Phase-sensitive inversion recovery for detecting myocardial infarction using gadolinium-delayed hyperenhancement

Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging

OBJECTIVES

To develop and share a deep learning method that can accurately identify optimal inversion time (TI) from multi-vendor, multi-institutional and multi-field strength inversion scout (TI scout) sequences for late gadolinium enhancement cardiac MRI.

MATERIALS AND METHODS

Retrospective multicentre study conducted on 1136 1.5-T and 3-T cardiac MRI examinations from four centres and three scanner vendors. Deep learning models, comprising a convolutional neural network (CNN) that provides input to a long short-term memory (LSTM) network, were trained on TI scout pixel data from centres 1 to 3 to identify optimal TI, using ground truth annotations by two readers. Accuracy within 50 ms, mean absolute error (MAE), Lin's concordance coefficient (LCCC) and reduced major axis regression (RMAR) were used to select the best model from validation results, and applied to holdout test data. Robustness of the best-performing model was also tested on imaging data from centre 4.

RESULTS

The best model (SE-ResNet18-LSTM) produced accuracy of 96.1%, MAE 22.9 ms and LCCC 0.47 compared to ground truth on the holdout test set and accuracy of 97.3%, MAE 15.2 ms and LCCC 0.64 when tested on unseen external (centre 4) data. Differences in vendor performance were observed, with greatest accuracy for the most commonly represented vendor in the training data.

CONCLUSION

A deep learning model was developed that can identify optimal inversion time from TI scout images on multi-vendor data with high accuracy, including on previously unseen external data. We make this model available to the scientific community for further assessment or development.

CLINICAL RELEVANCE STATEMENT

A robust automated inversion time selection tool for late gadolinium-enhanced imaging allows for reproducible and efficient cross-vendor inversion time selection.

KEY POINTS

• A model comprising convolutional and recurrent neural networks was developed to extract optimal TI from TI scout images. • Model accuracy within 50 ms of ground truth on multi-vendor holdout and external data of 96.1% and 97.3% respectively was achieved. • This model could improve workflow efficiency and standardise optimal TI selection for consistent LGE imaging.

Defining echocardiographic predictors of outcome in cardiac amyloidosis by subtype

BACKGROUND

Current echocardiographic risk factors for prognosis in cardiac amyloidosis (CA) do not distinguish between the two main subtypes: transthyretin cardiomyopathy (TTR) and immunoglobulin light chain cardiomyopathy (AL), each of which require distinct diagnostic and therapeutic approaches. Additionally, only traditional parameters have been studied with little data on advanced techniques. Accordingly, we sought to determine whether differences exist in 2D transthoracic echocardiography (2DE) predictors of survival between the CA subtypes using a comprehensive approach.

METHODS

220 patients (72±12 years) with confirmed CA (AL=89, TTR=131) who underwent 2DE at the time of CA diagnosis were enrolled. Left ventricular (LV) dimensions, indexed mass (LVMi), global longitudinal strain (LVGLS), apical-sparing ratio (LVASR), diastology, right ventricular (RV) size and function indices including tricuspid annular systolic excursion (TAPSE), RV free-wall (RVFWS) and global (RVGLS) strain, indexed left (LA) and right atrial volumes (LAVi and RAVi), LA strain (reservoir and booster) and RV systolic pressure (RVSP) were measured. A propensity-score weighted stepwise variable selection Cox proportional hazards model derived from NYHA class and renal impairment status at diagnosis was used to determine the associations between 2DE parameters and mortality specific to CA subtype over a median follow-up of 36-months.

RESULTS

After adjusting for age, atrial fibrillation and treatment, parameters associated with survival were RVFWS (p=0.003, HR 1.15, 95% CI[1.053,1.245]) and RVSP (p=0.03, HR 1.03, 95% CI[1.004,1.063]) in AL and LVASR (p=0.007, HR 6.68, 95% CI[1.75,25.492]) and RAVi (p=0.049, HR 1.03, 95% CI[1.000,1.052]) in TTR.

CONCLUSIONS

Echocardiographic prognosticators for survival are specific to cardiac amyloid subtype. These results potentially provide information critical for clinical decision-making and follow-up in these patients.

Differentiating Left Ventricular Remodeling in Aortic Stenosis From Systemic Hypertension

BACKGROUND

Left ventricular (LV) hypertrophy occurs in both aortic stenosis (AS) and systemic hypertension (HTN) in response to wall stress. However, differentiation of hypertrophy due to these 2 etiologies is lacking. The aim was to study the 3-dimensional geometric remodeling pattern in severe AS pre- and postsurgical aortic valve replacement and to compare with HTN and healthy controls.

METHODS

Ninety-one subjects (36 severe AS, 19 HTN, and 36 healthy controls) underwent cine cardiac magnetic resonance. Cardiac magnetic resonance was repeated 8 months post-aortic valve replacement (n=18). Principal component analysis was performed on the 3-dimensional meshes reconstructed from 109 cardiac magnetic resonance scans of 91 subjects at end-diastole. Principal component analysis modes were compared across experimental groups together with conventional metrics of shape, strain, and scar.

RESULTS

A unique AS signature was identified by wall thickness linked to a LV left-right axis shift and a decrease in short-axis eccentricity. HTN was uniquely linked to increased septal thickness. Combining these 3 features had good discriminative ability between AS and HTN (area under the curve, 0.792). The LV left-right axis shift was not reversible post-aortic valve replacement, did not associate with strain, age, or sex, and was predictive of postoperative LV mass regression (R2=0.339, P=0.014).

CONCLUSIONS

Unique remodeling signatures might differentiate the etiology of LV hypertrophy. Preliminary findings suggest that LV axis shift is characteristic in AS, is not reversible post-aortic valve replacement, predicts mass regression, and may be interpreted to be an adaptive mechanism.

Cardiac magnetic resonance imaging in the evaluation and management of mitral valve prolapse - a comprehensive review

Mitral valve prolapse is a common valve disorder that usually has a benign prognosis unless there is significant regurgitation or LV impairment. However, a subset of patients are at an increased risk of ventricular arrhythmias and sudden cardiac death, which has led to the recognition of "arrhythmic mitral valve prolapse" as a clinical entity. Emerging risk factors include mitral annular disjunction and myocardial fibrosis. While echocardiography remains the primary method of evaluation, cardiac magnetic resonance has become crucial in managing this condition. Cine magnetic resonance sequences provide accurate characterization of prolapse and annular disjunction, assessment of ventricular volumes and function, identification of early dysfunction and remodeling, and quantitative assessment of mitral regurgitation when integrated with flow imaging. However, the unique strength of magnetic resonance lies in its ability to identify tissue changes. T1 mapping sequences identify diffuse fibrosis, in turn related to early ventricular dysfunction and remodeling. Late gadolinium enhancement sequences detect replacement fibrosis, an independent risk factor for ventricular arrhythmias and sudden cardiac death. There are consensus documents and reviews on the use of cardiac magnetic resonance specifically in arrhythmic mitral valve prolapse. However, in this article, we propose an algorithm for the broader use of cardiac magnetic resonance in managing this condition in various scenarios. Future advancements may involve implementing techniques for tissue characterization and flow analysis, such as 4D flow imaging, to identify patients with ventricular dysfunction and remodeling, increased arrhythmic risk, and more accurate grading of mitral regurgitation, ultimately benefiting patient selection for surgical therapy.

Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study

This study investigated the impact of ComBat harmonization on the reproducibility of radiomic features extracted from magnetic resonance images (MRI) acquired on different scanners, using various data acquisition parameters and multiple image pre-processing techniques using a dedicated MRI phantom. Four scanners were used to acquire an MRI of a nonanatomic phantom as part of the TCIA RIDER database. In fast spin-echo inversion recovery (IR) sequences, several inversion durations were employed, including 50, 100, 250, 500, 750, 1000, 1500, 2000, 2500, and 3000 ms. In addition, a 3D fast spoiled gradient recalled echo (FSPGR) sequence was used to investigate several flip angles (FA): 2, 5, 10, 15, 20, 25, and 30 degrees. Nineteen phantom compartments were manually segmented. Different approaches were used to pre-process each image: Bin discretization, Wavelet filter, Laplacian of Gaussian, logarithm, square, square root, and gradient. Overall, 92 first-, second-, and higher-order statistical radiomic features were extracted. ComBat harmonization was also applied to the extracted radiomic features. Finally, the Intraclass Correlation Coefficient (ICC) and Kruskal-Wallis's (KW) tests were implemented to assess the robustness of radiomic features. The number of non-significant features in the KW test ranged between 0-5 and 29-74 for various scanners, 31-91 and 37-92 for three times tests, 0-33 to 34-90 for FAs, and 3-68 to 65-89 for IRs before and after ComBat harmonization, with different image pre-processing techniques, respectively. The number of features with ICC over 90% ranged between 0-8 and 6-60 for various scanners, 11-75 and 17-80 for three times tests, 3-83 to 9-84 for FAs, and 3-49 to 3-63 for IRs before and after ComBat harmonization, with different image pre-processing techniques, respectively. The use of various scanners, IRs, and FAs has a great impact on radiomic features. However, the majority of scanner-robust features is also robust to IR and FA. Among the effective parameters in MR images, several tests in one scanner have a negligible impact on radiomic features. Different scanners and acquisition parameters using various image pre-processing might affect radiomic features to a large extent. ComBat harmonization might significantly impact the reproducibility of MRI radiomic features.

Advanced Myocardial MRI Tissue Characterization Combining Contrast Agent-Free T1-Rho Mapping With Fully Automated Analysis

BACKGROUND

Myocardial T1-rho (T1ρ) mapping is a promising method for identifying and quantifying myocardial injuries without contrast agents, but its clinical use is hindered by the lack of dedicated analysis tools.

PURPOSE

To explore the feasibility of clinically integrated artificial intelligence-driven analysis for efficient and automated myocardial T1ρ mapping.

STUDY TYPE

Retrospective.

POPULATION

Five hundred seventy-three patients divided into a training (N = 500) and a test set (N = 73) including ischemic and nonischemic cases.

FIELD STRENGTH/SEQUENCE

Single-shot bSSFP T1ρ mapping sequence at 1.5 T.

ASSESSMENT

The automated process included: left ventricular (LV) wall segmentation, right ventricular insertion point detection and creation of a 16-segment model for segmental T1ρ value analysis. Two radiologists (20 and 7 years of MRI experience) provided ground truth annotations. Interobserver variability and segmentation quality were assessed using the Dice coefficient with manual segmentation as reference standard. Global and segmental T1ρ values were compared. Processing times were measured.

STATISTICAL TESTS

Intraclass correlation coefficients (ICCs) and Bland-Altman analysis (bias ±2SD); Paired Student's t-tests and one-way ANOVA. A P value <0.05 was considered significant.

RESULTS

The automated approach significantly reduced processing time (3 seconds vs. 1 minute 51 seconds ± 22 seconds). In the test set, automated LV wall segmentation closely matched manual results (Dice 81.9% ± 9.0) and closely aligned with interobserver segmentation (Dice 82.2% ± 6.5). Excellent ICCs were achieved on a patient basis (0.94 [95% CI: 0.91 to 0.96]) with bias of -0.93 cm2 ± 6.60. There was no significant difference in global T1ρ values between manual (54.9 msec ± 4.6; 95% CI: 53.8 to 56.0 msec, range: 46.6-70.9 msec) and automated processing (55.4 msec ± 5.1; 95% CI: 54.2 to 56.6 msec; range: 46.4-75.1 msec; P = 0.099). The pipeline demonstrated a high level of agreement with manual-derived T1ρ values at the patient level (ICC = 0.85; bias +0.52 msec ± 5.18). No significant differences in myocardial T1ρ values were found between methods across the 16 segments (P = 0.75).

DATA CONCLUSION

Automated myocardial T1ρ mapping shows promise for the rapid and noninvasive assessment of heart disease.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 1.

The beating heart: artificial intelligence for cardiovascular application in the clinic

Artificial intelligence (AI) integration in cardiac magnetic resonance imaging presents new and exciting avenues for advancing patient care, automating post-processing tasks, and enhancing diagnostic precision and outcomes. The use of AI significantly streamlines the examination workflow through the reduction of acquisition and postprocessing durations, coupled with the automation of scan planning and acquisition parameters selection. This has led to a notable improvement in examination workflow efficiency, a reduction in operator variability, and an enhancement in overall image quality. Importantly, AI unlocks new possibilities to achieve spatial resolutions that were previously unattainable in patients. Furthermore, the potential for low-dose and contrast-agent-free imaging represents a stride toward safer and more patient-friendly diagnostic procedures. Beyond these benefits, AI facilitates precise risk stratification and prognosis evaluation by adeptly analysing extensive datasets. This comprehensive review article explores recent applications of AI in the realm of cardiac magnetic resonance imaging, offering insights into its transformative potential in the field.

Fully automated contrast selection of joint bright- and black-blood late gadolinium enhancement imaging for robust myocardial scar assessment

PURPOSE

Joint bright- and black-blood MRI techniques provide improved scar localization and contrast. Black-blood contrast is obtained after the visual selection of an optimal inversion time (TI) which often results in uncertainties, inter- and intra-observer variability and increased workload. In this work, we propose an artificial intelligence-based algorithm to enable fully automated TI selection and simplify myocardial scar imaging.

METHODS

The proposed algorithm first localizes the left ventricle using a U-Net architecture. The localized left cavity centroid is extracted and a squared region of interest ("focus box") is created around the resulting pixel. The focus box is then propagated on each image and the sum of the pixel intensity inside is computed. The smallest sum corresponds to the image with the lowest intensity signal within the blood pool and healthy myocardium, which will provide an ideal scar-to-blood contrast. The image's corresponding TI is considered optimal. The U-Net was trained to segment the epicardium in 177 patients with binary cross-entropy loss. The algorithm was validated retrospectively in 152 patients, and the agreement between the algorithm and two magnetic resonance (MR) operators' prediction of TI values was calculated using the Fleiss' kappa coefficient. Thirty focus box sizes, ranging from 2.3mm2 to 20.3cm2, were tested. Processing times were measured.

RESULTS

The U-Net's Dice score was 93.0 ± 0.1%. The proposed algorithm extracted TI values in 2.7 ± 0.1 s per patient (vs. 16.0 ± 8.5 s for the operator). An agreement between the algorithm's prediction and the MR operators' prediction was found in 137/152 patients (κ= 0.89), for an optimal focus box of size 2.3cm2.

CONCLUSION

The proposed fully-automated algorithm has potential of reducing uncertainties, variability, and workload inherent to manual approaches with promise for future clinical implementation for joint bright- and black-blood MRI.

Late/delayed gadolinium enhancement in MRI after intravenous administration of extracellular gadolinium-based contrast agents: is it worth waiting?

The acquisition of images minutes or even hours after intravenous extracellular gadolinium-based contrast agents (GBCA) administration ("Late/Delayed Gadolinium Enhancement" imaging; in this review, further termed LGE) has gained significant prominence in recent years in magnetic resonance imaging. The major limitation of LGE is the long examination time; thus, it becomes necessary to understand when it is worth waiting time after the intravenous injection of GBCA and which additional information comes from LGE. LGE can potentially be applied to various anatomical sites, such as heart, arterial vessels, lung, brain, abdomen, breast, and the musculoskeletal system, with different pathophysiological mechanisms. One of the most popular clinical applications of LGE regards the assessment of myocardial tissue thanks to its ability to highlight areas of acute myocardial damage and fibrotic tissues. Other frequently applied clinical contexts involve the study of the urinary tract with magnetic resonance urography and identifying pathological abdominal processes characterized by high fibrous stroma, such as biliary tract tumors, autoimmune pancreatitis, or intestinal fibrosis in Crohn's disease. One of the current areas of heightened research interest revolves around the possibility of non-invasively studying the dynamics of neurofluids in the brain (the glymphatic system), the disruption of which could underlie many neurological disorders.

Feasibility and image quality of bright-blood and black-blood phase-sensitive inversion recovery (BOOST) sequence in clinical practice using for left atrial visualization in patients with atrial fibrillation

OBJECTIVES

Visualizing left atrial anatomy including the pulmonary veins (PVs) is important for planning the procedure of pulmonary vein isolation with ablation in patients with atrial fibrillation (AF). The aims of our study are to investigate the feasibility of the 3D whole-heart bright-blood and black-blood phase-sensitive (BOOST) inversion recovery sequence in patients with AF scheduled for ablation or electro-cardioversion, and to analyze the correlation between image quality and heart rate and rhythm of patients.

METHODS

BOOST was performed for assessing PVs both with T2 preparation pre-pulse (T2prep) and magnetization transfer preparation (MTC) in 45 patients with paroxysmal or permanent AF scheduled for ablation or electro-cardioversion. Image quality analyses were performed by two independent observers. Qualitative assessment was made using the Likert scale; for quantitative analysis, signal to noise ratios (SNR) and contrast to noise ratios (CNR) were calculated for each PV. Heart rate and rhythm were analyzed based on standard 12-lead ECGs.

RESULTS

All MTC-BOOST acquisitions achieved diagnostic quality in the PVs, while a significant proportion of T2prep-BOOST images were not suitable for assessing PVs. SNR and CNR values of the MTC-BOOST bright-blood images were higher if patients had sinus rhythm. We found a significant or nearly significant negative correlation between heart rate and the SNR and CNR values of MTC-BOOST bright-blood images.

CONCLUSION

3D whole-heart MTC-BOOST bright-blood imaging is suitable for visualizing the PVs in patients with AF, producing diagnostic image quality in 100% of cases. However, image quality was influenced by heart rate and rhythm.

CLINICAL RELEVANCE STATEMENT

The novel 3D whole-heart BOOST CMR sequence needs no contrast administration and is performed during free-breathing; therefore, it is easy to use for a wide range of patients and is suitable for visualizing the PVs in patients with AF.

KEY POINTS

• The applicability of the novel 3D whole-heart bright-blood and black-blood phase-sensitive sequence to pulmonary vein imaging in clinical practice is unknown. • Magnetization transfer-bright-blood and black-blood phase-sensitive imaging is suitable for visualizing the pulmonary veins in patients with atrial fibrillation with excellent or good image quality. • Bright-blood and black-blood phase-sensitive cardiac magnetic resonance sequence is easy to use for a wide range of patients as it needs no contrast administration and is performed during free-breathing.

Assessment of myocardial injuries in ischaemic and non-ischaemic cardiomyopathies using magnetic resonance T1-rho mapping

AIMS

To identify clinical correlates of myocardial T1ρ and to examine how myocardial T1ρ values change under various clinical scenarios.

METHODS AND RESULTS

A total of 66 patients (26% female, median age 57 years [Q1-Q3, 44-65 years]) with known structural heart disease and 44 controls (50% female, median age 47 years [28-57 years]) underwent cardiac magnetic resonance imaging at 1.5 T, including T1ρ mapping, T2 mapping, native T1 mapping, late gadolinium enhancement, and extracellular volume (ECV) imaging. In controls, T1ρ positively related with T2 (P = 0.038) and increased from basal to apical levels (P < 0.001). As compared with controls and remote myocardium, T1ρ significantly increased in all patients' sub-groups and all types of myocardial injuries: acute and chronic injuries, focal and diffuse tissue abnormalities, as well as ischaemic and non-ischaemic aetiologies (P < 0.05). T1ρ was independently associated with T2 in patients with acute injuries (P = 0.004) and with native T1 and ECV in patients with chronic injuries (P < 0.05). Myocardial T1ρ mapping demonstrated good intra- and inter-observer reproducibility (intraclass correlation coefficient = 0.86 and 0.83, respectively).

CONCLUSION

Myocardial T1ρ mapping appears to be reproducible and equally sensitive to acute and chronic myocardial injuries, whether of ischaemic or non-ischaemic origins. It may thus be a contrast-agent-free biomarker for gaining new and quantitative insight into myocardial structural disorders. These findings highlight the need for further studies through prospective and randomized trials.

Incorporation of view sharing and KWIC filtering into GRASP-Pro improves spatial resolution of single-shot, multi-TI, late gadolinium enhancement MRI

While single-shot late gadolinium enhancement (LGE) is useful for imaging patients with arrhythmia and/or dyspnea, it produces low spatial resolution. One approach to improve spatial resolution is to accelerate data acquisition using compressed sensing (CS). Our previous work described a single-shot, multi-inversion time (TI) LGE pulse sequence using radial k-space sampling and CS, but over-regularization resulted in significant image blurring that muted the benefits of data acceleration. The purpose of the present study was to improve the spatial resolution of the single-shot, multi-TI LGE pulse sequence by incorporating view sharing (VS) and k-space weighted contrast (KWIC) filtering into a GRASP-Pro reconstruction. In 24 patients (mean age = 61 ± 16 years; 9/15 females/males), we compared the performance of our improved multi-TI LGE and standard multi-TI LGE, where clinical standard LGE was used as a reference. Two clinical raters independently graded multi-TI images and clinical LGE images visually on a five-point Likert scale (1, nondiagnostic; 3, clinically acceptable; 5, best) for three categories: the conspicuity of myocardium or scar, artifact, and noise. The summed visual score (SVS) was defined as the sum of the three scores. Myocardial scar volume was quantified using the full-width at half-maximum method. The SVS was not significantly different between clinical breath-holding LGE (median 13.5, IQR 1.3) and multi-TI LGE (median 12.5, IQR 1.6) (P = 0.068). The myocardial scar volumes measured from clinical standard LGE and multi-TI LGE were strongly correlated (coefficient of determination, R2  = 0.99) and in good agreement (mean difference = 0.11%, lower limit of the agreement = -2.13%, upper limit of the agreement = 2.34%). The inter-rater agreement in myocardial scar volume quantification was strong (intraclass correlation coefficient = 0.79). The incorporation of VS and KWIC into GRASP-Pro improved spatial resolution. Our improved 25-fold accelerated, single-shot LGE sequence produces clinically acceptable image quality, multi-TI reconstruction, and accurate myocardial scar volume quantification.

Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning

BACKGROUND

A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI may help streamline the diagnostic workflow. To develop a DL model to detect cardiac pathologies on cardiac MRI T1-mapping and late gadolinium phase sensitive inversion recovery (PSIR) sequences were used.

METHODS

Subjects in this study were either diagnosed with cardiac pathology (n = 137) including acute and chronic myocardial infarction, myocarditis, dilated cardiomyopathy, and hypertrophic cardiomyopathy or classified as normal (n = 63). Cardiac MR imaging included T1-mapping and PSIR sequences. Subjects were split 65/15/20% for training, validation, and hold-out testing. The DL models were based on an ImageNet pretrained DenseNet-161 and implemented using PyTorch and fastai. Data augmentation with random rotation and mixup was applied. Categorical cross entropy was used as the loss function with a cyclic learning rate (1e-3). DL models for both sequences were developed separately using similar training parameters. The final model was chosen based on its performance on the validation set. Gradient-weighted class activation maps (Grad-CAMs) visualized the decision-making process of the DL model.

RESULTS

The DL model achieved a sensitivity, specificity, and accuracy of 100%, 38%, and 88% on PSIR images and 78%, 54%, and 70% on T1-mapping images. Grad-CAMs demonstrated that the DL model focused its attention on myocardium and cardiac pathology when evaluating MR images.

CONCLUSIONS

The developed DL models were able to reliably detect cardiac pathologies on cardiac MR images. The diagnostic performance of T1 mapping alone is particularly of note since it does not require a contrast agent and can be acquired quickly.

MRI Quantification of Cardiac Structure and Function in Cardiomyopathy Patients

Cardiac Magnetic Resonance Imaging (CMRI) is a quantitative technique that enables non-invasive assessment of heart structure and contractile function as well as the mechanisms underlying cardiovascular disease. Here we provide step-by-step instructions and imaging protocols for conducting cardiac MRI exam on the patients with cardiomyopathies. Our imaging protocols are specific to the 3 Tesla magnetic field strength.

Using Phase Difference Information to Detect Errors in the Flip Angle Measured with Actual Flip Angle Imaging at 7T

Flip angle (FA) measurements using the actual flip angle imaging (AFI) method may induce significant errors in ultrahigh fields. We aimed to develop a method for detecting errors in FA measurements using phase information at 7 tesla. We performed computer simulations to elucidate the relationship between the FA calculation errors and the phase difference between the two AFI source images. We then examined whether a method based on the phase difference could detect FA calculation errors and determine the prescribed nominal FA of the scanner for accurate measurements in phantoms and healthy volunteers. The simulations confirmed that the calculated FA values erroneously decreased when the longitudinal magnetization and phase in one of the source images were inverted. Tests on phantoms and human subjects demonstrated that the phase difference information between the source images with a cut-off of 90° could readily detect FA calculation errors in the AFI method.

Assessment of the Severity of Aortic Regurgitation by Noninvasive Imaging : Non-invasive MMI for AR

PURPOSE OF THE REVIEW

The role of multimodality imaging in the evaluation of patients with aortic regurgitation is summarized in this review.

RECENT FINDINGS

The etiology (mechanism) of the aortic regurgitation and the severity of aortic regurgitation and hemodynamic consequences are key in the decision making of patients with severe aortic regurgitation. While echocardiography remains as the leading technique to assess all these parameters, other imaging techniques have become essential for the accurate assessment of aortic regurgitation severity and the timing of aortic intervention. The anatomic suitability of transcatheter aortic valve implantation in inoperable patients with severe aortic regurgitation is usually assessed with computed tomography. Aortic regurgitation is a prevalent disease with various pathophysiological mechanisms that need a personalized treatment. The evaluation of the mechanism and severity of aortic regurgitation can be initially performed with echocardiography. Three-dimensional techniques, including echocardiography, have become very relevant for accurate assessment of the regurgitation severity and its hemodynamic consequences. Assessment of myocardial tissue characteristics with cardiac magnetic resonance is key in the risk stratification of patients and in the timing of aortic intervention. Computed tomography is important in the assessment of aortic dimensions and selection of patients for transcatheter aortic valve implantation.

Novel insights into diminished cardiac reserve in non-obstructive hypertrophic cardiomyopathy from four-dimensional flow cardiac magnetic resonance component analysis

AIMS

Hypertrophic cardiomyopathy (HCM) is characterized by hypercontractility and diastolic dysfunction, which alter blood flow haemodynamics and are linked with increased risk of adverse clinical events. Four-dimensional flow cardiac magnetic resonance (4D-flow CMR) enables comprehensive characterization of ventricular blood flow patterns. We characterized flow component changes in non-obstructive HCM and assessed their relationship with phenotypic severity and sudden cardiac death (SCD) risk.

METHODS AND RESULTS

Fifty-one participants (37 non-obstructive HCM and 14 matched controls) underwent 4D-flow CMR. Left-ventricular (LV) end-diastolic volume was separated into four components: direct flow (blood transiting the ventricle within one cycle), retained inflow (blood entering the ventricle and retained for one cycle), delayed ejection flow (retained ventricular blood ejected during systole), and residual volume (ventricular blood retained for >two cycles). Flow component distribution and component end-diastolic kinetic energy/mL were estimated. HCM patients demonstrated greater direct flow proportions compared with controls (47.9 ± 9% vs. 39.4 ± 6%, P = 0.002), with reduction in other components. Direct flow proportions correlated with LV mass index (r = 0.40, P = 0.004), end-diastolic volume index (r = -0.40, P = 0.017), and SCD risk (r = 0.34, P = 0.039). In contrast to controls, in HCM, stroke volume decreased with increasing direct flow proportions, indicating diminished volumetric reserve. There was no difference in component end-diastolic kinetic energy/mL.

CONCLUSION

Non-obstructive HCM possesses a distinctive flow component distribution pattern characterised by greater direct flow proportions, and direct flow-stroke volume uncoupling indicative of diminished cardiac reserve. The correlation of direct flow proportion with phenotypic severity and SCD risk highlight its potential as a novel and sensitive haemodynamic measure of cardiovascular risk in HCM.

Modeling of factors affecting late gadolinium enhancement kinetics in MRI of cardiac amyloid

BACKGROUND

Late gadolinium enhancement (LGE) is a valuable part of cardiac magnetic resonance imaging (CMR). In particular, inversion-recovery imaging of LGE, with nulling of the signal from reference areas of myocardium, can have a distinctive pattern in some patients with cardiac amyloid, including both diffuse (relatively faint) subendocardial LGE and a relatively dark appearance of the blood. However, the underlying reasons for this distinctive appearance have not previously been well investigated. Pharmacokinetic modeling of myocardial contrast enhancement kinetics can potentially provide insight into the mechanisms of the distinctive LGE appearance that can be seen in cardiac amyloid, as well as why it may be unreliable in some patients.

METHODS

An interactive three-compartment pharmacokinetic model of the dynamics of myocardial contrast enhancement in CMR was implemented, and used to simulate LGE dynamics in normal, scar, and cardiac amyloid myocardium; the results were compared with previously published values.

RESULTS

The three-compartment model is able to capture the qualitative features of LGE, in patients with cardiac amyloid. In particular, the characteristic "dark blood" appearance of PSIR images of LGE in cardiac amyloid is seen to likely primarily reflect expansion of the extravascular extracellular space (EES) by amyloid in the "reference" myocardium; the cardiac amyloid contrast enhancement dynamics also reflect expansion of the body EES.

CONCLUSION

The distinctive appearance of LGE in cardiac amyloid is likely due to a combination of diffuse expansion by amyloid of the EES of the reference myocardium and of the body EES.

Deep Learning-Based Reconstruction for Cardiac MRI: A Review

Cardiac magnetic resonance (CMR) is an essential clinical tool for the assessment of cardiovascular disease. Deep learning (DL) has recently revolutionized the field through image reconstruction techniques that allow unprecedented data undersampling rates. These fast acquisitions have the potential to considerably impact the diagnosis and treatment of cardiovascular disease. Herein, we provide a comprehensive review of DL-based reconstruction methods for CMR. We place special emphasis on state-of-the-art unrolled networks, which are heavily based on a conventional image reconstruction framework. We review the main DL-based methods and connect them to the relevant conventional reconstruction theory. Next, we review several methods developed to tackle specific challenges that arise from the characteristics of CMR data. Then, we focus on DL-based methods developed for specific CMR applications, including flow imaging, late gadolinium enhancement, and quantitative tissue characterization. Finally, we discuss the pitfalls and future outlook of DL-based reconstructions in CMR, focusing on the robustness, interpretability, clinical deployment, and potential for new methods.

Free-breathing, Contrast Agent-free Whole-Heart MTC-BOOST Imaging: Single-Center Validation Study in Adult Congenital Heart Disease

Purpose

To assess the clinical performance of the three-dimensional, free-breathing, Magnetization Transfer Contrast Bright-and-black blOOd phase-SensiTive (MTC-BOOST) sequence in adult congenital heart disease (ACHD).

Materials and Methods

In this prospective study, participants with ACHD undergoing cardiac MRI between July 2020 and March 2021 were scanned with the clinical T2-prepared balanced steady-state free precession sequence and proposed MTC-BOOST sequence. Four cardiologists scored their diagnostic confidence on a four-point Likert scale for sequential segmental analysis on images acquired with each sequence. Scan times and diagnostic confidence were compared using the Mann-Whitney test. Coaxial vascular dimensions at three anatomic landmarks were measured, and agreement between the research sequence and the corresponding clinical sequence was assessed with Bland-Altman analysis.

Results

The study included 120 participants (mean age, 33 years ± 13 [SD]; 65 men). The mean acquisition time of the MTC-BOOST sequence was significantly lower compared with that of the conventional clinical sequence (9 minutes ± 2 vs 14 minutes ± 5; P < .001). Diagnostic confidence was higher for the MTC-BOOST sequence compared with the clinical sequence (mean, 3.9 ± 0.3 vs 3.4 ± 0.7; P < .001). Narrow limits of agreement and mean bias less than 0.08 cm were found between the research and clinical vascular measurements.

Conclusion

The MTC-BOOST sequence provided efficient, high-quality, and contrast agent-free three-dimensional whole-heart imaging in ACHD, with shorter, more predictable acquisition time and improved diagnostic confidence compared with the reference standard clinical sequence.Keywords: MR Angiography, Cardiac Supplemental material is available for this article. Published under a CC BY 4.0 license.

Magnetization Transfer BOOST Noncontrast Angiography Improves Pulmonary Vein Imaging in Adults With Congenital Heart Disease

BACKGROUND

Cardiac MRI plays an important role in the diagnosis and follow-up of patients with congenital heart disease (CHD). Gadolinium-based contrast agents are often needed to overcome flow-related and off-resonance artifacts that can impair the quality of conventional noncontrast 3D imaging. As serial imaging is often required in CHD, the development of robust noncontrast 3D MRI techniques is desirable.

PURPOSE

To assess the clinical utility of noncontrast enhanced magnetization transfer and inversion recovery prepared 3D free-breathing sequence (MTC-BOOST) compared to conventional 3D whole heart imaging in patients with CHD.

STUDY TYPE

Prospective, image quality.

POPULATION

A total of 27 adult patients (44% female, mean age 30.9 ± 14.8 years) with CHD.

FIELD STRENGTH/SEQUENCE

A 1.5 T; free-breathing 3D MTC-BOOST sequence.

ASSESSMENT

MTC-BOOST was compared to diaphragmatic navigator-gated, noncontrast T2 prepared 3D whole-heart imaging sequence (T2prep-3DWH) for comparison of vessel dimensions, lumen-to-myocardium contrast ratio (CR), and image quality (vessel wall sharpness and presence and type of artifacts) assessed by two experienced cardiologists on a 5-point scale.

STATISTICAL TESTS

Mann-Whitney test, paired Wilcoxon signed-rank test, Bland-Altman plots. P < 0.05 was considered statistically significant.

RESULTS

MTC-BOOST significantly improved image quality and CR of the right-sided pulmonary veins (PV): (CR: right upper PV 1.06 ± 0.50 vs. 0.58 ± 0.74; right lower PV 1.32 ± 0.38 vs. 0.81 ± 0.73) compared to conventional T2prep-3DWH imaging where the PVs were not visualized in some cases due to off-resonance effects. MTC-BOOST demonstrated resistance to degradation of luminal signal (assessed by CR) secondary to accelerated or turbulent flow conditions. T2prep-3DWH had higher image quality scores than MTC-BOOST for the aorta and coronary arteries; however, great vessel dimensions derived from MTC-BOOST showed excellent agreement with standard T2prep-3DWH imaging.

DATA CONCLUSION

MTC-BOOST allows for improved contrast-free imaging of pulmonary veins and regions characterized by accelerated or turbulent blood flow compared to standard T2prep-3DWH imaging, with excellent agreement of great vessel dimensions.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Non-invasive diagnosis of transthyretin cardiac amyloidosis utilizing typical late gadolinium enhancement pattern on cardiac magnetic resonance and light chains

AIMS

While cardiac magnetic resonance (CMR) is often obtained early in the evaluation of suspected cardiac amyloidosis (CA), it currently cannot be utilized to differentiate immunoglobulin (AL) and transthyretin (ATTR) CA. We aimed to determine whether a novel CMR and light-chain biomarker-based algorithm could accurately diagnose ATTR-CA.

METHODS AND RESULTS

Patients with confirmed AL or ATTR-CA with typical late gadolinium enhancement (LGE) and Look-Locker pattern for CA on CMR were retrospectively identified at three academic medical centres. Comprehensive light-chain analysis including free light chains, serum, and urine electrophoresis/immunofixation was performed. The diagnostic accuracy of the typical CMR pattern for CA in combination with negative light chains for the diagnosis of ATTR-CA was determined both in the entire cohort and in the subset of patients with invasive tissue biopsy as the gold standard. A total of 147 patients (age 70 ± 11, 76% male, 51% black) were identified: 89 ATTR-CA and 58 AL-CA. Light-chain biomarkers were abnormal in 81 (55%) patients. Within the entire cohort, the sensitivity and specificity of a typical LGE and Look-Locker CMR pattern and negative light chains for ATTR-CA was 73 and 98%, respectively. Within the subset with biopsy-confirmed subtype, the CMR and light-chain algorithm were 69% sensitive and 98% specific.

CONCLUSION

The combination of a typical LGE and Look-Locker pattern on CMR with negative light chains is highly specific for ATTR-CA. The successful non-invasive diagnosis of ATTR-CA using CMR has the potential to reduce diagnostic and therapeutic delays and healthcare costs for many patients.

Myocardial First-Pass Perfusion With Increased Anatomic Coverage at 3 T Using Autocalibrated Multiband Imaging

BACKGROUND

Myocardial first-pass perfusion (FPP) imaging is a useful cardiac MRI method for the diagnosis of coronary artery disease. However, conventional 2D multislice FPP acquisitions usually have gaps between myocardium slices, which limits the overall assessment of myocardial ischemia.

PURPOSE

To increase the anatomic coverage of myocardial FPP imaging at 3 T by implementing both autocalibrated multiband (MB) acquisition and k-t space acceleration with compress sensing (CS) reconstruction, without the need for additional reference scans.

STUDY TYPE

Phantom and prospective human studies.

PHANTOM/SUBJECTS

A T1MES (T1 Mapping and ECV Standardization in cardiovascular magnetic resonance) phantom and 20 subjects (12 healthy subjects and 8 patients, 10 males, age 42 ± 16 years).

FIELD STRENGTH/SEQUENCE

A 3 T/saturation recovery prepared gradient echo sequence with contrast administration.

ASSESSMENT

Phantom experiments were performed to compare the performance of autocalibrated MB-FPP with k-t acceleration using slice-GRAPPA and CS reconstructions. In vivo experiments were performed to compare the performance of conventional FPP (2.5× acceleration) with autocalibrated MB + CS-FPP (6× acceleration). In phantom experiments, the error maps were calculated. In in vivo experiments, the contrast ratio (CR) and blurring were quantitatively measured, while image quality, perceived signal-to-noise ratio (SNR), and artifact level were qualitatively graded by three cardiologists on a 4-point scale.

STATISTICAL TESTS

Wilcoxon signed-rank test, paired t-test. A P value <0.05 was considered statistically significant.

RESULTS

In phantom experiments, residual artifact was reduced using the MB + CS-FPP reconstruction method compared with using the MB + slice-GRAPPA reconstruction method. In in vivo experiments, the proposed autocalibrated MB + CS-FPP method demonstrated significantly higher CR (3.52 ± 0.78 vs 2.91 ± 0.81) and had significantly better perceived SNR (2.69 ± 0.29 vs 2.48 ± 0.31) compared to the conventional sequence. Compared with conventional FPP, MB + CS-FPP doubled the spatial coverage (MB + CS-FPP vs conventional FPP) without compromising the image quality (2.69 ± 0.26 vs 2.60 ± 0.30) or increasing the artifact level (2.60 ± 0.26 vs 2.52 ± 0.31).

CONCLUSION

Autocalibrated MB + CS-FPP improved the myocardial coverage and achieved comparable image quality with the same spatial resolution and scan time as conventional FPP and is a promising technique for clinical myocardial perfusion imaging.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 3.

Impairment in quantitative microvascular function in non-ischemic cardiomyopathy as demonstrated using cardiovascular magnetic resonance

Background

Microvascular dysfunction (MVD) is present in various cardiovascular diseases and portends worse outcomes. We assessed the prevalence of MVD in patients with non-ischemic cardiomyopathy (NICM) as compared to subjects with preserved ejection fraction (EF) using stress cardiovascular magnetic resonance (CMR).

Methods

We retrospectively studied consecutive patients with NICM and 58 subjects with preserved left ventricular (LV) EF who underwent stress CMR between 2011–2016. MVD was defined visually as presence of a subendocardial perfusion defect and semiquantitatively by myocardial perfusion reserve index (MPRI<1.51). MPRI was compared between groups using univariate analysis and multivariable linear regression.

Results

In total, 41 patients with NICM (mean age 51 ± 14, 59% male) and 58 subjects with preserved LVEF (mean age 51 ± 13, 31% male) were identified. In the NICM group, MVD was present in 23 (56%) and 11 (27%) by semiquantitative and visual evaluation respectively. Compared to those with preserved LVEF, NICM patients had lower rest slope (3.9 vs 4.9, p = 0.05) and stress perfusion slope (8.8 vs 11.7, p<0.001), and MPRI (1.41 vs 1.74, p = 0.02). MPRI remained associated with NICM after controlling for age, gender, hypertension, ethnicity, diabetes, and late gadolinium enhancement (log MPR, β coefficient = -0.19, p = 0.007).

Conclusions

MVD—as assessed using CMR—is highly prevalent in NICM as compared to subjects with preserved LVEF even after controlling for covariates. Semiquantitative is able to detect a greater number of incidences of MVD compared to visual methods alone. Further studies are needed to determine whether treatment of MVD is beneficial in NICM.

Accelerating 3D MTC-BOOST in patients with congenital heart disease using a joint multi-scale variational neural network reconstruction

PURPOSE

Free-breathing Magnetization Transfer Contrast Bright blOOd phase SensiTive (MTC-BOOST) is a prototype balanced-Steady-State Free Precession sequence for 3D whole-heart imaging, that employs the endogenous magnetisation transfer contrast mechanism. This achieves reduction of flow and off-resonance artefacts, that often arise with the clinical T2prepared balanced-Steady-State Free Precession sequence, enabling high quality, contrast-agent free imaging of the thoracic cardiovascular anatomy. Fully-sampled MTC-BOOST acquisition requires long scan times (~10-24 min) and therefore acceleration is needed to permit its clinical incorporation. The aim of this study is to enable and clinically validate the 5-fold accelerated MTC-BOOST acquisition with joint Multi-Scale Variational Neural Network (jMS-VNN) reconstruction.

METHODS

Thirty-six patients underwent free-breathing, 3D whole-heart imaging with the MTC-BOOST sequence, which is combined with variable density spiral-like Cartesian sampling and 2D image navigators for translational motion estimation. This sequence acquires two differently weighted bright-blood volumes in an interleaved fashion, which are then joined in a phase sensitive inversion recovery reconstruction to obtain a complementary fully co-registered black-blood volume. Data from eighteen patients were used for training, whereas data from the remaining eighteen patients were used for testing/evaluation. The proposed deep-learning based approach adopts a supervised multi-scale variational neural network for joint reconstruction of the two differently weighted bright-blood volumes acquired with the 5-fold accelerated MTC-BOOST. The two contrast images are stacked as different channels in the network to exploit the shared information. The proposed approach is compared to the fully-sampled MTC-BOOST and 5-fold undersampled MTC-BOOST acquisition with Compressed Sensing (CS) reconstruction in terms of scan/reconstruction time and bright-blood image quality. Comparison against conventional 2-fold undersampled T2-prepared 3D bright-blood whole-heart clinical sequence (T2prep-3DWH) is also included.

RESULTS

Acquisition time was 3.0 ± 1.0 min for the 5-fold accelerated MTC-BOOST versus 9.0 ± 1.1 min for the fully-sampled MTC-BOOST and 11.1 ± 2.6 min for the T2prep-3DWH (p < 0.001 and p < 0.001, respectively). Reconstruction time was significantly lower with the jMS-VNN method compared to CS (10 ± 0.5 min vs 20 ± 2 s, p < 0.001). Image quality was higher for the proposed 5-fold undersampled jMS-VNN versus conventional CS, comparable or higher to the corresponding T2prep-3DWH dataset and similar to the fully-sampled MTC-BOOST.

CONCLUSION

The proposed 5-fold accelerated jMS-VNN MTC-BOOST framework provides efficient 3D whole-heart bright-blood imaging in fast acquisition and reconstruction time with concomitant reduction of flow and off-resonance artefacts, that are frequently encountered with the clinical sequence. Image quality of the cardiac anatomy and thoracic vasculature is comparable or superior to the clinical scan and 5-fold CS reconstruction in faster reconstruction time, promising potential clinical adoption.

Cardiac phase-resolved late gadolinium enhancement imaging

Late gadolinium enhancement (LGE) with cardiac magnetic resonance (CMR) imaging is the clinical reference for assessment of myocardial scar and focal fibrosis. However, current LGE techniques are confined to imaging of a single cardiac phase, which hampers assessment of scar motility and does not allow cross-comparison between multiple phases. In this work, we investigate a three step approach to obtain cardiac phase-resolved LGE images: (1) Acquisition of cardiac phase-resolved imaging data with varying T₁ weighting. (2) Generation of semi-quantitative T1* maps for each cardiac phase. (3) Synthetization of LGE contrast to obtain functional LGE images. The proposed method is evaluated in phantom imaging, six healthy subjects at 3T and 20 patients at 1.5T. Phantom imaging at 3T demonstrates consistent contrast throughout the cardiac cycle with a coefficient of variation of 2.55 ± 0.42%. In-vivo results show reliable LGE contrast with thorough suppression of the myocardial tissue is healthy subjects. The contrast between blood and myocardium showed moderate variation throughout the cardiac cycle in healthy subjects (coefficient of variation 18.2 ± 3.51%). Images were acquired at 40–60 ms and 80 ms temporal resolution, at 3T and 1.5, respectively. Functional LGE images acquired in patients with myocardial scar visualized scar tissue throughout the cardiac cycle, albeit at noticeably lower imaging resolution and noise resilience than the reference technique. The proposed technique bears the promise of integrating the advantages of phase-resolved CMR with LGE imaging, but further improvements in the acquisition quality are warranted for clinical use.

Prognostic significance of myocardial salvage assessed by cardiac magnetic resonance in reperfused ST-segment elevation myocardial infarction

Aims

Myocardial salvage index (MSI) is attracting increasing attention for predicting prognosis in acute myocardial infarction (AMI); however, the evaluation of MSI is mainly based on contrast agent-dependent cardiac magnetic resonance (CMR) scanning sequences. This study aims to investigate the prognostic value of MSI in reperfused ST-segment elevation myocardial infarction (STEMI) through the contrast agent-free CMR technique.

Methods and results

Nighty-two patients with acute STEMI, who underwent CMR after primary percutaneous coronary intervention (PPCI), were finally enrolled. Patients were subcategorized into two groups according to median MSI. T1 and T2 mapping were conducted for measuring infarct size (IS) and area at risk (AAR). IS was significantly larger in < median MSI group than ≥ median MSI group (P < 0.001). AAR between the two groups showed no obvious differences (P = 0.108). Left ventricular ejection fraction (LVEF) was lower in < median MSI group than ≥ median MSI group (P = 0.014). There was an obvious inverse correlation between MSI and reperfusion time (R = –0.440, P < 0.001) and a strong inverse correlation between MSI and IS (R = –0.716, P = 0.011). As for the relationship LVEF, MSI showed positive but weak correlation (R = 0.2265, P < 0.001). Over a median follow-up period of 263 (227–238) days, prevalence of MACEs was significantly higher in the < median MSI group [HR: 0.15 (0.04–0.62); Log-rank P = 0.008]. The univariate Cox regression analysis revealed that LVEF, IS, and MSI were significant predictors for major adverse cardiovascular events (MACEs) (all P < 0.05). In the stepwise multivariate Cox regression analysis, LVEF and MSI were identified as independent parameters for predicting MACEs (both P < 0.05). In the receiver-operating characteristic analysis, LVEF, IS, and MSI showed prognostic value in predicting MACEs with AUCs of 0.809, 0.779, and 0.896, respectively, all (P < 0.05). A combination of MSI with LVEF showed the strongest prognostic value of MACEs (AUC: 0.901, sensitivity: 77.78%, specificity: 98.80%, P < 0.001). Delong’s test showed that the combination of LVEF with MSI had an incremental value than LVEF itself in predicting MACEs (P = 0.026).

Conclusion

Contrast agent-free CMR technique provides a reliable evaluation of MSI, which contributes to assessing the efficacy of reperfusion therapy and predicting the occurrence of MACEs.

A novel myocardial T1 analysis method robust to fluctuations in longitudinal magnetization recovery due to heart rate variability in polarity-corrected inversion time preparation

Myocardial T1 mapping is useful for characterizing the myocardial tissues. Polarity-corrected inversion time preparation (PCTIP), one of the T1 mapping techniques, was expected to reduce measurement underestimation versus the MOLLI method. However, measurement accuracy is reportedly reduced, especially at high heart rates (HR), owing to the shorter time interval of inversion recovery (IR) pulses. This phantom-based experiment aimed to evaluate the dependence of T1 mapping with PCTIP on HR. Here we proposed and evaluated the effectiveness of a novel HR-independent analysis method for T1 mapping. A PCTIP scan using a 3-T magnetic resonance imaging scanner was performed on a T1 measurement phantom. The virtual HR were set at 50, 60, 75, and 100 bpm. The T1 of the phantom was estimated by a least-squares fit of the PCTIP data for each obtained inversion time and a theoretical longitudinal relaxation formula. This analysis was performed for the conventional and proposed formulas. The proposed formula was derived for adapting to the transient state of longitudinal magnetization recovery caused by the trigger interval as a recurrence formula. The estimated T1 measurements using the conventional formula varied widely with HR and the accuracy decreased, especially at a high HR. However, the proposed analysis showed good accuracy versus the conventional method independent of HR. T1 mapping using the PCTIP method combined with the novel method proposed here showed good accuracy.

Isotropic 3D compressed sensing (CS) based sequence is comparable to 2D-LGE in left ventricular scar quantification in different disease entities

The goal of this study was to evaluate a three-dimensional compressed sensing (3D-CS) LGE prototype sequence for the detection and quantification of myocardial fibrosis in patients with chronic myocardial infarction (CMI) and myocarditis (MYC) compared with a 2D-LGE standard. Patients with left-ventricular LGE due to CMI (n = 33) or MYC (n = 20) were prospectively recruited. 2D-LGE and 3D-CS images were acquired in random order at 1.5 Tesla. 3D-CS short axis (SAX) images were reconstructed corresponding to 2D SAX images. LGE was quantitatively assessed on patient and segment level using semi-automated threshold methods. Image quality (4-point scoring system), Contrast-ratio (CR) and acquisition times were compared. There was no significant difference between 2D and 3D sequences regarding global LGE (%) (CMI [2D-LGE: 11.4 ± 7.5; 3D-LGE: 11.5 ± 8.5; p = 0.99]; MYC [2D-LGE: 27.0 ± 15.7; 3D-LGE: 26.2 ± 13.1; p = 0.70]) and segmental LGE-extent (p = 0.63). 3D-CS identified papillary infarction in 5 cases which was not present in 2D images. 2D-LGE acquisition time was shorter (2D: median: 06:59 min [IQR: 05:51-08:18]; 3D: 14:48 min [12:45-16:57]). 3D-CS obtained better quality scores (2D: 2.06 ± 0.56 vs. 3D: 2.29 ± 0.61). CR did not differ (p = 0.63) between basal and apical regions in 3D-CS images but decreased significantly in 2D apical images (CR basal: 2D: 0.77 ± 0.11, 3D: 0.59 ± 0.10; CR apical: 2D: 0.64 ± 0.17, 3D: 0.53 ± 0.11). 3D-LGE shows high congruency with standard LGE and allows better identification of small lesions. However, the current 3D-CS LGE sequence did not provide PSIR reconstruction and acquisition time was longer.

Role of Cardiovascular Magnetic Resonance to Assess Cardiovascular Inflammation

Cardiovascular inflammatory diseases still represent a challenge for physicians. Inflammatory cardiomyopathy, pericarditis, and large vessels vasculitis can clinically mimic a wide spectrum of diseases. While the underlying etiologies are varied, the common physio-pathological process is characterized by vasodilation, exudation, leukocytes infiltration, cell damage, and fibrosis. Cardiovascular magnetic resonance (CMR) allows the visualization of some of these diagnostic targets. CMR provides not only morphological and functional assessment but also tissue catheterization revealing edema, hyperemia, tissue injury, and reparative fibrosis through T2 weighted images, early and late gadolinium enhancement, and parametric mapping techniques. Recent developments showed the role of CMR in the identification of ongoing inflammation also in other CV diseases like myocardial infarction, atherosclerosis, arrhythmogenic and hypertrophic cardiomyopathy. Future developments of CMR, aiming at the specific assessment of immune cell infiltration, will give deeper insight into cardiovascular inflammatory diseases.

The image quality and diagnostic accuracy of T1-mapping-based synthetic late gadolinium enhancement imaging: comparison with conventional late gadolinium enhancement imaging in real-life clinical situation

BACKGROUNDS

Synthetic late gadolinium enhancement (LGE) images are less sensitive to inversion time (TI) and robust to motion artifact, because it is generated retrospectively by post-contrast T1-mapping images. To explore the clinical applicability of synthetic LGE, we investigated the image quality and diagnostic accuracy of synthetic LGE images, in comparison to that of conventional LGE for various disease groups.

METHOD AND MATERIALS

From July to November 2019, a total of 98 patients who underwent cardiovascular magnetic resonance imaging (CMR), including LGE and T1-mapping sequences, with suspicion of myocardial abnormality were retrospectively included. Synthetic magnitude inversion-recovery (IR) and phase-sensitive IR (PSIR) images were generated through calculations based on the post-contrast T1-mapping sequence. Three cardiothoracic radiologists independently analyzed the image quality of conventional and synthetic LGE images on an ordinal scale with per-segment basis and the image qualities were compared with chi-square test. The agreement of LGE detection was analyzed on per-patient and per-segment basis with Cohen's kappa test. In addition, the LGE area and percentage were semi-quantitatively analyzed for LGE positive ischemic (n = 14) and hypertrophic cardiomyopathy (n = 13) subgroups by two cardiothoracic radiologists. The difference of quantified LGE area and percentage between conventional and synthetic LGE images were assessed with Mann-Whitney U-test and the inter-reader agreement was assessed with Bland-Altman analysis.

RESULTS

The image quality of synthetic images was significantly better than conventional images in both magnitude IR and PSIR through all three observers (P < 0.001, all). The agreements of per-patient and per-segment LGE detection rates were excellent (kappa = 0.815-0.864). The semi-quantitative analysis showed no significant difference in the LGE area and percentage between conventional and synthetic LGE images. In the inter-reader agreement showed only small systematic differences in both magnitude IR and PSIR and synthetic LGE images showed smaller systematic biases compared to conventional LGE images.

CONCLUSION

Compared to conventional LGE images, synthetic LGE images have better image quality in real-life clinical situation.

Study protocol: MyoFit46-the cardiac sub-study of the MRC National Survey of Health and Development

BACKGROUND

The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world's longest running continued surveillance birth cohort providing a unique opportunity to understand life course determinants of myocardial dysfunction as part of MyoFit46-the cardiac sub-study of the NSHD.

METHODS

We aim to recruit 550 NSHD participants of approximately 75 years+ to undertake high-density surface electrocardiographic imaging (ECGI) and stress perfusion cardiovascular magnetic resonance (CMR). Through comprehensive myocardial tissue characterization and 4-dimensional flow we hope to better understand the burden of clinical and subclinical cardiovascular disease. Supercomputers will be used to combine the multi-scale ECGI and CMR datasets per participant. Rarely available, prospectively collected whole-of-life data on exposures, traditional risk factors and multimorbidity will be studied to identify risk trajectories, critical change periods, mediators and cumulative impacts on the myocardium.

DISCUSSION

By combining well curated, prospectively acquired longitudinal data of the NSHD with novel CMR-ECGI data and sharing these results and associated pipelines with the CMR community, MyoFit46 seeks to transform our understanding of how early, mid and later-life risk factor trajectories interact to determine the state of cardiovascular health in older age.

TRIAL REGISTRATION

Prospectively registered on ClinicalTrials.gov with trial ID: 19/LO/1774 Multimorbidity Life-Course Approach to Myocardial Health- A Cardiac Sub-Study of the MCRC National Survey of Health and Development (NSHD).

Cardiovascular magnetic resonance for suspected cardiac amyloidosis: where are we now?

Cardiac amyloidosis (CA) is an underdiagnosed form of restrictive cardiomyopathy leading to a rapid progression into heart failure. Evaluation of CA requires a multimodality approach making use of echocardiography, cardiac magnetic imaging (CMR), and nuclear imaging. With superior tissue characterization, high-resolution imaging, and precise cardiac assessment, CMR has emerged as a versatile tool in the workup of cardiac amyloidosis with a wide array of parameters both visual and quantitative. This includes late gadolinium enhancement patterns, T1/T2 mapping, and extracellular volume (ECV) measurement providing robust diagnostic accuracies, patient stratification, and prognostication. Recent advancements have introduced new measures able to identify early disease, track disease progression, and response to therapy positioning CMR as an instrumental imaging modality in the era of rising interest in CA screening and emerging effective therapies.

Cardiac MR: From Theory to Practice

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.

Myocardial tissue imaging with cardiovascular magnetic resonance

Alteration in myocardial tissue, such as myocardial fibrosis, edema, inflammation, or accumulation with amyloid, lipids, or iron, has an important role in the cardiac remodeling that leads to diastolic and/or systolic dysfunction and the development of chronic heart failure, increasing the risk of adverse cardiovascular events. Thus, the early detection of changes at myocardial tissue level has great diagnostic and prognostic potential. The gold standard technique to assess these myocardial alterations is endomyocardial biopsy. However, this has been limited to a few patients due to the invasive nature, sampling errors, and its inability to assess the entire myocardium. Cardiovascular magnetic resonance (CMR) has emerged as the gold standard imaging not only for assessing cardiac volume, function quantification, and viability but also for noninvasive myocardial tissue characterization over the past decade. Its ability to characterize myocardial tissue composition is unique among noninvasive imaging modalities in cardiovascular disease. Currently, multi-parametric myocardial characterization with T1, T2, and extracellular volume has the potential to identify and track diffuse pathology in various diseases. In this review article, we present the role of established and emerging CMR techniques in myocardial tissue characterization, with an emphasis on T1 and T2 mapping, in clinical practice.

Late Gadolinium Enhancement Cardiac Magnetic Resonance Imaging: From Basic Concepts to Emerging Methods

BACKGROUND

 Late gadolinium enhancement (LGE) is a widely used cardiac magnetic resonance imaging (MRI) technique to diagnose a broad range of ischemic and non-ischemic cardiomyopathies. Since its development and validation against histology already more than two decades ago, the clinical utility of LGE and its span of applications have increased considerably.

METHODS

 In this review we will present the basic concepts of LGE imaging and its diagnostic and prognostic value, elaborate on recent developments and emerging methods, and finally discuss future prospects.

RESULTS

 Continuous developments in 3 D imaging methods, motion correction techniques, water/fat-separated imaging, dark-blood methods, and scar quantification improved the performance and further expanded the clinical utility of LGE imaging.

CONCLUSION

 LGE imaging is the current noninvasive reference standard for the assessment of myocardial viability. Improvements in spatial resolution, scar-to-blood contrast, and water/fat-separated imaging further strengthened its position.

KEY POINTS

  · LGE MRI is the reference standard for the noninvasive assessment of myocardial viability. · LGE MRI is used to diagnose a broad range of non-ischemic cardiomyopathies in everyday clinical practice.. · Improvements in spatial resolution and scar-to-blood contrast further strengthened its position. · Continuous developments improve its performance and further expand its clinical utility.

CITATION FORMAT

· Holtackers RJ, Emrich T, Botnar RM et al. Late Gadolinium Enhancement Cardiac Magnetic Resonance Imaging: From Basic Concepts to Emerging Methods. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1718-4355.

Dark-blood late gadolinium-enhancement cardiac magnetic resonance imaging for myocardial scar detection based on simplified timing scheme: single-center experience in patients with suspected coronary artery disease

Background

This study aims to examine scar detectability using dark-blood late gadolinium enhancement (LGE) with simplified timing scheme and fixed parameters comparing to two conventional bright-blood approaches in patients with known or suspected coronary artery disease.

Methods

Three LGE techniques were performed in all patients with known or suspected coronary artery disease at 3 T: dark blood two-dimensional (2D) phase-sensitive inversion recovery (PSIR) preceded with a T2-preparation pulse (DB-LGE), conventional three-dimensional (3D) gradient-echo inversion recovery (3D-IR) and conventional 2D PSIR. Timing parameters in DB-LGE were tested in five clinically confirmed coronary artery disease patients with scars and fixed for the rest of the study. Two independent readers evaluated images at both patient and segment levels. Image quality and contrast ratio between scar and adjacent tissues were assessed. Concordance between the three techniques and detection rate based on expert consensus were reported.

Results

Forty-six patients were recruited in the study (average age 66.8 years, 69.6% male). DB-LGE demonstrated superior image quality (P=0.001 vs. 3D-IR) and scar-to-blood contrast ratio (P<0.001 vs. 3D-IR and PSIR). Among 41 patients with suspected coronary artery disease, myocardial scar was present in 30 patients (73.2%), all detected by DB-LGE, yielding a detection rate of 100% compared to 93.3% and 96.7% for bright-blood 3D-IR and PSIR. For subendocardial scar detection among 656 segments, DB-LGE had a detection rate of 99.4% compared to 57.8% for 3D-IR and 61.0% for PSIR (both P<0.001).

Conclusions

DB-LGE improves detection of myocardial scar compared with conventional bright-blood LGE techniques, particularly of subendocardial scar.

A Late Diagnosis of Transthyretin Amyloidosis

Cardiac amyloidosis is a rare disease caused by the accumulation of protein-based fibrils that deposit into the myocardium, causing disease. The accumulation of amyloid in the heart tissue causes the heart to become increasingly stiff, reducing compliance, with the eventual decline of the heart’s systolic function over time as the disease progresses. The restrictive physiology of the disease usually prompts investigation; however, if allowed to progress, the systolic function becomes affected in the later stages of the disease. We present a case of late-stage transthyretin-related amyloidosis (ATTR).

Atrial function and geometry differences in transthyretin versus immunoglobulin light chain amyloidosis: a cardiac magnetic resonance study

To determine the differences in left atrial (LA) function and geometry assessed by cardiac magnetic resonance (CMR) between transthyretin (ATTR) and immunoglobulin light chain (AL) cardiac amyloidosis (CA). We performed a retrospective analysis of 54 consecutive patients (68.5% male, mean age 67 ± 11 years) with confirmed CA (24 ATTR, 30 AL) who underwent comprehensive CMR examinations. LA structural and functional assessment including LA volume, LA sphericity index, and LA strain parameters were compared between both subtypes. In addition, 15 age-matched controls were compared to all groups. Patients with ATTR-CA were older (73 ± 9 vs. 62 ± 10 years, p < 0.001) and more likely to be male (83.3% vs. 56.7%, p = 0.036) when compared to AL-CA. No significant difference existed in LA maximum volume and LA sphericity index between ATTR-CA and AL-CA. LA minimum volumes were larger in ATTR-CA when compared with AL-CA. There was a significant difference in LA function with worse strain values in ATTR vs AL: left atrial reservoir [7.4 (6.3–12.8) in ATTR vs. 13.8 (6.90–24.8) in AL, p = 0.017] and booster strains [3.6 (2.6–5.5) in ATTR vs. 5.2 (3.6–12.1) in AL, p = 0.039]. After adjusting for age, LA reservoir remained significantly lower in ATTR-CA compared to AL-CA (p = 0.03), but not LA booster (p = 0.16). We demonstrate novel differences in LA function between ATTR-CA and AL-CA despite similar LA geometry. Our findings of more impaired LA function in ATTR may offer insight into higher AF burden in these patients.

Cartesian dictionary-based native T1 and T2 mapping of the myocardium

PURPOSE

To implement and evaluate a new dictionary-based technique for native myocardial T₁ and T₂ mapping using Cartesian sampling.

METHODS

The proposed technique (Multimapping) consisted of single-shot Cartesian image acquisitions in 10 consecutive cardiac cycles, with inversion pulses in cycle 1 and 5, and T₂ preparation (TE: 30 ms, 50 ms, and 70 ms) in cycles 8-10. Multimapping was simulated for different T₁ and T₂ , where entries corresponding to the k-space centers were matched to acquired data. Experiments were performed in a phantom, 16 healthy subjects, and 3 patients with cardiovascular disease.

RESULTS

Multimapping phantom measurements showed good agreement with reference values for both T₁ and T₂ , with no discernable heart-rate dependency for T₁ and T₂ within the range of myocardium. In vivo mean T₁ in healthy subjects was significantly higher using Multimapping (T₁ = 1114 ± 14 ms) compared to the reference (T₁ = 991 ± 26 ms) (p < 0.01). Mean Multimapping T₂ (47.1 ± 1.3 ms) and T₂ spatial variability (5.8 ± 1.0 ms) was significantly lower compared to the reference (T₂ = 54.7 ± 2.2 ms, p < 0.001; spatial variability = 8.4 ± 2.0 ms, p < 0.01). Increased T₁ and T₂ was detected in all patients using Multimapping.

CONCLUSIONS

Multimapping allows for simultaneous native myocardial T₁ and T₂ mapping with a conventional Cartesian trajectory, demonstrating promising in vivo image quality and parameter quantification results.

Left atrial evaluation by cardiovascular magnetic resonance: sensitive and unique biomarkers

Left atrial (LA) imaging is still not routinely used for diagnosis and risk stratification, although recent studies have emphasized its importance as an imaging biomarker. Cardiovascular magnetic resonance is able to evaluate LA structure and function, metrics that serve as early indicators of disease, and provide prognostic information, e.g. regarding diastolic dysfunction, and atrial fibrillation (AF). MR angiography defines atrial anatomy, useful for planning ablation procedures, and also for characterizing atrial shapes and sizes that might predict cardiovascular events, e.g. stroke. Long-axis cine images can be evaluated to define minimum, maximum, and pre-atrial contraction LA volumes, and ejection fractions (EFs). More modern feature tracking of these cine images provides longitudinal LA strain through the cardiac cycle, and strain rates. Strain may be a more sensitive marker than EF and can predict post-operative AF, AF recurrence after ablation, outcomes in hypertrophic cardiomyopathy, stratification of diastolic dysfunction, and strain correlates with atrial fibrosis. Using high-resolution late gadolinium enhancement (LGE), the extent of fibrosis in the LA can be estimated and post-ablation scar can be evaluated. The LA LGE method is widely available, its reproducibility is good, and validations with voltage-mapping exist, although further scan-rescan studies are needed, and consensus regarding atrial segmentation is lacking. Using LGE, scar patterns after ablation in AF subjects can be reproducibly defined. Evaluation of 'pre-existent' atrial fibrosis may have roles in predicting AF recurrence after ablation, predicting new-onset AF and diastolic dysfunction in patients without AF. LA imaging biomarkers are ready to enter into diagnostic clinical practice.

Evaluation of accelerated motion-compensated 3d water/fat late gadolinium enhanced MR for atrial wall imaging

OBJECTIVE

3D late gadolinium enhancement (LGE) imaging is a promising non-invasive technique for the assessment of atrial fibrosis. However, current techniques result in prolonged and unpredictable scan times and high rates of non-diagnostic images. The purpose of this study was to compare the performance of a recently proposed accelerated respiratory motion-compensated 3D water/fat LGE technique with conventional 3D LGE for atrial wall imaging.

MATERIALS AND METHODS

18 patients (age: 55.7±17.1 years) with atrial fibrillation underwent conventional diaphragmatic navigator gated inversion recovery (IR)-prepared 3D LGE (dNAV) and proposed image-navigator motion-corrected water/fat IR-prepared 3D LGE (iNAV) imaging. Images were assessed for image quality and presence of fibrosis by three expert observers. The scan time for both techniques was recorded.

RESULTS

Image quality scores were improved with the proposed compared to the conventional method (iNAV: 3.1 ± 1.0 vs. dNAV: 2.6 ± 1.0, p = 0.0012, with 1: Non-diagnostic to 4: Full diagnostic). Furthermore, scan time for the proposed method was significantly shorter with a 59% reduction is scan time (4.5 ± 1.2 min vs. 10.9 ± 3.9 min, p < 0.0001). The images acquired with the proposed method were deemed as inconclusive less frequently than the conventional images (expert 1/expert 2: 4/7 dNAV and 2/4 iNAV images inconclusive).

DISCUSSION

The motion-compensated water/fat LGE method enables atrial wall imaging with diagnostic quality comparable to the current conventional approach with a significantly shorter scan of about 5 min.

Linear late gadolinium enhancement in the basal anterior septum and lateral wall may represent the contrast enhancement of vessels: A CMR and CCTA comparison study

BACKGROUND

The purpose of this paper was to verify that the linear high-intensity signal on late gadolinium enhancement-cardiac magnetic resonance (LGE-CMR) may represent the contrast enhancement of vessels rather than scars or fibrosis, and to assess whether this linear high-intensity signal will affect the quantification of myocardial fibrosis in patients with hypertrophic cardiomyopathy (HCM).

METHODS

A total of 58 patients who underwent both coronary computed tomography angiography (CCTA) and LGE-CMR in our hospital were ultimately enrolled. The definitions of positive linear LGE (LLGE+) were as follows: (1) LLGE in the basal anterior septum or lateral wall, and (2) LLGE observable at 10 mm or more. All other patients were regarded as negative LLGE (LLGE-). In LLGE+ patients, the length of the LLGE located in the anterior septum and lateral wall was compared with the length of the septal perforator artery and the circumflex artery on CCTA, respectively. For nine patients with HCM, the LGE% was measured before and after removal of LLGE.

RESULTS

Among the 58 patients, 40 showed LLGE+ and 18 showed LLGE-. For patients with LLGE in the anterior septum, there was a strong correlation between LLGE and anterior septal perforator arteries in length (r=0.887, p<0.001). For patients with LLGE in the lateral wall, LLGE also correlated well with the circumflex arteries in length (r=0.962, p<0.001). In nine patients with HCM, the LGE% decreased significantly after the removal of LLGE [9.50 (7.70 - 17.35)% vs. 8.80 (6.20 - 15.55)%, p<0.05].

CONCLUSIONS

The LLGE in the anterior septum and lateral wall may represent contrast enhancement of the anterior septal perforator artery and the circumflex artery, respectively. This LLGE may overestimate the extent of myocardial fibrosis in patients with HCM.

Cardiovascular Involvement in Transthyretin Cardiac Amyloidosis

Transthyretin cardiac amyloidosis (ATTR-CA) is a systemic disorder resulting from the extracellular deposition of amyloid fibrils of misfolded transthyretin protein in the heart. ATTR-CA is a life-threatening disease, which can be caused by progressive deposition of wild type transthyretin (wtATTR) or by aggregation of an inherited mutated variant of transthyretin (mATTR). mATTR Is a rare condition transmitted in an autosomal dominant manner with incomplete penetrance, causing heterogenous phenotypes which can range from predominant neuropathic involvement, predominant cardiomyopathy, or mixed. Diagnosis of ATTR-CA is complex and requires integration of different imaging tools (echocardiography, bone scintigraphy, magnetic resonance) with genetics, clinical signs, laboratory tests, and histology. In recent years, new therapeutic agents have shown good efficacy and impact on survival and quality of life in this subset of patients, nevertheless patients affected by ATTR-CA may still carry an unfavorable prognosis, thus highlighting the need for new therapies. This review aims to assess cardiovascular involvement, diagnosis, and management of patients affected by ATTR-CA.

Bright-blood and dark-blood phase sensitive inversion recovery late gadolinium enhancement and T1 and T2 maps in a single free-breathing scan: an all-in-one approach

BACKGROUND

Quantitative cardiovascular magnetic resonance (CMR) T1 and T2 mapping are used to detect diffuse disease such as myocardial fibrosis or edema. However, post gadolinium contrast mapping often lacks visual contrast needed for assessment of focal scar. On the other hand, late gadolinium enhancement (LGE) CMR which nulls the normal myocardium has excellent contrast between focal scar and normal myocardium but has poor ability to detect global disease. The objective of this work is to provide a calculated bright-blood (BB) and dark-blood (DB) LGE based on simultaneous acquisition of T1 and T2 maps, so that both diffuse and focal disease may be assessed within a single multi-parametric acquisition.

METHODS

The prototype saturation recovery-based SASHA T1 mapping may be modified to jointly calculate T1 and T2 maps (known as multi-parametric SASHA) by acquiring additional saturation recovery (SR) images with both SR and T2 preparations. The synthetic BB phase sensitive inversion recovery (PSIR) LGE may be calculated from the post-contrast T1, and the DB PSIR LGE may be calculated from the post-contrast joint T1 and T2 maps. Multi-parametric SASHA maps were acquired free-breathing (45 heartbeats). Protocols were designed to use the same spatial resolution and achieve similar signal-to-noise ratio (SNR) as conventional motion corrected (MOCO) PSIR. The calculated BB and DB LGE were compared with separate free breathing (FB) BB and DB MOCO PSIR acquisitions requiring 16 and 32 heart beats, respectively. One slice with myocardial infarction (MI) was acquired with all protocols within 4 min.

RESULTS

Multiparametric T1 and T2 maps and calculated BB and DB PSIR LGE images were acquired for patients with subendocardial chronic MI (n = 10), acute MI (n = 3), and myocarditis (n = 1). The contrast-to-noise (CNR) between scar (MI and myocarditis) and remote was 26.6 ± 7.7 and 20.2 ± 7.4 for BB and DB PSIR LGE, and 31.3 ± 10.6 and 21.8 ± 7.6 for calculated BB and DB PSIR LGE, respectively. The CNR between scar and the left ventricualr blood pool was 5.2 ± 6.5 and 29.7 ± 9.4 for conventional BB and DB PSIR LGE, and 6.5 ± 6.0 and 38.6 ± 11.6 for calculated BB and DB PSIR LGE, respectively.

CONCLUSIONS

A single free-breathing acquisition using multi-parametric SASHA provides T1 and T2 maps and calculated BB and DB PSIR LGE images for comprehensive tissue characterization.

The impact of dark-blood versus conventional bright-blood late gadolinium enhancement on the myocardial ischemic burden

PURPOSE

In perfusion cardiovascular magnetic resonance (CMR), ischemic burden predicts adverse prognosis and is often used to guide revascularization. Ischemic scar tissue can cause stress perfusion defects that do not represent myocardial ischemia. Dark-blood late gadolinium enhancement (LGE) methods detect more scar than conventional bright-blood LGE, however, the impact on the myocardial ischemic burden estimation is unknown and evaluated in this study.

METHODS

Forty patients with CMR stress perfusion defects and ischemic scar on both dark-blood and bright-blood LGE were included. For dark-blood LGE, phase sensitive inversion recovery imaging with left ventricular blood pool nulling was used. Ischemic scar burden was quantified for both methods using >5 standard deviations above remote myocardium. Perfusion defects were manually contoured, and the myocardial ischemic burden was calculated by subtracting the ischemic scar burden from the perfusion defect burden.

RESULTS

Ischemic scar burden by dark-blood LGE was higher than bright-blood LGE (13.3 ± 7.4% vs. 10.3 ± 7.1%, p < 0.001). Dark-blood LGE derived myocardial ischemic burden was lower compared with bright-blood LGE (15.6% (IQR: 10.3 to 22.0) vs. 19.3 (10.9 to 25.5), median difference -2.0%, p < 0.001) with a mean bias of -2.8% (95% confidence intervals: -4.0 to -1.6%) and a large effect size (r = 0.62).

CONCLUSION

Stress perfusion defects are associated with higher ischemic scar burden using dark-blood LGE compared with bright-blood LGE, which leads to a lower estimation of the myocardial ischemic burden. The prognostic value of using a dark-blood LGE derived ischemic burden to guide revascularization is unknown and warrants further investigation.

Endogenous T1ρ cardiovascular magnetic resonance in hypertrophic cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is characterized by increased left ventricular wall thickness, cardiomyocyte hypertrophy, and fibrosis. Adverse cardiac risk characterization has been performed using late gadolinium enhancement (LGE), native T1, and extracellular volume (ECV). Relaxation time constants are affected by background field inhomogeneity. T1ρ utilizes a spin-lock pulse to decrease the effect of unwanted relaxation. The objective of this study was to study T1ρ as compared to T1, ECV, and LGE in HCM patients.

METHODS

HCM patients were recruited as part of the Novel Markers of Prognosis in Hypertrophic Cardiomyopathy study, and healthy controls were matched for comparison. In addition to cardiac functional imaging, subjects underwent T1 and T1ρ cardiovascular magnetic resonance imaging at short-axis positions at 1.5T. Subjects received gadolinium and underwent LGE imaging 15-20 min after injection covering the entire heart. Corresponding basal and mid short axis LGE slices were selected for comparison with T1 and T1ρ. Full-width half-maximum thresholding was used to determine the percent enhancement area in each LGE-positive slice by LGE, T1, and T1ρ. Two clinicians independently reviewed LGE images for presence or absence of enhancement. If in agreement, the image was labeled positive (LGE + +) or negative (LGE --); otherwise, the image was labeled equivocal (LGE + -).

RESULTS

In 40 HCM patients and 10 controls, T1 percent enhancement area (Spearman's rho = 0.61, p < 1e-5) and T1ρ percent enhancement area (Spearman's rho = 0.48, p < 0.001e-3) correlated with LGE percent enhancement area. T1 and T1ρ percent enhancement areas were also correlated (Spearman's rho = 0.28, p = 0.047). For both T1 and T1ρ, HCM patients demonstrated significantly longer relaxation times compared to controls in each LGE category (p < 0.001 for all). HCM patients also showed significantly higher ECV compared to controls in each LGE category (p < 0.01 for all), and LGE -- slices had lower ECV than LGE + + (p = 0.01).

CONCLUSIONS

Hyperenhancement areas as measured by T1ρ and LGE are moderately correlated. T1, T1ρ, and ECV were elevated in HCM patients compared to controls, irrespective of the presence of LGE. These findings warrant additional studies to investigate the prognostic utility of T1ρ imaging in the evaluation of HCM patients.

Double spectral attenuated inversion recovery (DSPAIR)-an efficient fat suppression technique for late gadolinium enhancement at 3 tesla

Despite clinical use of late gadolinium enhancement (LGE) for two decades, an efficient, robust fat suppression (FS) technique still does not exist for this CMR mainstay. In ischemic and non-ischemic heart disease, differentiating fibrotic tissue from infiltrating and adjacent fat is crucial. Multiple groups have independently developed an FS technique for LGE, double spectral attenuated inversion recovery (DSPAIR), but no comprehensive evaluation was performed. This study aims to fill this gap. DSPAIR uses two SPAIR pulses and one non-selective IR pulse to enable FS LGE, including compatibility with phase sensitive inversion recovery (PSIR). We implemented a magnitude (MAGN) and a PSIR variant and compared them with LGE without FS (CONTROL) and with spectral presaturation with inversion recovery (SPIR) in simulations, phantoms, and patients. Fat magnetization by SPIR, MAGN DSPAIR, and PSIR DSPAIR was simulated as a function of pulse B₁ , readout (RO) pulse number, and fat T_I . A phantom with fat, fibrosis, and myocardium compartments was imaged using all FS methods and modifying pulse B₁ , RO pulse number, and heart rate. Signal was measured in SNR units. Fat, myocardium, and fibrosis SNR and fibrosis-to-fat CNR were obtained. Patient images were acquired with all FS techniques. Fat, myocardium, and fibrosis SNR, fibrosis-to-fat CNR, and image and FS quality were assessed. In the phantom, both DSPAIR variants provided superior FS compared with SPIR, independent of heart rate and RO pulse number. MAGN DSPAIR reduced fat signal by 99% compared with CONTROL, PSIR DSPAIR by 116%, and SPIR by 67% (25 RO pulses). In patients, both DSPAIR variants substantially reduced fat signal (MAGN DSPAIR by 87.1% ± 10.0%, PSIR DSPAIR by 130.5% ± 36.3%), but SPIR did not (35.8% ± 25.5%). FS quality was good to excellent for MAGN and PSIR DSPAIR, and moderate to poor for SPIR. DSPAIR provided highly effective FS across a wide range of parameters. PSIR DSPAIR performed best.