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.

Impact of observer experience on multi-detector computed tomography aortic valve morphology assessment and valve size selection for transcatheter aortic valve replacement.

Transcatheter aortic valve replacement (TAVR) has become the standard treatment for aortic stenosis in older patients. It increasingly relies on accurate pre-procedural planning using multidetector computed tomography (MDCT). Since little is known about the required competence levels for MDCT analyses, we comprehensively assessed MDCT TAVR planning reproducibility and accuracy with regard to valve selection in various healthcare workers. 20 randomly selected MDCT of TAVR patients were analyzed using dedicated software by healthcare professionals with varying backgrounds and experience (two structural interventionalists, one imaging specialist, one cardiac surgeon, one general physician, and one medical student). Following the analysis, the most appropriate Edwards SAPIEN 3™ and Medtronic CoreValve valve size was selected. Intra- and inter-observer variability were assessed. The first structural interventionalist was considered as reference standard for inter-observer comparison. Excellent intra- and inter-observer variability was found for the entire group in regard to the MDCT measurements. The best intra-observer agreement and reproducibility were found for the structural interventionalist, while the medical student had the lowest reproducibility. The highest inter-observer agreement was between both structural interventionalists, followed by the imaging specialist. As to valve size selection, the structural interventionalist showed the highest intra-observer reproducibility, independent of the brand of valve used. Compared to the reference structural interventionalist, the second structural interventionalist showed the highest inter-observer agreement for valve size selection [ICC 0.984, 95% CI 0.969-0.991] followed by the cardiac surgeon [ICC 0.947, 95%CI 0.900-0.972]. The lowest inter-observer agreement was found for the medical student [ICC 0.507, 95%CI 0.067-0.739]. While current state-of-the-art MDCT analysis software provides excellent reproducibility for anatomical measurements, the highest levels of confidence in terms of valve size selection were achieved by the performing interventional physicians. This was most likely attributable to observer experience.

Impact of fully automated assessment on interstudy reproducibility of biventricular volumes and function in cardiac magnetic resonance imaging.

Cardiovascular magnetic resonance (CMR) imaging provides reliable assessments of biventricular morphology and function. Since manual post-processing is time-consuming and prone to observer variability, efforts have been directed towards novel artificial intelligence-based fully automated analyses. Hence, we sought to investigate the impact of artificial intelligence-based fully automated assessments on the inter-study variability of biventricular volumes and function. Eighteen participants (11 with normal, 3 with heart failure and preserved and 4 with reduced ejection fraction (EF)) underwent serial CMR imaging at in median 63 days (range 49-87) interval. Short axis cine stacks were acquired for the evaluation of left ventricular (LV) mass, LV and right ventricular (RV) end-diastolic, end-systolic and stroke volumes as well as EF. Assessments were performed manually (QMass, Medis Medical Imaging Systems, Leiden, Netherlands) by an experienced (3 years) and inexperienced reader (no active reporting, 45 min of training with five cases from the SCMR consensus data) as well as fully automated (suiteHEART, Neosoft, Pewaukee, WI, USA) without any manual corrections. Inter-study reproducibility was overall excellent with respect to LV volumetric indices, best for the experienced observer (intraclass correlation coefficient (ICC) > 0.98, coefficient of variation (CoV, < 9.6%) closely followed by automated analyses (ICC > 0.93, CoV < 12.4%) and lowest for the inexperienced observer (ICC > 0.86, CoV < 18.8%). Inter-study reproducibility of RV volumes was excellent for the experienced observer (ICC > 0.88, CoV < 10.7%) but considerably lower for automated and inexperienced manual analyses (ICC > 0.69 and > 0.46, CoV < 22.8% and < 28.7% respectively). In this cohort, fully automated analyses allowed reliable serial investigations of LV volumes with comparable inter-study reproducibility to manual analyses performed by an experienced CMR observer. In contrast, RV automated quantification with current algorithms still relied on manual post-processing for reliability.

Fully Automated Cardiac Assessment for Diagnostic and Prognostic Stratification Following Myocardial Infarction.

Background Cardiovascular magnetic resonance imaging is considered the reference methodology for cardiac morphology and function but requires manual postprocessing. Whether novel artificial intelligence-based automated analyses deliver similar information for risk stratification is unknown. Therefore, this study aimed to investigate feasibility and prognostic implications of artificial intelligence-based, commercially available software analyses. Methods and Results Cardiovascular magnetic resonance data (n=1017 patients) from 2 myocardial infarction multicenter trials were included. Analyses of biventricular parameters including ejection fraction (EF) were manually and automatically assessed using conventional and artificial intelligence-based software. Obtained parameters entered regression analyses for prediction of major adverse cardiac events, defined as death, reinfarction, or congestive heart failure, within 1 year after the acute event. Both manual and uncorrected automated volumetric assessments showed similar impact on outcome in univariate analyses (left ventricular EF, manual: hazard ratio [HR], 0.93 [95% CI 0.91-0.95]; P<0.001; automated: HR, 0.94 [95% CI, 0.92-0.96]; P<0.001) and multivariable analyses (left ventricular EF, manual: HR, 0.95 [95% CI, 0.92-0.98]; P=0.001; automated: HR, 0.95 [95% CI, 0.92-0.98]; P=0.001). Manual correction of the automated contours did not lead to improved risk prediction (left ventricular EF, area under the curve: 0.67 automated versus 0.68 automated corrected; P=0.49). There was acceptable agreement (left ventricular EF: bias, 2.6%; 95% limits of agreement, -9.1% to 14.2%; intraclass correlation coefficient, 0.88 [95% CI, 0.77-0.93]) of manual and automated volumetric assessments. Conclusions User-independent volumetric analyses performed by fully automated software are feasible, and results are equally predictive of major adverse cardiac events compared with conventional analyses in patients following myocardial infarction. Registration URL: https://www.clinicaltrials.gov; Unique identifiers: NCT00712101 and NCT01612312.

Cardiac Magnetic Resonance Myocardial Feature Tracking for Optimized Risk Assessment After Acute Myocardial Infarction in Patients With Type 2 Diabetes.

Type 2 diabetes predicts outcome following acute myocardial infarction (AMI). Since underlying mechanics are incompletely understood, we investigated left ventricular (LV) and left atrial (LA) pathophysiological changes and their prognostic implications using cardiovascular magnetic resonance (CMR). Consecutive patients (N = 1,147; n = 265 with diabetes, n = 882 without diabetes) underwent CMR 3 days after AMI. Analyses included LV ejection fraction (LVEF); global longitudinal strain (GLS) and circumferential and radial strains; LA reservoir, conduit, and booster pump strains; and infarct size, edema, and microvascular obstruction. Predefined end points were major adverse cardiovascular events (MACE) within 12 months. Patients with diabetes had impaired LA reservoir (19.8% vs. 21.2%, P < 0.01) and conduit (7.6% vs. 9.0%, P < 0.01) strains but not ventricular function or myocardial damage. They were at higher risk of MACE than patients without diabetes (10.2% vs. 5.8%, P < 0.01), with most MACE occurring in patients with LVEF ≥35%. While LVEF (P = 0.045) and atrial reservoir strain (P = 0.024) were independent predictors of MACE in patients without diabetes, GLS was in patients with diabetes (P = 0.010). Considering patients with diabetes and LVEF ≥35% (n = 237), GLS and LA reservoir strain below median were significantly associated with MACE. In conclusion, in patients with diabetes, LA and LV longitudinal strain permit optimized risk assessment early after reperfused AMI with incremental prognostic value over and above that of LVEF.

Cardiac Magnetic Resonance Left Ventricular Mechanical Uniformity Alterations for Risk Assessment After Acute Myocardial Infarction.

Background Despite limitations as a stand-alone parameter, left ventricular (LV) ejection fraction is the preferred measure of myocardial function and marker for postinfarction risk stratification. LV myocardial uniformity alterations may provide superior prognostic information after acute myocardial infarction, which was the subject of this study. Methods and Results Consecutive patients with acute myocardial infarction (n=1082; median age: 63 years; 75% male) undergoing cardiac magnetic resonance at a median of 3 days after infarction were included in this multicenter observational study. Circumferential and radial uniformity ratio estimates were derived from cardiac magnetic resonance feature tracking as markers of mechanical uniformity alterations (values between 0 and 1 with 1 reflecting perfect uniformity). The clinical end point was the 12-month rate of major adverse cardiac events, consisting of all-cause death, reinfarction, and new congestive heart failure. Patients with major adverse cardiac events (n=73) had significantly impaired circumferential uniformity ratio estimates (0.76 [interquartile range: 0.67-0.86] versus 0.84 [interquartile range: 0.76-0.89]; P<0.001) and radial uniformity ratio estimates (0.69 [interquartile range: 0.60-0.79] versus 0.76 [interquartile range: 0.67-0.83]; P<0.001) compared with patients without events. Although uniformity estimates did not provide independent prognostic information in the overall cohort, a circumferential uniformity ratio estimate below the median of 0.84 emerged as an independent predictor of outcome in postinfarction patients with LV ejection fraction >35% (n=959), even after adjustment for established risk factors (hazard ratio: 1.99; 95% CI, 1.06-3.74; P=0.033 in multivariable Cox regression analysis). In contrast, LV ejection fraction was not associated with adverse events in this subgroup of patients with acute myocardial infarction. Conclusions Cardiac magnetic resonance-derived estimates of mechanical uniformity alterations are novel markers for risk assessment after acute myocardial infarction, and the circumferential uniformity ratio estimate provides independent prognostic information for patients with preserved or only moderately reduced LV ejection fraction.

Fast manual long-axis strain assessment provides optimized cardiovascular event prediction following myocardial infarction.

AIMS: Cardiovascular magnetic resonance feature tracking (CMR-FT) global longitudinal strain (GLS) provides incremental prognostic value following acute myocardial infarction (AMI) but requires substantial post-processing. Alternatively, manual global long-axis strain (LAS) can be easily assessed from standard steady state free precession images. We aimed to define the prognostic value of LAS in a large multicentre study in patients following AMI. METHODS AND RESULTS: A total of 1235 patients with myocardial infarction [n = 795 with ST-elevation myocardial infarction (STEMI) and 440 with non-ST-elevation myocardial infarction (NSTEMI)] underwent cardiovascular magnetic resonance imaging after primary percutaneous coronary intervention in eight centres across Germany. Assessment of LAS was performed in a blinded core-laboratory measuring the systolic shortening between the epicardial apical border and the middle of a line connecting the origins of the mitral leaflets. Primary clinical endpoint was the occurrence of major adverse clinical events (MACE) including death, reinfarction, and congestive heart failure within 1 year after AMI. During 1-year follow-up, 76 patients suffered from MACE. Impaired LAS was associated with higher MACE occurrence both in STEMI (P < 0.001) and NSTEMI (P = 0.001) patients. Association of LAS remained significant (P = 0.017) after correction for univariate significant parameters for MACE prediction. C-statistics revealed incremental value of additional LAS assessment for optimized event prediction compared with left ventricular ejection fraction (MACE P = 0.044; mortality P = 0.013) and a combination of established clinical and imaging parameters (MACE P = 0.084; mortality P = 0.027), but not CMR-FT GLS (MACE P = 0.075; mortality P = 0.380). CONCLUSION: LAS provides software independent, widely available, easy and fast approximation of longitudinal left ventricular shortening early after reperfused AMI with incremental prognostic value beyond established risk stratification parameters. CLINICAL TRIALS.GOV: NCT00712101 and NCT01612312.

Right ventricular strain assessment by cardiovascular magnetic resonance myocardial feature tracking allows optimized risk stratification in Takotsubo syndrome.

BACKGROUND: A substantial number of patients with Takotsubo syndrome (TTS) exhibit right ventricular (RV) dysfunction which has been associated with adverse outcome. The aim of this study was to assess the clinical and prognostic value of RV myocardial strain in TTS using cardiovascular magnetic resonance myocardial feature tracking (CMR-FT). METHODS: CMR-FT was performed in a core laboratory to determine RV longitudinal strain in 134 TTS patients undergoing CMR in median 2 days after admission to 2 experienced centers. For comparison, RV involvement was evaluated by sole visual assessment concerning RV contraction abnormalities. Both approaches were analyzed regarding their long-term prognostic value. RESULTS: The peak global RV longitudinal strain was in median -19%. Segmental analyses located contraction abnormalities primarily in the apical parts of the right ventricle. Sole visual assessment identified 38 patients (28%) with RV involvement. These patients showed a numerically higher long-term mortality without reaching statistical significance (17.1% versus 10.5%; hazard ratio 1.38 [95% confidence interval 0.49-3.88]; p = 0.31). The optimal RV strain cutoff value for risk prediction was -17.24%. Stratification according to this threshold categorized 41% of TTS patients (n = 55) in the high-risk group which demonstrated a significantly increased long-term mortality compared to patients with preserved global RV strain (20.0% versus 7.0%; hazard ratio 2.98 [95% confidence interval 1.02-8.73]; p = 0.03). CONCLUSIONS: The assessment of RV myocardial strain using CMR-FT enables an accurate evaluation of RV involvement in TTS and represents a promising approach for optimized risk stratification.

Quantitative assessment of left ventricular mechanical dyssynchrony using cine cardiovascular magnetic resonance imaging: Inter-study reproducibility.

OBJECTIVES: To determine the inter-study reproducibility of left ventricular (LV) mechanical dyssynchrony measures based on standard cardiovascular magnetic resonance (CMR) cine images. DESIGN: Steady-state free precession (SSFP) LV short-axis stacks and three long-axes were acquired on the same day at three time points. Circumferential strain systolic dyssynchrony indexes (SDI), area-SDI as well as circumferential and radial uniformity ratio estimates (CURE and RURE, respectively) were derived from CMR myocardial feature-tracking (CMR-FT) based on the tracking of three SSFP short-axis planes. Furthermore, 4D-LV-analysis based on SSFP short-axis stacks and longitudinal planes was performed to quantify 4D-volume-SDI. SETTING: A single-centre London teaching hospital. PARTICIPANTS: 16 healthy volunteers. MAIN OUTCOME MEASURES: Inter-study reproducibility between the repeated exams. RESULTS: CURE and RURE as well as 4D-volume-SDI showed good inter-study reproducibility (coefficient of variation [CoV] 6.4%-12.9%). Circumferential strain and area-SDI showed higher variability between the repeated measurements (CoV 24.9%-37.5%). Uniformity ratio estimates showed the lowest inter-study variability (CoV 6.4%-8.5%). CONCLUSIONS: Derivation of LV mechanical dyssynchrony measures from standard cine images is feasible using CMR-FT and 4D-LV-analysis tools. Uniformity ratio estimates and 4D-volume-SDI showed good inter-study reproducibility. Their clinical value should next be explored in patients who potentially benefit from cardiac resynchronization therapy.

Incidental findings in cardiac magnetic resonance imaging: superiority of bSSFP over T1w-HASTE for extra-cardiac findings assessment.

Incidental findings are frequent in radiological examinations and may have an impact on further patient management. The aim of this retrospective study was to analyze, which of two thoracic scout sequences is more suitable for detecting incidental extra-cardiac findings at cardiac magnetic resonance imaging (CMRI) with stress perfusion. During a 14-month period clinically indicated stress perfusion CMRI was performed in 97 consecutive patients. For anatomical orientation ECG-triggered (electrocardiography) T1w-Half-fourier acquisition single-shot turbo spin-echo (HASTE) and balanced steady state free precession (bSSFP) sequences were performed for planning the standard cardiac sequences. Two radiologists independently studied incidental extra-cardiac findings with both sequences and rated the diagnostic confidence of the sequences for this assessment using a multinomial model. Furthermore, the interobserver agreement between the observers was assessed by weighted kappa statistics. Eight patients without incidental findings were excluded. In the other 89 patients a total of 153 incidental extra-cardiac findings were observed. Overall, 47.1% of findings were seen with better diagnostic confidence at bSSFP as opposed to 20.6% at T1w-HASTE. 32.4% of findings were equally well seen with both sequences. Consequently the bSSFP sequence was significantly better in terms of diagnostic confidence for detecting the majority of extra-cardiac incidental findings (P < 0.01), whereas a minority of findings was better visible by the HASTE sequence. The weighted kappa statistics was 0.85, indicating good interobserver agreement. Compared with T1w-HASTE, the bSSFP sequence improved the visibility of incidental extra-cardiac findings at stress perfusion CMRI. While all findings were seen on both sequences, bSSFP resulted in improved diagnostic confidence, and the T1w-HASTE sequence provided complementary diagnostic information in only a minority of patients.