MRI-based strain and strain rate analysis of left ventricle: a modified hierarchical transformation model

The Combination of Feature Tracking and Late Gadolinium Enhancement for Identification Between Hypertrophic Cardiomyopathy and Hypertensive Heart Disease

Background

The differentiation between hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) is challenging due to similar myocardial hypertrophic phenotype. The purpose of this study is to evaluate the feasibility of cardiovascular magnetic resonance feature tracking (CMR-FT) and late gadolinium enhancement (LGE) to distinguish between HCM and HHD and the potential relationship between myocardial strain and cardiac functional parameters.

Methods

One hundred and seventy subjects (57 HCM, 45 HHD, and 68 controls) underwent 3.0 T CMR, including steady-state free precession cines and LGE images. Global and segmental (basal, mid, and apical) analyses of myocardial radial, circumferential, longitudinal strain, and left ventricular (LV) torsion, as well as global and 16 segments of LGE were assessed. The multivariate analysis was used to predict the diagnostic ability by combining comprehensive myocardial strain parameters and LGE.

Results

Global radial strain (GRS), global circumferential strain (GCS), and LV torsion were significantly higher in the HCM group than in the HHD group (GRS, 21.18 ± 7.52 vs. 14.56 ± 7.46%; GCS, −13.34 ± 3.52 vs. −10.11 ± 4.13%; torsion, 1.79 ± 0.69 vs. 1.23 ± 0.65 deg/cm, all P < 0.001). A similar trend was also seen in the corresponding strain rate. As for segmental strain analysis, basal radial strain (BRS), basal circumferential strain (BCS), basal longitudinal strain (BLS), mid-radial strain (MRS), and mid-circumferential strain (MCS) were higher in the HCM group than in the HHD group (all P < 0.001). The receiver operating characteristic (ROC) results showed that the area under the curve (AUC) of LGE in the mid-interventricular septum (mIVS) was the highest among global and segmental LGE analyses. On the multivariate regression analysis, a combined model of LGE (mIVS) with GRS obtained the highest AUC value, which was 0.835 with 88.89% sensitivity and 70.18% specificity, respectively. In addition, for patients with HCM, GRS, GCS, and global longitudinal strain had correlations with LV ejection fraction (LVEF), maximum interventricular septum thickness (IVST max), and left ventricular mass index (LVMi). Torsion was mildly associated with LVEF.

Conclusion

CMR-FT-derived myocardial strain and torsion provided valuable methods for evaluation of HCM and HHD. In addition, the combination of GRS and LGE (mIVS) achieved the highest diagnostic value.

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.

Ventricle stress/strain comparisons between Tetralogy of Fallot patients and healthy using models with different zero-load diastole and systole morphologies

Patient-specific in vivo ventricle mechanical wall stress and strain conditions are important for cardiovascular investigations and should be calculated from correct zero-load ventricle morphologies. Cardiac magnetic resonance (CMR) data were obtained from 6 healthy volunteers and 12 Tetralogy of Fallot (TOF) patients with consent obtained. 3D patient-specific CMR-based ventricle models with different zero-load diastole and systole geometries due to myocardium contraction and relaxation were constructed to qualify right ventricle (RV) diastole and systole stress and strain values at begin-filling, end-filling, begin-ejection, and end-ejection, respectively. Our new models (called 2G models) can provide end-diastole and end-systole stress/strain values which models with one zero-load geometries (called 1G models) could not provide. 2G mean end-ejection stress value from the 18 participants was 321.4% higher than that from 1G models (p = 0.0002). 2G mean strain values was 230% higher than that of 1G models (p = 0.0002). TOF group (TG) end-ejection mean stress value was 105.4% higher than that of healthy group (HG) (17.54±7.42kPa vs. 8.54±0.92kPa, p = 0.0245). Worse outcome group (WG, n = 6) post pulmonary valve replacement (PVR) begin-ejection mean stress was 57.4% higher than that of better outcome group (BG, 86.94±26.29 vs. 52.93±22.86 kPa; p = 0.041). Among 7 selected parameters, End-filling stress was the best predictor to differentiate BG patients from WG patients with prediction accuracy = 0.8208 and area under receiver operating characteristic curve (AUC) value at 0.8135 (EE stress). Large scale studies are needed to further validate our findings.

Patient-specific in vivo right ventricle material parameter estimation for patients with tetralogy of Fallot using MRI-based models with different zero-load diastole and systole morphologies

Patient-specific in vivo ventricle material parameter determination is important for cardiovascular investigations. A new cardiac magnetic image (CMR)-based modeling approach with different zero-load diastole and systole geometries was adopted to estimate right ventricle material parameter values for healthy and patients with Tetralogy of Fallot (TOF) and seeking potential clinical applications. CMR data were obtained from 6 healthy volunteers and 16 TOF patients with consent obtained. CMR-based RV/LV models were constructed using two zero-load geometries (diastole and systole, 2G model). Material parameter values for begin-filling (BF), end-filling (EF), begin-ejection (BE), and end-ejection (EE) were recorded for analyses. Effective Young's moduli (YM) for fiber direction stress-strain curves were calculated for easy comparisons. The mean EE YM value of TOF patients was 78.6% higher than that of the healthy group (HG). The mean end-ejection YM value from worse-outcome TOF group (WG) post pulmonary valve replacement (PVR) surgery was 59.5% higher than that from the better-outcome TOF group (BG). Using begin-filling YM and end-ejection YM as predictors and the classic logistic regression model to different better-outcome group patients from worse-outcome group patients, the areas under Receiver Operating Characteristic (ROC) curves were found to be 0.797 and 0.883 for begin-filling YM and end-ejection YM, respectively. The sensitivity and specificity 0.761 and 0.755 using end-ejection YM as the predictor. This preliminary study suggests that ventricle material stiffness could be a potential parameter to be used to differentiate BG patients from WG patients with further effort and large-scale patient data validations.

Patient-Specific MRI-Based Right Ventricle Models Using Different Zero-Load Diastole and Systole Geometries for Better Cardiac Stress and Strain Calculations and Pulmonary Valve Replacement Surgical Outcome Predictions

Background

Accurate calculation of ventricular stress and strain is critical for cardiovascular investigations. Sarcomere shortening in active contraction leads to change of ventricular zero-stress configurations during the cardiac cycle. A new model using different zero-load diastole and systole geometries was introduced to provide more accurate cardiac stress/strain calculations with potential to predict post pulmonary valve replacement (PVR) surgical outcome.

Methods

Cardiac magnetic resonance (CMR) data were obtained from 16 patients with repaired tetralogy of Fallot prior to and 6 months after pulmonary valve replacement (8 male, 8 female, mean age 34.5 years). Patients were divided into Group 1 (n = 8) with better post PVR outcome and Group 2 (n = 8) with worse post PVR outcome based on their change in RV ejection fraction (EF). CMR-based patient-specific computational RV/LV models using one zero-load geometry (1G model) and two zero-load geometries (diastole and systole, 2G model) were constructed and RV wall thickness, volume, circumferential and longitudinal curvatures, mechanical stress and strain were obtained for analysis. Pairwise T-test and Linear Mixed Effect (LME) model were used to determine if the differences from the 1G and 2G models were statistically significant, with the dependence of the pair-wise observations and the patient-slice clustering effects being taken into consideration. For group comparisons, continuous variables (RV volumes, WT, C- and L- curvatures, and stress and strain values) were summarized as mean ± SD and compared between the outcome groups by using an unpaired Student t-test. Logistic regression analysis was used to identify potential morphological and mechanical predictors for post PVR surgical outcome.

Results

Based on results from the 16 patients, mean begin-ejection stress and strain from the 2G model were 28% and 40% higher than that from the 1G model, respectively. Using the 2G model results, RV EF changes correlated negatively with stress (r = -0.609, P = 0.012) and with pre-PVR RV end-diastole volume (r = -0.60, P = 0.015), but did not correlate with WT, C-curvature, L-curvature, or strain. At begin-ejection, mean RV stress of Group 2 was 57.4% higher than that of Group 1 (130.1±60.7 vs. 82.7±38.8 kPa, P = 0.0042). Stress was the only parameter that showed significant differences between the two groups. The combination of circumferential curvature, RV volume and the difference between begin-ejection stress and end-ejection stress was the best predictor for post PVR outcome with an area under the ROC curve of 0.855. The begin-ejection stress was the best single predictor among the 8 individual parameters with an area under the ROC curve of 0.782.

Conclusion

The new 2G model may be able to provide more accurate ventricular stress and strain calculations for potential clinical applications. Combining morphological and mechanical parameters may provide better predictions for post PVR outcome.