Myocardial tagging by cardiovascular magnetic resonance: evolution of techniques--pulse sequences, analysis algorithms, and applications

Assessing Regurgitation Severity, Adverse Remodeling, and Fibrosis with CMR in Primary Mitral Regurgitation

PURPOSE OF REVIEW

This review offers an evidence-based analysis of established and emerging cardiovascular magnetic resonance (CMR) techniques used to assess the severity of primary mitral regurgitation (MR), identify adverse cardiac remodeling and its prognostic effect. The aim is to provide different insights regarding clinical decision-making and enhance the clinical outcomes of patients with MR.

RECENT FINDINGS

Cardiac remodeling and myocardial replacement fibrosis are observed frequently in the presence of substantial LV volume overload, particularly in cases with severe primary MR. CMR serves as a useful diagnostic imaging modality in assessing mitral regurgitation severity, early detection of cardiac remodeling, myocardial dysfunction, and myocardial fibrosis, enabling timely intervention before irreversible damage ensues. Incorporating myocardial remodeling in terms of left ventricular (LV) dilatation and myocardial fibrosis with quantitative MR severity assessment by CMR may assist in defining optimal timing of intervention.

The Role of Artificial Intelligence in Cardiac Imaging

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

New clinical opportunities of low-field MRI: heart, lung, body, and musculoskeletal

Contemporary whole-body low-field MRI scanners (< 1 T) present new and exciting opportunities for improved body imaging. The fundamental reason is that the reduced off-resonance and reduced SAR provide substantially increased flexibility in the design of MRI pulse sequences. Promising body applications include lung parenchyma imaging, imaging adjacent to metallic implants, cardiac imaging, and dynamic imaging in general. The lower cost of such systems may make MRI favorable for screening high-risk populations and population health research, and the more open configurations allowed may prove favorable for obese subjects and for pregnant women. This article summarizes promising body applications for contemporary whole-body low-field MRI systems, with a focus on new platforms developed within the past 5 years. This is an active area of research, and one can expect many improvements as MRI physicists fully explore the landscape of pulse sequences that are feasible, and as clinicians apply these to patient populations.

Evaluation of myocardial strain in patients with subclinical hypertrophic cardiomyopathy and subclinical Hypertensive Heart Disease using Cardiac magnetic resonance feature tracking

The evaluation of cardiac magnetic resonance feature tracking may have great diagnostic value in hypertrophic cardiomyopathy and hypertensive heart disease. Exploring the diagnostic and clinical research value of cardiac magnetic resonance feature tracks in evaluation of myocardium deformation in patients with subclinical hypertrophic cardiomyopathy(SHCM)and subclinical hypertensive heart disease(SHHD). Cardiovascular Magnetic Resonance (CMR) scans were performed on a 1.5 T MR scanner in 33 patients with SHCM, 31 patients with SHHD, and 27 controls(NS). The CMR image post-processing software was used to analyze the characteristics of routine cardiac function, different global and regional myocardial strain in each group. Analysis of variance (ANOVA) was used to compare age, blood pressure, heart rate, routine cardiac function, body mass index (BMI), as well as the strain between different segments within each of the three groups. Once a significant difference was detected, a least significant difference (LSD) comparison would be performed. The diagnostic efficacy of different parameters in differentiating SHHD from SHCM was evaluated through receiver operating characteristic (ROC) curve analysis, and the best cut-off value was determined. There was no statistical difference among three groups (P>0.05) in routine cardiac function while significant statistical differences were found in the global myocardial strain parameters and the peak strain parameters of some segments (especially basal segments) (P < 0.05). The global radial peak strain (GRPS) was most effective (AUC = 0.885, 95% CI: 0.085-0.971, P<0.001) with a sensitivity and specificity of 84% and 88% at a cut-off value of 40.105, contributing to distinguishing SHCM from SHHD group. Cardiac magnetic resonance feature tracking could detect left ventricular deformation in patients with SHCM and SHHD group. The abnormality of strain has important research value for subclinical diagnosis and clinical evaluation.

Highly accelerated free-breathing real-time myocardial tagging for exercise cardiovascular magnetic resonance

BACKGROUND

Exercise cardiovascular magnetic resonance (Ex-CMR) myocardial tagging would enable quantification of myocardial deformation after exercise. However, current electrocardiogram (ECG)-segmented sequences are limited for Ex-CMR.

METHODS

We developed a highly accelerated balanced steady-state free-precession real-time tagging technique for 3 T. A 12-fold acceleration was achieved using incoherent sixfold random Cartesian sampling, twofold truncated outer phase encoding, and a deep learning resolution enhancement model. The technique was tested in two prospective studies. In a rest study of 27 patients referred for clinical CMR and 19 healthy subjects, a set of ECG-segmented for comparison and two sets of real-time tagging images for repeatability assessment were collected in 2-chamber and short-axis views with spatiotemporal resolution 2.0 × 2.0 mm2 and 29 ms. In an Ex-CMR study of 26 patients with known or suspected cardiac disease and 23 healthy subjects, real-time images were collected before and after exercise. Deformation was quantified using measures of short-axis global circumferential strain (GCS). Two experienced CMR readers evaluated the image quality of all real-time data pooled from both studies using a 4-point Likert scale for tagline quality (1-excellent; 2-good; 3-moderate; 4-poor) and artifact level (1-none; 2-minimal; 3-moderate; 4-significant). Statistical evaluation included Pearson correlation coefficient (r), intraclass correlation coefficient (ICC), and coefficient of variation (CoV).

RESULTS

In the rest study, deformation was successfully quantified in 90% of cases. There was a good correlation (r = 0.71) between ECG-segmented and real-time measures of GCS, and repeatability was good to excellent (ICC = 0.86 [0.71, 0.94]) with a CoV of 4.7%. In the Ex-CMR study, deformation was successfully quantified in 96% of subjects pre-exercise and 84% of subjects post-exercise. Short-axis and 2-chamber tagline quality were 1.6 ± 0.7 and 1.9 ± 0.8 at rest and 1.9 ± 0.7 and 2.5 ± 0.8 after exercise, respectively. Short-axis and 2-chamber artifact level was 1.2 ± 0.5 and 1.4 ± 0.7 at rest and 1.3 ± 0.6 and 1.5 ± 0.8 post-exercise, respectively.

CONCLUSION

We developed a highly accelerated real-time tagging technique and demonstrated its potential for Ex-CMR quantification of myocardial deformation. Further studies are needed to assess the clinical utility of our technique.

Automated segmentation of long and short axis DENSE cardiovascular magnetic resonance for myocardial strain analysis using spatio-temporal convolutional neural networks

BACKGROUND

Cine Displacement Encoding with Stimulated Echoes (DENSE) facilitates the quantification of myocardial deformation, by encoding tissue displacements in the cardiovascular magnetic resonance (CMR) image phase, from which myocardial strain can be estimated with high accuracy and reproducibility. Current methods for analyzing DENSE images still heavily rely on user input, making this process time-consuming and subject to inter-observer variability. The present study sought to develop a spatio-temporal deep learning model for segmentation of the left-ventricular (LV) myocardium, as spatial networks often fail due to contrast-related properties of DENSE images.

METHODS

2D + time nnU-Net-based models have been trained to segment the LV myocardium from DENSE magnitude data in short- and long-axis images. A dataset of 360 short-axis and 124 long-axis slices was used to train the networks, from a combination of healthy subjects and patients with various conditions (hypertrophic and dilated cardiomyopathy, myocardial infarction, myocarditis). Segmentation performance was evaluated using ground-truth manual labels, and a strain analysis using conventional methods was performed to assess strain agreement with manual segmentation. Additional validation was performed using an externally acquired dataset to compare the inter- and intra-scanner reproducibility with respect to conventional methods.

RESULTS

Spatio-temporal models gave consistent segmentation performance throughout the cine sequence, while 2D architectures often failed to segment end-diastolic frames due to the limited blood-to-myocardium contrast. Our models achieved a DICE score of 0.83 ± 0.05 and a Hausdorff distance of 4.0 ± 1.1 mm for short-axis segmentation, and 0.82 ± 0.03 and 7.9 ± 3.9 mm respectively for long-axis segmentations. Strain measurements obtained from automatically estimated myocardial contours showed good to excellent agreement with manual pipelines, and remained within the limits of inter-user variability estimated in previous studies.

CONCLUSION

Spatio-temporal deep learning shows increased robustness for the segmentation of cine DENSE images. It provides excellent agreement with manual segmentation for strain extraction. Deep learning will facilitate the analysis of DENSE data, bringing it one step closer to clinical routine.

Localized strain characterization of cardiomyopathy in Duchenne muscular dystrophy using novel 4D kinematic analysis of cine cardiovascular magnetic resonance

BACKGROUND

Cardiomyopathy (CMP) is the most common cause of mortality in Duchenne muscular dystrophy (DMD), though the age of onset and clinical progression vary. We applied a novel 4D (3D + time) strain analysis method using cine cardiovascular magnetic resonance (CMR) imaging data to determine if localized strain metrics derived from 4D image analysis would be sensitive and specific for characterizing DMD CMP.

METHODS

We analyzed short-axis cine CMR image stacks from 43 DMD patients (median age: 12.23 yrs [10.6-16.5]; [interquartile range]) and 25 male healthy controls (median age: 16.2 yrs [13.3-20.7]). A subset of 25 male DMD patients age-matched to the controls (median age: 15.7 yrs [14.0-17.8]) was used for comparative metrics. CMR images were compiled into 4D sequences for feature-tracking strain analysis using custom-built software. Unpaired t-test and receiver operator characteristic area under the curve (AUC) analysis were used to determine statistical significance. Spearman's rho was used to determine correlation.

RESULTS

DMD patients had a range of CMP severity: 15 (35% of total) had left ventricular ejection fraction (LVEF) > 55% with no findings of myocardial late gadolinium enhancement (LGE), 15 (35%) had findings of LGE with LVEF > 55% and 13 (30%) had LGE with LVEF < 55%. The magnitude of the peak basal circumferential strain, basal radial strain, and basal surface area strain were all significantly decreased in DMD patients relative to healthy controls (p < 0.001) with AUC values of 0.80, 0.89, and 0.84 respectively for peak strain and 0.96, 0.91, and 0.98 respectively for systolic strain rate. Peak basal radial strain, basal radial systolic strain rate, and basal circumferential systolic strain rate magnitude values were also significantly decreased in mild CMP (No LGE, LVEF > 55%) compared to a healthy control group (p < 0.001 for all). Surface area strain significantly correlated with LVEF and extracellular volume (ECV) respectively in the basal (rho = - 0.45, 0.40), mid (rho = - 0.46, 0.46), and apical (rho = - 0.42, 0.47) regions.

CONCLUSION

Strain analysis of 3D cine CMR images in DMD CMP patients generates localized kinematic parameters that strongly differentiate disease from control and correlate with LVEF and ECV.

Myocardial Segmentation of Tagged Magnetic Resonance Images with Transfer Learning Using Generative Cine-To-Tagged Dataset Transformation

The use of deep learning (DL) segmentation in cardiac MRI has the potential to streamline the radiology workflow, particularly for the measurement of myocardial strain. Recent efforts in DL motion tracking models have drastically reduced the time needed to measure the heart's displacement field and the subsequent myocardial strain estimation. However, the selection of initial myocardial reference points is not automated and still requires manual input from domain experts. Segmentation of the myocardium is a key step for initializing reference points. While high-performing myocardial segmentation models exist for cine images, this is not the case for tagged images. In this work, we developed and compared two novel DL models (nnU-net and Segmentation ResNet VAE) for the segmentation of myocardium from tagged CMR images. We implemented two methods to transform cardiac cine images into tagged images, allowing us to leverage large public annotated cine datasets. The cine-to-tagged methods included (i) a novel physics-driven transformation model, and (ii) a generative adversarial network (GAN) style transfer model. We show that pretrained models perform better (+2.8 Dice coefficient percentage points) and converge faster (6×) than models trained from scratch. The best-performing method relies on a pretraining with an unpaired, unlabeled, and structure-preserving generative model trained to transform cine images into their tagged-appearing equivalents. Our state-of-the-art myocardium segmentation network reached a Dice coefficient of 0.828 and 95th percentile Hausdorff distance of 4.745 mm on a held-out test set. This performance is comparable to existing state-of-the-art segmentation networks for cine images.

Comparison of left ventricular global and segmental strain parameters by cardiovascular magnetic resonance tissue tracking in light-chain cardiac amyloidosis and hypertrophic cardiomyopathy

Background

Apical sparing of left ventricular (LV) strain can occur in light-chain cardiac amyloidosis (AL-CA). We employed indicators of the strain ratio of the apex to base (RAB) and the relative apical sparing of strain (RAS) on the basis of LV global and segmental strain to distinguish AL-CA from hypertrophic cardiomyopathy (HCM).

Methods

In all, 36 AL-CA patients, 37 HCM patients, and 36 healthy controls underwent 3.0 T cardiac magnetic resonance (CMR) examination. We compared LV strain parameters from CMR tissue tracking (CMR-TT), including global and segmental peak radial strain (PRS), peak circumferential strain (PCS), and peak longitudinal strain (PLS); the peak systolic strain rate in radial, circumferential, and longitudinal directions (PSSR_R, PSSR_C, PSSR_L); and the peak diastolic strain rate in radial, circumferential, and longitudinal directions (PDSR_R, PDSR_C, PDSR_L). We also assessed the values of RAB and RAS. Differences in all groups were compared using an independent t-test and a nonparametric rank sum test.

Results

In the comparison of global strain parameters, all the peak strain, systolic, and diastolic peak strain rates of the AL-CA group significantly decreased compared with those of the HCM and healthy control groups (all P<0.001). The values of PSSR in all directions were lower in the AL-CA than in the HCM patients (PSSR_R, P<0.001; PSSR_C, P=0.004; PSSR_L, P=0.010) . In the analysis of segmental strain parameters, all peak strains in the basal segment showed significant differences between the AL-CA and HCM groups (all P<0.001). Some strain rate parameters in the basal segment were also noted to be significantly different (PSSR_R, P<0.001; PSSR_L, P<0.001; PDSR_R, P=0.015; PDSR_C, P=0.020). Both the RAB and RAS of peak strain in all directions showed significant differences between the AL-CA and HCM groups (all P<0.001). The RAB of the radial and circumferential PSSR showed statistical differences between the 2 groups (P<0.001 and P=0.001). The RAS in the radial direction of both the PSSR and PDSR was statistically different (P=0.003 and P=0.012).

Conclusions

The CMR-TT technique can be used to quantitatively compare global and segmental strain differences between AL-CA and HCM. In addition, RAB and RAS are reliable parameters for assessing the apical sparing pattern and thus, for distinguishing AL-CA from HCM.

Myocardial Contractility Pattern Characterization in Radiation-Induced Cardiotoxicity Using Magnetic Resonance Imaging: A Pilot Study with ContractiX

Radiation therapy (RT) plays an integral role in treating thoracic cancers, despite the risk of radiation-induced cardiotoxicity. We hypothesize that our newly developed magnetic resonance imaging (MRI)-based contractility index (ContractiX) is a sensitive marker for early detection of RT-induced cardiotoxicity in a preclinical rat model of thoracic cancer RT. Adult salt-sensitive rats received image-guided heart RT and were imaged with MRI at 8 weeks and 10 weeks post-RT or sham. The MRI exam included cine and tagging sequences to measure left-ventricular ejection fraction (LVEF), mass, myocardial strain, and ContractiX. Furthermore, ventricular torsion, diastolic strain rate, and mechanical dyssynchrony were measured. Statistical analyses were performed between the sham, 8 weeks post-RT, and 10 weeks post-RT MRI parameters. The results showed that both LVEF and myocardial mass increased post-RT. Peak systolic strain and ContractiX significantly decreased post-RT, with a more relative reduction in ContractiX compared to strain. ContractiX showed an inverse nonlinear relationship with LVEF and continuously decreased with time post-RT. While early diastolic strain rate and mechanical dyssynchrony significantly changed post-RT, ventricular torsion changes were not significant post-RT. In conclusion, ContractiX measured via non-contrast MRI is a sensitive early marker for the detection of subclinical cardiac dysfunction post-RT, and it is superior to other MRI cardiac measures.

Computational Analysis of Cardiac Contractile Function

PURPOSE OF REVIEW

Heart failure results in the high incidence and mortality all over the world. Mechanical properties of myocardium are critical determinants of cardiac function, with regional variations in myocardial contractility demonstrated within infarcted ventricles. Quantitative assessment of cardiac contractile function is therefore critical to identify myocardial infarction for the early diagnosis and therapeutic intervention.

RECENT FINDINGS

Current advancement of cardiac functional assessments is in pace with the development of imaging techniques. The methods tailored to advanced imaging have been widely used in cardiac magnetic resonance, echocardiography, and optical microscopy. In this review, we introduce fundamental concepts and applications of representative methods for each imaging modality used in both fundamental research and clinical investigations. All these methods have been designed or developed to quantify time-dependent 2-dimensional (2D) or 3D cardiac mechanics, holding great potential to unravel global or regional myocardial deformation and contractile function from end-systole to end-diastole. Computational methods to assess cardiac contractile function provide a quantitative insight into the analysis of myocardial mechanics during cardiac development, injury, and remodeling.

Myocardial strain imaging in Duchenne muscular dystrophy

Cardiomyopathy (CM) is the leading cause of death for individuals with Duchenne muscular dystrophy (DMD). While DMD CM progresses rapidly and fatally for some in teenage years, others can live relatively symptom-free into their thirties or forties. Because CM progression is variable, there is a critical need for biomarkers to detect early onset and rapid progression. Despite recent advances in imaging and analysis, there are still no reliable methods to detect the onset or progression rate of DMD CM. Cardiac strain imaging is a promising technique that has proven valuable in DMD CM assessment, though much more work has been done in adult CM patients. In this review, we address the role of strain imaging in DMD, the mechanical and functional parameters used for clinical assessment, and discuss the gaps where emerging imaging techniques could help better characterize CM progression in DMD. Prominent among these emerging techniques are strain assessment from 3D imaging and development of deep learning algorithms for automated strain assessment. Improved techniques in tracking the progression of CM may help to bridge a crucial gap in optimizing clinical treatment for this devastating disease and pave the way for future research and innovation through the definition of robust imaging biomarkers and clinical trial endpoints.

Quantification of left ventricular strain and torsion by joint analysis of 3D tagging and cine MR images

Cardiovascular magnetic resonance (CMR) imaging is the gold standard for the non-invasive assessment of left-ventricular (LV) function. Prognostic value of deformation metrics extracted directly from regular SSFP CMR images has been shown by numerous studies in the clinical setting, but with some limitations to detect torsion of the myocardium. Tagged CMR introduces trackable features in the myocardium that allow for the assessment of local myocardial deformation, including torsion; it is, however, limited in the quantification of radial strain, which is a decisive metric for assessing the contractility of the heart. In order to improve SSFP-only and tagged-only approaches, we propose to combine the advantages of both image types by fusing global shape motion obtained from SSFP images with the local deformation obtained from tagged images. To this end, tracking is first performed on SSFP images, and subsequently, the resulting motion is utilized to mask and track tagged data. Our implementation is based on a recent finite element-based motion tracking tool with mechanical regularization. Joint SSFP and tagged images registration performance is assessed based on deformation metrics including LV strain and twist using human and in-house porcine datasets. Results show that joint analysis of SSFP and 3DTAG images provides better quantification of LV strain and twist as either data source alone.

MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI

Recovering the 3D motion of the heart from cine cardiac magnetic resonance (CMR) imaging enables the assessment of regional myocardial function and is important for understanding and analyzing cardiovascular disease. However, 3D cardiac motion estimation is challenging because the acquired cine CMR images are usually 2D slices which limit the accurate estimation of through-plane motion. To address this problem, we propose a novel multi-view motion estimation network (MulViMotion), which integrates 2D cine CMR images acquired in short-axis and long-axis planes to learn a consistent 3D motion field of the heart. In the proposed method, a hybrid 2D/3D network is built to generate dense 3D motion fields by learning fused representations from multi-view images. To ensure that the motion estimation is consistent in 3D, a shape regularization module is introduced during training, where shape information from multi-view images is exploited to provide weak supervision to 3D motion estimation. We extensively evaluate the proposed method on 2D cine CMR images from 580 subjects of the UK Biobank study for 3D motion tracking of the left ventricular myocardium. Experimental results show that the proposed method quantitatively and qualitatively outperforms competing methods.

Regional Cardiac Motion Scoring with Multi-scale Motion-based Spatial Attention

Regional cardiac motion scoring aims to classify the motion status of each myocardium segment into one of the four categories (normal, hypokinetic, akinetic and dyskinetic) from multiple short-axis MR sequences. It is essential for prognosis and early diagnosis for various cardiac diseases. However, the complex motion procedure of myocardium and the invisible pattern differences pose great challenges, leading to low performance for automatic methods. Most existing work mitigate the task by differentiating the normal motion patterns from the abnormal ones, without fine-grained motion scoring. We propose an effective method for the task of cardiac motion scoring by connecting a bottom-up and another top-down branch with a novel motion-based spatial attention module in multi-scale space. Specifically, we use the convolution blocks for low-level feature extraction that acts as a bottom-up mechanism, and the task of optical flow for explicit motion extraction that acts as a top-down mechanism for high-level allocation of spatial attention. To this end, a newly designed Multi-scale Motion-based Spatial Attention (MMSA) mechanism is used as the pivot connecting the bottom-up part and the top-down part, and adaptively weight the low-level features according to the motion information. Experimental results on a newly constructed dataset of 1440 myocardium segments from 90 subjects demonstrate that the proposed MMSA can accurately analyze the regional myocardium motion, with accuracies of 79.3% for 4-way motion scoring, 89.0% for abnormality detection, and correlation of 0.943 for estimation of motion score index. This work has great potential for practical assessment of cardiac motion function.

Taking It Personally: 3D Bioprinting a Patient-Specific Cardiac Patch for the Treatment of Heart Failure

Despite a massive global preventative effort, heart failure remains the major cause of death globally. The number of patients requiring a heart transplant, the eventual last treatment option, far outnumbers the available donor hearts, leaving many to deteriorate or die on the transplant waiting list. Treating heart failure by transplanting a 3D bioprinted patient-specific cardiac patch to the infarcted region on the myocardium has been investigated as a potential future treatment. To date, several studies have created cardiac patches using 3D bioprinting; however, testing the concept is still at a pre-clinical stage. A handful of clinical studies have been conducted. However, moving from animal studies to human trials will require an increase in research in this area. This review covers key elements to the design of a patient-specific cardiac patch, divided into general areas of biological design and 3D modelling. It will make recommendations on incorporating anatomical considerations and high-definition motion data into the process of 3D-bioprinting a patient-specific cardiac patch.

Real-time radial tagging for quantification of left ventricular torsion

PURPOSE

To develop a real-time radial tagging MRI for accurate measurement of rotational motion and twist of the left ventricle (LV).

METHODS

A FLASH-based radial tagging sequence with an undersampled radial reading scheme was developed for both single and double-slice imaging in real-time. The Polar Fourier Transform was used for reconstruction to push the undersampling artifacts out of a reduced FOV. The developed technique was used to image five normal subjects during rest, plus one during both exercise and rest conditions. LV rotational motions were estimated for five consecutive cardiac cycles in all cases. The process was validated using a numerical phantom. The real-time measurement of global rotational motion was compared with those measured from a non-real-time exam using linear regression analysis and the Bland-Altman plot.

RESULTS

The real-time acquisition was performed successfully with a temporal resolution of 46.2 ms. Image quality was sufficient for the reproducible calculation of rotation at rest and exercise. The feasibility of double-slice acquisition on human was further studied and a real-time twist of the left ventricle was demonstrated. The difference between LV global rotations from real-time and non-real-time approaches was 0.27 degrees. A significant reverse recoiling, induced by exercise, was reproducibly measured by the technique.

CONCLUSION

A real-time radial tagging MRI technique was developed based on the undersampled radial acquisition and Polar Fourier Transform reconstruction, for accurate measuring of the heart rotational motion and twist. The technique was able to extract a meaningful change of diastolic recoiling under stress test conditions during physical activities (cycling).

A Clinical Approach to Multimodality Imaging in Pulmonary Hypertension

Pulmonary hypertension (PH) is a clinical condition characterized by progressive elevations in mean pulmonary artery pressures and right ventricular dysfunction, associated with significant morbidity and mortality. For resting PH to develop, ~50-70% of the pulmonary vasculature must be affected, suggesting that even mild hemodynamic abnormalities are representative of advanced pulmonary vascular disease. The definitive diagnosis of PH is based upon hemodynamics measured by right heart catheterization; however this is an invasive and resource intense study. Early identification of pulmonary vascular disease offers the opportunity to improve outcomes by instituting therapies that slow, reverse, or potentially prevent this devastating disease. Multimodality imaging, including non-invasive modalities such as echocardiography, computed tomography, ventilation perfusion scans, and cardiac magnetic resonance imaging, has emerged as an integral tool for screening, classifying, prognosticating, and monitoring response to therapy in PH. Additionally, novel imaging modalities such as echocardiographic strain imaging, 3D echocardiography, dual energy CT, FDG-PET, and 4D flow MRI are actively being investigated to assess the severity of right ventricular dysfunction in PH. In this review, we will describe the utility and clinical application of multimodality imaging techniques across PH subtypes as it pertains to screening and monitoring of PH.

Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain)

Regional soft tissue mechanical strain offers crucial insights into tissue's mechanical function and vital indicators for different related disorders. Tagging magnetic resonance imaging (tMRI) has been the standard method for assessing the mechanical characteristics of organs such as the heart, the liver, and the brain. However, constructing accurate artifact-free pixelwise strain maps at the native resolution of the tagged images has for decades been a challenging unsolved task. In this work, we developed an end-to-end deep-learning framework for pixel-to-pixel mapping of the two-dimensional Eulerian principal strains [Formula: see text] and [Formula: see text] directly from 1-1 spatial modulation of magnetization (SPAMM) tMRI at native image resolution using convolutional neural network (CNN). Four different deep learning conditional generative adversarial network (cGAN) approaches were examined. Validations were performed using Monte Carlo computational model simulations, and in-vivo datasets, and compared to the harmonic phase (HARP) method, a conventional and validated method for tMRI analysis, with six different filter settings. Principal strain maps of Monte Carlo tMRI simulations with various anatomical, functional, and imaging parameters demonstrate artifact-free solid agreements with the corresponding ground-truth maps. Correlations with the ground-truth strain maps were R = 0.90 and 0.92 for the best-proposed cGAN approach compared to R = 0.12 and 0.73 for the best HARP method for [Formula: see text] and [Formula: see text], respectively. The proposed cGAN approach's error was substantially lower than the error in the best HARP method at all strain ranges. In-vivo results are presented for both healthy subjects and patients with cardiac conditions (Pulmonary Hypertension). Strain maps, obtained directly from their corresponding tagged MR images, depict for the first time anatomical, functional, and temporal details at pixelwise native high resolution with unprecedented clarity. This work demonstrates the feasibility of using the deep learning cGAN for direct myocardial and liver Eulerian strain mapping from tMRI at native image resolution with minimal artifacts.

Efficient Ventricular Parameter Estimation Using AI-Surrogate Models

The onset and progression of pathological heart conditions, such as cardiomyopathy or heart failure, affect its mechanical behaviour due to the remodelling of the myocardial tissues to preserve its functional response. Identification of the constitutive properties of heart tissues could provide useful biomarkers to diagnose and assess the progression of disease. We have previously demonstrated the utility of efficient AI-surrogate models to simulate passive cardiac mechanics. Here, we propose the use of this surrogate model for the identification of myocardial mechanical properties and intra-ventricular pressure by solving an inverse problem with two novel AI-based approaches. Our analysis concluded that: (i) both approaches were robust toward Gaussian noise when the ventricle data for multiple loading conditions were combined; and (ii) estimates of one and two parameters could be obtained in less than 9 and 18 s, respectively. The proposed technique yields a viable option for the translation of cardiac mechanics simulations and biophysical parameter identification methods into the clinic to improve the diagnosis and treatment of heart pathologies. In addition, the proposed estimation techniques are general and can be straightforwardly translated to other applications involving different anatomical structures.

Cardiovascular magnetic resonance virtual tagging with B-spline-based free-form deformation

PURPOSE

We developed a virtual tagging technique that reconstructs tagging images using the displacement field obtained by applying B-spline free-form deformation (FFD) between diastolic images and images of other cardiac phases in cardiac cine MRI. The purpose of this study was to validate its characteristics and usefulness in phantom and patient studies.

METHODS

Digital phantoms simulating uniform and non-uniform wall motion models were created, and virtual tagging images were reconstructed with various matrix sizes and tag resolutions to evaluate the accuracy of FFD and the characteristics of the tags. In the patient study, FFD's accuracy was assessed at three levels (base, middle, and apex) in healthy patients. In patients with heart failure, virtual tagging images were compared with strain maps obtained by feature tracking and virtual tagging.

RESULTS

In the phantom study, blurring of tags was observed when tags were reconstructed with high resolution using a small matrix size. In the patient study, the accuracy of FFD was lower in the base than in the apex. Patients with heart failure had decreased distortion of the displacement field vector and virtual tags, indicating decreased local wall motion, consistent with areas of abnormalities found in strain maps.

CONCLUSION

The virtual tagging technique does not require additional imaging and can visualize regional LV motion abnormalities via deformation of the tag as well as conventional cardiovascular magnetic resonance tagging.

Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation

Standard Electromechanical Wave Imaging isochrone generation relies on manual selection of zero-crossing (ZC) locations on incremental strain curves for a number of pixels in the segmented myocardium for each echocardiographic view and patient. When considering large populations, this becomes a time-consuming process, that can be limited by inter-observer variability and operator bias. In this study, we developed and optimized an automated ZC selection algorithm, towards a faster more robust isochrone generation approach. The algorithm either relies on heuristic-based baselines or machine learning classifiers. Manually generated isochrones, previously validated against 3D intracardiac mapping, were considered as ground truth during training and performance evaluation steps. The machine learning models applied herein for the first time were: i) logistic regression; ii) support vector machine (SVM); and iii) Random Forest. The SVM and Random Forest classifiers successfully identified accessory pathways in Wolff-Parkinson-White patients, characterized sinus rhythm in humans, and localized the pacing electrode location in left ventricular paced canines on the resulting isochrones. Nevertheless, the best performing classifier was proven to be Random Forest with a precision rising from 89.5% to 97%, obtained with the voting approach that sets a probability threshold upon ZC candidate selection. Furthermore, the predictivity was not dependent on the type of testing dataset it was applied to, contrary to SVM that exhibited a 5% drop in precision on the canine testing dataset. Finally, these findings indicate that a machine learning approach can reduce user variability and considerably decrease the durations required for isochrone generation, while preserving accurate activation patterns.

An off-resonance insensitive orthogonal CSPAMM sequence (ORI-O-CSPAMM) for the acquisition of CSPAMM and MICSR grids in half scan time

PURPOSE

To develop an Off-Resonance Insensitive Orthogonal CSPAMM sequence (ORI-O-CSPAMM) for the acquisition of CSPAMM and MICSR grids in half of the acquisition time.

METHODS

Phantom and mid-level left ventricle short-axis tagged images were acquired using CSPAMM, ORI-CSPAMM, O-CSPAMM, and the proposed ORI-O-CPAMM sequences to interrogate and compare its behavior under off-resonance effects produced by vegetable oil and subcutaneous and epicardial fat. The images were compared in terms of signal and the capacity to obtain complex difference and MICSR images.

RESULTS

Like ORI-CSPAMM, the proposed ORI-O-CSPAMM sequence removed almost completely the off-resonance artifacts produced during the tagging preparation. Tagging grids without DC components were obtained with ORI-O-CSPAMM using complex difference and MICSR from only two complementary images, which reduced the scan time to a half compared to CSPAMM and ORI-CSPAMM. The removal of off-resonance effects and the capacity to obtain MICSR images are advantages of ORI-O-CSPAMM over the O-CSPAMM sequence.

CONCLUSION

We developed a novel and fast tagging sequence designed to remove off-resonance effects during the tagging preparation, and to obtain complex difference and MICSR grids in half of the scan time compared to CSPAMM and ORI-CSPAMM sequences, which could allow its application to clinical protocols.

A comprehensive comparison between shortest-path HARP refinement, SinMod, and DENSEanalysis processing tools applied to CSPAMM and DENSE images

We addressed comprehensively the performance of Shortest-Path HARP Refinement (SP-HR), SinMod, and DENSEanalysis using 2D slices of synthetic CSPAMM and DENSE images with realistic contrasts obtained from 3D phantoms. The three motion estimation techniques were interrogated under ideal and no-ideal conditions (with MR induced artifacts, noise, and through-plane motion), considering several resolutions and noise levels. Under noisy conditions, and for isotropic pixel sizes of 1.5 mm and 3.0 mm in CSPAMM and DENSE images respectively, the nRMSE obtained for the circumferential and radial strain components were 10.7 ± 10.8% and 25.5 ± 14.8% using SP-HR, 11.9 ± 2.5% and 29.3 ± 6.5% using SinMod, and 6.4 ± 2.0% and 18.2 ± 4.6% using DENSEanalysis. Overall, the results showed that SP-HR tends to fail for large tissue motions, whereas SinMod and DENSEanalysis gave accurate displacement and strain field estimations, being the last which performed the best.

Arbitrary Point Tracking with Machine Learning to Measure Cardiac Strains in Tagged MRI

Cardiac tagged MR images allow for deformation fields to be measured in the heart by tracking the motion of tag lines throughout the cardiac cycle. Machine learning (ML) algorithms enable accurate and robust tracking of tag lines. Herein, the use of a massive synthetic physics-driven training dataset with known ground truth was used to train an ML network to enable tracking any number of points at arbitrary positions rather than anchored to the tag lines themselves. The tag tracking and strain calculation methods were investigated in a computational deforming cardiac phantom with known (ground truth) strain values. This enabled both tag tracking and strain accuracy to be characterized for a range of image acquisition and tag tracking parameters. The methods were also tested on in vivo volunteer data. Median tracking error was <0.26mm in the computational phantom, and strain measurements were improved in vivo when using the arbitrary point tracking for a standard clinical protocol.

Multiparametric Rest and Dobutamine Stress Magnetic Resonance in Assessment of Myocardial Viability

BACKGROUND

MR feature-tracking (FT) is a novel technique that quantitatively calculates myocardial strain and can assess myocardial viability.

PURPOSE

To evaluate the feasibility of FT at rest and with low-dose dobutamine (LDD), visual assessment of contractility with LDD and left ventricle (LV) end-diastolic wall thickness (EDWT) in the assessment of viability in ischemic cardiomyopathy (ICM) patients compared to delayed gadolinium enhancement (DGE).

STUDY TYPE

Prospective.

SUBJECTS

Thirty ICM patients and 30 healthy volunteers.

FIELD STRENGTH/SEQUENCES

A 1.5 T with balanced steady-state free precession (bSSFP) cine and phase-sensitive inversion prepared segmented gradient echo sequences.

ASSESSMENT

LDD (5 μg/kg/min and 10 μg/kg/min) was administered in the patient group. LV was divided into 16 segments and MR-FT was derived from bSSFP cine images using dedicated software. Viable segments were defined as those with a dobutamine-induced increase in resting MR-FT values >20%, a dobutamine-induced increase in systolic wall thickening ≥2 mm by visual assessment, ≤50% fibrosis on DGE, and resting EDWT ≥5.5 mm.

STATISTICAL TESTS

One-way analysis of variance (ANOVA), two-sampled t-test, paired samples t-test, and receiver operating characteristic (ROC) curve analysis. A P value < 0.05 was considered statistically significant.

RESULTS

Resting peak global circumferential (Ecc) and radial (Err) strains were significantly impaired in patients compared to controls (-11.7 ± 7.9 vs. -20.1 ± 5.7 and 19.7 ± 13.9 vs. 32.7 ± 15.4, respectively). Segments with no DGE (n = 354) and ≤ 50% (n = 38) DGE showed significant improvement of both Ecc and Err with LDD while segments with >50% DGE (n = 88) showed no improvement. In comparison to viable and nonviable segments identified by reference-standard DGE, the sensitivity, specificity, and diagnostic accuracy of the four methods were: 74%, 92%, and 89%, respectively, for Ecc; 70%, 89%, and 86%, respectively, for Err; 67%, 88%, and 84% for visual assessment; and 39%, 90%, and 80% for EDWT.

DATA CONCLUSION

Quantitative assessment of MR-FT, along with EDWT and qualitative visual assessment of myocardial contractility with LDD, are feasible alternative methods for the assessment of myocardial viability with moderate sensitivity and high specificity.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage: 2.

HARP-I: A Harmonic Phase Interpolation Method for the Estimation of Motion From Tagged MR Images

We proposed a novel method called HARP-I, which enhances the estimation of motion from tagged Magnetic Resonance Imaging (MRI). The harmonic phase of the images is unwrapped and treated as noisy measurements of reference coordinates on a deformed domain, obtaining motion with high accuracy using Radial Basis Functions interpolations. Results were compared against Shortest Path HARP Refinement (SP-HR) and Sine-wave Modeling (SinMod), two harmonic image-based techniques for motion estimation from tagged images. HARP-I showed a favorable similarity with both methods under noise-free conditions, whereas a more robust performance was found in the presence of noise. Cardiac strain was better estimated using HARP-I at almost any motion level, giving strain maps with less artifacts. Additionally, HARP-I showed better temporal consistency as a new method was developed to fix phase jumps between frames. In conclusion, HARP-I showed to be a robust method for the estimation of motion and strain under ideal and non-ideal conditions.

Validation of a deep-learning semantic segmentation approach to fully automate MRI-based left-ventricular deformation analysis in cardiotoxicity

OBJECTIVE

Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to chemotherapy for breast cancer. This study investigated an automated and supervised deep convolutional neural network (DCNN) model for LV chamber quantification before strain analysis in DENSE images.

METHODS

The DeepLabV3 +DCNN with three versions of ResNet-50 backbone was designed to conduct chamber quantification on 42 female breast cancer data sets. The convolutional layers in the three ResNet-50 backbones were varied as non-atrous, atrous and modified, atrous with accuracy improvements like using Laplacian of Gaussian filters. Parameters such as LV end-diastolic diameter (LVEDD) and ejection fraction (LVEF) were quantified, and myocardial strains analyzed with the Radial Point Interpolation Method (RPIM). Myocardial classification was validated with the performance metrics of accuracy, Dice, average perpendicular distance (APD) and others. Repeated measures ANOVA and intraclass correlation (ICC) with Cronbach's α (C-Alpha) tests were conducted between the three DCNNs and a vendor tool on chamber quantification and myocardial strain analysis.

RESULTS

Validation results in the same test-set for myocardial classification were accuracy = 97%, Dice = 0.92, APD = 1.2 mm with the modified ResNet-50, and accuracy = 95%, Dice = 0.90, APD = 1.7 mm with the atrous ResNet-50. The ICC results between the modified ResNet-50, atrous ResNet-50 and vendor-tool were C-Alpha = 0.97 for LVEF (55±7%, 54±7%, 54±7%, p = 0.6), and C-Alpha = 0.87 for LVEDD (4.6 ± 0.3 cm, 4.6 ± 0.3 cm, 4.6 ± 0.4 cm, p = 0.7).

CONCLUSION

Similar performance metrics and equivalent parameters obtained from comparisons between the atrous networks and vendor tool show that segmentation with the modified, atrous DCNN is applicable for automated LV chamber quantification and subsequent strain analysis in cardiotoxicity.

ADVANCES IN KNOWLEDGE

A novel deep-learning technique for segmenting DENSE images was developed and validated for LV chamber quantification and strain analysis in cardiotoxicity detection.

CMR for myocardial characterization in ischemic heart disease: state-of-the-art and future developments

Ischemic heart disease and its sequelae are one of the major contributors to morbidity and mortality worldwide. Over the last decades, technological developments have strengthened the role of noninvasive imaging for detection, risk stratification, and management of patients with ischemic heart disease. Cardiac magnetic resonance (CMR) imaging incorporates both functional and morphological characterization of the heart to determine presence, acuteness, and severity of ischemic heart disease by evaluating myocardial wall motion and function, the presence and extent of myocardial edema, ischemia, and scarring. Currently established clinical protocols have already demonstrated their diagnostic and prognostic value. Nevertheless, there are emerging imaging technologies that provide additional information based on advanced quantification of imaging biomarkers and improved diagnostic accuracy, therefore potentially allowing reduction or avoidance of contrast and/or stressor agents. The aim of this review is to summarize the current state of the art of CMR imaging for ischemic heart disease and to provide insights into promising future developments.

Comparison between conventional and compressed sensing cine cardiovascular magnetic resonance for feature tracking global circumferential strain assessment

BACKGROUND

Feature tracking (FT) has become an established tool for cardiovascular magnetic resonance (CMR)-based strain analysis. Recently, the compressed sensing (CS) technique has been applied to cine CMR, which has drastically reduced its acquisition time. However, the effects of CS imaging on FT strain analysis need to be carefully studied. This study aimed to investigate the use of CS cine CMR for FT strain analysis compared to conventional cine CMR.

METHODS

Sixty-five patients with different left ventricular (LV) pathologies underwent both retrospective conventional cine CMR and prospective CS cine CMR using a prototype sequence with the comparable temporal and spatial resolution at 3 T. Eight short-axis cine images covering the entire LV were obtained and used for LV volume assessment and FT strain analysis. Prospective CS cine CMR data over 1.5 heartbeats were acquired to capture the complete end-diastolic data between the first and second heartbeats. LV volume assessment and FT strain analysis were performed using a dedicated software (ci42; Circle Cardiovasacular Imaging, Calgary, Canada), and the global circumferential strain (GCS) and GCS rate were calculated from both cine CMR sequences.

RESULTS

There were no significant differences in the GCS (- 17.1% [- 11.7, - 19.5] vs. - 16.1% [- 11.9, - 19.3; p = 0.508) and GCS rate (- 0.8 [- 0.6, - 1.0] vs. - 0.8 [- 0.7, - 1.0]; p = 0.587) obtained using conventional and CS cine CMR. The GCS obtained using both methods showed excellent agreement (y = 0.99x - 0.24; r = 0.95; p < 0.001). The Bland-Altman analysis revealed that the mean difference in the GCS between the conventional and CS cine CMR was 0.1% with limits of agreement between -2.8% and 3.0%. No significant differences were found in all LV volume assessment between both types of cine CMR.

CONCLUSION

CS cine CMR could be used for GCS assessment by CMR-FT as well as conventional cine CMR. This finding further enhances the clinical utility of high-speed CS cine CMR imaging.

Quantification of Biventricular Myocardial Strain Using CMR Feature Tracking: Reproducibility in Small Animals

Myocardial strain is a well-validated parameter for evaluating myocardial contraction. Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a novel method for the quantitative measurements of myocardial strain from routine cine acquisitions. In this study, we investigated the influence of temporal resolution on tracking accuracy of CMR-FT and the intraobserver, interobserver, and interstudy reproducibilities for biventricular strain analysis in mice from self-gated CMR at 11.7 T. 12 constitutive nexilin knockout (Nexn-KO) mice, heterozygous (Het, N = 6) and wild-type (WT, N = 6), were measured with a well-established self-gating sequence twice within two weeks. CMR-FT measures of biventricular global and segmental strain parameters were derived. Interstudy, intraobserver, and interobserver reproducibilities were investigated. For the assessment of the impact of the temporal resolution for the outcome in CMR-FT, highly oversampled semi-4 chamber and midventricular short-axis data were acquired and reconstructed with 10 to 80 phases per cardiac cycle. A generally reduced biventricular myocardial strain was observed in Nexn-KO Het mice. Excellent intraobserver and interobserver reproducibility was achieved in all global strains (ICC range from 0.76 to 0.99), where global right ventricle circumferential strain (RCSSAX) showed an only good interobserver reproducibility (ICC 0.65, 0.11-0.89). For interstudy reproducibility, left ventricle longitudinal strain (LLSLAX) was the most reproducible measure of strain (ICC 0.90, 0.71-0.97). The left ventricle radial strain (LRSSAX) (ICC 0.50, 0.10-0.83) showed fair reproducibility and RCSSAX (ICC 0.36, 0.14-0.74) showed only poor reproducibility. In general, compared with global strains, the segmental strains showed relatively lower reproducibility. A minimal temporal resolution of 20 phases per cardiac cycle appeared sufficient for CMR-FT strain analysis. The analysis of myocardial strain from high-resolution self-gated cine images by CMR-FT provides a highly reproducible method for assessing myocardial contraction in small rodent animals. Especially, global LV longitudinal and circumferential strain revealed excellent reproducibility of intra- and interobserver and interstudy measurements.

Reference ranges ("normal values") for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update

Cardiovascular magnetic resonance (CMR) enables assessment and quantification of morphological and functional parameters of the heart, including chamber size and function, diameters of the aorta and pulmonary arteries, flow and myocardial relaxation times. Knowledge of reference ranges ("normal values") for quantitative CMR is crucial to interpretation of results and to distinguish normal from disease. Compared to the previous version of this review published in 2015, we present updated and expanded reference values for morphological and functional CMR parameters of the cardiovascular system based on the peer-reviewed literature and current CMR techniques. Further, databases and references for deep learning methods are included.

Clinical validation of three cardiovascular magnetic resonance techniques to measure strain and torsion in patients with suspected coronary artery disease

BACKGROUND

Several cardiovascular magnetic resonance (CMR) techniques can measure myocardial strain and torsion with high accuracy. The purpose of this study was to compare displacement encoding with stimulated echoes (DENSE), tagging and feature tracking (FT) for measuring circumferential and radial myocardial strain and myocardial torsion in order to assess myocardial function and infarct scar burden both at a global and at a segmental level.

METHOD

116 patients with a high likelihood of coronary artery disease (European SCORE > 15%) underwent CMR examination including cine images, tagging, DENSE and late gadolinium enhancement (LGE) in the short axis direction. In total, 97 patients had signs of myocardial disease and 19 had no abnormalities in terms of left ventricular (LV) wall mass index, LV ejection fraction, wall motion, LGE or a history of myocardial infarction. Thirty-four patients had myocardial infarct scar with a transmural LGE extent (transmurality) that exceeded 50% of the wall thickness in at least one segment. Global circumferential strain (GCS) and global radial strain (GRS) was analyzed using FT of cine loops, deformation of tag lines or DENSE displacement.

RESULTS

DENSE and tagging both showed high sensitivity (82% and 71%) at a specificity of 80% for the detection of segments with > 50% LGE transmurality, and receiver operating characteristics (ROC) analysis showed significantly higher area under the curve-values (AUC) for DENSE (0.87) than for tagging (0.83, p < 0.001) and FT (0.66, p = 0.003). GCS correlated with global LGE when determined with DENSE (r = 0.41), tagging (r = 0.37) and FT (r = 0.15). GRS had a low but significant negative correlation with LGE; DENSE r = - 0.10, FT r = - 0.07 and tagging r = - 0.16. Torsion from DENSE and tagging had a weak correlation (- 0.20 and - 0.22 respectively) with global LGE.

CONCLUSION

Circumferential strain from DENSE detected segments with > 50% scar with a higher AUC than strain determined from tagging and FT at a segmental level. GCS and torsion computed from DENSE and tagging showed similar correlation with global scar size, while when computed from FT, the correlation was lower.

Role of Cardiovascular Magnetic Resonance in Ischemic Cardiomyopathy

Ischemic heart disease is the most common cause of cardiovascular morbidity and mortality. Cardiac magnetic resonance (CMR) improves on other noninvasive modalities in detection, assessment, and prognostication of ischemic heart disease. The incorporation of CMR in clinical trials allows for smaller patient samples without the sacrifice of power needed to demonstrate clinical efficacy. CMR can accurately quantify infarct acuity, size, and complications; guide therapy; and prognosticate recovery. Timing of revascularization remains the holy grail of ischemic heart disease, and viability assessment using CMR may be the missing link needed to help reduce morbidity and mortality associated with the disease.

Cardiac Magnetic Resonance Quantification of Structure-Function Relationships in Heart Failure

Classification of heart failure is based on the left ventricular ejection fraction (EF): preserved EF, midrange EF, and reduced EF. There remains an unmet need for further heart failure phenotyping of ventricular structure-function relationships. Because of high spatiotemporal resolution, cardiac magnetic resonance (CMR) remains the reference modality for quantification of ventricular contractile function. The authors aim to highlight novel frameworks, including theranostic use of ferumoxytol, to enable more efficient evaluation of ventricular function in heart failure patients who are also frequently anemic, and to discuss emerging quantitative CMR approaches for evaluation of ventricular structure-function relationships in heart failure.

A Pilot Study of Cardiac MRI in Breast Cancer Survivors After Cardiotoxic Chemotherapy and Three-Dimensional Conformal Radiotherapy

PURPOSE/OBJECTIVES

Node-positive breast cancer patients often receive chemotherapy and regional nodal irradiation. The cardiotoxic effects of these treatments, however, may offset some of the survival benefit. Cardiac magnetic resonance (CMR) is an emerging modality to assess cardiac injury. This is a pilot trial assessing cardiac damage using CMR in patients who received anthracycline-based chemotherapy and three-dimensional conformal radiotherapy (3DCRT) regional nodal irradiation using heart constraints.

MATERIALS AND METHODS

Node-positive breast cancer patients (2000-2008) treated with anthracycline-based chemotherapy and 3DCRT regional nodal irradiation (including the internal mammary chain nodes) with heart ventricular constraints (V25 < 10%) were invited to participate. Cardiac tissues were contoured and analyzed separately for whole heart (pericardium) and for combined ventricles and left atrium (myocardium). CMR obtained ventricular function/dimensions, late gadolinium enhancement (LGE), global longitudinal strain (GLS), and extracellular volume fraction (ECV) as measures of cardiac injury and/or early fibrosis. CMR parameters were correlated with dose-volume constraints using Spearman correlations.

RESULTS

Fifteen left-sided and five right-sided patients underwent CMR. Median diagnosis age was 50 (32-77). No patients had baseline cardiac disease before regional nodal irradiation. Median time after 3DCRT was 8.3 years (5.2-14.4). Median left-sided mean heart dose (MHD) was 4.8 Gy (1.1-11.2) and V25 was 5.7% (0-12%). Median left ventricular ejection fraction (LVEF) was 63%. No abnormal LGE was observed. No correlations were seen between whole heart doses and LVEF, LV mass, GLS, or LV dimensions. Increasing ECV did not correlate with increased heart or ventricular doses. However, correlations between higher LV mass and ventricular mean dose, V10, and V25 were seen.

CONCLUSION

At a median follow-up of 8.3 years, this cohort of node-positive breast cancer patients who received anthracycline-based chemotherapy and regional nodal irradiation had no clinically abnormal CMR findings. However, correlations between ventricular mean dose, V10, and V25 and LV mass were seen. Larger corroborating studies that include advanced techniques for measuring regional heart mechanics are warranted.

Cardiac MRI Reveals Late Diastolic Changes in Left Ventricular Relaxation Patterns During Healthy Aging

BACKGROUND

Cardiac MRI is an emerging modality for evaluating left ventricular (LV) diastolic dysfunction (LVDD), a pathological condition that is prevalent in aging populations. However, there is a lack of reports of MRI-derived LV diastolic properties in late diastole.

PURPOSE

To test the hypothesis that cine MRI-derived motion/deformation indices can be used to characterize age-related changes on LV relaxation patterns in late diastole.

STUDY TYPE

Retrospective.

POPULATION

In all, 412 participants (72.5 ± 4.6 years old, range 65-84) without a documented history of cardiovascular diseases.

FIELD STRENGTH/SEQUENCE

Balanced steady-state free precession(bSSFP) acquired at 1.5T.

ASSESSMENT

Participants were divided into younger (65-74 years old, n = 275) and older (75-84 years old, n = 137) groups. Status of diabetes mellitus (DM), hypertension (HTN), and lipid disorders were recorded for each participant. Cine MRI datasets were analyzed by using heart deformation analysis (HDA). LV motion/deformation indices (displacement, velocity, strain, and strain rate) were measured through 22 phases within a cardiac cycle.

STATISTICAL TESTS

The prevalence of traditional cardiovascular risk conditions, LV ejection fraction (LVEF), peak LV regional displacement, velocity, and strain rates at early and late diastole were compared between two participant groups using chi-square tests or t-tests.

RESULTS

Older participants had a significantly lower peak early radial displacement (0.797 ± 0.249 cm vs. 0.876 ± 0.286 cm), radial velocity (19.3 ± 6.3 mm/s vs. 17.5 ± 5.2 mm/s), and circumferential strain rate (64.6 ± 15.7%/s vs. 70.1 ± 17%/s) but a higher peak late circumferential strain rate (69.8 ± 16.3 %/s vs. 66 ± 15.8 %/s) than their younger counterparts.

DATA CONCLUSION

Cine MRI can be used to characterize age-related LV relaxation patterns in late diastole.

LEVEL OF EVIDENCE

3.

TECHNICAL EFFICACY STAGE

1.

Detection of subclinical myocardial dysfunction in cocaine addicts with feature tracking cardiovascular magnetic resonance

BACKGROUND

Cocaine is an addictive, sympathomimetic drug with potentially lethal effects. We have previously shown with cardiovascular magnetic resonance (CMR) the presence of cardiovascular involvement in a significant percentage of consecutive asymptomatic cocaine addicts. CMR with feature-tracking analysis (CMR-FT) allows for the quantification of myocardial deformation which may detect preclinical involvement. Therefore, we aimed to assess the effects of cocaine on the left ventricular myocardium in a group of asymptomatic cocaine users with CMR-FT.

METHODS

In a cohort of asymptomatic cocaine addicts (CA) who had been submitted to CMR at 3 T, we used CMR-FT to measure strain, strain rate and dyssynchrony index in CA with mildly decreased left ventricular ejection fraction (CA-LVEFd) and in CA with preserved ejection fraction (CA-LVEFp). We also measured these parameters in 30 age-matched healthy subjects.

RESULTS

There were no differences according to age. Significant differences were seen in global longitudinal, radial and circumferential strain, in global longitudinal and radial strain rate and in radial and circumferential dyssynchrony index among the groups, with the lowest values in CA-LVEFd and intermediate values in CA-LVEFp. Longitudinal, radial and circumferential strain values were significantly lower in CA-LVEFp with respect to controls.

CONCLUSIONS

CA-LVEFp show decreased systolic strain and strain rate values, with intermediate values between healthy controls and CA-LVEFd. Signs suggestive of dyssynchrony were also detected. In CA, CMR-FT based strain analysis can detect early subclinical myocardial involvement.

Head-to-head comparison of cardiovascular MR feature tracking cine versus acquisition-based deformation strain imaging using myocardial tagging and strain encoding

PURPOSE

Myocardial feature-tracking (FT) deformation imaging is superior for risk stratification compared with volumetric approaches. Because there is no clear recommendation regarding FT postprocessing, we compared different FT-strain analyses with reference standard techniques, including tagging and strain-encoded (SENC) MRI.

METHODS

Feature-tracking software from four different vendors (TomTec, Medis, Circle [CVI], and Neosoft), tagging (Segment), and fastSENC (MyoStrain) were used to determine left ventricular global circumferential strains (GCS) and longitudinal strains (GLS) in 12 healthy volunteers and 12 patients with heart failure. Variability and agreements were assessed using intraclass correlation coefficients for absolute agreement (ICCa) and consistency (ICCc) as well as Pearson correlation coefficients.

RESULTS

For FT-GCS, consistency was excellent comparing different FT vendors (ICCc = 0.84-0.97, r = 0.86-0.95) and in comparison to fast SENC (ICCc = 0.78-0.89, r = 0.73-0.81). FT-GCS consistency was excellent compared with tagging (ICCc = 0.79-0.85, r = 0.74-0.77) except for TomTec (ICCc = 0.68, r = 0.72). Absolute FT-GCS agreements among FT vendors were highest for CVI and Medis (ICCa = 0.96) and lowest for TomTec and Neosoft (ICCa = 0.32). Similarly, absolute FT-GCS agreements were excellent for CVI and Medis compared with both tagging and fast SENC (ICCa = 0.84-0.88), good to excellent for Neosoft (ICCa = 0.77 and 0.64), and lowest for TomTec (ICCa = 0.41 and 0.47). For FT-GLS, consistency was excellent (ICCc ≥ 0.86, r ≥ 0.76). Absolute agreements among FT vendors were excellent (ICCa = 0.91-0.93) or good to excellent for TomTec (ICCa = 0.69-0.85). Absolute agreements (ICCa) were good (CVI 0.70, Medis 0.60) and fair (TomTec 0.41, Neosoft 0.59) compared with tagging, but excellent compared with fast SENC (ICCa = 0.77-0.90).

CONCLUSION

Although absolute agreements differ depending on deformation assessment approaches, consistency and correlation are consistently high regardless of the method chosen, thus indicating reliable strain assessment. Further standardisation and introduction of uniform references is warranted for routine clinical implementation.

Improved real-time tagged MRI using REALTAG

OBJECTIVES

To evaluate a novel method for real-time tagged MRI with increased tag persistence using phase sensitive tagging (REALTAG), demonstrated for speech imaging.

METHODS

Tagging is applied as a brief interruption to a continuous real-time spiral acquisition. REALTAG is implemented using a total tagging flip angle of 180° and a novel frame-by-frame phase sensitive reconstruction to remove smooth background phase while preserving the sign of the tag lines. Tag contrast-to-noise ratio of REALTAG and conventional tagging (total flip angle of 90°) is simulated and evaluated in vivo. The ability to extend tag persistence is tested during the production of vowel-to-vowel transitions by American English speakers.

RESULTS

REALTAG resulted in a doubling of contrast-to-noise ratio at each time point and increased tag persistence by more than 1.9-fold. The tag persistence was 1150 ms with contrast-to-noise ratio >6 at 1.5T, providing 2 mm in-plane resolution, 179 frames/s, with 72.6 ms temporal window width, and phase sensitive reconstruction. The new imaging window is able to capture internal tongue deformation over word-to-word transitions in natural speech production.

CONCLUSION

Tag persistence is substantially increased in intermittently tagged real-time MRI by using the improved REALTAG method. This makes it possible to capture longer motion patterns in the tongue, such as cross-word vowel-to-vowel transitions, and provides a powerful new window to study tongue biomechanics.

Assessment of diastolic dysfunction: comparison of different cardiovascular magnetic resonance techniques

Aims

Heart failure with preserved ejection fraction is still a diagnostic and therapeutic challenge, and accurate non‐invasive diagnosis of left ventricular (LV) diastolic dysfunction (DD) remains difficult. The current study aimed at identifying the most informative cardiovascular magnetic resonance (CMR) parameters for the assessment of LVDD.

Methods and results

We prospectively included 50 patients and classified them into three groups: with DD (DD+, n = 15), without (DD−, n = 26), and uncertain (DD±, n = 9). Diagnosis of DD was based on echocardiographic E/E′, invasive LV end‐diastolic pressure, and N‐terminal pro‐brain natriuretic peptide. CMR was performed at 1.5 T to assess LV and left atrial (LA) morphology, LV diastolic strain rate (SR) by tissue tracking and tagging, myocardial peak velocities by tissue phase mapping, and transmitral inflow profile using phase contrast techniques. Statistics were performed only on definitive DD+ and DD− (total number 41). DD+ showed enlarged LA with LA end‐diastolic volume/height performing best to identify DD+ with a cut‐off value of ≥0.52 mL/cm (sensitivity = 0.71, specificity = 0.84, and area under the receiver operating characteristic curve = 0.75). DD+ showed significantly reduced radial (inferolateral E peak: DD−: −14.5 ± 6.5%/s vs. DD+: −10.9 ± 5.9%/s, P = 0.04; anterolateral A peak: DD−: −4.2 ± 1.6%/s vs. DD+: −3.1 ± 1.4%/s, P = 0.04) and circumferential (inferolateral A peak: DD−: 3.8 ± 1.2%/s vs. DD+: 2.8 ± 0.8%/s, P = 0.007; anterolateral A peak: DD−: 3.5 ± 1.2%/s vs. DD+: 2.5 ± 0.8%/s, P = 0.048) SR in the basal lateral wall assessed by tissue tracking. In the same segments, DD+ showed lower peak myocardial velocity by tissue phase mapping (inferolateral radial peak: DD−: −3.6 ± 0.7 ms vs. DD+: −2.8 ± 1.0 ms, P = 0.017; anterolateral longitudinal peak: DD−: −5.0 ± 1.8 ms vs. DD+: −3.4 ± 1.4 ms, P = 0.006). Tagging revealed reduced global longitudinal SR in DD+ (DD−: 45.8 ± 12.0%/s vs. DD+: 34.8 ± 9.2%/s, P = 0.022). Global circumferential and radial SR by tissue tracking and tagging, LV morphology, and transmitral flow did not differ between DD+ and DD−.

Conclusions

Left atrial size and regional quantitative myocardial deformation applying CMR identified best patients with DD.

Rotation and torsion of the left ventricle with cardiovascular magnetic resonance tagging: comparison of two analysis methods

Background

Left ventricle rotation and torsion are fundamental components of myocardial function, and several software packages have been developed for analysis of these components. The purpose of this study was to compare the suitability of two software packages with different technical principles for analysis of rotation and torsion of the left ventricle during systole.

Methods

A group of hypertrophic cardiomyopathy (HCM) patients (N = 14, age 43 ± 11 years), mutation carriers without hypertrophy (N = 10, age 34 ± 13 years), and healthy relatives (N = 12, age 43 ± 17 years) underwent a cardiovascular magnetic resonance examination, including spatial modulation of magnetization tagging sequences in basal and apical planes of the left ventricle. The tagging images were analyzed offline using a harmonic phase image analysis method with Gabor filtering and a non-rigid registration-based free-form deformation technique. Left-ventricle rotation and torsion scores were obtained from end-diastole to end-systole with both software.

Results

Analysis was successful in all cases with both software applications. End-systolic torsion values between the study groups were not statistically different with either software. End-systolic apical rotation, end-systolic basal rotation, and end-systolic torsion were consistently higher when analyzed with non-rigid registration than with harmonic phase-based analysis (p <  0.0001). End-systolic rotation and torsion values had significant correlations between the two software (p <  0.0001), most significant in the apical plane.

Conclusions

When comparing absolute values of rotation and torsion between different individuals, software-specific reference values are required. Harmonic phase flow with Gabor filtering and non-rigid registration-based methods can both be used reliably in the analysis of systolic rotation and torsion patterns of the left ventricle.

Validation of Diffeomorphic Registration on Cine Cardiac MR via Direct Frame-to-Frame Comparison with HARP Tracking on Tagged MR

Cardiac magnetic resonance (MR) tissue tagging offers an excellent solution for tracking deformation and is considered the reference standard for the quantification of strain. However, due to the requirements for a dedicated acquisition sequence and post-processing software, tagged MR acquisitions are performed much less frequently in routine clinical practice than the anatomical cine MR sequence. Using tagged MR as the reference standard, this study proposes an approach to evaluate a diffeomorphic image registration algorithm applied on cine MR images to compute the cardiac deformation. In contrast to previous evaluation methods that compared the final results, such as strain, computed from cine and tagged MR sequences, the proposed method performs a direct frame-to-frame comparison in the evaluation. To overcome the problem of misalignment between the tagged and cine MR images, the proposed approach performs transformations to and from the two-dimensional image pixel coordinates and three-dimensional space using the meta-information encoded in the MR images. Linear temporal interpolation is performed using the frame acquisition time since the last R-wave peak value of the electrocardiogram signal recorded in the meta-information. Several statistic measures are computed and reported for the registration error using the Euclidean distances between the corresponding set of points obtained using cine and tagged MR images.

On the in vivo systolic compressibility of left ventricular free wall myocardium in the normal and infarcted heart

Although studied for many years, there remain continued gaps in our fundamental understanding of cardiac kinematics, such as the nature and extent of heart wall volumetric changes that occur over the cardiac cycle. Such knowledge is especially important for accurate in silico simulations of cardiac pathologies and in the development of novel therapies for their treatment. A prime example is myocardial infarction (MI), which induces profound, regionally variant maladaptive remodeling of the left ventricle (LV) wall. To address this problem, we conducted an in vivo fiduciary marker-based study in an established ovine model of MI to generate detailed, time-evolving transmural in vivo volumetric measurements of LV free wall deformations in the normal state, as well as up to 12 h post-MI. This was accomplished using a transmural array of sonomicrometry crystals that acquired fiducial positions at ∼250 Hz with a positional accuracy of ∼0.1 mm, covering the entire infarct, border, and remote zones. A convex-hull method was used to directly calculate the Jacobian J(t)=Δv(t)/ΔVED from sonocrystal positions over the entire cardiac cycle, where ΔV is the volume of each convex polyhedral at end diastole (ED) (typically ∼1 cc). We demonstrated significant in vivo compressibility in normal functioning LV free wall myocardium, with JES=0.85±0.07 at end systole (ES). We also observed substantial regional variations, with the largest reduction in local myocardial tissue volume during systole in the base region accompanied by substantial transmural gradients. These patterns changed profoundly following loss of perfusion post-MI, with the apical region showing the greatest loss of volume reduction at ES. To verify that the sonocrystals did not affect local volumetric measurements, JES measures were also verified by non-invasive magnetic resonance imaging, exhibiting very similar changes in regional volume. We note that while our estimates of regional compressibility were in close agreement with the values previously reported for large animals, ranging from 5% to 20%, the direct, comprehensive measurements of wall compressibility presented herein improved on the limitations of previous reports. These limitations included dependency on the small local volumes used for analysis and often indirect measurement of compressibility. Our novel findings suggest that proper accounting for the myocardial effective compressibility at the ∼1 cc volume scale can improve the accuracy of existing kinematic indices, such as wall thickening and axial shortening, and simulations of LV remodeling following MI.

2- and 3-Dimensional Myocardial Strain in Cardiac Health and Disease

Advances in speckle-tracking echocardiography allowed the rise of deformation imaging as a feasible, robust, and valuable tool for clinical routine. The global or segmental measurement of strain can objectively quantify myocardial deformation and can characterize myocardial function in a novel way. However, the proper interpretation of deformation measurements requires understanding of cardiac mechanics and the influence of loading conditions, ventricular geometry, conduction delays, and myocardial tissue characteristics on the measured values. The purpose of this manuscript is to review the basic concepts of deformation imaging, briefly describe imaging modalities for strain assessment, and discuss in depth the underlying physical and pathophysiological mechanisms which lead to the respective findings in a specific disease.

Inter-study repeatability of circumferential strain and diastolic strain rate by CMR tagging, feature tracking and tissue tracking in ST-segment elevation myocardial infarction

Strain assessment allows accurate evaluation of myocardial function and mechanics in ST-segment elevation myocardial infarction (STEMI). Strain using cardiovascular magnetic resonance (CMR) has traditionally been assessed with tagging but limitations of this technique have led to more widespread use of alternative methods, which may be more robust. We compared the inter-study repeatability of circumferential global peak-systolic strain (Ecc) and peak-early diastolic strain rate (PEDSR) derived by tagging with values obtained using novel cine-based software: Feature Tracking (FT) (TomTec, Germany) and Tissue Tracking (TT) (Circle cvi42, Canada) in patients following STEMI. Twenty male patients (mean age 56 ± 10 years, mean infarct size 13.7 ± 7.1% of left ventricular mass) were randomised to undergo CMR 1-5 days post-STEMI at 1.5 T or 3.0 T, repeated after ten minutes at the same field strength. Ecc and PEDSR were assessed using tagging, FT and TT. Inter-study repeatability was evaluated using Bland-Altman analyses, coefficients of variation (CoV) and intra-class correlation coefficient (ICC). Ecc (%) was significantly lower with tagging than with FT or TT at 1.5 T (- 9.5 ± 3.3 vs. - 17.5 ± 3.8 vs. -15.5 ± 5.2, respectively, p < 0.001) and 3.0 T (- 13.1 ± 1.8 vs. - 19.4 ± 2.9 vs. - 17.3 ± 2.1, respectively, p = 0.001). This was similar for PEDSR (.s-1): 1.5 T (0.6 ± 0.2 vs. 1.5 ± 0.4 vs. 1.0 ± 0.4, for tagging, FT and TT respectively, p < 0.001) and 3.0 T (0.6 ± 0.2 vs. 1.5 ± 0.3 vs. 0.9 ± 0.3, respectively, p < 0.001). Inter-study repeatability for Ecc at 1.5 T was good for tagging and excellent for FT and TT: CoV 16.7%, 6.38%, and 8.65%, respectively. Repeatability for Ecc at 3.0 T was good for all three techniques: CoV 14.4%, 11.2%, and 13.0%, respectively. However, repeatability of PEDSR was generally lower than that for Ecc at 1.5 T (CoV 15.1%, 13.1%, and 34.0% for tagging, FT and TT, respectively) and 3.0 T (CoV 23.0%, 18.6%, and 26.2%, respectively). Following STEMI, Ecc and PEDSR are higher when measured with FT and TT than with tagging. Inter-study repeatability of Ecc is good for tagging, excellent for FT and TT at 1.5 T, and good for all three methods at 3.0 T. The repeatability of PEDSR is good to moderate at 1.5 T and moderate at 3.0 T. Cine-based methods to assess Ecc following STEMI may be preferable to tagging.