Dataset Information

High spatial and temporal resolution retrospective cine cardiovascular magnetic resonance from shortened free breathing real-time acquisitions.

ABSTRACT: BACKGROUND: Cine cardiovascular magnetic resonance (CMR) is challenging in patients who cannot perform repeated breath holds. Real-time, free-breathing acquisition is an alternative, but image quality is typically inferior. There is a clinical need for techniques that achieve similar image quality to the segmented cine using a free breathing acquisition. Previously, high quality retrospectively gated cine images have been reconstructed from real-time acquisitions using parallel imaging and motion correction. These methods had limited clinical applicability due to lengthy acquisitions and volumetric measurements obtained with such methods have not previously been evaluated systematically. METHODS: This study introduces a new retrospective reconstruction scheme for real-time cine imaging which aims to shorten the required acquisition. A real-time acquisition of 16-20s per acquired slice was inputted into a retrospective cine reconstruction algorithm, which employed non-rigid registration to remove respiratory motion and SPIRiT non-linear reconstruction with temporal regularization to fill in missing data. The algorithm was used to reconstruct cine loops with high spatial (1.3-1.8?×?1.8-2.1 mm²) and temporal resolution (retrospectively gated, 30 cardiac phases, temporal resolution 34.3?±?9.1 ms). Validation was performed in 15 healthy volunteers using two different acquisition resolutions (256?×?144/192?×?128 matrix sizes). For each subject, 9 to 12 short axis and 3 long axis slices were imaged with both segmented and real-time acquisitions. The retrospectively reconstructed real-time cine images were compared to a traditional segmented breath-held acquisition in terms of image quality scores. Image quality scoring was performed by two experts using a scale between 1 and 5 (poor to good). For every subject, LAX and three SAX slices were selected and reviewed in the random order. The reviewers were blinded to the reconstruction approach and acquisition protocols and scores were given to segmented and retrospective cine series. Volumetric measurements of cardiac function were also compared by manually tracing the myocardium for segmented and retrospective cines. RESULTS: Mean image quality scores were similar for short axis and long axis views for both tested resolutions. Short axis scores were 4.52/4.31 (high/low matrix sizes) for breath-hold vs. 4.54/4.56 for real-time (paired t-test, P?=?0.756/0.011). Long axis scores were 4.09/4.37 vs. 3.99/4.29 (P?=?0.475/0.463). Mean ejection fraction was 60.8/61.4 for breath-held acquisitions vs. 60.3/60.3 for real-time acquisitions (P?=?0.439/0.093). No significant differences were seen in end-diastolic volume (P?=?0.460/0.268) but there was a trend towards a small overestimation of end-systolic volume of 2.0/2.5 ml, which did not reach statistical significance (P?=?0.052/0.083). CONCLUSIONS: Real-time free breathing CMR can be used to obtain high quality retrospectively gated cine images in 16-20s per slice. Volumetric measurements and image quality scores were similar in images from breath-held segmented and free breathing, real-time acquisitions. Further speedup of image reconstruction is still needed.

SUBMITTER: Xue H

PROVIDER: S-EPMC3842803 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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High spatial and temporal resolution retrospective cine cardiovascular magnetic resonance from shortened free breathing real-time acquisitions.

Xue Hui H Kellman Peter P Larocca Gina G Arai Andrew E AE Hansen Michael S MS

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance 20131114

<h4>Background</h4>Cine cardiovascular magnetic resonance (CMR) is challenging in patients who cannot perform repeated breath holds. Real-time, free-breathing acquisition is an alternative, but image quality is typically inferior. There is a clinical need for techniques that achieve similar image quality to the segmented cine using a free breathing acquisition. Previously, high quality retrospectively gated cine images have been reconstructed from real-time acquisitions using parallel imaging an ...[more]

PMID: 24228930

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Project description:Objective3D cine-magnetic resonance imaging (cine-MRI) can capture images of the human body volume with high spatial and temporal resolutions to study the anatomical dynamics. However, the reconstruction of 3D cine-MRI is challenged by highly undersampled k-space data in each dynamic (cine) frame, due to the slow speed of MR signal acquisition. We proposed a machine learning-based framework, spatial and temporal implicit neural representation learning (STINR-MR), for accurate 3D cine-MRI reconstruction from highly undersampled data.ApproachSTINR-MR used a joint reconstruction and deformable registration approach to achieve a high acceleration factor for cine volumetric imaging. It addressed the ill-posed spatiotemporal reconstruction problem by solving a reference-frame 3D MR image and a corresponding motion model which deforms the reference frame to each cine frame. The reference-frame 3D MR image was reconstructed as a spatial implicit neural representation (INR) network, which learns the mapping from input 3D spatial coordinates to corresponding MR values. The dynamic motion model was constructed via a temporal INR, as well as basis deformation vector fields (DVFs) extracted from prior/onboard 4D-MRIs using principal component analysis (PCA). The learned temporal INR encodes input time points and outputs corresponding weighting factors to combine the basis DVFs into time-resolved motion fields that represent cine-frame-specific dynamics. STINR-MR was evaluated using MR data simulated from the 4D extended cardiac-torso (XCAT) digital phantom, as well as MR data acquired clinically from a healthy human subject. Its reconstruction accuracy was also compared with that of the model-based non-rigid motion estimation method (MR-MOTUS).Main resultsSTINR-MR can reconstruct 3D cine-MR images with high temporal (<100 ms) and spatial (3 mm) resolutions. Compared with MR-MOTUS, STINR-MR consistently reconstructed images with better image quality and fewer artifacts and achieved superior tumor localization accuracy via the solved dynamic DVFs. For the XCAT study, STINR reconstructed the tumors to a mean±S.D. center-of-mass error of 1.0±0.4 mm, compared to 3.4±1.0 mm of the MR-MOTUS method. The high-frame-rate reconstruction capability of STINR-MR allows different irregular motion patterns to be accurately captured.SignificanceSTINR-MR provides a lightweight and efficient framework for accurate 3D cine-MRI reconstruction. It is a 'one-shot' method that does not require external data for pre-training, allowing it to avoid generalizability issues typically encountered in deep learning-based methods.

Project description:PurposeTo demonstrate an MRI technique-Submillisecond Periodic Event Encoded Dynamic Imaging (SPEEDI)-for capturing cyclic dynamic events with submillisecond temporal resolution.MethodsThe SPEEDI technique is based on an FID or an echo signal in which each time point in the signal is used to sample a distinct k-space raster, followed by repeated FIDs or echoes to produce the remaining k-space data in each k-space raster. All acquisitions are synchronized with a cyclic event, resulting in a set of time-resolved images of the cyclic event with a temporal resolution determined by the dwell time. In SPEEDI, spatial encoding is accomplished by phase encoding. The SPEEDI technique was demonstrated in two experiments at 3 T to (1) visualize fast-changing electric currents that mimicked the waveform of an action potential, and (2) characterize rapidly decaying eddy currents in an MRI system, with a temporal resolution of 0.2 ms and 0.4 ms, respectively. In both experiments, compressed sensing was incorporated to reduce the scan times. Phase difference maps related to the dynamics of electric currents or eddy currents were then obtained.ResultsIn the first experiment, time-resolved phase maps resulting from the action potential-mimicking current waveform were successfully obtained and agreed well with theoretical calculations (normalized RMS error = 0.07). In the second experiment, spatially resolved eddy current phase maps revealed time constants (27.1 ± 0.2 ms, 41.1 ± 3.5 ms, and 34.8 ± 0.7 ms) that matched well with those obtained from an established method using point sources (26.4 ms, 41.2 ms and 34.8 ms). For both experiments, phase maps from fully sampled and compressed-sensing-accelerated k-space data exhibited a high structural similarity (> 0.8) despite a two-fold to three-fold acceleration.ConclusionsWe have illustrated that SPEEDI can provide submillisecond temporal resolution. This capability will likely lead to future exploration of ultrafast, cyclic biomedical processes using MRI.

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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.

Dataset Information

High spatial and temporal resolution retrospective cine cardiovascular magnetic resonance from shortened free breathing real-time acquisitions.

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High spatial and temporal resolution retrospective cine cardiovascular magnetic resonance from shortened free breathing real-time acquisitions.

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