Dataset Information

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

ABSTRACT: PURPOSE:This study aimed to develop a self-navigated method for free-breathing spiral cine displacement encoding with stimulated echoes (DENSE), a myocardial strain imaging technique that uses phase-cycling for artifact suppression. The method needed to address 2 consequences of motion for DENSE: striping artifacts from incomplete suppression of the T1 -relaxation echo and blurring. METHODS:The method identifies phase-cycled spiral interleaves at matched respiratory phases by minimizing the residual signal due to T1 relaxation after phase-cycling subtraction. Next, the method reconstructs image-based navigators from matched phase-cycled interleaves that are comprised of the stimulated echo (ste-iNAVs). Ste-iNAVs are used for motion estimation and compensation of k-space data. The method was demonstrated in phantoms and compared to diaphragm-based navigator (dNAV) and conventional iNAV (c-iNAV) methods for the reconstruction of free-breathing volunteer data sets (N?=?10). RESULTS:Phantom experiments demonstrated that the proposed method removes striping artifacts and blurring due to motion. Volunteer results showed that respiratory motion measured by ste-iNAVs was better correlated than c-iNAVs to dNAV data (R2 ?=?0.82?±?0.03 vs. 0.70?±?0.05, P?

SUBMITTER: Cai X

PROVIDER: S-EPMC6107388 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

Cai Xiaoying X Epstein Frederick H FH

Magnetic resonance in medicine 20180401 5

<h4>Purpose</h4>This study aimed to develop a self-navigated method for free-breathing spiral cine displacement encoding with stimulated echoes (DENSE), a myocardial strain imaging technique that uses phase-cycling for artifact suppression. The method needed to address 2 consequences of motion for DENSE: striping artifacts from incomplete suppression of the T<sub>1</sub> -relaxation echo and blurring.<h4>Methods</h4>The method identifies phase-cycled spiral interleaves at matched respiratory pha ...[more]

PMID: 29607538

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Project description:Defining myocardial contours is often the most time-consuming portion of dynamic cardiac MRI image analysis. Displacement encoding with stimulated echoes (DENSE) is a quantitative MRI technique that encodes tissue displacement into the phase of the complex MRI images. Cine DENSE provides a time series of these images, thus facilitating the non-invasive study of myocardial kinematics. Epicardial and endocardial contours need to be defined at each frame on cine DENSE images for the quantification of regional displacement and strain as a function of time. This work presents a reliable and effective two-dimensional semi-automated segmentation technique that uses the encoded motion to project a manually-defined region of interest through time. Contours can then easily be extracted for each cardiac phase. This method boasts several advantages, including, (1) parameters are based on practical physiological limits, (2) contours are calculated for the first few cardiac phases, where it is difficult to visually distinguish blood from myocardium, and (3) the method is independent of the shape of the tissue delineated and can be applied to short- or long-axis views, and on arbitrary regions of interest. Motion-guided contours were compared to manual contours for six conventional and six slice-followed mid-ventricular short-axis cine DENSE datasets. Using an area measure of segmentation error, the accuracy of the segmentation algorithm was shown to be similar to inter-observer variability. In addition, a radial segmentation error metric was introduced for short-axis data. The average radial epicardial segmentation error was 0.36+/-0.08 and 0.40+/-0.10 pixels for slice-followed and conventional cine DENSE, respectively, and the average radial endocardial segmentation error was 0.46+/-0.12 and 0.46+/-0.16 pixels for slice following and conventional cine DENSE, respectively. Motion-guided segmentation employs the displacement-encoded phase shifts intrinsic to DENSE MRI to accurately propagate a single set of pre-defined contours throughout the remaining cardiac phases.

Project description:PurposeTo determine the optimal respiratory navigator gating configuration for the quantification of left ventricular strain using spiral cine displacement encoding with stimulated echoes (DENSE) MRI.Materials and methodsTwo-dimensional spiral cine DENSE was performed on a 3 Tesla MRI using two single-navigator configurations (retrospective, prospective) and a combined "dual-navigator" configuration in 10 healthy adults and 20 healthy children. The adults also underwent breathhold DENSE as a reference standard for comparisons. Peak left ventricular strains, signal-to-noise ratio (SNR), and navigator efficiency were compared. Subjects also underwent dual-navigator gating with and without visual feedback to determine the effect on navigator efficiency.ResultsThere were no differences in circumferential, radial, and longitudinal strains between navigator-gated and breathhold DENSE (P = 0.09-0.95) (as confidence intervals, retrospective: [-1.0%-1.1%], [-7.4%-2.0%], [-1.0%-1.2%]; prospective: [-0.6%-2.7%], [-2.8%-8.3%], [-0.3%-2.9%]; dual: [-1.6%-0.5%], [-8.3%-3.2%], [-0.8%-1.9%], respectively). The dual configuration maintained SNR compared with breathhold acquisitions (16 versus 18, P = 0.06). SNR for the prospective configuration was lower than for the dual navigator in adults (P = 0.004) and children (P < 0.001). Navigator efficiency was higher (P < 0.001) for both retrospective (54%) and prospective (56%) configurations compared with the dual configuration (35%). Visual feedback improved the dual configuration navigator efficiency to 55% (P < 0.001).ConclusionWhen quantifying left ventricular strains using spiral cine DENSE MRI, a dual navigator configuration results in the highest SNR in adults and children. In adults, a retrospective configuration has good navigator efficiency without a substantial drop in SNR. Prospective gating should be avoided because it has the lowest SNR. Visual feedback represents an effective option to maintain navigator efficiency while using a dual navigator configuration.Level of evidence2 J. Magn. Reson. Imaging 2017;45:786-794.

Project description:PurposeTo develop a three-dimensional (two dimensions + time) convolutional neural network trained with displacement encoding with stimulated echoes (DENSE) data for displacement and strain analysis of cine MRI.Materials and methodsIn this retrospective multicenter study, a deep learning model (StrainNet) was developed to predict intramyocardial displacement from contour motion. Patients with various heart diseases and healthy controls underwent cardiac MRI examinations with DENSE between August 2008 and January 2022. Network training inputs were a time series of myocardial contours from DENSE magnitude images, and ground truth data were DENSE displacement measurements. Model performance was evaluated using pixelwise end-point error (EPE). For testing, StrainNet was applied to contour motion from cine MRI. Global and segmental circumferential strain (Ecc) derived from commercial feature tracking (FT), StrainNet, and DENSE (reference) were compared using intraclass correlation coefficients (ICCs), Pearson correlations, Bland-Altman analyses, paired t tests, and linear mixed-effects models.ResultsThe study included 161 patients (110 men; mean age, 61 years ± 14 [SD]), 99 healthy adults (44 men; mean age, 35 years ± 15), and 45 healthy children and adolescents (21 males; mean age, 12 years ± 3). StrainNet showed good agreement with DENSE for intramyocardial displacement, with an average EPE of 0.75 mm ± 0.35. The ICCs between StrainNet and DENSE and FT and DENSE were 0.87 and 0.72, respectively, for global Ecc and 0.75 and 0.48, respectively, for segmental Ecc. Bland-Altman analysis showed that StrainNet had better agreement than FT with DENSE for global and segmental Ecc.ConclusionStrainNet outperformed FT for global and segmental Ecc analysis of cine MRI.Keywords: Image Postprocessing, MR Imaging, Cardiac, Heart, Pediatrics, Technical Aspects, Technology Assessment, Strain, Deep Learning, DENSE Supplemental material is available for this article. © RSNA, 2023.

Dataset Information

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

Publications

Free-breathing cine DENSE MRI using phase cycling with matchmaking and stimulated-echo image-based navigators.

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