Real-time Cardiac Magnetic Resonance Research Articles

Assessment of the cardiac output at rest and during exercise stress using real-time cardiovascular magnetic resonance imaging in HFpEF-patients

This methodological study aimed to validate the cardiac output (CO) measured by exercise-stress real-time phase-contrast cardiovascular magnetic resonance imaging (CMR) in patients with heart failure and preserved ejection fraction (HFpEF). 68 patients with dyspnea on exertion (NYHA ≥ II) and echocardiographic signs of diastolic dysfunction underwent rest and exercise stress right heart catheterization (RHC) and CMR within 24 h. Patients were diagnosed as overt HFpEF (pulmonary capillary wedge pressure (PCWP) ≥ 15mmHg at rest), masked HFpEF (PCWP ≥ 25mmHg during exercise stress but < 15mmHg at rest) and non-cardiac dyspnea. CO was calculated using RHC as the reference standard, and in CMR by the volumetric stroke volume, conventional phase-contrast and rest and stress real-time phase-contrast imaging. At rest, the CMR based CO showed good agreement with RHC with an ICC of 0.772 for conventional phase-contrast, and 0.872 for real-time phase-contrast measurements. During exercise stress, the agreement of real-time CMR and RHC was good with an ICC of 0.805. Real-time measurements underestimated the CO at rest (Bias:0.71 L/min) and during exercise stress (Bias:1.4 L/min). Patients with overt HFpEF had a significantly lower cardiac index compared to patients with masked HFpEF and with non-cardiac dyspnea during exercise stress, but not at rest. Real-time phase-contrast CO can be assessed with good agreement with the invasive reference standard at rest and during exercise stress. While moderate underestimation of the CO needs to be considered with non-invasive testing, the CO using real-time CMR provides useful clinical information and could help to avoid unnecessary invasive procedures in HFpEF patients.

CMR 3-105 - Exercise Stress in Healthy Adults: Normal Ranges for Real Time Cardiac Magnetic Resonance Imaging

CMR 3-105 - Exercise Stress in Healthy Adults: Normal Ranges for Real Time Cardiac Magnetic Resonance Imaging

Improved visualization of free-running cardiac magnetic resonance by respiratory phase using principal component analysis

Rationale and objectivesTo support cardiac MR acquisitions during breathing without ECG, we developed software to mitigate the effects of respiratory displacement of the heart. The algorithm resolves respiratory motions and cardiac cycles from DICOM files. The new software automatically detects heartbeats from expiration and inspiration to decrease apparent respiratory motion. Materials and methodsOur software uses principal component analysis to resolve respiratory motions from cardiac cycles. It groups heartbeats from expiration and inspiration to decrease apparent respiratory motion. The respiratory motion correction was evaluated on short-axis views (acquired with compressed sensing) of 11 healthy subjects and 8 cardiac patients. Two expert radiologists, blinded to the processing, assessed the dynamic images in terms of blood-myocardial contrast, endocardial interface definition, and motion artifacts. ResultsThe smallest correlation coefficients between end-systolic frames of the original dynamic scans averaged 0.79. After segregation of cardiac cycles by respiratory phase, the mean correlation coefficients between cardiac cycles were 0.94±0.03 at end-expiration and 0.90±0.08 at end-inspiration. The improvements in correlation coefficients were significant in paired t-tests for healthy subjects and heart patients at end-expiration. Clinical assessment preferred cardiac cycles during end-expiration, which maintained or enhanced scores in 90% of healthy subjects and 83% of the heart patients. Performance remained high with arrhythmia and irregular breathing present. ConclusionHeartbeats collected from end-expiration mitigate respiratory motion and are accessible by applying the new software to DICOM files from real-time CMR. Inspiratory heartbeats are also accessible for examination of arrhythmias or abnormalities at end-inspiration.

Right ventricular quantification using 3D echocardiography: a comparison with CMR

Abstract Background Volumetric and functional right ventricular (RV) indices such as ejection fraction (EF) and global strains are known independent predictors of adverse cardiovascular events. While cardiac magnetic resonance (CMR) imaging remains the reference standard for volume quantification, echocardiography is more accessible and allows for rapid ventricular assessment. Compared to conventional 2D echocardiography, 3D echocardiography (3DE) enables full volume acquisitions and the ability to circumvent geometric assumptions. Given the complexity of RV geometry and sensitivity to image plane positioning, this advantage offers the potential to obtain more accurate diagnostic measurements. Purpose Tools for RV analysis in 3DE have been less extensively studied compared to those for the left ventricle (LV). We sought to quantify discrepancies in RV indices derived from 3DE and CMR. Methods Transthoracic real-time 3DE and cine CMR imaging were performed in 20 prospectively recruited participants (12 patients with acquired cardiac disease and 8 healthy controls), &amp;lt;1 hour apart. Dynamic 3D biventricular models were constructed semi-automatically from CMR by identifying fiducial landmarks, correcting in-plane breath-hold mis-registrations, and interactively fitting contours to the endocardial and epicardial borders on long- and short-axis slices. For 3DE, right ventricular endocardial models were created by fitting contours on 2D image planes resampled from the 3D volume at end-diastole and end-systole, which were subsequently tracked over one cardiac cycle (Figure 1). RV indices including end-diastolic volume (EDV), end-systolic volume (ESV), EF, global longitudinal strain (GLS), and global circumferential strain (GCS) were calculated from the 3DE- and CMR-derived 3D geometric models and compared. Paired-sample t-tests were performed to identify statistically significant differences (where P&amp;lt;0.05), and intraclass correlation coefficients (ICC) for absolute agreement were computed to assess the reliability for each measurement. Results Differences (mean ± SD) in RV indices between 3DE and CMR, with corresponding ICCs are presented in Table 1. Statistically significant differences in RV EDV, ESV, EF, and GLS were observed, with 3DE consistently underestimating volumes and overestimating function when compared to CMR. Although a statistically significant difference in RV GCS was not observed, a low ICC score indicated poor reliability. Conclusions Volume underestimation in RV indices between 3DE and CMR were found to be larger than those previously reported for the LV, which is likely due to the increased geometric complexity and surface area to volume ratio for the RV. Moreover, 3DE tends to overestimate RV function in terms of EF and GLS, which may impact treatment pathways if used in a clinical setting. Recognising systematic differences between modalities reinforces the need to further develop 3DE technologies for more accurate RV quantification. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Health Research Council (HRC) of New Zealand;National Heart Foundation (NHF) of New Zealand

Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images

Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that semi-automatically sorts real-time CMR images according to breathing to facilitate quantification of LV function in free breathing exercise. A semi-automatic algorithm utilizing manifold learning (Laplacian Eigenmaps) was developed for respiratory sorting. Feasibility was tested in eight healthy volunteers and eight patients who underwent ECG-gated and real-time CMR at rest. Additionally, volunteers performed exercise CMR at 60% of maximum heart rate. The algorithm was validated for exercise by comparing LV mass during exercise to rest. Respiratory sorting to end expiration and end inspiration (processing time 20 to 40 min) succeeded in all research participants. Bias ± SD for LV mass was 0 ± 5 g when comparing real-time CMR at rest, and 0 ± 7 g when comparing real-time CMR during exercise to ECG-gated at rest. This study presents a semi-automatic algorithm to retrospectively perform respiratory sorting in free breathing real-time CMR. This can facilitate implementation of exercise CMR with non-ECG-gated free breathing real-time imaging, without any additional physiological input.

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

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

Exercise-dependent changes in ventricular-arterial coupling and aortopulmonary collateral flow in Fontan patients: a real-time CMR study.

Inefficient ventricular-arterial (V-A) coupling has been described in Fontan patients and may result in adverse haemodynamics. A varying amount of aortopulmonary collateral (APC) flow is also frequently present that increases volume load of the single ventricle. The aim of the study was to assess changes in V-A coupling and APC flow during exercise CMR. Eighteen Fontan patients (age 24 ± 3 years) and 14 controls (age 23 ± 4 years) underwent exercise CMR using a cycle ergometer. Ventricular volumetry and flow measurements in the ascending aorta (AAO), inferior (IVC), and superior (SVC) vena cava were assessed using real-time sequences during stepwise increases in work load. Measures of systemic arterial elastance Ea, ventricular elastance Ees, and V-A coupling (Ea/Ees) were assessed. APC flow was quantified as AAO - (SVC + IVC). Ea remained unchanged during all levels of exercise in both groups (P = 0.39 and P = 0.11). Ees increased in both groups (P = 0.001 and P < 0.001) with exercise but was lower in the Fontan group (P = 0.04). V-A coupling was impaired in Fontan patients at baseline (P = 0.04). Despite improvement during exercise (P = 0.002) V-A coupling remained impaired compared with controls (P = 0.001). Absolute APC flow in Fontan patients did not change during exercise even at maximum work load (P = 0.98). Inefficient V-A coupling was already present at rest in Fontan patients and aggravated during exercise due to a limited increase in ventricular contractility which demonstrates the importance of a limited functional reserve of the single ventricle. APC flow remained unchanged suggesting no further increase in volume load during exercise.

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

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

Imaging of arrhythmia: Real-time cardiac magnetic resonance imaging in atrial fibrillation

ObjectivesQuantitative evaluations of function, volume and mass are fundamental in the diagnostic workup of different cardiovascular diseases and can be exactly determined by CMRI in sinus rhythm. This does not hold true in arrhythmia as CMR is hampered by reconstruction artifacts caused by inconsistent data from multiple heartbeats. Real-time (RT) MRI at high temporal resolution might reduce these problems. MethodsConsecutive patients with atrial fibrillation were prospectively included and underwent RT and conventional CINE CMR in randomized order. 29 patients were studied at 1.5 T and 30 patients at 3 T. At 3 T a group of 20 subjects in sinus rhythm served as controls. RT and CINE image quality was evaluated in different planes and for different wall sections using a Likert scale (from zero to four). Volumetric analysis was performed using two types of software and differences between RT and CINE CMR were evaluated. ResultsIn patients with atrial fibrillation RT CMR short axis (SA) resulted in a significantly higher image quality compared to CINE imaging both at 1.5 T and 3 T (1.5 T: mid SA: 3.55 ± 0.5 RT vs 2.6 ± 0.9 CINE, p = 0.0001; 3 T: mid SA: 3.15 ± 0.9 RT vs 2.6 ±1.0 CINE, p = 0.03); This qualitative difference was more marked and significant for the long axis views (2CV and 4CV) at 1.5 T (1.5 T: 2CV: 3.2 ± 0.6 RT vs 2.65 ± 1.1 CINE; p = 0.011; 4CV: 2.9 ± 0.69 RT vs 2.4 ± 0.9 CINE; p = 0.0044). During sinus rhythm CINE images were superior concerning diagnostic quality (3 T mid SA: 3.35 ± 0.45 RT vs 3.8 ± 0.5 CINE, p = 0.008). Quantitative analysis was successful with both software packages and the results showed a good correlation (Pearson correlation between 0.679 and 0.921 for patients). RT CMR resulted in slightly lower functional volumes than CINE CMR (3 T: patients: EDVI 86 ± 29 ml/m2 RT vs 93 29 ml/m2± 29 CINE, Pearson r = 0.902) but similar ejection fractions (3 T: patients: EF 47 ± 16% RT vs 45 ± 13% CINE, Pearson r = 0679; controls: EF 63 ± 6 RT vs 63 ± 3 CINE, Pearson r = 0.695). ConclusionRT CMR improves image quality in arrhythmic patients and renders studies more comfortable. Volumetric analysis is feasible with slightly lower values relative to CINE CMR, while ejection fractions are comparable.

Ensuring respiratory phase consistency to improve cardiac function quantification in real-time CMR.

To develop an automatic method for selecting heartbeats with consistent respiratory phase to improve accuracy of cardiac function quantification in real-time (RT) cardiac MRI. The respiratory signal is extracted by a principal component analysis method from RT cine images. Then, a two-step procedure is used to determine the directionality (sign) of the respiratory signal. With the motion in a manually selected region-of-interest as a reference, the quality of the extracted respiratory signal is assessed using multislice RT cine data from 11 volunteers and 10 patients. In addition, the impact of selecting heartbeats with consistent respiratory phase on the cardiac function quantification is evaluated. The extracted respiratory signal using the proposed method exhibits a high, positive correlation with the reference in all cases and is more robust compared to a recently proposed method. Also, for right ventricular function quantification, selecting heartbeats at expiratory position improves agreement between RT cine and breath-held reference. The proposed method enables fully automatic extraction and directionality determinations of respiratory signal from RT cardiac cine images, allowing accurate cardiac function quantification.

Exercise Stress Real-Time Cardiac Magnetic Resonance Imaging for Noninvasive Characterization of Heart Failure With Preserved Ejection Fraction: The HFpEF-Stress Trial.

Right heart catheterization using exercise stress is the reference standard for the diagnosis of heart failure with preserved ejection fraction (HFpEF) but carries the risk of the invasive procedure. We hypothesized that real-time cardiac magnetic resonance (RT-CMR) exercise imaging with pathophysiologic data at excellent temporal and spatial resolution may represent a contemporary noninvasive alternative for diagnosing HFpEF. The HFpEF-Stress trial (CMR Exercise Stress Testing in HFpEF; URL: https://www.clinicaltrials.gov; Unique identifier: NCT03260621. URL: https://dzhk.de/; Unique identifier: DZHK-17) prospectively recruited 75 patients with echocardiographic signs of diastolic dysfunction and dyspnea on exertion (E/e'>8, New York Heart Association class ≥II) to undergo echocardiography, right heart catheterization, and RT-CMR at rest and during exercise stress. HFpEF was defined according to pulmonary capillary wedge pressure (≥15 mm Hg at rest or ≥25 mm Hg during exercise stress). RT-CMR functional assessments included time-volume curves for total and early (1/3) diastolic left ventricular filling, left atrial (LA) emptying, and left ventricular/LA long axis strain. Patients with HFpEF (n=34; median pulmonary capillary wedge pressure at rest, 13 mm Hg; at stress, 27 mm Hg) had higher E/e' (12.5 versus 9.15), NT-proBNP (N-terminal pro-B-type natriuretic peptide; 255 versus 75 ng/L), and LA volume index (43.8 versus 36.2 mL/m2) compared with patients with noncardiac dyspnea (n=34; rest, 8 mm Hg; stress, 18 mm Hg; P≤0.001 for all). Seven patients were excluded because of the presence of non-HFpEF cardiac disease causing dyspnea on imaging. There were no differences in RT-CMR left ventricular total and early diastolic filling at rest and during exercise stress (P≥0.164) between patients with HFpEF and noncardiac dyspnea. RT-CMR revealed significantly impaired LA total and early (P<0.001) diastolic emptying in patients with HFpEF during exercise stress. RT-CMR exercise stress LA long axis strain was independently associated with HFpEF (adjusted odds ratio, 0.657 [95% CI, 0.516-0.838]; P=0.001) after adjustment for clinical and imaging measures and emerged as the best predictor for HFpEF (area under the curve at rest 0.82 versus exercise stress 0.93; P=0.029). RT-CMR allows highly accurate identification of HFpEF during physiologic exercise and qualifies as a suitable noninvasive diagnostic alternative. These results will need to be confirmed in multicenter prospective research studies to establish widespread routine clinical use. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03260621. URL: https://dzhk.de/; Unique identifier: DZHK-17.

Real-time cardiovascular magnetic resonance tissue characterisation in patients undergoing transcatheter aortic valve replacement

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): German Research Foundation (DFG, CRC 1002, D1) Background Myocardial fibrosis is a major determinant of outcome in aortic stenosis (AS). Novel fast real-time (RT) cardiac magnetic resonance (CMR) mapping techniques allow comprehensive quantification of fibrosis but have not yet been compared against standard techniques and histology. Methods Patients with severe AS underwent CMR before (n = 110) and left ventricular (LV) endomyocardial biopsy (n = 46) at transcatheter aortic valve replacement (TAVR). Midventricular short axis (SAX) native, post-contrast T1 and extracellular volume fraction (ECV) maps were generated using commercially available MOLLI (native: 5(3)3, post-contrast: 4(1)3(1)2) and RT single-shot inversion recovery fast low-angle shot (FLASH) with radial undersampling. Focal late gadolinium enhancement was excluded from T1 and ECV regions of interest. ECV and LV mass were used to calculate LV matrix volumes. Variability and agreements were assessed between RT, MOLLI and histology using intraclass correlation coefficients, coefficients of variation and Bland Altman analyses. Results RT and MOLLI derived ECV were similar for midventricular SAX slice coverage (26.2 vs. 26.5, p = 0.073) and septal region of interest (26.2 vs. 26.5, p = 0.216). MOLLI native T1 time was in median 20 ms longer compared to RT (p &amp;lt; 0.001). Agreement between RT and MOLLI was best for ECV (ICC &amp;gt;0.91), excellent for post-contrast T1 times (ICC &amp;gt;0.81) and good for native T1 times (ICC &amp;gt;0.62). Diffuse collagen volume fraction by biopsies was in median 7.8%. ECV (RT r = 0.345, p = 0.039; MOLLI r = 0.40, p = 0.010) and LV matrix volumes (RT r = 0.45, p = 0.005; MOLLI r = 0.43, p = 0.007) were the only parameters associated with histology. Conclusions RT mapping offers fast and sufficient ECV and LV matrix volume calculation in AS. ECV and LV matrix volume represent robust and universally comparable parameters with associations to histologically assessed fibrosis and may emerge as potential targets for clinical decision making.

Abstract 15545: Exercise-stress Real-time Cardiac Magnetic Resonance Imaging for Non-invasive Characterisation of Heart Failure With Preserved Ejection Fraction: The Hfpef Stress Trial

Introduction: Invasive right heart catherization (RHC) using exercise-stress is the reference-standard for the diagnosis of heart failure with preserved ejection fraction (HFpEF) but carries the risk of the procedure. Real-time cardiovascular magnetic resonance (RT-CMR) imaging allows bicycle exercise CMR with unprecedented temporal and spatial resolution and may represent a novel non-invasive alternative. Methods: The HFpEF stress trial (NCT03260621) prospectively included 75 patients with echocardiographic signs of diastolic dysfunction and dyspnoea on exertion (E/E’&gt;8, NYHA≥II) who underwent echocardiography, RHC and RT-CMR at rest and exercise-stress. HFpEF was defined according to pulmonary capillary wedge pressure (PCWP ≥15mmHg at rest or ≥25mmHg during exercise stress). RT-CMR functional assessments included time-volume-curves for total and early (1/3) diastolic left ventricular (LV) filling or left atrial (LA) emptying and LV/LA long axis strain (LAS). Results: HFpEF patients (n=34, mean PCWP rest 13mmHg, stress 27mmHg) had higher E/e’ (12.5 vs 9.15), NT-proBNP (255 vs 75ng/l) and LA volume index (43.8 vs 36.2ml/m 2 ) compared to non-HFpEF patients (n=34, rest 8mmHg, stress 18mmHg, p≤0.001 for all). There were no differences in RT-CMR LV total and early diastolic filling at rest and during exercise-stress (p≥0.164). In contrast, RT-CMR revealed impaired stress LA total (p=0.033) and early (p&lt;0.001) diastolic emptying in HFpEF. LA LAS was the only impaired parameter at rest (p&lt;0.001) and emerged as the best predictor for the presence of HFpEF during exercise-stress testing (AUC rest 0.82 vs stress 0.93, p=0.029). Conclusions: RT-CMR allows highly accurate identification of HFpEF during physiological exercise and may establish itself as a novel non-invasive diagnostic alternative for routine clinical use.

Real-time cardiac magnetic resonance tissue characterisation for fibrosis assessment in aortic stenosis

Abstract Background Myocardial fibrosis is a major determinant of outcome in aortic stenosis (AS). Novel fast real-time (RT) cardiac magnetic resonance (CMR) mapping techniques allow comprehensive quantification of fibrosis but have not yet been adequately validated against standard techniques and histology. Methods Patients with severe AS underwent CMR before (n=110) and left ventricular (LV) endomyocardial biopsy (n=46) at transcatheter aortic valve replacement (TAVR). Midventricular short axis native, post-contrast T1 and extracellular volume fraction (ECV) maps were generated using commercially available 5(3)3 MOLLI and RT single-shot inversion recovery fast low-angle shot (FLASH) with radial undersampling. ECV and LV mass were used to calculate LV matrix volumes. Variability and agreements were assessed between RT, MOLLI and histology using intraclass correlation coefficients, coefficients of variation and Bland Altman analyses. Results RT and MOLLI derived ECV were similar for myocardium (26.2 vs. 26.5, p=0.073) and inter-ventricular septum (26.2 vs. 26.5, p=0.216). MOLLI native T1 time was in median 20 ms longer compared to RT (p&amp;lt;0.001). Agreement between RT and MOLLI was best for ECV (ICC &amp;gt;0.91), excellent for post-contrast T1 times (ICC &amp;gt;0.81) and good for native T1 times (ICC &amp;gt;0.62). Diffuse collagen volume fraction by biopsies was in median 7.8%. ECV (RT r=0.345, p=0.039; MOLLI r=0.40, p=0.010) and LV matrix volumes (RT r=0.45, p=0.005; MOLLI r=0.43, p=0.007) were the only parameters associated with histology. Conclusions RT mapping offers precise T1 and ECV assessments with similar agreement with histology as compared to conventional MOLLI techniques. Single-shot real time techniques may be advantageous in sicker patients prone to dyspnoea or arrhythmia. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): German Research Foundation

Abstract 535: Mathematical Modeling of Hyperpolarized Pyruvate Metabolism in Human Heart

Background: Dissolution dynamic nuclear polarization is a novel method that increases more than 10,000-fold the 13 C signal-to-noise ratio and emerges as a useful tool for detection of molecules much less prevalent than water in the human body. Hyperpolarized [1- 13 C] pyruvate (HP) permits the noninvasive, nonradioactive study of metabolic flux via pyruvate dehydrogenase, a key enzyme in the complex cardiac adaptation to physical activity, energy sources, and in various disease states. The aim of this study is to define an analysis pipeline of multiparametric, non-steady-state, real-time human cardiac magnetic resonance spectroscopic investigations. Methods: HP was infused intravenously into five human subjects. Dynamic spectroscopic data was acquired for [1- 13 C]- pyruvate, 13 C-alanine, [1- 13 C]-lactate, and 13 C-bicarbonate at two consecutive times for each subject. Imaging data were exported into MATLAB. We employed a first-order kinetic model to fit the signal for the hyperpolarized metabolites assuming bidirectional flow between pyruvate and lactate as well as pyruvate and alanine. A gamma variate input function was used to model the initial pyruvate bolus. We also calculated non-parametric values to describe the signal for each metabolite, specifically area-under-curve (AUC) and time-to-peak (TTP). The repeatability analysis was performed using an ANOVA-based method. Results: Rate constants derived from the kinetic model: kPL 0.016 ± 0.008s -1 , kPA 0.012 ± 0.006s -1 , kPB 0.024±0.0095s -1 are of similar order of magnitude to prior studies. The reverse constant for lactate to pyruvate conversion (kLP) is relatively unchanged across the subjects (0.0099±0.0005), and reverse constant for alanine to pyruvate (kAP) conversion is almost negligible (0.0008 ± 0.0012). The model well describes the metabolites signal over time. Within subject repeatability was higher for TTP (lactate: 0.981 ± 0.018) ) than for rate constants (kPL 0.823 ± 0.153) and AUC (lactate 0.697 ± 0.244) with kPB having the lowest repeatability (0.325 ± 0.424) due to a single outlier. Conclusions: We present a real-time pipeline for analysis and modelling of pyruvate metabolism in the human heart and confirm that it is reproducible within the same subject under same conditions.

AUTOMATIC EXTRACTION AND SIGN DETERMINATION OF RESPIRATORY SIGNAL IN REAL-TIME CARDIAC MAGNETIC RESONANCE IMAGING.

In real-time (RT) cardiac cine imaging, a stack of 2D slices is collected sequentially under free-breathing conditions. A complete heartbeat from each slice is then used for cardiac function quantification. The inter-slice respiratory mismatch can compromise accurate quantification of cardiac function. Methods based on principal components analysis (PCA) have been proposed to extract the respiratory signal from RT cardiac cine, but these methods cannot resolve the inter-slice sign ambiguity of the respiratory signal. In this work, we propose a fully automatic sign correction procedure based on the similarity of neighboring slices and correlation to the center-of-mass curve. The proposed method is evaluated in eleven volunteers, with ten slices per volunteer. The motion in a manually selected region-of-interest (ROI) is used as a reference. The results show that the extracted respiratory signal has a high, positive correlation with the reference in all cases. The qualitative assessment of images also shows that the proposed approach can accurately identify heartbeats, one from each slice, belonging to the same respiratory phase. This approach can improve cardiac function quantification for RT cine without manual intervention.

FREE-BREATHING CARDIOVASCULAR MRI USING A PLUG-AND-PLAY METHOD WITH LEARNED DENOISER.

Cardiac magnetic resonance imaging (CMR) is a noninvasive imaging modality that provides a comprehensive evaluation of the cardiovascular system. The clinical utility of CMR is hampered by long acquisition times, however. In this work, we propose and validate a plug-and-play (PnP) method for CMR reconstruction from undersampled multicoil data. To fully exploit the rich image structure inherent in CMR, we pair the PnP framework with a deep learning (DL)-based denoiser that is trained using spatiotemporal patches from high-quality, breath-held cardiac cine images. The resulting "PnP-DL" method iterates over data consistency and denoising subroutines. We compare the reconstruction performance of PnP-DL to that of compressed sensing (CS) using eight breath-held and ten real-time (RT) free-breathing cardiac cine datasets. We find that, for breath-held datasets, PnP-DL offers more than one dB advantage over commonly used CS methods. For RT free-breathing datasets, where ground truth is not available, PnP-DL receives higher scores in qualitative evaluation. The results highlight the potential of PnP-DL to accelerate RT CMR.

MRI Catheterization: Ready for Broad Adoption.

In recent years, interventional cardiac magnetic resonance imaging (iCMR) has evolved from attractive theory to clinical routine at several centers. Real-time cardiac magnetic resonance imaging (CMR fluoroscopy) adds value by combining soft-tissue visualization, concurrent hemodynamic measurement, and freedom from radiation. Clinical iCMR applications are expanding because of advances in catheter devices and imaging. In the near future, iCMR promises novel procedures otherwise unsafe under standalone X-Ray guidance.

Assessment of left ventricle magnetic resonance temperature stability in patients in the presence of arrhythmias.

Magnetic resonance (MR) thermometry allows visualization of lesion formation in real-time during cardiac radiofrequency (RF) ablation. The present study was performed to evaluate the precision of MR thermometry without RF heating in patients exhibiting cardiac arrhythmia in a clinical setting. The evaluation relied on quantification of changes in temperature measurements caused by noise and physiological motion. Fourteen patients referred for cardiovascular magnetic resonance imaging underwent an extra sequence to test the temperature mapping stability during free-breathing acquisition. Phase images were acquired using a multi-slice, cardiac-triggered, single-shot echo planar imaging sequence. Temperature maps were calculated and displayed in real-time while the electrocardiogram (ECG) was recorded. The precision of temperature measurement was assessed by measuring the temporal standard deviation and temporal mean of consecutive temperature maps over a period of three minutes. The cardiac cycle was analyzed from ECG recordings to quantify the impact of arrhythmia events on the precision of temperature measurement. Finally, two retrospective strategies were tested to remove acquisition dynamics related either to arrhythmia events or sudden breathing motion. ECG synchronization allowed categorization of inter-beat intervals (RR) into distinct beat morphologies. Five patients were in stable sinus rhythm, while nine patients showed irregular RR intervals due to ectopic beats. An average temporal standard deviation of temperature of 1.6°C was observed in patients under sinus rhythm with a frame rate corresponding to the heart rate of the patient. The temporal standard deviation rose to 2.5°C in patients with arrhythmia. The retrospective rejection strategies increased the temperature precision measurement while maintaining a sufficient frame rate. Our results indicated that real-time cardiac MR thermometry shows good precision in patients under clinical conditions, even in the presence of arrhythmia. By providing real-time visualization of temperature distribution within the myocardium during RF delivery, MR thermometry could prevent insufficient or excessive heating and thus improve safety and efficacy.

A Deep Learning Segmentation Approach in Free-Breathing Real-Time Cardiac Magnetic Resonance Imaging.

Objectives The purpose of this study was to segment the left ventricle (LV) blood pool, LV myocardium, and right ventricle (RV) blood pool of end-diastole and end-systole frames in free-breathing cardiac magnetic resonance (CMR) imaging. Automatic and accurate segmentation of cardiac structures could reduce the postprocessing time of cardiac function analysis. MethodWe proposed a novel deep learning network using a residual block for the segmentation of the heart and a random data augmentation strategy to reduce the training time and the problem of overfitting. Automated cardiac diagnosis challenge (ACDC) data were used for training, and the free-breathing CMR data were used for validation and testing. Results The average Dice was 0.919 (LV), 0.806 (myocardium), and 0.818 (RV). The average IoU was 0.860 (LV), 0.699 (myocardium), and 0.761 (RV). Conclusions The proposed method may aid in the segmentation of cardiac images and improves the postprocessing efficiency of cardiac function analysis.