Human heart: tagging with MR imaging--a method for noninvasive assessment of myocardial motion

Myocardial Strain Imaging: Theory, Current Practice, and the Future

Myocardial strain imaging by echocardiography or cardiac magnetic resonance (CMR) is a powerful method to diagnose cardiac disease. Strain imaging provides measures of myocardial shortening, thickening, and lengthening and can be applied to any cardiac chamber. Left ventricular (LV) global longitudinal strain by speckle-tracking echocardiography is the most widely used clinical strain parameter. Several CMR-based modalities are available and are ready to be implemented clinically. Clinical applications of strain include global longitudinal strain as a more sensitive method than ejection fraction for diagnosing mild systolic dysfunction. This applies to patients suspected of having heart failure with normal LV ejection fraction, to early systolic dysfunction in valvular disease, and when monitoring myocardial function during cancer chemotherapy. Segmental LV strain maps provide diagnostic clues in specific cardiomyopathies, when evaluating LV dyssynchrony and ischemic dysfunction. Strain imaging is a promising modality to quantify right ventricular function. Left atrial strain may be used to evaluate LV diastolic function and filling pressure.

Automatic analysis of three-dimensional cardiac tagged magnetic resonance images using neural networks trained on synthetic data

BACKGROUND

Three-dimensional (3D) tagged magnetic resonance (MR) imaging enables in-vivo quantification of cardiac motion. While deep learning methods have been developed to analyze these images, they have been restricted to two-dimensional datasets. We present a deep learning approach specifically designed for displacement analysis of 3D cardiac tagged MR images.

METHODS

We developed two neural networks to predict left-ventricular motion throughout the cardiac cycle. Networks were trained using synthetic 3D tagged MR images, generated by combining a biophysical left-ventricular model with an analytical MR signal model. Network performance was initially validated on synthetic data, including assessment of signal-to-noise ratio sensitivity. The networks were then retrospectively evaluated on an in-vivo external validation human dataset and an in-vivo porcine study.

RESULTS

For the external validation dataset, predicted displacements deviated from manual tracking by median (interquartile range) values of 0.72 (1.17), 0.81 (1.64), and 1.12 (4.17) mm in x, y, and z directions, respectively. In the porcine dataset, strain measurements showed median (interquartile range) differences from manual annotations of 0.01 (0.04), 0.01 (0.06), and -0.01 (0.18) for circumferential, longitudinal, and radial components, respectively. These strain values are within physiological ranges and demonstrate superior performance of the network approach compared to existing 3D tagged image analysis methods.

CONCLUSION

The method enables rapid analysis times of approximately 10 s per cardiac phase, making it suitable for large cohort investigations.

The White Matter Fiber Tract Deforms Most in the Perpendicular Direction During In Vivo Volunteer Impacts

White matter (WM) tract-related strains are increasingly used to quantify brain mechanical responses, but their dynamics in live human brains during in vivo impact conditions remain largely unknown. Existing research primarily looked into the normal strain along the WM fiber tracts (i.e., tract-oriented normal strain), but it is rarely the case that the fiber tract only endures tract-oriented normal strain during impacts. In this study, we aim to extend the in vivo measurement of WM fiber deformation by quantifying the normal strain perpendicular to the fiber tract (i.e., tract-perpendicular normal strain) and the shear strain along and perpendicular to the fiber tract (i.e., tract-oriented shear strain and tract-perpendicular shear strain, respectively). To achieve this, we combine the three-dimensional strain tensor from the tagged magnetic resonance imaging with the diffusion tensor imaging (DTI) from an open-access dataset, including 44 volunteer impacts under two head loading modes, i.e., neck rotations (N = 30) and neck extensions (N = 14). The strain tensor is rotated to the coordinate system with one axis aligned with DTI-revealed fiber orientation, and then four tract-related strain measures are calculated. The results show that tract-perpendicular normal strain peaks are the largest among the four strain types (p < 0.05, Friedman's test). The distribution of tract-related strains is affected by the head loading mode, of which laterally symmetric patterns with respect to the midsagittal plane are noted under neck extensions, but not under neck rotations. Our study presents a comprehensive in vivo strain quantification toward a multifaceted understanding of WM dynamics. We find that the WM fiber tract deforms most in the perpendicular direction, illuminating new fundamentals of brain mechanics. The reported strain images can be used to evaluate the fidelity of computational head models, especially those intended to predict fiber deformation under noninjurious conditions.

Adolescent Reference Values for MR-Derived Biventricular Strain Obtained Using Feature-Tracking and Myocardial Tagging

BACKGROUND

Myocardial strain is a promising marker for the detection of early left or right ventricular (LV or RV) dysfunction in pediatric populations. The reference standard for MR strain measurement is myocardial tagging (MT); however, MT has limited clinical utility because the additional acquisitions needed are time-consuming. In contrast, MR-feature tracking (FT) allows strain quantification from routinely acquired cine sequences. Studies providing reference values obtained with both FT and MT for adolescents are lacking.

PURPOSE

To use MR-FT and MT to define sex-specific LV and RV strain reference values for adolescents.

STUDY TYPE

Cross-sectional, prospective.

POPULATION

One hundred twenty-three adolescents aged 15-18 years (52% girls) without known cardiovascular disease.

FIELD STRENGTH/SEQUENCE

Balanced steady-state free-precession sequence for FT analysis and a spatial modulation of magnetization hybrid TFE-EPI sequence for MT acquisitions at 3.0-T.

ASSESSMENT

Segment Medviso software was used to obtain longitudinal (LS) and circumferential (CS) strain for both ventricles, and radial strain (RS) for LV.

STATISTICAL TESTS

The Student t-test was used for between-sex comparisons of continuous variables. Sex-specific percentiles were calculated using the weighted average method. Intraobserver and interobserver agreement was assessed in 30 randomly selected studies using intraclass correlation coefficients (ICC). A P-value <0.05 was considered statistically significant.

RESULTS

FT-derived LVLS and LVCS were significantly higher in girls than in boys (-19.8% vs. -17.8% and -22.2% vs. -21.0%, respectively), as they were with MT (LVLS: -18.1% vs. -16.8%; LVCS: -20.8% vs. -19.7%). FT-LVRS was higher in girls than in boys (44.8% vs. 35.1%), while MT-LVRS was the opposite (18.6% vs. 22.7%). FT-RVLS was higher in girls (-23.4% vs. -21.3%), but there were no between-sex differences in MT-derived RVLS or RVCS. ICC values for intraobserver agreement were ≥0.89, whereas for interobserver agreement were <0.80 for MT-LVRS and ≥0.80 for all remaining parameters.

DATA CONCLUSION

This study provides sex-specific reference biventricular strain values obtained with MR-MT and MR-FT for adolescents aged 15-18 years. MR-FT may be a valid method for obtaining strain values in pediatric populations.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 3.

Fetal cardiovascular magnetic resonance feature tracking myocardial strain analysis in congenital heart disease

BACKGROUND

Cardiovascular magnetic resonance (CMR) is an emerging imaging modality for assessing the anatomy and function of the fetal heart in congenital heart disease (CHD). This study aimed to evaluate myocardial strain using fetal CMR feature tracking (FT) in different subtypes of CHD.

METHODS

Fetal CMR FT analysis was retrospectively performed on four-chamber cine images acquired with Doppler ultrasound gating at 3T. Left ventricular (LV) global longitudinal strain (GLS), LV global radial strain (GRS), LV global longitudinal systolic strain rate, and right ventricular (RV) GLS were quantified using dedicated software optimized for fetal strain analysis. Analysis was performed in normal fetuses and different CHD subtypes (d-transposition of the great arteries [dTGA], hypoplastic left heart syndrome [HLHS], coarctation of the aorta [CoA], tetralogy of Fallot [TOF], RV-dominant atrioventricular septal defect [AVSD], and critical pulmonary stenosis or atresia [PS/PA]). Analysis of variance with Tukey post-hoc test was used for group comparisons.

RESULTS

A total of 60 fetuses were analyzed (8/60 (13%) without CHD, 52/60 (87%) with CHD). Myocardial strain was successfully assessed in 113/120 ventricles (94%). Compared to controls, LV GLS was significantly reduced in fetuses with HLHS (-18.6±2.7% vs -6.2±5.6%; p<0.001) and RV-dominant AVSD (-18.6±2.7% vs -7.7±5.0%; p = 0.003) and higher in fetuses with CoA (-18.6±2.7% vs -25.0±4.3%; p = 0.038). LV GRS was significantly reduced in fetuses with HLHS (25.7±7.5% vs 11.4±9.7%; p = 0.024). Compared to controls, RV GRS was significantly reduced in fetuses with PS/PA (-16.1±2.8% vs -8.3±4.2%; p = 0.007). Across all strain parameters, no significant differences were present between controls and fetuses diagnosed with dTGA and TOF.

CONCLUSION

Fetal myocardial strain assessment with CMR FT in CHD is feasible. Distinct differences are present between various types of CHD, suggesting potential implications for clinical decision-making and prognostication in fetal CHD.

Quantification of left ventricular myocardial strain: Comparison between MRI tagging, MRI feature tracking, and ultrasound speckle tracking

Ultrasound speckle tracking is frequently used to quantify myocardial strain, and magnetic resonance imaging (MRI) feature tracking is rapidly gaining interest. Our aim is to validate cardiac MRI feature tracking by comparing it with the gold standard method (i.e., MRI tagging) in healthy subjects and patients. Furthermore, we aim to perform an indirect validation by comparing ultrasound speckle tracking with MRI feature tracking. Forty-two subjects (17 formerly preeclamptic women, three healthy women, and 22 left bundle branch block patients of both sexes) received 3-T cardiac MRI and echocardiography. Cine and tagged MRI, and B-mode ultrasound images, were acquired. Intrapatient global and segmental left ventricular circumferential (MRI tagging vs. MRI feature tracking) and longitudinal (MRI feature tracking vs. ultrasound speckle tracking) peak strain and time to peak strain were compared between the three techniques. Intraclass correlation coefficient (ICC) (< 0.50 = poor, 0.50-0.75 = moderate, > 0.75-0.90 = good, > 0.90 = excellent) and Bland-Altman analysis were used to assess correlation and bias; p less than 0.05 indicates a significant ICC or bias. Global peak strain parameters showed moderate-to-good correlations between methods (ICC = 0.71-0.83, p < 0.01) with no significant biases. Global time to peak strain parameters showed moderate-to-good correlations (ICC = 0.56-0.82, p < 0.01) with no significant biases. Segmental peak strains showed significant biases in all parameters and moderate-to-good correlation (ICC = 0.62-0.77, p < 0.01), except for lateral longitudinal peak strain (ICC = 0.23, p = 0.22). Segmental time to peak strain parameters showed moderate-to-good correlation (ICC = 0.58-0.74, p < 0.01) with no significant biases. MRI feature tracking is a valid method to examine myocardial strain, but there is bias in absolute segmental strain values between imaging techniques. MRI feature tracking shows adequate comparability with ultrasound speckle tracking.

Compositional and Functional MRI of Skeletal Muscle: A Review

Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

A New Coding System for the Identification of Left Ventricular Rotation Patterns and Their Relevance to Myocardial Function

Rotational mechanics is a fundamental determinant of left ventricular ejection fraction (LVEF). The coding system currently employed in clinical practice does not distinguish between rotational patterns. We propose an alternative coding system that makes possible to identify the rotational pattern of the LV and relate it to myocardial function. Echocardiographic images were used to generate speckle tracking-derived transmural global longitudinal strain (tGLS) and rotational parameters. The existence of twist (basal and apical rotations in opposite directions) is expressed as a rotational gradient with a positive value that is the sum of the basal and apical rotation angles. Conversely, when there is rigid rotation (basal and apical rotations in the same direction) the resulting gradient is assigned a negative value that is the subtraction between the two rotation angles. The rotational patterns were evaluated in 87 healthy subjects and 248 patients with LV hypertrophy (LVH) and contrasted with their myocardial function. Our approach allowed us to distinguish between the different rotational patterns. Twist pattern was present in healthy controls and 104 patients with LVH and normal myocardial function (tGLS ≥ 17%, both). Among 144 patients with LVH and myocardial dysfunction (tGLS < 17%), twist was detected in 83.3% and rigid rotation in 16.7%. LVEF was < 50% in 34.7%, and all patients with rigid rotation had a LVEF < 50%. The gradient rotational values showed a close relationship with LVEF (r = 0.73; p < 0.001). The proposed coding system allows us to identify the rotational patterns of the LV and to relate their values with LVEF.

Feature-Tracking Strain Parameters Differ Between Highly Accelerated and Conventional Acquisitions: A Multisoftware Assessment

BACKGROUND

Cardiac magnetic resonance imaging protocols have been adapted to fit the needs for faster, more efficient acquisitions, resulting in the development of highly accelerated, compressed sensing-based (CS) sequences. The aim of this study was to evaluate intersoftware and interacquisition differences for postprocessing software applied to both CS and conventional cine sequences.

MATERIALS AND METHODS

A total of 106 individuals (66 healthy volunteers, 40 patients with dilated cardiomyopathy, 51% female, 38±17 y) underwent cardiac magnetic resonance at 3T with retrospectively gated conventional cine and CS sequences. Postprocessing was performed using 2 commercially available software solutions and 1 research prototype from 3 different developers. The agreement of clinical and feature-tracking strain parameters between software solutions and acquisition types was assessed by Bland-Altmann analyses and intraclass correlation coefficients. Differences between softwares and acquisitions were assessed using Kruskal-Wallis analysis of variances. In addition, receiver operating characteristic curve-derived cutoffs were used to evaluate whether sequence-specific cutoffs influence disease classification.

RESULTS

There were significant intersoftware ( P <0.002 for all except LV end-diastolic volume per body surface area) and interacquisition differences ( P <0.02 for all except end-diastolic volume per body surface area from Neosoft, left ventricular mass per body surface area from cvi42 and TrufiStrain and global circumferential strain from Neosoft). However, the intraclass correlation coefficients between acquisitions were strong-to-excellent for all parameters (all ≥0.81). In comparing individual softwares to a pooled mean, Bland-Altmann analyses revealed smaller magnitudes of bias for cine acquisition than for CS acquisition. In addition, the application of conventional cutoffs to CS measurements did not result in the false reclassification of patients.

CONCLUSION

Significantly lower magnitudes of strain and volumetric parameters were observed in retrospectively gated CS acquisitions, despite strong-to-excellent agreement amongst software solutions and acquisition types. It remains important to be aware of the acquisition type in the context of follow-up examinations, where different cutoffs might lead to misclassifications.

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.

Clinical Usefulness of Speckle-Tracking Echocardiography in Patients with Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is defined as HF with left ventricular ejection fraction (LVEF) not less than 50%. HFpEF accounts for more than 50% of all HF patients, and its prevalence is increasing year to year with the aging population, with its prognosis worsening. The clinical assessment of cardiac function and prognosis in patients with HFpEF remains challenging due to the normal range of LVEF and the nonspecific symptoms and signs. In recent years, new echocardiographic techniques have been continuously developed, particularly speckle-tracking echocardiography (STE), which provides a sensitive and accurate method for the comprehensive assessment of cardiac function and prognosis in patients with HFpEF. Therefore, this article reviewed the clinical utility of STE in patients with HFpEF.

MRI tagging of colonic chyme mixing in healthy subjects: Inter-observer variability and reliability of the measurement with time

BACKGROUND

Magnetic resonance imaging (MRI) tagging techniques have been applied to the GI tract to assess bowel contractions and content mixing. We aimed to evaluate the dependence of a tagging measurement (for assessing chyme mixing) on inter-observer variability in both the ascending colon (AC) and descending colon (DC) and to investigate the temporal variation and hence reliability of the colonic tagging technique by acquiring multiple measurements over time on healthy participants.

METHODS

Two independent datasets of healthy adults were used for the retrospective inter-observer variability (Study 1: 13 datasets and Study 2: 31 datasets), and ten participants were scanned for the prospective temporal variation study following a 1 L mannitol oral preparation. All colonic tagging data were acquired on 3 T MRI scanners. The mean and the standard deviation (SD) maps were generated pixel-by-pixel using custom-written software in MATLAB. The colonic regions of interest were defined using MIPAV software. Bland-Altman plots and scatter plots were used for the inter-observer variability. The mean and SD of all repeated measures for each subject were calculated along with a one-way ANOVA to test for variations with time.

RESULTS

Scatter plots and Bland-Altman plots showed a large range of data with low variation and small limits of agreements (<5% CoV). The intraclass correlation coefficient of inter-rater reliability was excellent and 0.97 or above for the AC and DC measurements for both datasets. The temporal variation study shows that there was no significant difference found between the multiple measures with time (p = 0.53, one-way repeated measures ANOVA test).

CONCLUSIONS

MRI tagging technique can provide an assessment of colonic chyme mixing. The inter-observer study data showed high inter-rater agreement. The temporal variation study showed some individual variations with time suggesting multiple measurements may be needed to increase accuracy.

Deep Learning Synthetic Strain: Quantitative Assessment of Regional Myocardial Wall Motion at MRI

Purpose

To assess the feasibility of a newly developed algorithm, called deep learning synthetic strain (DLSS), to infer myocardial velocity from cine steady-state free precession (SSFP) images and detect wall motion abnormalities in patients with ischemic heart disease.

Materials and Methods

In this retrospective study, DLSS was developed by using a data set of 223 cardiac MRI examinations including cine SSFP images and four-dimensional flow velocity data (November 2017 to May 2021). To establish normal ranges, segmental strain was measured in 40 individuals (mean age, 41 years ± 17 [SD]; 30 men) without cardiac disease. Then, DLSS performance in the detection of wall motion abnormalities was assessed in a separate group of patients with coronary artery disease, and these findings were compared with consensus results of four independent cardiothoracic radiologists (ground truth). Algorithm performance was evaluated by using receiver operating characteristic curve analysis.

Results

Median peak segmental radial strain in individuals with normal cardiac MRI findings was 38% (IQR: 30%-48%). Among patients with ischemic heart disease (846 segments in 53 patients; mean age, 61 years ± 12; 41 men), the Cohen κ among four cardiothoracic readers for detecting wall motion abnormalities was 0.60-0.78. DLSS achieved an area under the receiver operating characteristic curve of 0.90. Using a fixed 30% threshold for abnormal peak radial strain, the algorithm achieved a sensitivity, specificity, and accuracy of 86%, 85%, and 86%, respectively.

Conclusion

The deep learning algorithm had comparable performance with subspecialty radiologists in inferring myocardial velocity from cine SSFP images and identifying myocardial wall motion abnormalities at rest in patients with ischemic heart disease.Keywords: Neural Networks, Cardiac, MR Imaging, Ischemia/Infarction Supplemental material is available for this article. © RSNA, 2023.

Cardiovascular imaging in conduction system pacing: What does the clinician need?

Permanent pacemakers are used for symptomatic bradycardia and biventricular pacing (BVP)-cardiac resynchronization therapy (BVP-CRT) is established for heart failure (HF) patients traditionally. According to guidelines, patients' selection for CRT is based on QRS duration (QRSd) and morphology by surface electrocardiogram (ECG). Cardiovascular imaging techniques evaluate cardiac structure and function as well as identify pathophysiological substrate changes including the presence of scar. Cardiovascular imaging helps by improving the selection of candidates, guiding left ventricular (LV) lead placement, and optimization devices during the follow-up. Conduction system pacing (CSP) includes His bundle pacing (HBP) and left bundle branch pacing (LBBP) which is screwed into the interventricular septum. CSP maintains and restores ventricular synchrony in patients with native narrow QRSd and left bundle branch block (LBBB), respectively. LBBP is more feasible than HBP due to a wider target area. This review highlights the role of multimodality cardiovascular imaging including fluoroscopy, echocardiography, cardiac magnetic resonance (CMR), myocardial scintigraphy, and computed tomography (CT) in the pre-procedure assessment for CSP, better selection for CSP candidates, the guidance of CSP lead implantation, and the optimization of devices programming after the procedure. We also compare the different characteristics of multimodality imaging and discuss their potential roles in future CSP implantation.

Analysis of Tongue Muscle Strain During Speech From Multimodal Magnetic Resonance Imaging

PURPOSE

Muscle groups within the tongue in healthy and diseased populations show different behaviors during speech. Visualizing and quantifying strain patterns of these muscle groups during tongue motion can provide insights into tongue motor control and adaptive behaviors of a patient.

METHOD

We present a pipeline to estimate the strain along the muscle fiber directions in the deforming tongue during speech production. A deep convolutional network estimates the crossing muscle fiber directions in the tongue using diffusion-weighted magnetic resonance imaging (MRI) data acquired at rest. A phase-based registration algorithm is used to estimate motion of the tongue muscles from tagged MRI acquired during speech. After transforming both muscle fiber directions and motion fields into a common atlas space, strain tensors are computed and projected onto the muscle fiber directions, forming so-called strains in the line of actions (SLAs) throughout the tongue. SLAs are then averaged over individual muscles that have been manually labeled in the atlas space using high-resolution T2-weighted MRI. Data were acquired, and this pipeline was run on a cohort of eight healthy controls and two glossectomy patients.

RESULTS

The crossing muscle fibers reconstructed by the deep network show orthogonal patterns. The strain analysis results demonstrate consistency of muscle behaviors among some healthy controls during speech production. The patients show irregular muscle patterns, and their tongue muscles tend to show more extension than the healthy controls.

CONCLUSIONS

The study showed visual evidence of correlation between two muscle groups during speech production. Patients tend to have different strain patterns compared to the controls. Analysis of variations in muscle strains can potentially help develop treatment strategies in oral diseases.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21957011.

Clinical Utility of Strain Imaging in Assessment of Myocardial Fibrosis

Myocardial fibrosis (MF) is a non-reversible process that occurs following acute or chronic myocardial damage. MF worsens myocardial deformation, remodels the heart and raises myocardial stiffness, and is a crucial pathological manifestation in patients with end-stage cardiovascular diseases and closely related to cardiac adverse events. Therefore, early quantitative analysis of MF plays an important role in risk stratification, clinical decision, and improvement in prognosis. With the advent and development of strain imaging modalities in recent years, MF may be detected early in cardiovascular diseases. This review summarizes the clinical usefulness of strain imaging techniques in the non-invasive assessment of MF.

CMR left ventricular strains beyond global longitudinal strain in differentiating light-chain cardiac amyloidosis from hypertrophic cardiomyopathy

Background

The clinical value of left ventricular (LV) global longitudinal strain (GLS) in the differential diagnosis of light-chain cardiac amyloidosis (AL-CA) and hypertrophic cardiomyopathy (HCM) has been previously reported. In this study, we analyzed the potential clinical value of the LV long-axis strain (LAS) to discriminate AL-CA from HCM. Furthermore, we analyzed the association between all the LV global strain parameters derived from cardiac magnetic resonance (CMR) feature tracking and LAS in both the AL-CA and HCM patients to assess the differential diagnostic efficacies of these global peak systolic strains.

Materials and methods

Thus, this study enrolled 89 participants who underwent cardiac MRI (CMRI), consisting of 30 AL-CA patients, 30 HCM patients, and 29 healthy controls. The intra- and inter-observer reproducibility of the LV strain parameters including GLS, global circumferential strain (GCS), global radial strain (GRS), and LAS were assessed in all the groups and compared. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic performances of the CMR strain parameters in discriminating AL-CA from HCM.

Results

The intra- and inter-observer reproducibility of the LV global strains and LAS were excellent (range of interclass correlation coefficients: 0.907-0.965). ROC curve analyses showed that the differential diagnostic performances of the global strains in discriminating AL-CA from HCM were good to excellent (GRS, AUC = 0.921; GCS, AUC = 0.914; GLS, AUC = 0.832). Furthermore, among all the strain parameters analyzed, LAS showed the highest diagnostic efficacy in differentiating between AL-CA and HCM (AUC = 0.962).

Conclusion

CMRI-derived strain parameters such as GLS, LAS, GRS, and GCS are promising diagnostic indicators that distinguish AL-CA from HCM with high accuracy. LAS showed the highest diagnostic accuracy among all the strain parameters.

Emerging MRI techniques for molecular and functional phenotyping of the diseased heart

Recent advances in cardiac MRI (CMR) capabilities have truly transformed its potential for deep phenotyping of the diseased heart. Long known for its unparalleled soft tissue contrast and excellent depiction of three-dimensional (3D) structure, CMR now boasts a range of unique capabilities for probing disease at the tissue and molecular level. We can look beyond coronary vessel blockages and detect vessel disease not visible on a structural level. We can assess if early fibrotic tissue is being laid down in between viable cardiac muscle cells. We can measure deformation of the heart wall to determine early presentation of stiffening. We can even assess how cardiomyocytes are utilizing energy, where abnormalities are often precursors to overt structural and functional deficits. Finally, with artificial intelligence gaining traction due to the high computing power available today, deep learning has proven itself a viable contender with traditional acceleration techniques for real-time CMR. In this review, we will survey five key emerging MRI techniques that have the potential to transform the CMR clinic and permit early detection and intervention. The emerging areas are: (1) imaging microvascular dysfunction, (2) imaging fibrosis, (3) imaging strain, (4) imaging early metabolic changes, and (5) deep learning for acceleration. Through a concerted effort to develop and translate these areas into the CMR clinic, we are committing ourselves to actualizing early diagnostics for the most intractable heart disease phenotypes.

Left Ventricle Wall Motion Analysis with Real-Time MRI Feature Tracking in Heart Failure Patients: A Pilot Study

Volumetric measurements with cardiac magnetic resonance imaging (MRI) are effective for evaluating heart failure (HF) with systolic dysfunction that typically induces a lower ejection fraction (EF) than normal (<50%) while they are not sensitive to diastolic dysfunction in HF patients with preserved EF (≥50%). This work is to investigate whether HF evaluation with cardiac MRI can be improved with real-time MRI feature tracking. In a cardiac MRI study, we recruited 16 healthy volunteers, 8 HF patients with EF < 50% and 10 HF patients with preserved EF. Using real-time feature tracking, a cardiac MRI index, torsion correlation, was calculated which evaluated the correlation of torsional and radial wall motion in the left ventricle (LV) over a series of sequential cardiac cycles. The HF patients with preserved EF and the healthy volunteers presented significant difference in torsion correlation (one-way ANOVA, p < 0.001). In the scatter plots of EF against torsion correlation, the HF patients with EF < 50%, the HF patients with preserved EF and the healthy volunteers were well differentiated, indicating that real-time MRI feature tracking provided LV function assessment complementary to volumetric measurements. This study demonstrated the potential of cardiac MRI for evaluating both systolic and diastolic dysfunction in HF patients.

Inflamed adipose tissue: A culprit underlying obesity and heart failure with preserved ejection fraction

The incidence of heart failure with preserved ejection fraction is increasing in patients with obesity, diabetes, hypertension, and in the aging population. However, there is a lack of adequate clinical treatment. Patients with obesity-related heart failure with preserved ejection fraction display unique pathophysiological and phenotypic characteristics, suggesting that obesity could be one of its specific phenotypes. There has been an increasing recognition that overnutrition in obesity causes adipose tissue expansion and local and systemic inflammation, which consequently exacerbates cardiac remodeling and leads to the development of obese heart failure with preserved ejection fraction. Furthermore, overnutrition leads to cellular metabolic reprogramming and activates inflammatory signaling cascades in various cardiac cells, thereby promoting maladaptive cardiac remodeling. Growing evidence indicates that the innate immune response pathway from the NLRP3 inflammasome, to interleukin-1 to interleukin-6, is involved in the generation of obesity-related systemic inflammation and heart failure with preserved ejection fraction. This review established the existence of obese heart failure with preserved ejection fraction based on structural and functional changes, elaborated the inflammation mechanisms of obese heart failure with preserved ejection fraction, proposed that NLRP3 inflammasome activation may play an important role in adiposity-induced inflammation, and summarized the potential therapeutic approaches.

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.

Comparison of DeepStrain and Feature Tracking for Cardiac MRI Strain Analysis

BACKGROUND

Myocardial feature tracking (FT) provides a comprehensive analysis of myocardial deformation from cine balanced steady-state free-precession images (bSSFP). However, FT remains time-consuming, precluding its clinical adoption.

PURPOSE

To compare left-ventricular global radial strain (GRS) and global circumferential strain (GCS) values measured using automated DeepStrain analysis of short-axis cine images to those calculated using manual commercially available FT analysis.

STUDY TYPE

Retrospective, single-center.

POPULATION

A total of 30 healthy subjects and 120 patients with cardiac disease for DeepStrain development. For evaluation, 47 healthy subjects (36 male, 53 ± 5 years) and 533 patients who had undergone a clinical cardiac MRI (373 male, 59 ± 14 years). FIELD STRENGTH/SEQUENCE: bSSFP sequence at 1.5 T (Phillips) and 3 T (Siemens).

ASSESSMENT

Automated DeepStrain measurements of GRS and GCS were compared to commercially available FT (Circle, cvi42) measures obtained by readers with 1 year and 3 years of experience. Comparisons were performed overall and stratified by scanner manufacturer.

STATISTICAL TESTS

Paired t-test, linear regression slope, Pearson correlation coefficient (r).

RESULTS

Overall, FT and DeepStrain measurements of GCS were not significantly different (P = 0.207), but measures of GRS were significantly different. Measurements of GRS from Philips (slope = 1.06 [1.03 1.08], r = 0.85) and Siemens (slope = 1.04 [0.99 1.09], r = 0.83) data showed a very strong correlation and agreement between techniques. Measurements of GCS from Philips (slope = 0.98 [0.98 1.01], r = 0.91) and Siemens (slope = 1.0 [0.96 1.03], r = 0.88) data similarly showed a very strong correlation. The average analysis time per subject was 4.1 ± 1.2 minutes for FT and 34.7 ± 3.3 seconds for DeepStrain, representing a 7-fold reduction in analysis time.

DATA CONCLUSION

This study demonstrated high correlation of myocardial GCS and GRS measurements between freely available fully automated DeepStrain and commercially available manual FT software, with substantial time-saving in the analysis.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Cardiac functional imaging

During the last 20 years, cardiac imaging has drastically evolved. Positron emission tomography (PET), fast three-dimensional (3D) imaging with the latest generations of echocardiography & multi-detector computed tomography (CT), stress perfusion assessed by magnetic resonance imaging (MRI), blood flow analysis using four-dimensional (4D) flow MRI, all these techniques offer new trends for optimal noninvasive functional cardiac imaging. Dynamic functional imaging is obtained by acquiring images of the heart at different phases of the cardiac cycle, allowing assessment of cardiac motion, function, and perfusion. Between CT and Cardiac MRI (CMR), CMR has the best temporal resolution, which is suitable for functional imaging while cardiac CT provides higher spatial resolution with isotropic data that have an identical resolution in the three dimensions of the space. The latest generations of CT scanners enable whole heart assessment in one beat, offering also an acceptable temporal resolution with the possibility to display the images in a dynamic mode. Another rapidly growing technique using functional and molecular imaging for the assessment of biological and metabolic pathways is the PET using radio-labeled tracers. Meanwhile, the oldest cardiac imaging tool with doppler ultrasound technology has never stopped evolving. Echocardiography today performs 3D imaging, stress perfusion, and myocardial strain assessment, with high temporal resolution. It still is the first line and more accessible exam for the patient. These different modalities are complementary and may be even combined into PET-CT or PET-MRI. The ability to combine the functional/molecular data with anatomical images may implement a new dimension to our diagnostic tools.

Ventricular longitudinal function by cardiovascular magnetic resonance predicts cardiovascular morbidity in HFrEF patients

Aims

Ventricular longitudinal function measured as basal‐apical atrioventricular plane displacement (AVPD) or global longitudinal strain (GLS) is a potent predictor of mortality and could potentially be a predictor of heart failure‐associated morbidity. We hypothesized that low AVPD and GLS are associated with the combined endpoint of cardiovascular mortality and heart failure‐associated morbidity.

Methods and results

Two hundred eighty‐seven patients (age 62 ± 12 years, 78% male) with heart failure with reduced (≤40%) ejection fraction (HFrEF) referred to a cardiovascular magnetic resonance exam were included. Ventricular longitudinal function, ventricular volume, and myocardial fibrosis or infarction were analysed from cine and late gadolinium enhancement images. National registries provided data on causes of cardiovascular hospitalizations and cardiovascular mortality for the combined endpoint. Time‐to‐event analysis capable of including reoccurring events was employed with a 5‐year follow‐up. HFrEF patients had EF 26.5 ± 8.0%, AVPD 7.8 ± 2.4 mm, and GLS −7.5 ± 3.0%. In contrast, ventricular longitudinal function was approximately twice as large in an age‐matched control group (AVPD 15.3 ± 1.6 mm; GLS −20.6 ± 2.0%; P < 0.001 for both). There were 578 events in total, and the majority were HF hospitalizations (n = 418). Other major events were revascularizations (n = 64), cardiovascular deaths (n = 40), and myocardial infarctions (n = 21). One hundred fifty‐five (54%) patients experienced at least one event (mean 2.0, range 0–64). Of these patients, 119 (71%) had three events or fewer, and the first three events comprised 51% of all events (295 events). Patients in the bottom AVPD or GLS tertile (<6.8 mm or >−6.1%) overall experienced more than 3 times as many events as the top tertile (>8.8 mm or <−8.4%; P < 0.001). Patients in this tertile also faced more cardiovascular deaths (P < 0.05), HF hospitalizations (P = 0.001), myocardial infarctions (only GLS: P = 0.032), and accumulated longer in‐hospital length‐of‐stay overall (AVPD 20.9 vs. 9.1 days; GLS 22.4 vs. 6.5 days; P = 0.001 for both), and from HF hospitalizations (AVPD 19.3 vs. 8.3 days; GLS 19.3 vs. 5.4 days; P = 0.001 for both). In multivariate analysis adjusted for significant covariates, AVPD and GLS remained independent predictors of events (hazard ratio 1.12 per‐mm‐decrease and 1.13 per‐%‐increase) alongside hyponatremia (<135 mmol/L), aetiology of HF, and LV end‐diastolic volume index.

Conclusions

Low ventricular longitudinal function is associated with an increase in number of events as well as longer in‐hospital stay from cardiovascular causes. In addition, AVPD and GLS have independent prognostic value for cardiovascular mortality and morbidity in HFrEF patients.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

State-of-the-art myocardial strain by CMR feature tracking: clinical applications and future perspectives

Based on conventional cine sequences of cardiac magnetic resonance (CMR), feature tracking (FT) is an emerging tissue tracking technique that evaluates myocardial motion and deformation quantitatively by strain, strain rate, torsion, and dyssynchrony. It has been widely accepted in modern literature that strain analysis can offer incremental information in addition to classic global and segmental functional analysis. Furthermore, CMR-FT facilitates measurement of all cardiac chambers, including the relatively thin-walled atria and the right ventricle, which has been a difficult measurement to obtain with the reference standard technique of myocardial tagging. CMR-FT objectively quantifies cardiovascular impairment and characterizes myocardial function in a novel way through direct assessment of myocardial fiber deformation. The purpose of this review is to discuss the current status of clinical applications of myocardial strain by CMR-FT in a variety of cardiovascular diseases. KEY POINTS: • CMR-FT is of great value for differential diagnosis and provides incremental value for evaluating the progression and severity of diseases. • CMR-FT guides the early diagnosis of various cardiovascular diseases and provides the possibility for the early detection of myocardial impairment and additional information regarding subclinical cardiac abnormalities. • Direct assessment of myocardial fiber deformation using CMR-FT has the potential to provide prognostic information incremental to common clinical and CMR risk factors.

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).

Multiparametric Cardiac Magnetic Resonance Imaging Detects Altered Myocardial Tissue and Function in Heart Transplantation Recipients Monitored for Cardiac Allograft Vasculopathy

BACKGROUND

Cardiac allograft vasculopathy (CAV) is a complication beyond the first-year post-heart transplantation (HTx). We aimed to test the utility of cardiac magnetic resonance (CMR) to detect functional/structural changes in HTx recipients with CAV.

METHODS

Seventy-seven prospectively recruited HTx recipients beyond the first-year post-HTx and 18 healthy controls underwent CMR, including cine imaging of ventricular function and T1- and T2-mapping to assess myocardial tissue changes. Data analysis included quantification of global cardiac function and regional T2, T1 and extracellular volume based on the 16-segment model. International Society for Heart and Lung Transplantation criteria was used to adjudicate CAV grade (0–3) based on coronary angiography.

RESULTS

The majority of HTx recipients (73%) presented with CAV (1: n = 42, 2/3: n = 14, 0: n = 21). Global and segmental T2 (49.5 ± 3.4 ms vs 50.6 ± 3.4 ms, p < 0.001;16/16 segments) were significantly elevated in CAV-0 compared to controls. When comparing CAV-2/3 to CAV-1, global and segmental T2 were significantly increased (53.6 ± 3.2 ms vs. 50.6 ± 2.9 ms, p < 0.001; 16/16 segments) and left ventricular ejection fraction was significantly decreased (54 ± 9% vs. 59 ± 9%, p < 0.05). No global, structural, or functional differences were seen between CAV-0 and CAV-1.

CONCLUSIONS

Transplanted hearts display functional and structural alteration compared to native hearts, even in those without evidence of macrovasculopathy (CAV-0). In addition, CMR tissue parameters were sensitive to changes in CAV-1 vs. 2/3 (mild vs. moderate/severe). Further studies are warranted to evaluate the diagnostic value of CMR for the detection and classification of CAV.

Applications of multimodality imaging for left atrial catheter ablation

Atrial arrhythmias, including atrial fibrillation and atrial flutter, may be treated through catheter ablation. The process of atrial arrhythmia catheter ablation, which includes patient selection, pre-procedural planning, intra-procedural guidance, and post-procedural assessment, is typically characterized by the use of several imaging modalities to sequentially inform key clinical decisions. Increasingly, advanced imaging modalities are processed via specialized image analysis techniques and combined with intra-procedural electrical measurements to inform treatment approaches. Here, we review the use of multimodality imaging for left atrial ablation procedures. The article first outlines how imaging modalities are routinely used in the peri-ablation period. We then describe how advanced imaging techniques may inform patient selection for ablation and ablation targets themselves. Ongoing research directions for improving catheter ablation outcomes by using imaging combined with advanced analyses for personalization of ablation targets are discussed, together with approaches for their integration in the standard clinical environment. Finally, we describe future research areas with the potential to improve catheter ablation outcomes.

A Direct NMR Method To Measure Self-Diffusion Coefficients in Liquids by Monitoring Diffusing Molecules through One-Dimensional Imaging

Diffusion processes can be followed directly by recording one-dimensional images of a selected slice at variable intervals after selective inversion of the magnetization. The resulting diffusion coefficients of H₂ O and DMSO are consistent with earlier studies at different temperatures, obtained by monitoring the attenuation of NMR signals as a function of the gradient amplitude in gradient echo sequences.

Automated segmentation of biventricular contours in tissue phase mapping using deep learning

Tissue phase mapping (TPM) is an MRI technique for quantification of regional biventricular myocardial velocities. Despite its potential, clinical use is limited due to the requisite labor-intensive manual segmentation of cardiac contours for all time frames. The purpose of this study was to develop a deep learning (DL) network for automated segmentation of TPM images, without significant loss in segmentation and myocardial velocity quantification accuracy compared with manual segmentation. We implemented a multi-channel 3D (three dimensional; 2D + time) dense U-Net that trained on magnitude and phase images and combined cross-entropy, Dice, and Hausdorff distance loss terms to improve the segmentation accuracy and suppress unnatural boundaries. The dense U-Net was trained and tested with 150 multi-slice, multi-phase TPM scans (114 scans for training, 36 for testing) from 99 heart transplant patients (44 females, 1-4 scans/patient), where the magnitude and velocity-encoded (V_x , V_y , V_z ) images were used as input and the corresponding manual segmentation masks were used as reference. The accuracy of DL segmentation was evaluated using quantitative metrics (Dice scores, Hausdorff distance) and linear regression and Bland-Altman analyses on the resulting peak radial and longitudinal velocities (V_r and V_z ). The mean segmentation time was about 2 h per patient for manual and 1.9 ± 0.3 s for DL. Our network produced good accuracy (median Dice = 0.85 for left ventricle (LV), 0.64 for right ventricle (RV), Hausdorff distance = 3.17 pixels) compared with manual segmentation. Peak V_r and V_z measured from manual and DL segmentations were strongly correlated (R ≥ 0.88) and in good agreement with manual analysis (mean difference and limits of agreement for V_z and V_r were -0.05 ± 0.98 cm/s and -0.06 ± 1.18 cm/s for LV, and -0.21 ± 2.33 cm/s and 0.46 ± 4.00 cm/s for RV, respectively). The proposed multi-channel 3D dense U-Net was capable of reducing the segmentation time by 3,600-fold, without significant loss in accuracy in tissue velocity measurements.

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.

Left-Ventricular Reference Myocardial Strain Assessed by Cardiovascular Magnetic Resonance Feature Tracking and fSENC-Impact of Temporal Resolution and Cardiac Muscle Mass

Aims: Cardiac strain parameters are increasingly measured to overcome shortcomings of ejection fraction. For broad clinical use, this study provides reference values for the two strain assessment methods feature tracking (FT) and fast strain-encoded (fSENC) cardiovascular magnetic resonance (CMR) imaging, including the child/adolescent group and systematically evaluates the influence of temporal resolution and muscle mass on strain.

Methods and Results: Global longitudinal (GLS), circumferential (GCS), and radial (GRS) strain values in 181 participants (54% women, 11–70 years) without cardiac illness were assessed with FT (CVI42® software). GLS and GCS were also analyzed using fSENC (MyoStrain® software) in a subgroup of 84 participants (60% women). Fourteen patients suffering hypertrophic cardiomyopathy (HCM) were examined with both techniques. CMR examinations were done on a 3.0T MR-system.

FT-GLS, FT-GCS, and FT-GRS were −16.9 ± 1.8%, −19.2 ± 2.1% and 34.2 ± 6.1%. fSENC-GLS was higher at −20.3 ± 1.8% (p < 0.001). fSENC-GCS was comparable at−19.7 ± 1.8% (p = 0.06). All values were lower in men (p < 0.001). Cardiac muscle mass correlated (p < 0.001) with FT-GLS (r = 0.433), FT-GCS (r = 0.483) as well as FT-GRS (r = −0.464) and acts as partial mediator for sex differences. FT-GCS, FT-GRS and fSENC-GLS correlated weakly with age. FT strain values were significantly lower at lower cine temporal resolutions, represented by heart rates (r = −0.301, −0.379, 0.385) and 28 or 45 cardiac phases per cardiac cycle (0.3–1.9% differences). All values were lower in HCM patients than in matched controls (p < 0.01). Cut-off values were −15.0% (FT-GLS), −19.3% (FT-GCS), 32.7% (FT-GRS), −17.2% (fSENC-GLS), and −17.7% (fSENC-GCS).

Conclusion: The analysis of reference values highlights the influence of gender, temporal resolution, cardiac muscle mass and age on myocardial strain values.

In-silico study of accuracy and precision of left-ventricular strain quantification from 3D tagged MRI

Cardiac Magnetic Resonance Imaging (MRI) allows quantifying myocardial tissue deformation and strain based on the tagging principle. In this work, we investigate accuracy and precision of strain quantification from synthetic 3D tagged MRI using equilibrated warping. To this end, synthetic biomechanical left-ventricular tagged MRI data with varying tag distance, spatial resolution and signal-to-noise ratio (SNR) were generated and processed to quantify errors in radial, circumferential and longitudinal strains relative to ground truth. Results reveal that radial strain is more sensitive to image resolution and noise than the other strain components. The study also shows robustness of quantifying circumferential and longitudinal strain in the presence of geometrical inconsistencies of 3D tagged data. In conclusion, our study points to the need for higher-resolution 3D tagged MRI than currently available in practice in order to achieve sufficient accuracy of radial strain quantification.

MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury

Computational models of the brain and its biomechanical response to skull accelerations are important tools for understanding and predicting traumatic brain injuries (TBIs). However, most models have been developed using experimental data collected on animal models and cadaveric specimens, both of which differ from the living human brain. Here we describe efforts to noninvasively measure the biomechanical response of the human brain with MRI-at non-injurious strain levels-and generate data that can be used to develop, calibrate, and evaluate computational brain biomechanics models. Specifically, this paper reports on a project supported by the National Institute of Neurological Disorders and Stroke to comprehensively image brain anatomy and geometry, mechanical properties, and brain deformations that arise from impulsive and harmonic skull loadings. The outcome of this work will be a publicly available dataset ( http://www.nitrc.org/projects/bbir ) that includes measurements on both males and females across an age range from adolescence to older adulthood. This article describes the rationale and approach for this study, the data available, and how these data may be used to develop new computational models and augment existing approaches; it will serve as a reference to researchers interested in using these data.

Recommendation for Cardiac Magnetic Resonance Imaging-Based Phenotypic Study: Imaging Part

Cardiac magnetic resonance (CMR) imaging provides important biomarkers for the early diagnosis of many cardiovascular diseases and has been reported to reveal phenome-wide associations of cardiac/aortic structure and functionality in population studies. Nevertheless, due to the complexity of operation and variations among manufactural vendors, magnetic field strengths, coils, sequences, scan parameters, and image analysis approaches, CMR is rarely used in large cohort studies. Existing guidelines mainly focused on the diagnosis of cardiovascular diseases, which did not aim to basic research. The purpose of this study was to propose a recommendation for CMR based phenotype measurements for cohort study. We classify the imaging sequences of CMR into three categories according to the importance and universality of corresponding measurable phenotypes. The acquisition time and repeatability of the phenotypic measurement were also taken into consideration during the categorization. Unlike other guidelines, this recommendation focused on quantitative measurement of large amount of phenotypes from CMR.

An image registration framework to estimate 3D myocardial strains from cine cardiac MRI in mice

Accurate and efficient quantification of cardiac motion offers promising biomarkers for non-invasive diagnosis and prognosis of structural heart diseases. Cine cardiac magnetic resonance imaging remains one of the most advanced imaging tools to provide image acquisitions needed to assess and quantify in-vivo heart kinematics. The majority of cardiac motion studies are focused on human data, and there remains a need to develop and implement an image-registration pipeline to quantify full three-dimensional (3D) cardiac motion in mice where ideal image acquisition is challenged by the subject size and heart rate and the possibility of traditional tagged imaging is hampered. In this study, we used diffeomorphic image registration to estimate strains in the left ventricular wall in two wild-type mice and one diabetic mouse. Our pipeline resulted in a continuous and fully 3D strain map over one cardiac cycle. The estimation of 3D regional and transmural variations of strains is a critical step towards identifying mechanistic biomarkers for improved diagnosis and phenotyping of structural left heart diseases including heart failure with reduced or preserved ejection fraction.

Comparing cardiovascular magnetic resonance strain software packages by their abilities to discriminate outcomes in patients with heart failure with preserved ejection fraction

BACKGROUND

Cardiovascular magnetic resonance (CMR) myocardial strain analysis using feature tracking (FT) is an increasingly popular method to assess cardiac function. However, different software packages produce different strain values from the same images and there is little guidance regarding which software package would be the best to use. We explored a framework under which different software packages could be compared and used based on their abilities to differentiate disease from health and differentiate disease severity based on outcome.

METHOD

To illustrate this concept, we compared 4-chamber left ventricular (LV) peak longitudinal strain (GLS) analyzed from retrospective electrocardiogram gated cine imaging performed on 1.5 T CMR scanners using three CMR post-processing software packages in their abilities to discriminate a group of 45 patients with heart failure with preserved ejection fraction (HFpEF) from 26 controls without cardiovascular disease and to discriminate disease severity based on outcomes. The three different post-processing software used were SuiteHeart, cvi42, and DRA-Trufistrain.

RESULTS

All three software packages were able to distinguish HFpEF patients from controls. 4-chamber peak GLS by SuiteHeart was shown to be a better discriminator of adverse outcomes in HFpEF patients than 4-chamber GLS derived from cvi42 or DRA-Trufistrain.

CONCLUSION

We illustrated a framework to compare feature tracking GLS derived from different post-processing software packages. Publicly available imaging data sets with outcomes would be important to validate the growing number of CMR-FT software packages.

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.

Role of cardiovascular magnetic resonance in early detection and treatment of cardiac dysfunction in oncology patients

The purpose of this review is to provide an overview of the essential role that cardiovascular magnetic resonance (CMR) has in the field of cardio-oncology. Recent findings: CMR has been increasingly used for early identification of cancer therapy related cardiac dysfunction (CTRCD) due to its precision in detecting subtle changes in cardiac function and for myocardial tissue characterization. Summary: CMR is able to identify subclinical CTRCD in patients receiving potentially cardiotoxic chemotherapy and guide initiation of cardio protective therapy. Multiparametric analysis with myocardial strain, tissue characterization play a critical role in understanding important clinical questions in cardio-oncology.

Myocardial Strain Imaging in Resistant Hypertension

PURPOSE OF REVIEW

Resistant hypertension (RH) is a major contributor to cardiovascular diseases and is associated with increased all-cause and cardiovascular mortality. Cardiac changes such as impaired left ventricular (LV) function, left ventricular hypertrophy (LVH), myocardial fibrosis, and enlarged left atrium (LA) are consequences of chronic exposure to an elevated blood pressure. The purpose of this review article is to demonstrate the potential benefits of using STE as a non-invasive imaging technique in the assessment of cardiac remodeling in patients with hypertension and specifically in uncontrolled and RH population.

RECENT FINDINGS

It is well-recognized that conventional transthoracic echocardiography is a useful analytic imaging modality to evaluate hypertension-mediated organ damage (HMOD) and in a resistant hypertensive population. More recently two-dimensional speckle tracking echocardiography (STE) has been utilized to provide further risk assessment to this population. Recent data has shown that STE is a new promising echocardiographic marker to evaluate early stage LV dysfunction and myocardial fibrosis over conventional 2D parameters in patients with cardiovascular diseases.

Quantification of Myocardial Deformation Applying CMR-Feature-Tracking-All About the Left Ventricle?

Purpose of Review

Cardiac magnetic resonance-feature-tracking (CMR-FT)-based deformation analyses are key tools of cardiovascular imaging and applications in heart failure (HF) diagnostics are expanding. In this review, we outline the current range of application with diagnostic and prognostic implications and provide perspectives on future trends of this technique.

Recent Findings

By applying CMR-FT in different cardiovascular diseases, increasing evidence proves CMR-FT-derived parameters as powerful diagnostic and prognostic imaging biomarkers within the HF continuum partly outperforming traditional clinical values like left ventricular ejection fraction. Importantly, HF diagnostics and deformation analyses by CMR-FT are feasible far beyond sole left ventricular performance evaluation underlining the holistic nature and accuracy of this imaging approach.

Summary

As an established and continuously evolving technique with strong prognostic implications, CMR-FT deformation analyses enable comprehensive cardiac performance quantification of all cardiac chambers.

Impact of Cardiovascular Hemodynamics on Cognitive Aging

[Figure: see text].