Evaluating a novel accelerated free-breathing late gadolinium enhancement imaging sequence for assessment of myocardial injury.

INTRODUCTION: Cardiac magnetic resonance imaging (MRI), including late gadolinium enhancement (LGE), plays an important role in the diagnosis and prognostication of ischemic and non-ischemic myocardial injury. Conventional LGE sequences require patients to perform multiple breath-holds and require long acquisition times. In this study, we compare image quality and assessment of myocardial LGE using an accelerated free-breathing sequence to the conventional standard-of-care sequence. METHODS: In this prospective cohort study, a total of 41 patients post Coronavirus 2019 (COVID-19) infection were included. Studies were performed on a 1.5 Tesla scanner with LGE imaging acquired using a conventional inversion recovery rapid gradient echo (conventional LGE) sequence followed by the novel accelerated free-breathing (FB-LGE) sequence. Image quality was visually scored (ordinal scale from 1 to 5) and compared between conventional and free-breathing sequences using the Wilcoxon rank sum test. Presence of per-segment LGE was identified according to the American Heart Association 16-segment myocardial model and compared across both conventional LGE and FB-LGE sequences using a two-sided chi-square test. The perpatient LGE extent was also evaluated using both sequences and compared using the Wilcoxon rank sum test. Interobserver variability in detection of per-segment LGE and per-patient LGE extent was evaluated using Cohen's kappa statistic and interclass correlation (ICC), respectively. RESULTS: The mean acquisition time for the FB-LGE sequence was 17 s compared to 413 s for the conventional LGE sequence (P < 0.001). Assessment of image quality was similar between both sequences (P = 0.19). There were no statistically significant differences in LGE assessed using the FB-LGE versus conventional LGE on a per-segment (P = 0.42) and per-patient (P = 0.06) basis. Interobserver variability in LGE assessment for FB-LGE was good for per-segment (= 0.71) and per-patient extent (ICC = 0.92) analyses. CONCLUSIONS: The accelerated FB-LGE sequence performed comparably to the conventional standard-of-care LGE sequence in a cohort of patients post COVID-19 infection in a fraction of the time and without the need for breath-holding. Such a sequence could impact clinical practice by increasing cardiac MRI throughput and accessibility for frail or acutely ill patients unable to perform breath-holding.

Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study.

OBJECTIVE: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world dataset, it is important to quantify segmentation uncertainty and identify segmentations which could be problematic. In this work, we performed a systematic study of Bayesian and non-Bayesian methods for estimating uncertainty in segmentation neural networks. METHODS: We evaluated Bayes by Backprop, Monte Carlo Dropout, Deep Ensembles, and Stochastic Segmentation Networks in terms of segmentation accuracy, probability calibration, uncertainty on out-of-distribution images, and segmentation quality control. RESULTS: We observed that Deep Ensembles outperformed the other methods except for images with heavy noise and blurring distortions. We showed that Bayes by Backprop is more robust to noise distortions while Stochastic Segmentation Networks are more resistant to blurring distortions. For segmentation quality control, we showed that segmentation uncertainty is correlated with segmentation accuracy for all the methods. With the incorporation of uncertainty estimates, we were able to reduce the percentage of poor segmentation to 5% by flagging 31-48% of the most uncertain segmentations for manual review, substantially lower than random review without using neural network uncertainty (reviewing 75-78% of all images). CONCLUSION: This work provides a comprehensive evaluation of uncertainty estimation methods and showed that Deep Ensembles outperformed other methods in most cases. SIGNIFICANCE: Neural network uncertainty measures can help identify potentially inaccurate segmentations and alert users for manual review.

Low Prevalence of Late Myocardial Injury on Cardiac MRI Following COVID-19 Infection.

BACKGROUND: The prevalence of abnormal cardiac magnetic resonance imaging (MRI) findings indicative of myocardial injury in patients who recovered from coronavirus disease 2019 (COVID-19) is currently unclear, with a high variability in the reported prevalence. PURPOSE: To assess the prevalence of myocardial injury after a COVID-19 infection. STUDY TYPE: Prospective, bicentric study. SUBJECTS: Seventy consecutive patients who recovered from COVID-19 and were previously hospitalized. Mean age was 57 years and 39% of the patients were female. Ten healthy controls and a comparator group of 75 nonischemic cardiomyopathy (NICM) patients were employed. FIELD STRENGTH/SEQUENCE: 1.5-T, steady-state free precession (SSFP) gradient-echo sequence, modified Look-Locker inversion recovery sequence with balanced SSFP readout, T2-prepared spiral readout sequence and a T1-weighted inversion recovery fast gradient-echo sequence was acquired ~4-5 months after recovery from COVID-19. ASSESSMENT: The SSFP sequence was utilized for the calculation of left and right ventricular volumes and ejection fractions (LVEF and RVEF) following manual endocardial contouring. T1 and T2 mapping was performed by pixel-wise exponential fitting, and T1 and T2 values were computed by manual contouring of the left ventricular endocardial and epicardial walls. Late gadolinium enhancement (LGE) images were graded qualitatively as LGE present or absent. STATISTICAL TESTS: T-tests and the χ2 or Fisher's exact tests were used to compare continuous and categorical variables respectively between the COVID-19 and NICM groups. Inter-rater agreement was evaluated by the intraclass correlation coefficient for continuous variables and Cohen's kappa test for LGE. RESULTS: Reduced RVEF occurred in 10%, LGE and elevated native T1 in 9%, reduced LVEF in 4%, and elevated T2 in 3% of COVID-19 patients, respectively. Patients with NICM had lower mean LVEF (41.6% ± 6% vs. 60% ± 7%), RVEF (46% ± 5% vs. 61% ± 9%), and a significantly higher prevalence of LGE (27% vs. 9%) when compared to those post-COVID-19. DATA CONCLUSION: Abnormal cardiac MRI findings may show a low prevalence in patients who recovered from COVID-19 and were previously hospitalized. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

A Deep Learning Segmentation Pipeline for Cardiac T1 Mapping Using MRI Relaxation-based Synthetic Contrast Augmentation.

Purpose: To design and evaluate an automated deep learning method for segmentation and analysis of cardiac MRI T1 maps with use of synthetic T1-weighted images for MRI relaxation-based contrast augmentation. Materials and Methods: This retrospective study included MRI scans acquired between 2016 and 2019 from 100 patients (mean age ± SD, 55 years ± 13; 72 men) across various clinical abnormalities with use of a modified Look-Locker inversion recovery, or MOLLI, sequence to quantify native T1 (T1native), postcontrast T1 (T1post), and extracellular volume (ECV). Data were divided into training (n = 60) and internal (n = 40) test subsets. "Synthetic" T1-weighted images were generated from the T1 exponential inversion-recovery signal model at a range of optimal inversion times, yielding high blood-myocardium contrast, and were used for contrast-based image augmentation during training and testing of a convolutional neural network for myocardial segmentation. Automated segmentation, T1, and ECV were compared with experts with use of Dice similarity coefficients (DSCs), correlation coefficients, and Bland-Altman analysis. An external test dataset (n = 147) was used to assess model generalization. Results: Internal testing showed high myocardial DSC relative to experts (0.81 ± 0.08), which was similar to interobserver DSC (0.81 ± 0.08). Automated segmental measurements strongly correlated with experts (T1native, R = 0.87; T1post, R = 0.91; ECV, R = 0.92), which were similar to interobserver correlation (T1native, R = 0.86; T1post, R = 0.94; ECV, R = 0.95). External testing showed strong DSC (0.80 ± 0.09) and T1native correlation (R = 0.88) between automatic and expert analysis. Conclusion: This deep learning method leveraging synthetic contrast augmentation may provide accurate automated T1 and ECV analysis for cardiac MRI data acquired across different abnormalities, centers, scanners, and T1 sequences.Keywords: MRI, Cardiac, Tissue Characterization, Segmentation, Convolutional Neural Network, Deep Learning Algorithms, Machine Learning Algorithms, Supervised Learning Supplemental material is available for this article. © RSNA, 2022.

Vendor-neutral sequences and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI.

PURPOSE: We developed an end-to-end workflow that starts with a vendor-neutral acquisition and tested the hypothesis that vendor-neutral sequences decrease inter-vendor variability of T1, magnetization transfer ratio (MTR), and magnetization transfer saturation-index (MTsat) measurements. METHODS: We developed and deployed a vendor-neutral 3D spoiled gradient-echo (SPGR) sequence on three clinical scanners by two MRI vendors. We then acquired T1 maps on the ISMRM-NIST system phantom, as well as T1, MTR, and MTsat maps in three healthy participants. We performed hierarchical shift function analysis in vivo to characterize the differences between scanners when the vendor-neutral sequence is used instead of commercial vendor implementations. Inter-vendor deviations were compared for statistical significance to test the hypothesis. RESULTS: In the phantom, the vendor-neutral sequence reduced inter-vendor differences from 8% to 19.4% to 0.2% to 5% with an overall accuracy improvement, reducing ground truth T1 deviations from 7% to 11% to 0.2% to 4%. In vivo, we found that the variability between vendors is significantly reduced (p = 0.015) for all maps (T1, MTR, and MTsat) using the vendor-neutral sequence. CONCLUSION: We conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor variability using vendor-neutral sequences has important implications for qMRI research and for the reliability of multicenter clinical trials.

MRI-Guided Cardiac RF Ablation for Comparing MRI Characteristics of Acute Lesions and Associated Electrophysiologic Voltage Reductions.

OBJECTIVE: Radiofrequency (RF) energy delivered to cardiac tissue produces a core ablation lesion with surrounding edema, the latter of which has been implicated in acute procedural failure of Ventricular Tachycardia (VT) ablation and late arrhythmia recurrence. This study sought to investigate the electrophysiological characteristics of acute RF lesions in the left ventricle (LV) visualized with native-contrast Magnetic Resonance Imaging (MRI). METHODS: An MR-guided electrophysiology system was used to deliver RF ablation in the LV of 8 swine (9 RF lesions in total), then perform MRI and electroanatomic mapping. The permanent RF lesions and transient edema were delineated via native-contrast MRI segmentation of T1-weighted images and T2 maps respectively. Bipolar voltage measurements were matched with image characteristics of pixels adjacent to the catheter tip. Native-contrast MR visualization was verified with 3D late gadolinium enhanced MRI and histology. RESULTS: The T2-derived edema was significantly larger than the T1-derived RF lesion (2.1 ±1.5 mL compared to 0.58 ±0.34 mL; p=0.01). Bipolar voltage was significantly reduced in the presence of RF lesion core (p 0.05) and edema (p 0.05), with similar trends suggesting that both the permanent lesion and transient edema contributed to the region of reduced voltage. While bipolar voltage was significantly decreased where RF lesions are present (p 0.05), voltage did not change significantly with lesion transmurality (p 0.05). CONCLUSION: Permanent RF lesions and transient edema are distinct in native-contrast MR images, but not differentiable using bipolar voltage. SIGNIFICANCE: Intraprocedural native-contrast MRI may provide valuable lesion assessment in MR-guided ablation, whose clinical application is now feasible.

Suspected subclinical myocarditis detected by cardiac magnetic resonance imaging late post COVID-19 recovery.

There is growing evidence of the potential for cardiac involvement in patients who have been infected with COVID-19. In this case study, we present a patient with no history of cardiovascular disease, who was hospitalized for COVID-19 pneumonia and subsequently recovered. Despite normal serum troponin levels and left ventricular structure and function, multi-parametric cardiac magnetic resonance imaging revealed a classic myocarditis-like pattern of injury approximately 6 months after his convalescence. Physicians should be aware of the possibility of late myocardial injury/inflammation in patients with recovered COVID-19, even in the absence of elevated troponin levels and/or left ventricular dysfunction. .

Technical Note: Fully automatic segmental relaxometry (FASTR) for cardiac magnetic resonance T1 mapping.

PURPOSE: Cardiac relaxometry techniques, particularly T1 mapping, have recently gained clinical importance in various cardiac pathologies. Myocardial T1 and extracellular volume are usually calculated from manual identification of left ventricular epicardial and endocardial regions. This is a laborious process, particularly for large volume studies. Here we present a fully automated relaxometry framework (FASTR) for segmental analysis of T1 maps (both native and postcontrast) and partition coefficient (λ). METHODS: Patients (N = 11) were imaged postacute myocardial infarction on a 1.5T clinical scanner. The scan protocol involved CINE-SSFP imaging, native, and post-contrast T1 mapping using the Modified Look-Locker Inversion (MOLLI) recovery sequence. FASTR consisted of automatic myocardial segmentation of spatio-temporally coregistered CINE images as an initial guess, followed by refinement of the contours on the T1 maps to derive segmental T1 and λ. T1 and λ were then compared to those obtained from two trained expert observers. RESULTS: Robust endocardial and epicardial contours were achieved on T1 maps despite the presence of infarcted tissue. Relative to experts, FASTR resulted in myocardial Dice coefficients (native T1: 0.752 ± 0.041; postcontrast T1: 0.751 ± 0.057) that were comparable to interobserver Dice (native T1: 0.803 ± 0.045; postcontrast T1: 0.799 ± 0.054). There were strong correlations observed for T1 and λ derived from experts and FASTR (native T1: r = 0.83; postcontrast T1: r = 0.87; λ: r = 0.78; P < 0.0001), which were comparable to inter-expert correlation coefficients (native T1: r = 0.90; postcontrast T1: r = 0.93; λ: r = 0.80; P < 0.0001). CONCLUSIONS: Our fully automated framework, FASTR, can generate accurate myocardial segmentations for native and postcontrast MOLLI T1 analysis without the need for manual intervention. Such a design is appealing for high volume clinical protocols.

Evaluating a novel free-breathing accelerated cardiac MRI cine sequence in patients with cardiomyopathy.

INTRODUCTION: Cardiac magnetic resonance imaging (CMR) is the gold standard for the assessment of left ventricular (LV) function. However, traditional sequences are time-consuming and require breath-holding. Our aim was to evaluate the image quality of LV functional assessment with a novel, accelerated, free-breathing cine sequence and to compare LV functional parameters between it and a traditional sequence. METHODS: This was a prospective cohort study of 31 patients with cardiomyopathy. All studies were performed on a 1.5 Tesla scanner. LV function was first determined using contiguous short axis slices covering the left ventricle from the base to the apex acquired with the standard cine sequence. Next, the accelerated sequence was acquired for each patient. The Wilcoxon Matched-Pair Sign Rank Test was used to compare image quality between the accelerated and traditional cine imaging sequences. Standard and accelerated left ventricular volumes and ejection fraction were compared using linear regression. Bland-Altman plots were then constructed to evaluate agreement, interobserver and intraobserver variability for left ventricular volumes and ejection fraction. RESULTS: Mean acquisition time was 29 s for the accelerated sequence vs. 410 s for the traditional sequence. Qualitative assessment of image quality was similar for both sequences (p = 0.23). There were no significant differences in terms of LVEDV, LVESV, LVSV, LV mass and LVEF when calculated from either sequence with very good agreement between the standard and accelerated sequences. The mean differences with 95% limits of agreement were as follows: LV mass (-0.6, -22.9 g, 21.6 g), LVEDV (5.1 mL, -18.4 mL, 28.9 mL), LVEF (-0.3, -5.4, 4.7), LVESV (4.0 mL, -12.0 mL, 20.0 mL), LVSV (1.1 mL, -13.3 mL, 15.5 mL). Interobserver variability ranged from 0.1 to 6.3% while intraobserver variability ranged from 0.1 to 1.8%. CONCLUSIONS: The accelerated free-breathing cine sequence performed similarly to standard of care multi breath-hold cine imaging and was acquired in a fraction of the time without the need for breath-holding. If applied to clinical practice, this sequence can significantly reduce scanning time and facilitate CMR scanning in those patients who are unable to breath-hold.

Omnipolarity applied to equi-spaced electrode array for ventricular tachycardia substrate mapping.

AIMS: Bipolar electrogram (BiEGM)-based substrate maps are heavily influenced by direction of a wavefront to the mapping bipole. In this study, we evaluate high-resolution, orientation-independent peak-to-peak voltage (Vpp) maps obtained with an equi-spaced electrode array and omnipolar EGMs (OTEGMs), measure its beat-to-beat consistency, and assess its ability to delineate diseased areas within the myocardium compared against traditional BiEGMs on two orientations: along (AL) and across (AC) array splines. METHODS AND RESULTS: The endocardium of the left ventricle of 10 pigs (three healthy and seven infarcted) were each mapped using an Advisor™ HD grid with a research EnSite Precision™ system. Cardiac magnetic resonance images with late gadolinium enhancement were registered with electroanatomical maps and were used for gross scar delineation. Over healthy areas, OTEGM Vpp values are larger than AL bipoles by 27% and AC bipoles by 26%, and over infarcted areas OTEGM Vpp values are 23% larger than AL bipoles and 27% larger than AC bipoles (P < 0.05). Omnipolar EGM voltage maps were 37% denser than BiEGM maps. In addition, OTEGM Vpp values are more consistent than bipolar Vpps showing less beat-by-beat variation than BiEGM by 39% and 47% over both infarcted and healthy areas, respectively (P < 0.01). Omnipolar EGM better delineate infarcted areas than traditional BiEGMs from both orientations. CONCLUSION: An equi-spaced electrode grid when combined with omnipolar methodology yielded the largest detectable bipolar-like voltage and is void of directional influences, providing reliable voltage assessment within infarcted and non-infarcted regions of the heart.

Cardiovascular magnetic resonance guided ablation and intra-procedural visualization of evolving radiofrequency lesions in the left ventricle.

BACKGROUND: Radiofrequency (RF) ablation has become a mainstay of treatment for ventricular tachycardia, yet adequate lesion formation remains challenging. This study aims to comprehensively describe the composition and evolution of acute left ventricular (LV) lesions using native-contrast cardiovascular magnetic resonance (CMR) during CMR-guided ablation procedures. METHODS: RF ablation was performed using an actively-tracked CMR-enabled catheter guided into the LV of 12 healthy swine to create 14 RF ablation lesions. T2 maps were acquired immediately post-ablation to visualize myocardial edema at the ablation sites and T1-weighted inversion recovery prepared balanced steady-state free precession (IR-SSFP) imaging was used to visualize the lesions. These sequences were repeated concurrently to assess the physiological response following ablation for up to approximately 3 h. Multi-contrast late enhancement (MCLE) imaging was performed to confirm the final pattern of ablation, which was then validated using gross pathology and histology. RESULTS: Edema at the ablation site was detected in T2 maps acquired as early as 3 min post-ablation. Acute T2-derived edematous regions consistently encompassed the T1-derived lesions, and expanded significantly throughout the 3-h period post-ablation to 1.7 ± 0.2 times their baseline volumes (mean ± SE, estimated using a linear mixed model determined from n = 13 lesions). T1-derived lesions remained approximately stable in volume throughout the same time frame, decreasing to 0.9 ± 0.1 times the baseline volume (mean ± SE, estimated using a linear mixed model, n = 9 lesions). CONCLUSIONS: Combining native T1- and T2-based imaging showed that distinctive regions of ablation injury are reflected by these contrast mechanisms, and these regions evolve separately throughout the time period of an intervention. An integrated description of the T1-derived lesion and T2-derived edema provides a detailed picture of acute lesion composition that would be most clinically useful during an ablation case.

Feasibility Study of Respiratory Motion Modeling Based Correction for MRI-Guided Intracardiac Interventional Procedures.

GOAL: The purpose of this study is to improve the accuracy of interventional catheter guidance during intracardiac procedures. Specifically, the use of preprocedural magnetic resonance roadmap images for interventional guidance has limited anatomical accuracy due to intraprocedural respiratory motion of the heart. Therefore, we propose to build a novel respiratory motion model to compensate for this motion-induced error during magnetic resonance imaging (MRI)-guided procedures. METHODS: We acquire 2-D real-time free-breathing images to characterize the respiratory motion, and build a smooth motion model via registration of 3-D prior roadmap images to the real-time images within a novel principal axes frame of reference. The model is subsequently used to correct the interventional catheter positions with respect to the anatomy of the heart. RESULTS: We demonstrate that the proposed modeling framework can lead to smoother motion models, and potentially lead to more accurate motion estimates. Specifically, MRI-guided intracardiac ablations were performed in six preclinical animal experiments. Then, from retrospective analysis, the proposed motion modeling technique showed the potential to achieve a 27% improvement in ablation targeting accuracy. CONCLUSION: The feasibility of a respiratory motion model-based correction framework has been successfully demonstrated. SIGNIFICANCE: The improvement in ablation accuracy may lead to significant improvements in success rate and patient outcomes for MRI-guided intracardiac procedures.

Distribution of abnormal potentials in chronic myocardial infarction using a real time magnetic resonance guided electrophysiology system.

BACKGROUND: Identification of viable slow conduction zones manifested by abnormal local potentials is integral to catheter ablation of ventricular tachycardia (VT) sites. The relationship between contrast patterns in cardiovascular magnetic resonance (CMR) and local electrical mapping is not well characterized. The purpose of this study was to identify regions of isolated, late and fractionated diastolic potentials in sinus rhythm and controlled-paced rhythm in post-infarct animals relative to regions detected by late gadolinium enhancement CMR (LGE-CMR). METHODS: Using a real-time MR-guided electrophysiology system, electrogram (EGM) recordings were used to generate endocardial electroanatomical maps in 6 animals. LGE-CMR was also performed and tissue classification (dense infarct, gray zone and healthy myocardium) was then correlated to locations of abnormal potentials. RESULTS: For abnormal potentials in sinus rhythm, relative occurrence was equivalent 24%, 27% and 22% in dense scar, gray zone and healthy tissue respectively (p = NS); in paced rhythm, the relative occurrence of abnormal potentials was found to be different with 30%, 42% and 21% in dense scar, gray zone and healthy myocardium respectively (p = 0.001). For location of potentials, in the paced case, the relative frequency of abnormal EGMs was 19.9%, 65.4% and 14.7% in the entry, central pathway and exit respectively (p = 0.05), putative regions being defined by activation times. CONCLUSIONS: Our data suggests that gray zone quantified by LGE-CMR exhibits abnormal potentials more frequently than in healthy tissue or dense infarct when right ventricular apex pacing is used.

Postinfarction ventricular tachycardia substrate characterization: a comparison between late enhancement magnetic resonance imaging and voltage mapping using an MR-guided electrophysiology system.

Catheter ablation of ventricular tachycardia (VT) is preceded by characterization of the myocardial substrate via electroanatomical voltage mapping (EAVM). The purpose of this study was to characterize the relationship between chronic myocardial fibrotic scar detected by multicontrast late enhancement (MCLE) MRI and by EAVM obtained using an MR-guided electrophysiology system, with a final aim to better understand how these measures may improve identification of potentially arrhythmogenic substrates. Real-time MR-guided EAVM was performed in six chronically infarcted animals in a 1.5T MR system. The MCLE images were analyzed to identify the location and extent of the fibrotic infarct. Voltage maps of the left ventricle (LV) were created with an average of 231 ± 35 points per LV. Correlation analysis was conducted between bipolar voltage and three MR parameters (infarct transmurality, tissue categorization into healthy and scar classes, and normalized relaxation rate R1). In general, tissue regions classified as scar by normalized R1 values were well correlated with locations with low bipolar voltage values. Moreover, our results demonstrate that MRI information (transmurality, tissue classification, and relaxation rate) can accurately predict areas of myocardial fibrosis identified with bipolar voltage mapping, as demonstrated by ROC analysis. MCLE can help overcome limitations of bipolar voltage mapping including long durations and lower spatial discrimination and may help identify the sites within scars, which are commonly believed to trigger arrhythmic events in postinfarction patients.

The feasibility of endocardial propagation mapping using magnetic resonance guidance in a Swine model, and comparison with standard electroanatomic mapping.

The introduction of electroanatomic mapping (EAM) has improved the understanding of the substrate of ventricular tachycardia. EAM systems are used to delineate scar regions responsible for the arrhythmia by creating voltage or activation time maps. Previous studies have identified the benefits of creating MR-guided voltage maps; however, in some cases voltage maps may not identify regions of slow propagation that can cause the reentrant tachycardia. In this study, we obtained local activation time maps and analyzed propagation properties by performing MR-guided mapping of the porcine left ventricle while pacing from the right ventricle. Anatomical and myocardial late gadolinium enhancement images were used for catheter navigation and identification of scar regions. Our MR-guided mapping procedure showed qualitative correspondence to conventional clinical EAM systems in healthy pigs and demonstrated altered propagation in endocardial infarct models.

Free-breathing, nongated real-time delayed enhancement MRI of myocardial infarcts: a comparison with conventional delayed enhancement.

PURPOSE: To compare a free-breathing, nongated, and black-blood real-time delayed enhancement (RT-DE) sequence to the conventional inversion recovery gradient echo (IR-GRE) sequence for delayed enhancement MRI. MATERIALS AND METHODS: Twenty-three patients with suspected myocardial infarct (MI) were examined using both the IR-GRE and RT-DE imaging sequences. The sensitivity and specificity of RT-DE for detecting MI, using IR-GRE as the gold standard, was determined. The contrast-to-noise ratios (CNR) between the two techniques were also compared. RESULTS: RT-DE had a high sensitivity and specificity (94% and 98%, respectively) for identifying MI. The total acquisition time to image the entire left ventricle was significantly shorter using RT-DE than IR-GRE (5.6+/-0.9 versus 11.5+/-1.9 min). RT-DE had a slightly lower infarct-myocardium CNR but a higher infarct-blood CNR than IR-GRE imaging. Compared with IR-GRE, RT-DE accurately measured total infarct sizes. CONCLUSION: RT-DE can be used for delayed enhancement imaging during free-breathing and without cardiac gating.