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Objectives The goal of this study was to use machine learning to more accurately predict survival after echocardiography. Background Predicting patient outcomes (e.g., survival) following echocardiography is primarily based on ejection fraction (EF) and comorbidities. However, there may be significant predictive information within additional echocardiography-derived measurements combined with clinical electronic health record data. Methods Mortality was studied in 171,510 unselected patients who underwent 331,317 echocardiograms in a large regional health system. We investigated the predictive performance of nonlinear machine learning models compared with that of linear logistic regression models using 3 different inputs: 1) clinical variables, including 90 cardiovascular-relevant International Classification of Diseases, Tenth Revision, codes, and age, sex, height, weight, heart rate, blood pressures, low-density lipoprotein, high-density lipoprotein, and smoking; 2) clinical variables plus physician-reported EF; and 3) clinical variables and EF, plus 57 additional echocardiographic measurements. Missing data were imputed with a multivariate imputation by using a chained equations algorithm (MICE). We compared models versus each other and baseline clinical scoring systems by using a mean area under the curve (AUC) over 10 cross-validation folds and across 10 survival durations (6 to 60 months). Results Machine learning models achieved significantly higher prediction accuracy (all AUC >0.82) over common clinical risk scores (AUC = 0.61 to 0.79), with the nonlinear random forest models outperforming logistic regression (p Conclusions Machine learning can fully utilize large combinations of disparate input variables to predict survival after echocardiography with superior accuracy.

Introduction: An intriguing U-shape relationship between left ventricular ejection fraction (LVEF) and survival has recently been reported, with LVEFs of 60-65% associated with the lowest mortality risk. In heart failure, LVEF recovery has been linked to improved outcomes; however, the relationship between changes in LVEF (ΔLVEF) and survival in a general clinical population has not been studied. We hypothesized that ΔLVEF would have a non-linear relationship with all-cause mortality. Methods: A total of 194,599 echocardiograms from 57,823 patients with physician-reported LVEF were identified from Geisinger health records, along with dates of death or last living encounter, age, sex, smoking status, height, weight, and active diagnoses. ΔLVEF for a given echocardiogram was calculated for 136,776 studies as the difference between the most recent previous and current LVEF. Cox Proportional Hazards Regression was used to relate interaction between ΔLVEF and current LVEF to all-cause mortality while adjusting for confounders. Results: Death occurred in 15,419 patients who underwent 39,562 (29%) echocardiograms. Median follow up duration was 3.6 years (IQR, 1.3-7.2), and median time between tests was 1.0 year (IQR, 0.2-2.3). The interaction between LVEF and ΔLVEF ( P < 0.001) demonstrated that a stable LVEF of 60-65% was associated with the best survival (Figure). A decreased LVEF was universally associated with increased mortality, while LVEFs that had increased showed non-linear interactions. In general, an LVEF of 35-55% that had increased from the previous test was associated with a similar or slightly lower mortality than the same LVEF that was unchanged or had decreased, while an LVEF >55% that had increased was associated with an increase in mortality risk compared to those with a stable LVEF. Conclusions: Changes in LVEF have a non-linear relationship with all-cause mortality. In general, a constant, stable LVEF associates with the lowest risk of mortality.

Machine learning promises to assist physicians with predictions of mortality and of other future clinical events by learning complex patterns from historical data, such as longitudinal electronic health records. Here we show that a convolutional neural network trained on raw pixel data in 812,278 echocardiographic videos from 34,362 individuals provides superior predictions of one-year all-cause mortality. The model’s predictions outperformed the widely used pooled cohort equations, the Seattle Heart Failure score (measured in an independent dataset of 2,404 patients with heart failure who underwent 3,384 echocardiograms), and a machine learning model involving 58 human-derived variables from echocardiograms and 100 clinical variables derived from electronic health records. We also show that cardiologists assisted by the model substantially improved the sensitivity of their predictions of one-year all-cause mortality by 13% while maintaining prediction specificity. Large unstructured datasets may enable deep learning to improve a wide range of clinical prediction models. A deep learning model trained on raw pixel data in hundreds of thousands of echocardiographic videos for the prediction of one-year all-cause mortality outperforms clinical scores and improves predictions by cardiologists.

Aims We investigated the relationship between clinically assessed left ventricular ejection fraction (LVEF) and survival in a large, heterogeneous clinical cohort. Methods and results Physician-reported LVEF on 403 977 echocardiograms from 203 135 patients were linked to all-cause mortality using electronic health records (1998–2018) from US regional healthcare system. Cox proportional hazards regression was used for analyses while adjusting for many patient characteristics including age, sex, and relevant comorbidities. A dataset including 45 531 echocardiograms and 35 976 patients from New Zealand was used to provide independent validation of analyses. During follow-up of the US cohort, 46 258 (23%) patients who had undergone 108 578 (27%) echocardiograms died. Overall, adjusted hazard ratios (HR) for mortality showed a u-shaped relationship for LVEF with a nadir of risk at an LVEF of 60–65%, a HR of 1.71 [95% confidence interval (CI) 1.64–1.77] when ≥70% and a HR of 1.73 (95% CI 1.66–1.80) at LVEF of 35–40%. Similar relationships with a nadir at 60–65% were observed in the validation dataset as well as for each age group and both sexes. The results were similar after further adjustments for conditions associated with an elevated LVEF, including mitral regurgitation, increased wall thickness, and anaemia and when restricted to patients reported to have heart failure at the time of the echocardiogram. Conclusion Deviation of LVEF from 60% to 65% is associated with poorer survival regardless of age, sex, or other relevant comorbidities such as heart failure. These results may herald the recognition of a new phenotype characterized by supra-normal LVEF.

PURPOSE To determine the optimal respiratory navigator gating configuration for the quantification of left ventricular strain using spiral cine displacement encoding with stimulated echoes (DENSE) MRI. MATERIALS AND METHODS Two-dimensional spiral cine DENSE was performed on a 3 Tesla MRI using two single-navigator configurations (retrospective, prospective) and a combined "dual-navigator" configuration in 10 healthy adults and 20 healthy children. The adults also underwent breathhold DENSE as a reference standard for comparisons. Peak left ventricular strains, signal-to-noise ratio (SNR), and navigator efficiency were compared. Subjects also underwent dual-navigator gating with and without visual feedback to determine the effect on navigator efficiency. RESULTS There were no differences in circumferential, radial, and longitudinal strains between navigator-gated and breathhold DENSE (P = 0.09-0.95) (as confidence intervals, retrospective: [-1.0%-1.1%], [-7.4%-2.0%], [-1.0%-1.2%]; prospective: [-0.6%-2.7%], [-2.8%-8.3%], [-0.3%-2.9%]; dual: [-1.6%-0.5%], [-8.3%-3.2%], [-0.8%-1.9%], respectively). The dual configuration maintained SNR compared with breathhold acquisitions (16 versus 18, P = 0.06). SNR for the prospective configuration was lower than for the dual navigator in adults (P = 0.004) and children (P

Introduction Displacement encoding with stimulated echoes (DENSE) is a phase contrast technique that encodes tissue displacement into phase images, which are typically processed into measures of cardiac function such as strains. For improved signal to noise ratio and spatiotemporal resolution, DENSE is often acquired with a spiral readout using an 11.1 ms readout duration. However, long spiral readout durations are prone to blurring due to common phenomena such as off-resonance and T2* decay, which may alter the resulting quantifications of strain. We hypothesized that longer readout durations would reduce image quality and underestimate cardiac strains at both 3.0 T and 1.5 T and that using short readout durations could overcome these limitations. Material and methods Computational simulations were performed to investigate the relationship between off-resonance and T2* decay, the spiral cine DENSE readout duration, and measured radial and circumferential strain. Five healthy participants subsequently underwent 2D spiral cine DENSE at both 3.0 T and 1.5 T with several different readout durations 11.1 ms and shorter. Pearson correlations were used to assess the relationship between cardiac strains and the spiral readout duration. Results Simulations demonstrated that long readout durations combined with off-resonance and T2* decay yield blurred images and underestimate strains. With the typical 11.1 ms DENSE readout, blurring was present in the anterior and lateral left ventricular segments of participants and was markedly improved with shorter readout durations. Radial and circumferential strains from those segments were significantly correlated with the readout duration. Compared to the 1.9 ms readout, the 11.1 ms readout underestimated radial and circumferential strains in those segments at both field strengths by up to 19.6% and 1.5% (absolute), or 42% and 7% (relative), respectively. Conclusions Blurring is present in spiral cine DENSE images acquired at both 3.0 T and 1.5 T using the typical 11.1 ms readout duration, which yielded substantially reduced radial strains and mildly reduced circumferential strains. Clinical studies using spiral cine DENSE should consider these limitations, while future technical advances may need to leverage accelerated techniques to improve the robustness and accuracy of the DENSE acquisition rather than focusing solely on reduced acquisition time.

Aims Previous studies using regression analyses have failed to identify which patients with repaired tetralogy of Fallot (rTOF) are at risk for deterioration in ventricular size and function despite using common clinical and cardiac function parameters as well as cardiac mechanics (strain and dyssynchrony). This study used a machine learning pipeline to comprehensively investigate the predictive value of the baseline variables derived from cardiac magnetic resonance (CMR) imaging and provide models for identifying patients at risk for deterioration. Methods and results Longitudinal deterioration for 153 patients with rTOF was categorized as 'none', 'minor', or 'major' based on changes in ventricular size and ejection fraction between two CMR scans at least 6 months apart (median 2.7 years). Baseline variables were measured at the time of the first CMR. An exhaustive variable search with a support vector machine classifier and five-fold cross-validation was used to predict deterioration and identify the most useful variables. For predicting any deterioration (minor or major) vs. no deterioration, the mean area under the curve (AUC) was 0.82 ± 0.06. For predicting major deterioration vs. minor or no deterioration, the AUC was 0.77 ± 0.07. Baseline left ventricular (LV) ejection fraction, LV circumferential strain, and pulmonary regurgitation were most useful for achieving accurate predictions. Conclusion For the prediction of deterioration in patients with rTOF, a machine learning pipeline uncovered the utility of baseline variables that was previously lost to regression analyses. The predictive models may be useful for planning early interventions in patients with high risk.

Background Left ventricular (LV) torsion is an important indicator of cardiac function that is limited by high inter-test variability (50% of the mean value). We hypothesized that this high inter-test variability is partly due to inconsistent breath-hold positions during serial image acquisitions, which could be significantly improved by using a respiratory navigator for cardiovascular magnetic resonance (CMR) based quantification of LV torsion. Methods We assessed respiratory-related variability in measured LV torsion with two distinct experimental protocols. First, 17 volunteers were recruited for CMR with cine displacement encoding with stimulated echoes (DENSE) in which a respiratory navigator was used to measure and then enforce variability in end-expiratory position between all LV basal and apical acquisitions. From these data, we quantified the inter-test variability of torsion in the absence and presence of enforced end-expiratory position variability, which established an upper bound for the expected torsion variability. For the second experiment (in 20 new, healthy volunteers), 10 pairs of cine DENSE basal and apical images were each acquired from consecutive breath-holds and consecutive navigator-gated scans (with a single acceptance position). Inter-test variability of torsion was compared between the breath-hold and navigator-gated scans to quantify the variability due to natural breath-hold variation. To demonstrate the importance of these variability reductions, we quantified the reduction in sample size required to detect a clinically meaningful change in LV torsion with the use of a respiratory navigator. Results The mean torsion was 3.4 ± 0.2°/cm. From the first experiment, enforced variability in end-expiratory position translated to considerable variability in measured torsion (0.56 ± 0.34°/cm), whereas inter-test variability with consistent end-expiratory position was 57% lower (0.24 ± 0.16°/cm, p

Mechanics of the left ventricle (LV) are important indicators of cardiac function. The role of right ventricular (RV) mechanics is largely unknown due to the technical limitations of imaging its thin wall and complex geometry and motion. By combining 3D Displacement Encoding with Stimulated Echoes (DENSE) with a post-processing pipeline that includes a local coordinate system, it is possible to quantify RV strain, torsion, and synchrony. In this study, we sought to characterize RV mechanics in 50 healthy individuals and compare these values to their LV counterparts. For each cardiac frame, 3D displacements were fit to continuous and differentiable radial basis functions, allowing for the computation of the 3D Cartesian Lagrangian strain tensor at any myocardial point. The geometry of the RV was extracted via a surface fit to manually delineated endocardial contours. Throughout the RV, a local coordinate system was used to transform from a Cartesian strain tensor to a polar strain tensor. It was then possible to compute peak RV torsion as well as peak longitudinal and circumferential strain. A comparable analysis was performed for the LV. Dyssynchrony was computed from the standard deviation of regional activation times. Global circumferential strain was comparable between the RV and LV (−18.0% for both) while longitudinal strain was greater in the RV (−18.1% vs. −15.7%). RV torsion was comparable to LV torsion (6.2 vs. 7.1 degrees, respectively). Regional activation times indicated that the RV contracted later but more synchronously than the LV. 3D spiral cine DENSE combined with a post–processing pipeline that includes a local coordinate system can resolve both the complex geometry and 3D motion of the RV.

Rat models have assumed an increasingly important role in cardiac research. However, a detailed profile of regional cardiac mechanics, such as strains and torsion, is lacking for rats. We hypothesized that healthy rat left ventricles (LVs) exhibit regional differences in cardiac mechanics, which are part of normal function. In this study, images of the LV were obtained with 3D cine displacement encoding with stimulated echoes (DENSE) cardiovascular magnetic resonance in 10 healthy rats. To evaluate regional cardiac mechanics, the LV was divided into basal, mid-ventricular, and apical regions. The myocardium at the mid-LV was further partitioned into four wall segments (i.e. septal, inferior, lateral, and anterior) and three transmural layers (i.e. sub-endocardium, mid-myocardium, and sub-epicardium). The six Lagrangian strain components (i.e. Err , Ecc , Ell , Ecl , Erl , and Ecr ) were computed from the 3D displacement field and averaged within each region of interest. Torsion was quantified using the circumferential-longitudinal shear angle. While peak systolic Ecl differed between the mid-ventricle and apex, the other five components of peak systolic strain were similar across the base, mid-ventricle, and apex. In the mid-LV myocardium, Ecc decreased gradually from the sub-endocardial to the sub-epicardial layer. Ell demonstrated significant differences between the four wall segments, with the largest magnitude in the inferior segment. Err was uniform among the four wall segments. Ecl varied along the transmural direction and among wall segments, whereas Erl differed only among the wall segments. Erc was not associated with significant variations. Torsion also varied along the transmural direction and among wall segments. These results provide fundamental insights into the regional contractile function of healthy rat hearts, and form the foundation for future studies on regional changes induced by disease or treatments.

To determine the optimal respiratory navigator gating configuration for the quantification of left ventricular strain using spiral cine displacement encoding with stimulated echoes (DENSE) MRI.Two-dimensional spiral cine DENSE was performed on a 3 Tesla MRI using two single-navigator configurations (retrospective, prospective) and a combined "dual-navigator" configuration in 10 healthy adults and 20 healthy children. The adults also underwent breathhold DENSE as a reference standard for comparisons. Peak left ventricular strains, signal-to-noise ratio (SNR), and navigator efficiency were compared. Subjects also underwent dual-navigator gating with and without visual feedback to determine the effect on navigator efficiency.There were no differences in circumferential, radial, and longitudinal strains between navigator-gated and breathhold DENSE (P = 0.09-0.95) (as confidence intervals, retrospective: [-1.0%-1.1%], [-7.4%-2.0%], [-1.0%-1.2%]; prospective: [-0.6%-2.7%], [-2.8%-8.3%], [-0.3%-2.9%]; dual: [-1.6%-0.5%], [-8.3%-3.2%], [-0.8%-1.9%], respectively). The dual configuration maintained SNR compared with breathhold acquisitions (16 versus 18, P = 0.06). SNR for the prospective configuration was lower than for the dual navigator in adults (P = 0.004) and children (P 0.001). Navigator efficiency was higher (P 0.001) for both retrospective (54%) and prospective (56%) configurations compared with the dual configuration (35%). Visual feedback improved the dual configuration navigator efficiency to 55% (P 0.001).When quantifying left ventricular strains using spiral cine DENSE MRI, a dual navigator configuration results in the highest SNR in adults and children. In adults, a retrospective configuration has good navigator efficiency without a substantial drop in SNR. Prospective gating should be avoided because it has the lowest SNR. Visual feedback represents an effective option to maintain navigator efficiency while using a dual navigator configuration.2 J. Magn. Reson. Imaging 2017;45:786-794.

Background Obesity affects nearly one in five children and is associated with increased risk of premature death. Obesity-related heart disease contributes to premature death. We aimed to use cardiovascular magnetic resonance (CMR) to comprehensively characterize the changes in cardiac geometry and function in obese children. Methods and results Forty-one obese/overweight (age 12 ± 3 years, 56 % female) and 29 healthy weight children (age 14 ± 3 years, 41 % female) underwent CMR, including both standard cine imaging and displacement encoded imaging, for a complete assessment of left ventricular (LV) structure and function. After adjusting for age, LV mass index was 23 % greater (27 ± 4 g/m2.7 vs 22 ± 3 g/m2.7, p

Background Advanced cardiac magnetic resonance (CMR) acquisitions often require long scan durations that necessitate respiratory navigator gating. This is particularly important in children with limited ability to hold their breath. We hypothesized that visual feedback of diaphragm position using an interactive videogame during CMR would increase navigator efficiency and improve image quality in children.

Background Displacement Encoding with Stimulated Echoes (DENSE) encodes displacement into the phase of the magnetic resonance signal. The encoding frequency (ke) maps the measured phase to tissue displacement while the strength of the encoding gradients affects image quality. 2D cine DENSE studies have used a ke of 0.10 cycles/mm, which is high enough to remove an artifact-generating echo from k-space, provide high sensitivity to tissue displacements, and dephase the blood pool. However, through-plane dephasing can remove the unwanted echo and dephase the blood pool without relying on high ke. Additionally, the high sensitivity comes with the costs of increased phase wrapping and intra-voxel dephasing. We hypothesized that ke below 0.10 cycles/mm can be used to improve image characteristics and provide accurate measures of cardiac mechanics. Methods Spiral cine DENSE images were obtained for 10 healthy subjects and 10 patients with a history of heart disease on a 3 T Siemens Trio. A mid-ventricular short-axis image was acquired with different ke: 0.02, 0.04, 0.06, 0.08, and 0.10 cycles/mm. Peak twist, circumferential strain, and radial strain were compared between acquisitions employing different ke using Bland-Altman analyses and coefficients of variation. The percentage of wrapped pixels in the phase images at end-systole was calculated for each ke. The dephasing of the blood signal and signal to noise ratio (SNR) were also calculated and compared. Results Negligible differences were seen in strains and twist for all ke between 0.04 and 0.10 cycles/mm. These differences were of the same magnitude as inter-test differences. Specifically, the acquisitions with 0.04 cycles/mm accurately quantified cardiac mechanics and had zero phase wrapping. Compared to 0.10 cycles/mm, the acquisitions with 0.04 cycles/mm had 9 % greater SNR and negligible differences in blood pool dephasing. Conclusions For 2D cine DENSE with through-plane dephasing, the encoding frequency can be lowered to 0.04 cycles/mm without compromising the quantification of twist or strain. The amount of wrapping can be reduced with this lower value to greatly simplify the input to unwrapping algorithms. The strain and twist results from studies using different encoding frequencies can be directly compared.

Background Obesity affects one in five children in the US and these children tend to maintain excess weight into adulthood. It has recently been shown that childhood obesity is associated with both cardiac remodeling (hypertrophy) and contractile dysfunction. However, the etiology of these cardiac changes is not well understood. We hypothesized that cardiac remodeling and dysfunction could not be entirely explained by elevations in blood pressure and that excess abdominal and epicardial adiposity may also correlate with cardiac changes.

Background Displacement Encoding with Stimulated Echoes (DENSE) directly measures tissue displacements and can be used to quantify cardiac mechanics. Multi-dimensional DENSE results in lengthy scans that require respiratory gating, acquiring data only while the diaphragm is within a prespecified “acceptance window.” Because it is not possible to perform respiratory gating during data acquisition, DENSE can employ the following respiratory gating strategies: 1) acquire data and keep it if the diaphragm is inside the window after acquisition (retrospective) 2) acquire data and keep it only if the diaphragm was inside the window right before data acquisition (prospective) or 3) a combination of retrospective and prospective where the diaphragm must be inside the window both before and after data acquisition (combined) (Fig 1). Combined respiratory gating is not used often because more data is discarded, resulting in longer scan times. It is possible, however, that with only retrospective or prospective respiratory gating, the diaphragm may not be within the acceptance window for the entirety of data acquisition (i.e. drifting into or out of the window), negatively affecting image quality. We hypothesized that the combined respiratory gating would result in significantly different estimates of left ventricular strains compared to either retrospective or prospective respiratory gating.

Background Cardiac magnetic resonance (CMR) can be used to quantify cardiac mechanics from images that are generally acquired during an end-expiratory breath-hold. Unfortunately, it is difficult for subjects to hold their breath at the exact same position when undergoing a series of breath-holds during a typical CMR study. The effect of patient-specific variability in breath-hold positions on measures of cardiac mechanics has not been investigated. We hypothesized that normal variability in breath-hold positions would significantly affect estimates of left ventricular strains and torsion.

Background Right ventricular (RV) function is important in many disease states, but is difficult to quantify from routine MR imaging. Previous work has shown that long-axis deformation/strain is the most critical contributor to global RV function; however, short-axis datasets allow for better coverage of the RV. Thus it would be ideal to be able to quantify RV long-axis function using shortaxis slice orientations. We hypothesized that a stack of three-dimensional (3D) displacement encoded (DENSE) images could reliably quantify longitudinal deformation of the RV to overcome the need for acquiring additional long-axis views of the RV.

Background Advanced measures of cardiac mechanics such as left ventricular (LV) strains can be used in conjunction with classical biomarkers to gauge cardiovascular health and improve prediction of patient outcomes. Several imaging techniques, including displacement-encoded magnetic resonance imaging (DENSE), are used to non-invasively assess cardiac mechanics. These data are predominantly acquired in two dimensions (2D) due to simplified postprocessing and shorter acquisition times; however, this type of acquisition and subsequent analysis cannot account for through-plane motion caused by longitudinal contraction of the left ventricle. We hypothesized that through-plane motion has a significant effect on 2D strain estimates. Methods

Background Advanced cardiovascular magnetic resonance (CMR) acquisitions often require long scan durations that necessitate respiratory navigator gating. The tradeoff of navigator gating is reduced scan efficiency, particularly when the patient’s breathing patterns are inconsistent, as is commonly seen in children. We hypothesized that engaging pediatric participants with a navigator-controlled videogame to help control breathing patterns would improve navigator efficiency and maintain image quality. Methods We developed custom software that processed the Siemens respiratory navigator image in real-time during CMR and represented diaphragm position using a cartoon avatar, which was projected to the participant in the scanner as visual feedback. The game incentivized children to breathe such that the avatar was positioned within the navigator acceptance window (±3 mm) throughout image acquisition. Using a 3T Siemens Tim Trio, 50 children (Age: 14 ± 3 years, 48 % female) with no significant past medical history underwent a respiratory navigator-gated 2D spiral cine displacement encoding with stimulated echoes (DENSE) CMR acquisition first with no feedback (NF) and then with the feedback game (FG). Thirty of the 50 children were randomized to undergo extensive off-scanner training with the FG using a MRI simulator, or no off-scanner training. Navigator efficiency, signal-to-noise ratio (SNR), and global left-ventricular strains were determined for each participant and compared. Results Using the FG improved average navigator efficiency from 33 ± 15 to 58 ± 13 % (p

Background Patients with repaired tetralogy of Fallot (rTOF) suffer from progressive ventricular dysfunction decades after their surgical repair. We hypothesized that measures of ventricular strain and dyssynchrony would predict deterioration of ventricular function in patients with rTOF. Methods A database search identified all patients at a single institution with rTOF who underwent cardiovascular magnetic resonance (CMR) at least twice, >6 months apart, without intervening surgical or catheter procedures. Seven primary predictors were derived from the first CMR using a custom feature tracking algorithm: left (LV), right (RV) and inter-ventricular dyssynchrony, LV and RV peak global circumferential strains, and LV and RV peak global longitudinal strains. Three outcomes were defined, whose changes were assessed over time: RV end-diastolic volume, and RV and LV ejection fraction. Multivariate linear mixed models were fit to investigate relationships of outcomes to predictors and ten potential baseline confounders. Results One hundred fifty-three patients with rTOF (23 ± 14 years, 50 % male) were included. The mean follow-up duration between the first and last CMR was 2.9 ± 1.3 years. After adjustment for confounders, none of the 7 primary predictors were significantly associated with change over time in the 3 outcome variables. Only 1–17 % of the variability in the change over time in the outcome variables was explained by the baseline predictors and potential confounders. Conclusions In patients with repaired tetralogy of Fallot, ventricular dyssynchrony and global strain derived from cine CMR were not significantly related to changes in ventricular size and function over time. The ability to predict deterioration in ventricular function in patients with rTOF using current methods is limited. Electronic supplementary material The online version of this article (doi:10.1186/s12968-016-0268-8) contains supplementary material, which is available to authorized users.

Background: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30–40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis. Methods and Results: We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30–40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing. Conclusions: Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow.

Background Measures of left ventricular cardiac mechanics such as strains and torsion are becoming increasingly important for assessing heart function. Cardiac magnetic resonance (CMR) can be used to quantify cardiac mechanics using several methods such as tagged CMR or cine Displacement Encoding with Stimulated Echoes (DENSE). These images are generally acquired during an end-expiratory breath-hold. Unfortunately, it is difficult for subjects to hold their breath at the exact same position when undergoing a series of breath-holds during a typical CMR study. For example, end-expiratory breath-hold positions have an average range of about 8 millimeters (mm). The effects of different breath-hold positions on measures of cardiac mechanics have not been investigated. We hypothesized that the normal variability in breath-hold positions would significantly affect the quantification of left ventricular strains and torsion.

Background Displacement Encoding with Stimulated Echoes (DENSE) encodes displacement into the phase of the magnetic resonance signal. Due to the stimulated echo, the signal is inherently low and fades through the cardiac cycle. To compensate, a spiral acquisition has been used at 1.5T. This spiral sequence has not been validated at 3T, where the increased signal would be valuable, but field inhomogeneities may result in measurement errors. We hypothesized that spiral cine DENSE is valid at 3T and tested this hypothesis by measuring displacement errors at both 1.5T and 3T in vivo. Methods Two-dimensional spiral cine DENSE and tagged imaging of the left ventricle were performed on ten healthy subjects at 3T and six healthy subjects at 1.5T. Intersection points were identified on tagged images near end-systole. Displacements from the DENSE images were used to project those points back to their origins. The deviation from a perfect grid was used as a measure of accuracy and quantified as root-mean-squared error. This measure was compared between 3T and 1.5T with the Wilcoxon rank sum test. Inter-observer variability of strains and torsion quantified by DENSE and agreement between DENSE and harmonic phase (HARP) were assessed by Bland-Altman analyses. The signal to noise ratio (SNR) at each cardiac phase was compared between 3T and 1.5T with the Wilcoxon rank sum test. Results The displacement accuracy of spiral cine DENSE was not different between 3T and 1.5T (1.2 ± 0.3 mm and 1.2 ± 0.4 mm, respectively). Both values were lower than the DENSE pixel spacing of 2.8 mm. There were no substantial differences in inter-observer variability of DENSE or agreement of DENSE and HARP between 3T and 1.5T. Relative to 1.5T, the SNR at 3T was greater by a factor of 1.4 ± 0.3. Conclusions The spiral cine DENSE acquisition that has been used at 1.5T to measure cardiac displacements can be applied at 3T with equivalent accuracy. The inter-observer variability and agreement of DENSE-derived peak strains and torsion with HARP is also comparable at both field strengths. Future studies with spiral cine DENSE may take advantage of the additional SNR at 3T.

Background Displacement Encoding with Stimulated Echoes (DENSE) encodes displacement into the phase of the MR signal to quantify cardiac mechanics. The encoding frequency (ke) links myocardial displacement to phase. Studies with 2D cine DENSE have used ke of 0.10 cycles/mm, which is high enough to remove the stimulated anti-echo from the sampled k-space and is partially responsible for dephasing the blood signal. This ke leads to wrapping in the phase images and causes intra-voxel dephasing. With the advent of through-plane dephasing, the unwanted echo can be removed without relying on high ke. This may allow the use of lower ke to simplify post-processing and increase SNR. Low ke, however, may be less sensitive to displacement and result in inaccurate measures of cardiac mechanics. We hypothesized that ke below 0.10 cycles/mm will 1) provide accurate measures of cardiac mechanics, 2) minimize phase wrapping, 3) dephase the blood signal, and 4) improve SNR.