Dataset Information

Accelerated magnetic resonance imaging tissue phase mapping of the rat myocardium using compressed sensing with iterative soft-thresholding.

ABSTRACT:

Introduction

Tissue Phase Mapping (TPM) MRI can accurately measure regional myocardial velocities and strain. The lengthy data acquisition, however, renders TPM prone to errors due to variations in physiological parameters, and reduces data yield and experimental throughput. The purpose of the present study is to examine the quality of functional measures (velocity and strain) obtained by highly undersampled TPM data using compressed sensing reconstruction in infarcted and non-infarcted rat hearts.

Methods

Three fully sampled left-ventricular short-axis TPM slices were acquired from 5 non-infarcted rat hearts and 12 infarcted rat hearts in vivo. The datasets were used to generate retrospectively (simulated) undersampled TPM datasets, with undersampling factors of 2, 4, 8 and 16. Myocardial velocities and circumferential strain were calculated from all datasets. The error introduced from undersampling was then measured and compared to the fully sampled data in order to validate the method. Finally, prospectively undersampled data were acquired and compared to the fully sampled datasets.

Results

Bland Altman analysis of the retrospectively undersampled and fully sampled data revealed narrow limits of agreement and little bias (global radial velocity: median bias = -0.01 cm/s, 95% limits of agreement = [-0.16, 0.20] cm/s, global circumferential strain: median bias = -0.01%strain, 95% limits of agreement = [-0.43, 0.51] %strain, all for 4x undersampled data at the mid-ventricular level). The prospectively undersampled TPM datasets successfully demonstrated the feasibility of method implementation.

Conclusion

Through compressed sensing reconstruction, highly undersampled TPM data can be used to accurately measure the velocity and strain of the infarcted and non-infarcted rat myocardium in vivo, thereby increasing experimental throughput and simultaneously reducing error introduced by physiological variations over time.

SUBMITTER: McGinley G

PROVIDER: S-EPMC6611593 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Accelerated magnetic resonance imaging tissue phase mapping of the rat myocardium using compressed sensing with iterative soft-thresholding.

McGinley Gary G Bendiksen Bård A BA Zhang Lili L Aronsen Jan Magnus JM Nordén Einar Sjaastad ES Sjaastad Ivar I Espe Emil K S EKS

PloS one 20190705 7

<h4>Introduction</h4>Tissue Phase Mapping (TPM) MRI can accurately measure regional myocardial velocities and strain. The lengthy data acquisition, however, renders TPM prone to errors due to variations in physiological parameters, and reduces data yield and experimental throughput. The purpose of the present study is to examine the quality of functional measures (velocity and strain) obtained by highly undersampled TPM data using compressed sensing reconstruction in infarcted and non-infarcted ...[more]

PMID: 31276508

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Project description:Electron paramagnetic resonance (EPR) imaging has evolved as a promising tool to provide non-invasive assessment of tissue oxygenation levels. Due to the extremely short T2 relaxation time of electrons, single point imaging (SPI) is used in EPRI, limiting achievable spatial and temporal resolution. This presents a problem when attempting to measure changes in hypoxic state. In order to capture oxygen variation in hypoxic tissues and localize cycling hypoxia regions, an accelerated EPRI imaging method with minimal loss of information is needed.We present an image acceleration technique, partial Fourier compressed sensing (PFCS), that combines compressed sensing (CS) and partial Fourier reconstruction. PFCS augments the original CS equation using conjugate symmetry information for missing measurements. To further improve image quality in order to reconstruct low-resolution EPRI images, a projection onto convex sets (POCS)-based phase map and a spherical-sampling mask are used in the reconstruction process. The PFCS technique was used in phantoms and in vivo SCC7 tumor mice to evaluate image quality and accuracy in estimating O2 concentration.In both phantom and in vivo experiments, PFCS demonstrated the ability to reconstruct images more accurately with at least a 4-fold acceleration compared to traditional CS. Meanwhile, PFCS is able to better preserve the distinct spatial pattern in a phantom with a spatial resolution of 0.6mm. On phantoms containing Oxo63 solution with different oxygen concentrations, PFCS reconstructed linewidth maps that were discriminative of different O2 concentrations. Moreover, PFCS reconstruction of partially sampled data provided a better discrimination of hypoxic and oxygenated regions in a leg tumor compared to traditional CS reconstructed images.EPR images with an acceleration factor of four are feasible using PFCS with reasonable assessment of tissue oxygenation. The technique can greatly enhance EPR applications and improve our understanding cycling hypoxia. Moreover this technique can be easily extended to various MRI applications.

Project description:BACKGROUND:Cardiovascular magnetic resonance (CMR) allows for non-invasive assessment of arterial stiffness by means of measuring pulse wave velocity (PWV). PWV can be calculated from the time shift between two time-resolved flow curves acquired at two locations within an arterial segment. These flow curves can be derived from two-dimensional CINE phase contrast CMR (2D CINE PC CMR). While CMR-derived PWV measurements have proven to be accurate for the aorta, this is more challenging for smaller arteries such as the carotids due to the need for both high spatial and temporal resolution. In this work, we present a novel method that combines retrospectively gated 2D CINE PC CMR, high temporal binning of data and compressed sensing (CS) reconstruction to accomplish a temporal resolution of 4 ms. This enables accurate flow measurements and assessment of PWV in regional carotid artery segments. METHODS:Retrospectively gated 2D CINE PC CMR data acquired in the carotid artery was binned into cardiac frames of 4 ms length, resulting in an incoherently undersampled ky-t-space with a mean undersampling factor of 5. The images were reconstructed by a non-linear CS reconstruction using total variation over time as a sparsifying transform. PWV values were calculated from flow curves by using foot-to-foot and cross-correlation methods. Our method was validated against ultrasound measurements in a flow phantom setup representing the carotid artery. Additionally, PWV values of two groups of 23 young (30 ± 3 years, 12 [52%] women) and 10 elderly (62 ± 10 years, 5 [50%] women) healthy subjects were compared using the Wilcoxon rank-sum test. RESULTS:Our proposed method produced very similar flow curves as those measured using ultrasound at 1 ms temporal resolution. Reliable PWV estimation proved possible for transit times down to 7.5 ms. Furthermore, significant differences in PWV values between healthy young and elderly subjects were found (4.7 ± 1.0 m/s and 7.9 ± 2.4 m/s, respectively; p < 0.001) in accordance with literature. CONCLUSIONS:Retrospectively gated 2D CINE PC CMR with CS allows for high spatiotemporal resolution flow measurements and accurate regional carotid artery PWV calculations. We foresee this technique will be valuable in protocols investigating early development of carotid atherosclerosis.

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Dataset Information

Accelerated magnetic resonance imaging tissue phase mapping of the rat myocardium using compressed sensing with iterative soft-thresholding.

Introduction

Methods

Results

Conclusion

Publications

Accelerated magnetic resonance imaging tissue phase mapping of the rat myocardium using compressed sensing with iterative soft-thresholding.

Similar Datasets

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