Three‐dimensional regional strain computation method with displacement encoding with stimulated echoes (DENSE) in non‐ischemic, non‐valvular dilated cardiomyopathy patients and healthy subjects validated by tagged MRI

Abstract

Purpose Fast cine displacement encoding with stimulated echoes (DENSE) MR has higher spatial resolution and enables rapid post-processing. Thus we compared the accuracy of regional strains computation by DENSE with tagged MR in healthy and non-ischemic, non-valvular dilated cardiomyopathy (DCM) subjects. Materials and Methods Validation of 3D regional strains computed with DENSE was conducted in reference to standard tagged MRI (TMRI) in healthy subjects and patients with DCM. Additional repeatability studies in healthy subjects were conducted to increase confidence in DENSE. A meshfree multiquadrics radial point interpolation method (RPIM) was used for computing Lagrange strains in sixteen left ventricular segments. Bland-Altman analysis and Student's t-tests were conducted to observe similarities in regional strains between sequences and in DENSE repeatability studies. Results Regional circumferential strains ranged from -0.21 ± 0.07 (Lateral-Apex) to -0.11 ± 0.05 (Posterorseptal-Base) in healthy subjects and -0.15 ± 0.04 (Anterior-Apex) to -0.02 ± 0.08 (Posterorseptal-Base) in DCM patients. Computed mean differences in regional circumferential strain from the DENSE-TMRI comparison study was 0.01 ± 0.03 (95% limits of agreement) in normal subjects, -0.01 ± 0.06 in DCM patients and 0.0 ± 0.02 in repeatability studies, with similar agreements in longitudinal and radial strains. Conclusion We found agreement between DENSE and tagged MR in patients and volunteers in terms of evaluation of regional strains.

Preliminary investigation of multiparametric strain Z‐score (MPZS) computation using displacement encoding with simulated echoes (DENSE) and radial point interpretation method (RPIM)

“…All subjects signed informed consents in accordance with the university’s Institutional Review Board (IRB) guidelines. MRI data from the normal volunteer data formed the healthy subjects’ database for normalizing patient strains and computing MPZS [7, 14, 20]. The normal subjects filled out a questionnaire approved by the IRB that established absence of any form of cardiac disease.…”

“…The core of the RPIM methodology involves a continuous displacement field function, u ( x ), passing through a group of scattered nodes, x , within a domain [7, 35, 36], $$ufalse(\mathrm{normalx}false)=\sum _{i=1}^n{B}_{i}false(\mathrm{normalx}false)a_i+\sum _{k=1}^m{p}_{k}false(\mathrm{normalx}false)b_k={\mathrm{B}}^{\mathrm{T}}false(\mathrm{normalx}false)\mathrm{normala}+{\mathrm{p}}^{\mathrm{T}}false(\mathrm{normalx}false)\mathrm{normalb}$$ where p(x) is the matrix of monomial bases and b is vector of coefficients to which radial basis functions (RBF), B(x) , with a as the coefficient vector, are added. It is the existence of B −1 for arbitrary scattered nodes that is considered a major advantage of RBFs [7].…”

“…There are three important steps undertaken in assignment of this metric and brief descriptions of these steps are given in the following. The first step involves image acquisition where Displacement Encoding with Stimulated Echoes (DENSE) is a higher resolution MR imaging sequence which measures tissue displacement from a fixed encoding point at end-diastole [7–9]. Tissue displacements at the fixed spatial locations were obtained using fast automated unwrapping of the phases, where phase shifts occur between initial position encoding and readout [8–10].…”

Quantifying “normalized” regional left ventricular contractile function in ischemic coronary artery disease

“…7 In contrast, since our methodology relies heavily upon a quantitative comparison of patient-specific strain to a fixed standard (normal human strain database), there is very little room for temporal inconsistency. 21, 22 …”

“…17–20 Clinical validation of this methodology has demonstrated resistance to inter-observer variability. 21, 22 Briefly, endocardial and epicardial wall boundaries were manually identified on each of the tagged images used in the study. Tag lines were tracked on each of the images semi-automatically utilizing an active contour approach.…”