN was then used to reconstruct actual real-time, tiny golden angle (tGA) radial SSFP data (13 × undersampled) acquired in 10 new patients with CHD. The same real-time data was also reconstructed with compressed sensing (CS) to compare image quality and reconstruction time. Ventricular volume measurements made using both the CNN and CS reconstructed images were compared to reference standard breath hold data. RESULTS: It was feasible to train a CNN to remove artifact from highly undersampled radial real-time data. The overall reconstruction time with the CNN (including creation of aliased images) was shown to be >5 × faster than the CS reconstruction. In addition, the image quality and accuracy of biventricular volumes measured from the CNN reconstructed images were superior to the CS reconstructions. CONCLUSION: This article has demonstrated the potential for the use of a CNN for reconstruction of real-time radial data within the clinical setting. Clinical measures of ventricular volumes using real-time data with CNN reconstruction are not statistically significantly different from gold-standard, cardiac-gated, breath-hold techniques.

Cardiac Structural and Functional Consequences of Amyloid Deposition by Cardiac Magnetic Resonance and Echocardiography and Their Prognostic Roles.

OBJECTIVES: This cross-sectional study aimed to describe the functional and structural cardiac abnormalities that occur across a spectrum of cardiac amyloidosis burden and to identify the strongest cardiac functional and structural prognostic predictors in amyloidosis using cardiac magnetic resonance (CMR) and echocardiography. BACKGROUND: Cardiac involvement in light chain and transthyretin amyloidosis is the main driver of prognosis and influences treatment strategies. Numerous measures of cardiac structure and function are assessed by multiple imaging modalities in amyloidosis. METHODS: A total f 322 subjects (311 systemic amyloidosis and 11 transthyretin gene mutation carriers) underwent comprehensive CMR and transthoracic echocardiography. The probabilities of 11 commonly measured structural and functional cardiac parameters being abnormal with increasing cardiac amyloidosis burden were evaluated. Cardiac amyloidosis burden was quantified using CMR-derived extracellular volume. The prognostic capacities of these parameters to predict death in amyloidosis were assessed using Cox proportional hazards models. RESULTS: Left ventricular mass and mitral annular plane systolic excursion by CMR along with strain and E/e' by echocardiography have high probabilities of being abnormal at low cardiac amyloid burden. Reductions in biventricular ejection fractions and elevations in biatrial areas occur at high burdens of infiltration. The probabilities of indexed stroke volume, myocardial contraction fraction, and tricuspid annular plane systolic excursion (TAPSE) being abnormal occur more gradually with increasing extracellular volume. Ninety patients (28%) died during a median follow-up of 22 months (interquartile range: 10 to 38 months). Univariable analysis showed that all imaging markers studied significantly predicted outcome. Multivariable analysis showed that TAPSE (hazard ratio: 1.46; 95% confidence interval: 1.16 to 1.85; p < 0.01) and indexed stroke volume (hazard ratio: 1.24; 95% confidence interval: 1.04 to 1.48; p < 0.05) by CMR were the only independent predictors of mortality. CONCLUSIONS: Specific functional and structural abnormalities characterize different burdens of cardiac amyloid deposition. In a multimodality imaging assessment of a large cohort of amyloidosis patients, CMR-derived TAPSE and indexed stroke volume are the strongest prognostic cardiac functional markers.

Real-time assessment of right and left ventricular volumes and function in children using high spatiotemporal resolution spiral bSSFP with compressed sensing.

BACKGROUND: Real-time cardiovascular magnetic resonance (CMR) assessment of ventricular volumes and function enables data acquisition during free-breathing. The requirement for high spatiotemporal resolution in children necessitates the use of highly accelerated imaging techniques. METHODS: A novel real-time balanced steady state free precession (bSSFP) spiral sequence reconstructed using Compressed Sensing (CS) was prospectively validated against the breath-hold clinical standard for assessment of ventricular volumes in 60 children with congenital heart disease. Qualitative image scoring, quantitative image quality, as well as evaluation of biventricular volumes was performed. Standard BH and real-time measures were compared using the paired t-test and agreement for volumetric measures were evaluated using Bland Altman analysis. RESULTS: Acquisition time for the entire short axis stack (~ 13 slices) using the spiral real-time technique was ~ 20 s, compared to ~ 348 s for the standard breath hold technique. Qualitative scores reflected more residual aliasing artefact (p < 0.001) and lower edge definition (p < 0.001) in spiral real-time images than standard breath hold images, with lower quantitative edge sharpness and estimates of image contrast (p < 0.001). There was a small but statistically significant (p < 0.05) overestimation of left ventricular (LV) end-systolic volume (1.0 ± 3.5 mL), and underestimation of LV end-diastolic volume (- 1.7 ± 4.6 mL), LV stroke volume (- 2.6 ± 4.8 mL) and LV ejection fraction (- 1.5 ± 3.0%) using the real-time technique. We also observed a small underestimation of right ventricular stroke volume (- 1.8 ± 4.9 mL) and ejection fraction (- 1.4 ± 3.7%) using the real-time imaging technique. No difference in inter-observer or intra-observer variability were observed between the BH and real-time sequences. CONCLUSIONS: Real-time bSSFP imaging using spiral trajectories combined with a compressed sensing reconstruction showed good agreement for quantification of biventricular metrics in children with heart disease, despite slightly lower image quality. This technique holds the potential for free breathing data acquisition, with significantly shorter scan times in children.

Quantitation of 99mTc-DPD uptake in patients with transthyretin-related cardiac amyloidosis.

PURPOSE: Transthyretin (ATTR) amyloidosis is a rare but serious infiltrative disease associated with a wide spectrum of morphologic and functional cardiac involvement. 99mTc-labelled 3,3-diphosphono-1,2-propanodicarboxylic acid (DPD), initially developed as a bone-seeking radiotracer, is remarkably sensitive for imaging cardiac ATTR amyloid deposits. Our aim was to investigate the feasibility and utility of estimating 99mTc-DPD uptake in myocardial tissue; this has the potential to yield reliable quantitative information on cardiac amyloid burden, which is urgently required to monitor disease progression and response to novel treatments. METHODS: Three methods of quantitation were developed and tested on 74 patients with proven cardiac ATTR amyloidosis who had recently undergone 99mTc-DPD planar whole-body imaging and SPECT-CT. Quantitative results were compared to measurements of extracellular volume fraction (ECV) by cardiac magnetic resonance imaging, a validated technique for measuring amyloid burden. RESULTS: An experienced clinician graded uptake using a widely-used visual scoring system as 1 (n = 15), 2 (n = 39) or 3 (n = 20). Linear correlations between the SPECT and ECV data (p < .001) were demonstrated. None of the methods showed that 99mTc-DPD uptake in the heart was significantly greater in patients with grade-3 uptake than in those with grade-2 uptake. CONCLUSIONS: Quantitation of 99mTc-DPD uptake in cardiac transthyretin amyloid deposits is complex and is hindered by competition for radiotracer with amyloid in skeletal muscle. The latter underlies differences in uptake between grade-2 and grade-3 patients, not cardiac uptake.

A comprehensive characterization of myocardial and vascular phenotype in pediatric chronic kidney disease using cardiovascular magnetic resonance imaging.

BACKGROUND: Children with chronic kidney disease (CKD) have increased cardiovascular mortality. Identifying high-risk children who may benefit from further therapeutic intervention is difficult as cardiovascular abnormalities are subtle. Although transthoracic echocardiography may be used to detect sub-clinical abnormalities, it has well-known problems with reproducibility that limit its ability to accurately detect these changes. Cardiovascular magnetic resonance (CMR) is the reference standard method for assessing blood flow, cardiac structure and function. Furthermore, recent innovations enable the assessment of radial and longitudinal myocardial velocity, such that detection of sub-clinical changes is now possible. Thus, CMR may be ideal for cardiovascular assessment in pediatric CKD. This study aims to comprehensively assess cardiovascular function in pediatric CKD using CMR and determine its relationship with CKD severity. METHODS: A total of 120 children (40 mild, 40 moderate, 20 severe pre-dialysis CKD subjects and 20 healthy controls) underwent CMR with non-invasive blood pressure (BP) measurements. Cardiovascular parameters measured included systemic vascular resistance (SVR), total arterial compliance (TAC), left ventricular (LV) structure, ejection fraction (EF), cardiac timings, radial and longitudinal systolic and diastolic myocardial velocities. Between group comparisons and regression modelling were used to identify abnormalities in CKD and determine the effects of renal severity on myocardial function. RESULTS: The elevation in mean BP in CKD was accompanied by significantly increased afterload (SVR), without evidence of arterial stiffness (TAC) or increased fluid overload. Left ventricular volumes and global function were not abnormal in CKD. However, there was evidence of LV remodelling, prolongation of isovolumic relaxation time and reduced systolic and diastolic myocardial velocities. CONCLUSION: Abnormal cardiovascular function is evident in pre-dialysis pediatric CKD. Novel CMR biomarkers may be useful for the detection of subtle abnormalities in this population. Further studies are needed to determine to prognostic value of these biomarkers.

Automatic quantification of the myocardial extracellular volume by cardiac computed tomography: Synthetic ECV by CCT.

BACKGROUND: The quantification of extracellular volume fraction (ECV) by Cardiac Computed Tomography (CCT) can identify changes in the myocardial interstitium due to fibrosis or infiltration. Current methodologies require laboratory blood hematocrit (Hct) measurement - which complicates the technique. The attenuation of blood (HUblood) is known to change with anemia. We hypothesized that the relationship between Hct and HUblood could be calibrated to rapidly generate a synthetic ECV without formally measuring Hct. METHODS: The association between Hct and HUblood was derived from forty non-contrast thoracic CT scans using regression analysis. Synthetic Hct was then used to calculate synthetic ECV, and in turn compared with ECV using blood Hct in a validation cohort with mild interstitial expansion due to fibrosis (aortic stenosis, n = 28, ECVCT = 28 ± 4%) and severe interstitial expansion due to amyloidosis (n = 27; ECVCT = 54 ± 11%, p < 0.001). For histological validation, synthetic ECV was correlated with collagen volume fraction (CVF) in a separate cohort with aortic stenosis (n = 18). All CT scans were performed at 120 kV and 160 mAs. RESULTS: HUblood was a good predictor of Hct (R2 = 0.47; p < 0.01), with the regression model (Hct = [0.51 * HUblood] + 17.4) describing the association. Synthetic ECV correlated well with conventional ECV (R2 = 0.96; p < 0.01) with minimal bias and 2SD difference of 5.7%. Synthetic ECV correlated as well as conventional ECV with histological CVF (both R2 = 0.50, p < 0.01). Finally, we implemented an automatic ECV plug-in for offline analysis. CONCLUSION: Synthetic ECV by CCT provides instantaneous quantification of the myocardial extracellular space without the need for blood sampling.

Abnormal Wave Reflections and Left Ventricular Hypertrophy Late After Coarctation of the Aorta Repair.

Patients with repaired coarctation of the aorta are thought to have increased afterload due to abnormalities in vessel structure and function. We have developed a novel cardiovascular magnetic resonance protocol that allows assessment of central hemodynamics, including central aortic systolic blood pressure, resistance, total arterial compliance, pulse wave velocity, and wave reflections. The main study aims were to (1) characterize group differences in central aortic systolic blood pressure and peripheral systolic blood pressure, (2) comprehensively evaluate afterload (including wave reflections) in the 2 groups, and (3) identify possible biomarkers among covariates associated with elevated left ventricular mass (LVM). Fifty adult patients with repaired coarctation and 25 age- and sex-matched controls were recruited. Ascending aorta area and flow waveforms were obtained using a high temporal-resolution spiral phase-contrast cardiovascular magnetic resonance flow sequence. These data were used to derive central hemodynamics and to perform wave intensity analysis noninvasively. Covariates associated with LVM were assessed using multivariable linear regression analysis. There were no significant group differences (P≥0.1) in brachial systolic, mean, or diastolic BP. However central aortic systolic blood pressure was significantly higher in patients compared with controls (113 versus 107 mm Hg, P=0.002). Patients had reduced total arterial compliance, increased pulse wave velocity, and larger backward compression waves compared with controls. LVM index was significantly higher in patients than controls (72 versus 59 g/m2, P<0.0005). The magnitude of the backward compression waves was independently associated with variation in LVM (P=0.01). Using a novel, noninvasive hemodynamic assessment, we have shown abnormal conduit vessel function after coarctation of the aorta repair, including abnormal wave reflections that are associated with elevated LVM.