Abstract
Objective:Displacement ENcoding with Stimulated Echoes (DENSE) is an MRI technique developed to encode phase related to myocardial tissue displacements, and the displacement information directly applied towards detecting left-ventricular (LV) myocardial motion during the cardiac cycle. The purpose of this study is to present a novel, three-dimensional (3D) DENSE displacement-based and magnitude image quantization-based, semi-automated detection technique for myocardial wall motion, whose boundaries are used for rapid and automated computation of 3D myocardial strain.Methods:The architecture of this boundary detection algorithm is primarily based on pixelwise spatiotemporal increments in LV tissue displacements during the cardiac cycle and further reinforced by radially searching for pixel-based image gradients in multithreshold quantized magnitude images. This spatiotemporal edge detection methodology was applied to all LV partitions and their subsequent timeframes that lead to full 3D LV reconstructions. It was followed by quantifications of 3D chamber dimensions and myocardial strains, whose rapid computation was the primary motivation behind developing this algorithm. A pre-existing two-dimensional (2D) semi-automated contouring technique was used in parallel to validate the accuracy of the algorithm and both methods tested on DENSE data acquired in (N = 14) healthy subjects. Chamber quantifications between methods were compared using paired t-tests and Bland–Altman analysis established regional strain agreements.Results:There were no significant differences in the results of chamber quantifications between the 3D semi-automated and existing 2D boundary detection techniques. This included comparisons of ejection fractions, which were 0.62 ± 0.04 vs 0.60 ± 0.06 (p = 0.23) for apical, 0.60 ± 0.04 vs 0.59 ± 0.05 (p = 0.76) for midventricular and 0.56 ± 0.04 vs 0.58 ± 0.05 (p = 0.07) for basal segments, that were quantified using the 3D semi-automated and 2D pre-existing methodologies, respectively. Bland–Altman agreement between regional strains generated biases of 0.01 ± 0.06, –0.01 ± 0.01 and 0.0 ± 0.06 for the radial, circumferential and longitudinal directions, respectively.Conclusion:A new, 3D semi-automated methodology for contouring the entire LV and rapidly generating chamber quantifications and regional strains is presented that was validated in relation to an existing 2D contouring technique.Advances in knowledge:This study introduced a scientific tool for rapid, semi-automated generation of clinical information regarding shape and function in the 3D LV.
Highlights
Displacement ENcoding with Stimulated Echoes (DENSE) is a sequence that can ideally be used to automate all computations, including boundary detection, determination of functional parameters as well as chamber quantifications, an approach which was demonstrated in a two-dimensional (2D) semi-automated motion estimation study by Spottiswoode et al.[7,9,10,11]
Validation is provided by comparing the LV chamber quantifications and 3D strains computed with this new 3D methodology to those generated using the fully validated 2D boundary detection approach developed by Spottiswoode et al.[18,19,20,21,22]
Other fundamental measurements for which significant differences were not found between the methodologies include apical EDD (p = 0.19), midventricular EDD (p = 0.63), basal EDD (p = 0.10), apical end-systolic diameter (ESD) (p = 0.14) and midventricular ESD (p = 0.52), with the only exception seen in the basal ESD (p = 0.04)
Summary
The quantification of cardiac chamber dimensions and function is the foundation of cardiac imaging, of which MRI is the most reliable modality, providing superior resolution for soft-tissue contrast and multiplanar information that cannot be delivered by other modalities.[1,2,3,4] Over the last few decades, specific MRI sequences have been developed for detecting cardiac cycle-based tissue motion, including spatial modulation of magnetization (SPAMM) or tissue-tagging, Displacement ENcoding with StimulatedEchoes (DENSE) and others.[5,6,7,8,9,10] A particular matter of interest in relation to processing efficiency is automating the detection of myocardial wall motion for faster chamber quantification and functional assessment in the left-ventricle (LV). This study was conducted to investigate the feasibility of a highly automated, single-scan, MRI-based methodology for assessing full LV function (stain-based contraction and chamber quantifications), whose unprecedented rapid processing time (3.5 min approximately) might be of significant advantage in clinical applications To achieve this goal, a novel and fast three-dimensional (3D) semi-automated methodology was used that primarily tracks LV boundary motion (during cardiac systole) using phase-encoded 3D displacement data recorded with the navigator-gated spiral DENSE MRI sequence.[11,12,13,14,15] The displacement-based boundary search is further reinforced with a histogram distribution-based, multilevel thresholding-based image compression approach called Otsu’s method that was applied to identify myocardial tissue according to a discrete range of quantized indices.[16,17] In this regard, presented here is the first 3D, single-scan DENSE study that applies spatiotemporal displacements and the semi-automatedly detected LV boundaries toward rapid and automated 3D strain analysis and generation of surface strain maps.[9,10] Validation is provided by comparing the LV chamber quantifications and 3D strains computed with this new 3D methodology to those generated using the fully validated 2D boundary detection approach developed by Spottiswoode et al.[18,19,20,21,22]
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