Multimodality imaging for the evaluation and management of patients with long-term (durable) left ventricular assist devices A Clinical Consensus Statement of the European Association of Cardiovascular Imaging (EACVI) of the ESC.

Left ventricular assist devices (LVADs) are gaining increasing importance as therapeutic strategy in advanced heart failure (HF), not only as bridge to recovery or to transplant, but also as destination therapy. Even though long-term LVADs are considered a precious resource to expand the treatment options and improve clinical outcome these patients, these are limited by peri-operative and post-operative complications, such as device-related infections, haemocompatibility-related events, device mispositioning and right ventricular failure. For this reason, a precise pre-operative, peri-operative and post-operative evaluation of these patients is crucial for the selection of LVADs candidates and the management LVADs recipients. The use of different imaging modalities offers important information to complete the study of patients with LVADs in each phase of their assessment, with peculiar advantages/disadvantages, ideal application and reference parameters for each modality. This clinical consensus statement sought to guide the use of multimodality imaging for the evaluation of patients with advanced HF undergoing LVADs implantation.

Development and validation of AI-derived segmentation of four-chamber cine cardiac magnetic resonance.

BACKGROUND: Cardiac magnetic resonance (CMR) in the four-chamber plane offers comprehensive insight into the volumetrics of the heart. We aimed to develop an artificial intelligence (AI) model of time-resolved segmentation using the four-chamber cine. METHODS: A fully automated deep learning algorithm was trained using retrospective multicentre and multivendor data of 814 subjects. Validation, reproducibility, and mortality prediction were evaluated on an independent cohort of 101 subjects. RESULTS: The mean age of the validation cohort was 54 years, and 66 (65%) were males. Left and right heart parameters demonstrated strong correlations between automated and manual analysis, with a ρ of 0.91-0.98 and 0.89-0.98, respectively, with minimal bias. All AI four-chamber volumetrics in repeatability analysis demonstrated high correlation (ρ = 0.99-1.00) and no bias. Automated four-chamber analysis underestimated both left ventricular (LV) and right ventricular (RV) volumes compared to ground-truth short-axis cine analysis. Two correction factors for LV and RV four-chamber analysis were proposed based on systematic bias. After applying the correction factors, a strong correlation and minimal bias for LV volumetrics were observed. During a mean follow-up period of 6.75 years, 16 patients died. On stepwise multivariable analysis, left atrial ejection fraction demonstrated an independent association with death in both manual (hazard ratio (HR) = 0.96, p = 0.003) and AI analyses (HR = 0.96, p < 0.001). CONCLUSION: Fully automated four-chamber CMR is feasible, reproducible, and has the same real-world prognostic value as manual analysis. LV volumes by four-chamber segmentation were comparable to short-axis volumetric assessment. TRIALS REGISTRATION: ClinicalTrials.gov: NCT05114785. RELEVANCE STATEMENT: Integrating fully automated AI in CMR promises to revolutionise clinical cardiac assessment, offering efficient, accurate, and prognostically valuable insights for improved patient care and outcomes. KEY POINTS: • Four-chamber cine sequences remain one of the most informative acquisitions in CMR examination. • This deep learning-based, time-resolved, fully automated four-chamber volumetric, functional, and deformation analysis solution. • LV and RV were underestimated by four-chamber analysis compared to ground truth short-axis segmentation. • Correction bias for both LV and RV volumes by four-chamber segmentation, minimises the systematic bias.

CMR characterization of patients with heart failure and left bundle branch block.

Aims: We aimed to identify the distinctive cardiovascular magnetic resonance (CMR) features of patients with left bundle branch block (LBBB) and heart failure with reduced ejection fraction (HFrEF) of presumed non-ischaemic aetiology. The secondary aim was to determine whether these individuals exhibit characteristics that could potentially serve as predictors of left ventricular ejection fraction (LVEF) recovery as compared with patients without LBBB. Methods and results: We prospectively recruited patients with HFrEF (LVEF ≤ 40%) on echocardiography who were referred for early CMR examination. Patients with an established diagnosis of coronary artery disease and known structural or congenital heart disease were excluded. LV recovery was defined as achieving ≥10% absolute improvement to ≥40% in LVEF between baseline evaluation to CMR. A total of 391 patients were recruited including 115 (29.4%) with LBBB. Compared with HF patients without LBBB, those with LBBB exhibited larger left ventricles and smaller right ventricles, but no differences were observed with respect to LVEF (35.8 ± 12 vs. 38 ± 12%, P = 0.105). The overall rate of LV recovery from baseline echocardiogram to CMR (70 [42-128] days) was not significantly different between LBBB and non-LBBB patients (27.8% vs. 31.5%, P = 0.47). Reduced LVEF remained an independent predictor of LV non-recovery only in patients with LBBB. Conclusion: Patients presenting with HFrEF and LBBB had larger LV cavities and smaller RV cavities than those without LBBB but no difference in prevalence of scar or ischaemia. The rates of LV recovery were similar between both groups, which supports current guidelines to defer device therapy until 3-6 months of guideline-directed medical therapy, rather than early CMR and device implantation.

Pulmonary transit time is a predictor of outcomes in heart failure: a cardiovascular magnetic resonance first-pass perfusion study.

BACKGROUND: Pulmonary transit time (PTT) can be measured automatically from arterial input function (AIF) images of dual sequence first-pass perfusion imaging. PTT has been validated against invasive cardiac catheterisation correlating with both cardiac output and left ventricular filling pressure (both important prognostic markers in heart failure). We hypothesized that prolonged PTT is associated with clinical outcomes in patients with heart failure. METHODS: We recruited outpatients with a recent diagnosis of non-ischaemic heart failure with left ventricular ejection fraction (LVEF) < 50% on referral echocardiogram. Patients were followed up by a review of medical records for major adverse cardiovascular events (MACE) defined as all-cause mortality, heart failure hospitalization, ventricular arrhythmia, stroke or myocardial infarction. PTT was measured automatically from low-resolution AIF dynamic series of both the LV and RV during rest perfusion imaging, and the PTT was measured as the time (in seconds) between the centroid of the left (LV) and right ventricle (RV) indicator dilution curves. RESULTS: Patients (N = 294) were followed-up for median 2.0 years during which 37 patients (12.6%) had at least one MACE event. On univariate Cox regression analysis there was a significant association between PTT and MACE (Hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.08-1.25, P = 0.0001). There was also significant association between PTT and heart failure hospitalisation (HR 1.15, 95% CI 1.02-1.29, P = 0.02) and moderate correlation between PTT and N-terminal pro B-type natriuretic peptide (NT-proBNP, r = 0.51, P < 0.001). PTT remained predictive of MACE after adjustment for clinical and imaging factors but was no longer significant once adjusted for NT-proBNP. CONCLUSIONS: PTT measured automatically during CMR perfusion imaging in patients with recent onset non-ischaemic heart failure is predictive of MACE and in particular heart failure hospitalisation. PTT derived in this way may be a non-invasive marker of haemodynamic congestion in heart failure and future studies are required to establish if prolonged PTT identifies those who may warrant closer follow-up or medicine optimisation to reduce the risk of future adverse events.

Mitral regurgitation assessment by cardiovascular magnetic resonance imaging during continuous in-scanner exercise: a feasibility study.

PURPOSE: Exercise imaging using current modalities can be challenging. This was patient focused study to establish the feasibility and reproducibility of exercise-cardiovascular magnetic resonance imaging (EX-CMR) acquired during continuous in-scanner exercise in asymptomatic patients with primary mitral regurgitation (MR). METHODS: This was a prospective, feasibility study. Biventricular volumes/function, aortic flow volume, MR volume (MR-Rvol) and regurgitant fraction (MR-RF) were assessed at rest and during low- (Low-EX) and moderate-intensity exercise (Mod-EX) in asymptomatic patients with primary MR. RESULTS: Twenty-five patients completed EX-CMR without complications. Whilst there were no significant changes in the left ventricular (LV) volumes, there was a significant increase in the LVEF (rest 63 ± 5% vs. Mod-EX 68 ± 6%;p = 0.01). There was a significant reduction in the right ventricular (RV) end-systolic volume (rest 68 ml(60-75) vs. Mod-EX 46 ml(39-59);p < 0.001) and a significant increase in the RV ejection fraction (rest 55 ± 5% vs. Mod-EX 65 ± 8%;p < 0.001). Whilst overall, there were no significant group changes in the MR-Rvol and MR-RF, individual responses were variable, with MR-Rvol increasing by ≥ 15 ml in 4(16%) patients and decreasing by ≥ 15 ml in 9(36%) of patients. The intra- and inter-observer reproducibility of LV volumes and aortic flow measurements were excellent, including at Mod-EX. CONCLUSION: EX-CMR is feasible and reproducible in patients with primary MR. During exercise, there is an increase in the LV and RV ejection fraction, reduction in the RV end-systolic volume and a variable response of MR-Rvol and MR-RF. Understanding the individual variability in MR-Rvol and MR-RF during physiological exercise may be clinically important.

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology.

Recent genome-wide association studies have successfully identified associations between genetic variants and simple cardiac morphological parameters derived from cardiac magnetic resonance images. However, the emergence of large databases, including genetic data linked to cardiac magnetic resonance facilitates the investigation of more nuanced patterns of cardiac shape variability than those studied so far. Here we propose a framework for gene discovery coined unsupervised phenotype ensembles. The unsupervised phenotype ensemble builds a redundant yet highly expressive representation by pooling a set of phenotypes learnt in an unsupervised manner, using deep learning models trained with different hyperparameters. These phenotypes are then analysed via genome-wide association studies, retaining only highly confident and stable associations across the ensemble. We applied our approach to the UK Biobank database to extract geometric features of the left ventricle from image-derived three-dimensional meshes. We demonstrate that our approach greatly improves the discoverability of genes that influence left ventricle shape, identifying 49 loci with study-wide significance and 25 with suggestive significance. We argue that our approach would enable more extensive discovery of gene associations with image-derived phenotypes for other organs or image modalities.

Role of epicardial adipose tissue in diabetic cardiomyopathy through the lens of cardiovascular magnetic resonance imaging - a narrative review.

Accumulating evidence suggests that ectopic/visceral adiposity may play a key role in the pathogenesis of nonischaemic cardiovascular diseases associated with type 2 diabetes. Epicardial adipose tissue (EAT) is a complex visceral fat depot, covering 80% of the cardiac surface with anatomical and functional contiguity to the myocardium and coronary arteries. EAT interacts with the biology of the underlying myocardium by secreting a wide range of adipokines. Magnetic resonance imaging (MRI) is the reference modality for structural and functional imaging of the heart. The technique is now also emerging as the reference imaging modality for EAT quantification. With this narrative review, we (a) surveyed contemporary clinical studies that utilized cardiovascular MRI to characterize EAT (studies published 2010-2023); (b) listed the clinical trials monitoring the response to treatment in EAT size as well as myocardial functional and structural parameters and (c) discussed the potential pathophysiological role of EAT in the development of diabetic cardiomyopathy. We concluded that increased EAT quantity and its inflammatory phenotype correlate with early signs of left ventricle dysfunction and may have a role in the pathogenesis of cardiac disease in diabetes with and without coronary artery disease.

Early signs of myocardial systolic dysfunction in patients with type 2 diabetes are strongly associated with myocardial microvascular dysfunction independent of myocardial fibrosis: a prospective cohort study.

BACKGROUND: Patients with diabetes demonstrate early left ventricular systolic dysfunction. Notably reduced global longitudinal strain (GLS) is related to poor outcomes, the underlying pathophysiology is however still not clearly understood. We hypothesized that pathophysiologic changes with microvascular dysfunction and interstitial fibrosis contribute to reduced strain. METHODS: 211 patients with type 2 diabetes and 25 control subjects underwent comprehensive cardiovascular phenotyping by magnetic resonance imaging. Myocardial blood flow (MBF), perfusion reserve (MPR), extracellular volume (ECV), and 3D feature tracking GLS and global circumferential (GCS) and radial strain (GRS) were quantified. RESULTS: Patients (median age 57 [IQR 50, 67] years, 70% males) had a median diabetes duration of 12 [IQR 6, 18] years. Compared to control subjects GLS, GCS, and GRS were reduced in the total diabetes cohort, and GLS was also reduced in the sub-group of patients without diabetic complications compared to control subjects (controls - 13.9 ± 2.0%, total cohort - 11.6 ± 3.0%; subgroup - 12.3 ± 2.6%, all p < 0.05). Reduced GLS, but not GCS or GRS, was associated with classic diabetes complications of albuminuria (UACR ≥ 30 mg/g) [ß (95% CI) 1.09 (0.22-1.96)] and autonomic neuropathy [ß (95% CI) 1.43 (0.54-2.31)] but GLS was not associated with retinopathy or peripheral neuropathy. Independently of ECV, a 10% increase in MBF at stress and MPR was associated with higher GLS [multivariable regression adjusted for age, sex, hypertension, smoking, and ECV: MBF stress (ß (95% CI) - 0.2 (- 0.3 to - 0.08), MPR (ß (95% CI) - 0.5 (- 0.8 to - 0.3), p < 0.001 for both]. A 10% increase in ECV was associated with a decrease in GLS in univariable [ß (95% CI) 0.6 (0.2 to 1.1)] and multivariable regression, but this was abolished when adjusted for MPR [multivariable regression adjusted for age, sex, hypertension, smoking, and MPR (ß (95% CI) 0.1 (- 0.3 to 0.6)]. On the receiver operating characteristics curve, GLS showed a moderate ability to discriminate a significantly lowered stress MBF (AUC 0.72) and MPR (AUC 0.73). CONCLUSIONS: Myocardial microvascular dysfunction was independent of ECV, a biomarker of myocardial fibrosis, associated with GLS. Further, 3D GLS could be a potential screening tool for myocardial microvascular dysfunction. Future directions should focus on confirming these results in longitudinal and/or interventional studies.

4D Flow Cardiac MR in Primary Mitral Regurgitation.

BACKGROUND: Four-dimensional-flow cardiac MR (4DF-MR) offers advantages in primary mitral regurgitation. The relationship between 4DF-MR-derived mitral regurgitant volume (MR-Rvol) and the post-operative left ventricular (LV) reverse remodeling has not yet been established. PURPOSE: To ascertain if the 4DF-MR-derived MR-Rvol correlates with the LV reverse remodeling in primary mitral regurgitation. STUDY TYPE: Prospective, single-center, two arm, interventional vs. nonintervention observational study. POPULATION: Forty-four patients (male N = 30; median age 68 [59-75]) with at least moderate primary mitral regurgitation; either awaiting mitral valve surgery (repair [MVr], replacement [MVR]) or undergoing "watchful waiting" (WW). FIELD STRENGTH/SEQUENCE: 5 T/Balanced steady-state free precession (bSSFP) sequence/Phase contrast imaging/Multishot echo-planar imaging pulse sequence (five shots). ASSESSMENT: Patients underwent transthoracic echocardiography (TTE), phase-contrast MR (PMRI), 4DF-MR and 6-minute walk test (6MWT) at baseline, and a follow-up PMRI and 6MWT at 6 months. MR-Rvol was quantified by PMRI, 4DF-MR, and TTE by one observer. The pre-operative MR-Rvol was correlated with the post-operative decrease in the LV end-diastolic volume index (LVEDVi). STATISTICAL TESTS: Included Student t-test/Mann-Whitney test/Fisher's exact test, Bland-Altman plots, linear regression analysis and receiver operating characteristic curves. Statistical significance was defined as P < 0.05. RESULTS: While Bland-Altman plots demonstrated similar bias between all the modalities, the limits of agreement were narrower between 4DF-MR and PMRI (bias 15; limits of agreement -36 mL to 65 mL), than between 4DF-MR and TTE (bias -8; limits of agreement -106 mL to 90 mL) and PMRI and TTE (bias -23; limits of agreement -105 mL to 59 mL). Linear regression analysis demonstrated a significant association between the MR-Rvol and the post-operative decrease in the LVEDVi, when the MR-Rvol was quantified by PMRI and 4DF-MR, but not by TTE (P = 0.73). 4DF-MR demonstrated the best diagnostic performance for reduction in the post-operative LVEDVi with the largest area under the curve (4DF-MR 0.83; vs. PMRI 0.78; and TTE 0.51; P = 0.89). DATA CONCLUSION: This study demonstrates the potential clinical utility of 4DF-MR in the assessment of primary mitral regurgitation. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 5.

High Prevalence of New Clinically Significant Findings in Patients With Embolic Stroke of Unknown Source Evaluated by Cardiac Magnetic Resonance Imaging.

BACKGROUND: Embolic stroke of unknown source (ESUS) accounts for 1 in 6 ischemic strokes. Current guidelines do not recommend routine cardiac magnetic resonance (CMR) imaging in ESUS, and beyond the identification of cardioembolic sources, there are no data assessing new clinical findings from CMR in ESUS. This study aimed to assess the prevalence of new cardiac and noncardiac findings and to determine their impact on clinical care in patients with ESUS. METHODS AND RESULTS: In this prospective, multicenter, observational study, CMR imaging was performed within 3 months of ESUS. All scans were reported according to standard clinical practice. A new clinical finding was defined as one not previously identified through prior clinical evaluation. A clinically significant finding was defined as one resulting in further investigation, follow-up, or treatment. A change in patient care was defined as initiation of medical, interventional, surgical, or palliative care. From 102 patients recruited, 96 underwent CMR imaging. One or more new clinical findings were observed in 59 patients (61%). New findings were clinically significant in 48 (81%) of these patients. Of 40 patients with a new clinically significant cardiac finding, 21 (53%) experienced a change in care (medical therapy, n=15; interventional/surgical procedure, n=6). In 12 patients with a new clinically significant extracardiac finding, 6 (50%) experienced a change in care (medical therapy, n=4; palliative care, n=2). CONCLUSIONS: CMR imaging identifies new clinically significant cardiac and noncardiac findings in half of patients with recent ESUS. Advanced cardiovascular screening should be considered in patients with ESUS. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04555538.

Echocardiography versus Cardiac MRI for Measurement of Left Ventricular Ejection Fraction in Individuals with Cancer and Suspected Cardiotoxicity.

Purpose To compare left ventricular ejection fraction (LVEF) measured with echocardiography and cardiac MRI in individuals with cancer and suspected cardiotoxicity and assess the potential effect on downstream clinical decision-making. Materials and Methods In this prospective, single-center observational cohort study, participants underwent same-day two-dimensional (2D) echocardiography and cardiac MRI between 2011 and 2021. Participants with suboptimal image quality were excluded. A subset of 74 participants also underwent three-dimensional (3D) echocardiography. The agreement of LVEF derived from each modality was assessed using Bland-Altman analysis and at relevant thresholds for cardiotoxicity. Results A total of 745 participants (mean age, 60 years ± 5 [SD]; 460 [61.7%] female participants) underwent same-day echocardiography and cardiac MRI. According to Bland-Altman analysis, the mean bias was -3.7% ± 7.6 (95% limits of agreement [LOA]: -18.5% to 11.1%) for 2D echocardiography versus cardiac MRI. In 74 participants who underwent cardiac MRI, 3D echocardiography, and 2D echocardiography, the mean LVEFs were 60.0% ± 10.4, 58.4% ± 9.4, and 57.2% ± 8.9, respectively (P < .001). At the 50% LVEF threshold for detection of cardiotoxicity, there was disagreement for 9.3% of participants with 2D echocardiography and cardiac MRI. Agreement was better with 3D echocardiography and cardiac MRI (mean bias, -1.6% ± 6.3 [95% LOA: -13.9% to 10.7%]) compared with 2D echocardiography and cardiac MRI (mean bias, -2.8% ± 6.3 [95% LOA: -15.2% to 9.6%]; P = .016). Conclusion Two-dimensional echocardiography had variations of ±15% for LVEF measurement compared with cardiac MRI in participants with cancer and led to misclassification of approximately 10% of participants for cardiotoxicity detection. Three-dimensional echocardiography had better agreement with cardiac MRI and should be used as first-line imaging. Keywords: Echocardiography, MR Functional Imaging, Cardiac Supplemental material is available for this article. © RSNA, 2024.

Deep learning based automated left ventricle segmentation and flow quantification in 4D flow cardiac MRI.

BACKGROUND: 4D flow MRI enables assessment of cardiac function and intra-cardiac blood flow dynamics from a single acquisition. However, due to the poor contrast between the chambers and surrounding tissue, quantitative analysis relies on the segmentation derived from a registered cine MRI acquisition. This requires an additional acquisition and is prone to imperfect spatial and temporal inter-scan alignment. Therefore, in this work we developed and evaluated deep learning-based methods to segment the left ventricle (LV) from 4D flow MRI directly. METHODS: We compared five deep learning-based approaches with different network structures, data pre-processing and feature fusion methods. For the data pre-processing, the 4D flow MRI data was reformatted into a stack of short-axis view slices. Two feature fusion approaches were proposed to integrate the features from magnitude and velocity images. The networks were trained and evaluated on an in-house dataset of 101 subjects with 67,567 2D images and 3030 3D volumes. The performance was evaluated using various metrics including Dice, average surface distance (ASD), end-diastolic volume (EDV), end-systolic volume (ESV), LV ejection fraction (LVEF), LV blood flow kinetic energy (KE) and LV flow components. The Monte Carlo dropout method was used to assess the confidence and to describe the uncertainty area in the segmentation results. RESULTS: Among the five models, the model combining 2D U-Net with late fusion method operating on short-axis reformatted 4D flow volumes achieved the best results with Dice of 84.52% and ASD of 3.14 mm. The best averaged absolute and relative error between manual and automated segmentation for EDV, ESV, LVEF and KE was 19.93 ml (10.39%), 17.38 ml (22.22%), 7.37% (13.93%) and 0.07 mJ (5.61%), respectively. Flow component results derived from automated segmentation showed high correlation and small average error compared to results derived from manual segmentation. CONCLUSIONS: Deep learning-based methods can achieve accurate automated LV segmentation and subsequent quantification of volumetric and hemodynamic LV parameters from 4D flow MRI without requiring an additional cine MRI acquisition.

Competency based curriculum for cardiovascular magnetic resonance: A position statement of the Society for Cardiovascular Magnetic Resonance.

This position statement guides cardiovascular magnetic resonance (CMR) imaging program directors and learners on the key competencies required for Level II and III CMR practitioners, whether trainees come from a radiology or cardiology background. This document is built upon existing curricula and was created and vetted by an international panel of cardiologists and radiologists on behalf of the Society for Cardiovascular Magnetic Resonance (SCMR).

High-resolution quantification of stress perfusion defects by cardiac magnetic resonance.

Aims: Quantitative stress perfusion cardiac magnetic resonance (CMR) is becoming more widely available, but it is still unclear how to integrate this information into clinical decision-making. Typically, pixel-wise perfusion maps are generated, but diagnostic and prognostic studies have summarized perfusion as just one value per patient or in 16 myocardial segments. In this study, the reporting of quantitative perfusion maps is extended from the standard 16 segments to a high-resolution bullseye. Cut-off thresholds are established for the high-resolution bullseye, and the identified perfusion defects are compared with visual assessment. Methods and results: Thirty-four patients with known or suspected coronary artery disease were retrospectively analysed. Visual perfusion defects were contoured on the CMR images and pixel-wise quantitative perfusion maps were generated. Cut-off values were established on the high-resolution bullseye consisting of 1800 points and compared with the per-segment, per-coronary, and per-patient resolution thresholds. Quantitative stress perfusion was significantly lower in visually abnormal pixels, 1.11 (0.75-1.57) vs. 2.35 (1.82-2.9) mL/min/g (Mann-Whitney U test P < 0.001), with an optimal cut-off of 1.72 mL/min/g. This was lower than the segment-wise optimal threshold of 1.92 mL/min/g. The Bland-Altman analysis showed that visual assessment underestimated large perfusion defects compared with the quantification with good agreement for smaller defect burdens. A Dice overlap of 0.68 (0.57-0.78) was found. Conclusion: This study introduces a high-resolution bullseye consisting of 1800 points, rather than 16, per patient for reporting quantitative stress perfusion, which may improve sensitivity. Using this representation, the threshold required to identify areas of reduced perfusion is lower than for segmental analysis.

Myocardial Blood Flow Determination From Contrast-Free Magnetic Resonance Imaging Quantification of Coronary Sinus Flow.

BACKGROUND: Determination of myocardial blood flow (MBF) with MRI is usually performed with dynamic contrast enhanced imaging (MBFDCE ). MBF can also be determined from coronary sinus blood flow (MBFCS ), which has the advantage of being a noncontrast technique. However, comparative studies of MBFDCE and MBFCS in large cohorts are lacking. PURPOSE: To compare MBFCS and MBFDCE in a large cohort. STUDY TYPE: Prospective, sequence-comparison study. POPULATION: 147 patients with type 2 diabetes mellitus (age: 56+/-12 years; 106 male; diabetes duration: 12.9+/-8.1 years), and 25 age-matched controls. FIELD STRENGTH/SEQUENCES: 1.5 Tesla scanner. Saturation recovery sequence for MBFDCE vs. phase-contrast gradient-echo pulse sequence (free-breathing) for MBFCS . ASSESSMENT: MBFDCE and MBFCS were determined at rest and during coronary dilatation achieved by administration of adenosine at 140 µg/kg/min. Myocardial perfusion reserve (MPR) was calculated as the stress/rest ratio of MBF values. Coronary sinus flow was determined twice in the same imaging session for repeatability assessment. STATISTICAL TESTS: Agreement between MBFDCE and MBFCS was assessed with Bland and Altman's technique. Repeatability was determined from single-rater random intraclass and repeatability coefficients. RESULTS: Rest and stress flows, including both MBFDCE and MBFCS values, ranged from 33 to 146 mL/min/100 g and 92 to 501 mL/min/100 g, respectively. Intraclass and repeatability coefficients for MBFCS were 0.95 (CI 0.90; 0.95) and 5 mL/min/100 g. In Bland-Altman analysis, mean bias at rest was -1.1 mL/min/100 g (CI -3.1; 0.9) with limits of agreement of -27 and 24.8 mL/min/100 g. Mean bias at stress was 6.3 mL/min/100 g (CI -1.1; 14.1) with limits of agreement of -86.9 and 99.9. Mean bias of MPR was 0.11 (CI: -0.02; 0.23) with limits of agreement of -1.43 and 1.64. CONCLUSION: MBF may be determined from coronary sinus blood flow, with acceptable bias, but relatively large limits of agreement, against the reference of MBFDCE . LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

The impact of water exchange on estimates of myocardial extracellular volume calculated using contrast enhanced T1 measurements: A preliminary analysis in patients with severe aortic stenosis.

PURPOSE: Guidelines recommend measuring myocardial extracellular volume (ECV) using T1 -mapping before and 10-30 min after contrast agent administration. Data are then analyzed using a linear model (LM), which assumes fast water exchange (WX) between the ECV and cardiomyocytes. We investigated whether limited WX influences ECV measurements in patients with severe aortic stenosis (AS). METHODS: Twenty-five patients with severe AS and 5 healthy controls were recruited. T1 measurements were made on a 3 T Siemens system using a multiparametric saturation-recovery single-shot acquisition (a) before contrast; (b) 4 min post 0.05 mmol/kg gadobutrol; and (c) 4 min, (d) 10 min, and (e) 30 min after an additional gadobutrol dose (0.1 mmol/kg). Three LM-based ECV estimates, made using paired T1 measurements (a and b), (a and d), and (a and e), were compared to ECV estimates made using all 5 T1 measurements and a two-site exchange model (2SXM) accounting for WX. RESULTS: Median (range) ECV estimated using the 2SXM model was 25% (21%-39%) for patients and 26% (22%-29%) for controls. ECV estimated in patients using the LM at 10 min following a cumulative contrast dose of 0.15 mmol/kg was 21% (17%-32%) and increased significantly to 22% (19%-35%) at 30 min (p = 0.0001). ECV estimated using the LM was highest following low dose gadobutrol, 25% (19%-38%). CONCLUSION: Current guidelines on contrast agent dose for ECV measurements may lead to underestimated ECV in patients with severe AS because of limited WX. Use of a lower contrast agent dose may mitigate this effect.

Comparison of distortion correction preprocessing pipelines for DTI in the upper limb.

PURPOSE: DTI characterizes tissue microstructure and provides proxy measures of nerve health. Echo-planar imaging is a popular method of acquiring DTI but is susceptible to various artifacts (e.g., susceptibility, motion, and eddy currents), which may be ameliorated via preprocessing. There are many pipelines available but limited data comparing their performance, which provides the rationale for this study. METHODS: DTI was acquired from the upper limb of heathy volunteers at 3T in blip-up and blip-down directions. Data were independently corrected using (i) FSL's TOPUP & eddy, (ii) FSL's TOPUP, (iii) DSI Studio, and (iv) TORTOISE. DTI metrics were extracted from the median, radial, and ulnar nerves and compared (between pipelines) using mixed-effects linear regression. The geometric similarity of corrected b = 0 images and the slice matched T1-weighted (T1w) images were computed using the Sörenson-Dice coefficient. RESULTS: Without preprocessing, the similarity coefficient of the blip-up and blip-down datasets to the T1w was 0·80 and 0·79, respectively. Preprocessing improved the geometric similarity by 1% with no difference between pipelines. Compared to TOPUP & eddy, DSI Studio and TORTOISE generated 2% and 6% lower estimates of fractional anisotropy, and 6% and 13% higher estimates of radial diffusivity, respectively. Estimates of anisotropy from TOPUP & eddy versus TOPUP were not different but TOPUP reduced radial diffusivity by 3%. The agreement of DTI metrics between pipelines was poor. CONCLUSIONS: Preprocessing DTI from the upper limb improves geometric similarity but the choice of the pipeline introduces clinically important variability in diffusion parameter estimates from peripheral nerves.

Comparison of Stress-Rest and Stress-LGE Analysis Strategy in Patients Undergoing Stress Perfusion Cardiovascular Magnetic Resonance.

BACKGROUND: Stress perfusion cardiovascular magnetic resonance can be performed without rest perfusion for the quantification of ischemia burden. However, the optimal method of analysis is uncertain. METHODS: We identified 666 patients from CE-MARC (Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease) with complete stress perfusion, rest perfusion, late gadolinium enhancement (LGE), and quantitative coronary angiography data. For each segment of the 16-segment model, perfusion was visually graded during stress and rest imaging, with infarct transmurality assessed from LGE imaging. In the stress-LGE analysis, a segment was defined as ischemic if it had a subendocardial perfusion defect with no infarction. Rest perfusion was not used in this analysis. We compared the diagnostic accuracy of stress-LGE analysis against quantitative coronary angiography and the stress-rest method validated in the original CE-MARC analysis. The diagnostic accuracy of the stress-LGE method was evaluated with different thresholds of infarct transmurality used to define whether an infarcted segment had peri-infarct ischemia. RESULTS: The optimal stress-LGE analysis classified all segments with a stress perfusion defect as ischemic unless they had >75% infarct transmurality (area under the curve, 0.843; sensitivity, 75.6%; specificity, 93.1%; P<0.001). This analysis method has superior diagnostic accuracy to the stress-rest method (area under the curve, 0.834; sensitivity, 73.6%; specificity, 93.1%; P<0.001, P value for difference=0.02). Patients were followed-up for median 6.5 years for major adverse cardiovascular events, with the presence of inducible ischemia by either the stress-LGE or stress-rest analysis being similar and strongly predictive (hazard ratio, 2.65; P<0.001, for both). CONCLUSIONS: In this analysis of CE-MARC, the optimum definition of inducible ischemia was the presence of a stress-induced perfusion defect without transmural infarction. This definition improved the diagnostic accuracy compared with the stress-rest analysis validated in the original study. The absence of ischemia by either analysis strategy conferred a favorable long-term prognosis.