Publications

PURPOSE
To reduce inflow and motion artifacts in free-breathing, free-running, steady-state spoiled gradient echo T1-weighted (SPGR) myocardial perfusion imaging.

METHOD
Unsaturated spins from inflowing blood or out-of-plane motion cause flashing artifacts in free-running SPGR myocardial perfusion. During free-running SPGR, 1 non-selective RF excitation was added after every 3 slice-selective RF excitations to suppress inflow artifacts by forcing magnetization in neighboring regions to steady-state. Bloch simulations and phantom experiments were performed to evaluate the impact of the flip angle and non-selective RF frequency on inflowing spins and tissue contrast. Free-running perfusion with (n = 11) interleaved non-selective RF or without (n = 11) were studied in 22 subjects (age = 60.2 ± 14.3 years, 11 male). Perfusion images were graded on a 5-point Likert scale for conspicuity of wall enhancement, inflow/motion artifact, and streaking artifact and compared using Wilcoxon sum-rank testing.

RESULT
Numeric simulation showed that 1 non-selective RF excitation applied after every 3 slice-selective RF excitations produced superior out-of-plane signal suppression compared to 1 non-selective RF excitation applied after every 6 or 9 sliceselective RF excitations. In vitro experiments showed that a 30° flip angle produced near-optimal myocardial contrast. In vivo experiments demonstrated that the addition of interleaved non-selective RF significantly (P < .01) improved conspicuity of wall enhancement (mean score = 4.4 vs. 3.2) and reduced inflow/motion (mean score = 4.5 vs. 2.5) and streaking (mean score = 3.9 vs. 2.4) artifacts.
CONCLUSION
Non-selective RF excitations interleaved between slice-selective excitations can reduce image artifacts in free-breathing, ungated perfusion images. Further studies are warranted to assess the diagnostic accuracy of the proposed solution for evaluating myocardial ischemia.

AIMS
Cardiovascular magnetic resonance (CMR) with late-gadolinium enhancement (LGE) is increasingly being used in hypertrophic cardiomyopathy (HCM) for diagnosis, risk stratification, and monitoring. However, recent data demonstrating brain gadolinium deposits have raised safety concerns. We developed and validated a machine-learning (ML) method that incorporates features extracted from cine to identify HCM patients without fibrosis in whom gadolinium can be avoided.

METHODS AND RESULTS
An XGBoost ML model was developed using regional wall thickness and thickening, and radiomic features of myocardial signal intensity, texture, size, and shape from cine. A CMR dataset containing 1099 HCM patients collected using 1.5T CMR scanners from different vendors and centres was used for model development (n=882) and validation (n=217). Among the 2613 radiomic features, we identified 7 features that provided best discrimination between þLGE and -LGE using 10-fold stratified cross-validation in the development cohort. Subsequently, an XGBoost model was developed using these radiomic features, regional wall thickness and thickening. In the independent validation cohort, the ML model yielded an area under the curve of 0.83 (95% CI: 0.77–0.89), sensitivity of 91%, specificity of 62%, F1-score of 77%, true negatives rate (TNR) of 34%, and negative predictive value (NPV) of 89%. Optimization for sensitivity provided sensitivity of 96%, F2-score of 83%, TNR of 19% and NPV of 91%; false negatives halved from 4% to 2%.

CONCLUSIONS
An ML model incorporating novel radiomic markers of myocardium from cine can rule-out myocardial fibrosis in one-third of HCM patients referred for CMR reducing unnecessary gadolinium administration.

BACKGROUND
Quantification of myocardium scarring in late gadolinium enhanced (LGE) cardiac magnetic resonance imaging can be challenging due to low scar-to-background contrast and low image quality. To resolve ambiguous LGE regions, experienced readers often use conventional cine sequences to accurately identify the myocardium borders.
PURPOSE
To develop a deep learning model for combining LGE and cine images to improve the robustness and accuracy of LGE scar quantification.
Study Type: Retrospective.
Population: A total of 191 hypertrophic cardiomyopathy patients: 1) 162 patients from two sites randomly split into train- ing (50%; 81 patients), validation (25%, 40 patients), and testing (25%; 41 patients); and 2) an external testing dataset (29 patients) from a third site.
FIELD STRENGTH/SEQUENCE
1.5T, inversion-recovery segmented gradient-echo LGE and balanced steady-state free-preces- sion cine sequences
Assessment: Two convolutional neural networks (CNN) were trained for myocardium and scar segmentation, one with and one without LGE-Cine fusion. For CNN with fusion, the input was two aligned LGE and cine images at matched cardiac phase and anatomical location. For CNN without fusion, only LGE images were used as input. Manual segmentation of the datasets was used as reference standard.
STATISTICAL TESTS
Manual and CNN-based quantifications of LGE scar burden and of myocardial volume were assessed using Pearson linear correlation coefficients (r) and Bland–Altman analysis.
Results: Both CNN models showed strong agreement with manual quantification of LGE scar burden and myocardium vol- ume. CNN with LGE-Cine fusion was more robust than CNN without LGE-Cine fusion, allowing for successful segmenta- tion of significantly more slices (603 [95%] vs. 562 (89%) of 635 slices; P < 0.001). Also, CNN with LGE-Cine fusion showed better agreement with manual quantification of LGE scar burden than CNN without LGE-Cine fusion (%ScarLGE-cine = 0.82 × %Scarmanual, r = 0.84 vs. %ScarLGE = 0.47 × %Scarmanual, r = 0.81) and myocardium volume (VolumeLGE-cine = 1.03 × Volumemanual, r = 0.96 vs. VolumeLGE = 0.91 × Volumemanual, r = 0.91).
DATA CONCLUSION
CNN based LGE-Cine fusion can improve the robustness and accuracy of automated scar quantification.

Background: Over the past decade, there have been tremendous advances in electroanatomical mapping (EAM) technologies, including introduction of multielectrode catheters for high-resolution mapping of scar. While EAM may not be suitable for detecting mid-wall scar, it has been assumed that these are capable. We sought to examine the sensitivity of EAM for detecting cardiac MRI (CMR)-defined subendocardial scar in a swine model of myocardial infarction.
Methods: Fourteen swine underwent balloon occlusion of the mid circumflex (LCx group, 7 pigs) or mid left anterior descending artery (LAD group, 7 pigs). After 8-10 weeks, Late Gadolinium Enhancement (LGE) was performed. Within one week after CMR, EAM was performed using a multielectrode catheter (Carto®, Octaray®) by experienced electrophysiologist blinded to CMR.
Results: On CMR, both groups had similar scar size, left ventricular volumes and function. However, LAD group had significantly thinner LV walls (2.3±0.5 vs. 6.7±1.4mm), and there was good visual correspondence between the location and area of scar with low bipolar / unipolar voltage. In contrast, in LCx group, CMR scar seen was significantly larger than the area of low bipolar / unipolar voltage (Fig 1), despite large subendocardial and transmural scar. In 5 out 7 LCx group, there was no areas of low voltage, despite presence of transmural scar on CMR.
Conclusion: In preclinical model of healed MI, EAM voltage amplitude is insensitive to detect subendocardial and transmural scar on a thick wall.

Background: Non-ischemic idiopathic dilated cardiomyopathy (DCM) patients with scar on Late Gadolinium Enhancement (LGE) cardiac MR (CMR) are at higher risk of developing VT or VF. However, many patients with no scar on LGE still experience VT/VF. CMR feature tracking (CMR-FT) allows quantification of mechanics by evaluating myocardial fiber deformation. We sought to investigate if mechanical deformation measured by CMR-FT differs in DCM patients with/without VT/VF.
Methods: In a retrospective study, we identified DCM patients referred for CMR viability assessment. Patients were divided into two groups based on the history of documented VT/VF prior to CMR. Global longitudinal (GLS), circumferential (GCS) and radial (GRS) strains were measured (CVI42). The presence and extent of scar were evaluated using the threshold of 5 SD.
Results: A total of 354 patients were included. 77 (22%) patients had documented VT/VF and 277 had no history of VT/VF. There were no differences in the extent of LGE between the two groups (Table), however there were significant differences between global strains among the two groups (Table). No correlations were found between global strain values and the presence or extent of scar in the whole cohort, either in +VT/VF or -VT/VF groups.
Conclusion: Myocardial deformation measured using CMR-FT differs between DCM patients referred for CMR with/without VT/VF. This preliminary study suggests potential role of strain imaging for risk stratification in DCM patients.

PURPOSE
To develop a free-breathing sequence, that is, Multislice Joint T₁-T₂, for simultaneous
measurement of myocardial T₁ and T₂ for multiple slices to achieve whole left-ventricular coverage.

METHODS
Multislice Joint T₁-T₂ adopts slice-interleaved acquisition to collect 10 single-shot electrocardiogram-triggered images for each slice prepared by saturation and T₂ preparation to simultaneously estimate myocardial T₁ and T₂ and achieve whole left-ventricular coverage. Prospective slice-tracking using a respiratory navigator and retrospective image registration are used to reduce through-plane and in-plane motion, respectively. Multislice Joint T₁-T₂ was validated through numerical simulations and phantom and in vivo experiments, and compared with saturation-recovery single-shot acquisition and T₂-prepared balanced Steady-State Free Precession (T₂-prep SSFP) sequences.

RESULTS

Phantom T₁ and T₂ from Multislice Joint T₁-T₂ had good accuracy and precision, and were insensitive to heart rate. Multislice Joint T₁-T₂ yielded T₁ and T₂ maps of nine left-ventricular slices in 1.4 minutes. The mean left-ventricular T₁ difference between saturation-recovery single-shot acquisition and Multislice Joint T₁-T₂ across healthy subjects and patients was 191 ms (1564 ± 60 ms versus 1373 ± 50 ms; P < .05) and 111 ms (1535 ± 49 ms vs 1423 ± 49 ms; P < .05), respectively. The mean difference in left-ventricular T₂ between T₂-prep SSFP and Multislice Joint T₁-T₂ across healthy subjects and patients was −6.3 ms (42.4 ± 1.4 ms vs 48.7 ± 2.5; P < .05) and −5.7 ms (41.6 ± 2.5 ms vs 47.3 ± 2.7; P < .05), respectively.

CONCLUSION
Multislice Joint T₁-T₂ enables quantification of whole left-ventricular T₁ and T₂ during free breathing within a clinically feasible scan time of less than 2 minutes.

BACKGROUND
In patients with nonischemic cardiomyopathy, nonischemic fibrosis detected by late gadolinium enhancement (LGE) cardiovascular magnetic resonance is related to adverse cardiovascular outcomes. However, its relationship with left ventricular (LV) mechanical deformation parameters remains unclear. We sought to investigate the association between LV mechanics and the presence, location, and extent of fibrosis in patients with nonischemic cardiomyopathy.

METHODS AND RESULTS
We retrospectively identified 239 patients with nonischemic cardiomyopathy (67% male; 55±14 years) referred for a clinical cardiovascular magnetic resonance. LGE was present in 109 patients (46%), most commonly (n=52; 22%) in the septum. LV deformation parameters did not differentiate between LGE‐positive and LGE‐negative groups. Global longitudinal, radial, and circumferential strains, twist and torsion showed no association with extent of fibrosis. Patients with septal fibrosis had a more depressed LV ejection fraction (30±12% versus 35±14%; P=0.032) and more impaired global circumferential strain (−7.9±3.5% versus −9.7±4.4%; P=0.045) and global radial strain (10.7±5.2% versus 13.3±7.7%; P=0.023) than patients without septal LGE. Global longitudinal strain was similar in both groups. While patients with septal‐only LGE (n=28) and free wall–only LGE (n=32) had similar fibrosis burden, the septal‐only LGE group had more impaired LV ejection fraction and global circumferential, longitudinal, and radial strains (all P<0.05).

CONCLUSION
There is no association between LV mechanical deformation parameters and presence or extent of fibrosis in patients with nonischemic cardiomyopathy. Septal LGE was associated with poor global LV function, more impaired global circumferential and radial strains, and more impaired global strain rates.

OBJECTIVES
This study sought to investigate the sensitivity of electroanatomical mapping (EAM) to detect scar as identified by late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR).

BACKGROUND
Previous studies have shown correlation between low voltage electrogram amplitude and myocardial scar. However, voltage amplitude is influenced by the distance between the scar and the mapping surface and its extent.The aim of this study is to examine the reliability of low voltage EAM as a surrogate for myocardial scar using LGE-derived scar as the reference.

METHODS
Twelve swine underwent anterior wall infarction by occlusion of the left anterior descending artery (LAD) (n ¼ 6) or inferior wall infarction by occlusion of the left circumflex artery (LCx) (n ¼ 6). Subsequently, animals underwent CMR and EAM using a multielectrode mapping catheter. CMR characteristics, including wall thickness, LGE location and extent, and EAM maps, were independently analyzed, and concordance between voltage maps and CMR characteristics was assessed.

RESULTS
LGE volume was similar between the LCx and LAD groups (8.5 _ 2.2 ml vs. 8.3 _ 2.5 ml, respectively; p ¼ 0.852). LGE scarring in the LAD group was more subendocardial, affected a larger surface area, and resulted in significant wall thinning (4.88 _ 0.43 mm). LGE scarring in the LCx group extended from the endocardium to the epicardium with minimal reduction in wall thickness (scarred: 5.4 _ 0.67 mm vs. remote: 6.75 _ 0.38 mm). In all the animals in the LAD group, areas of low voltage corresponded with LGE and wall thinning, whereas only 2 of 6 animals in the LCx group had low voltage areas on EAM. Bipolar and unipolar voltage amplitudes were higher in thick inferior walls in the LCx group than in thin anterior walls in the LAD group, despite a similar LGE volume.

CONCLUSIONS
Discordances between LGE-detected scar areas and low voltage areas by EAM highlighted the limitations of the current EAM system to detect scar in thick myocardial wall regions. (J Am Coll Cardiol EP 2020;6:1452–64)