“PINOT”: Time-resolved parallel magnetic resonance imaging with a reduced dynamic field of view (original) (raw)
Related papers
Sparsity adaptive reconstruction for highly accelerated cardiac MRI
Magnetic Resonance in Medicine, 2019
To enable parameter-free, accelerated cardiovascular magnetic resonance (CMR). Methods: Regularized reconstruction methods, such as compressed sensing (CS), can significantly accelerate MRI data acquisition but require tuning of regularization weights. In this work, a technique, called Sparsity adaptive Composite Recovery (SCoRe) that exploits sparsity in multiple, disparate sparsifying transforms is presented. A data-driven adjustment of the relative contributions of different transforms yields a parameter-free CS recovery process. SCoRe is validated in a dynamic digital phantom as well as in retrospectively and prospectively undersampled cine CMR data. Results: The results from simulation and 6 retrospectively undersampled datasets indicate that SCoRe with auto-tuned regularization weights yields lower root-meansquare error (RMSE) and higher structural similarity index (SSIM) compared to state-of-the-art CS methods. In 45 prospectively undersampled datasets acquired from 15 volunteers, the image quality was scored by 2 expert reviewers, with SCoRe receiving a higher average score (p < 0.01) compared to other CS methods. Conclusions: SCoRe enables accelerated cine CMR from highly undersampled data. In contrast to other acceleration techniques, SCoRe adapts regularization weights based on noise power and level of sparsity in each transform, yielding superior performance without admitting any free parameters. K E Y W O R D S adaptive, cardiac MRI, cine, compressed sensing, image reconstruction 3876 | Chong Chen et al. F I G U R E 1 Decomposition of a typical GRAPPA-reconstructed segmented cardiac cine dataset (input) using 3D nondecimated wavelet transform (NWT) with single-level Haar wavelet filter. LLL, HLL, LHL, HHL, LLH, HLH, LHH, and HHH represent 8 NWT subbands in the (x, y, t) domain, with x, y, and t representing vertical axis, horizontal axis, and time, respectively. Only one representative temporal frame is shown. Compared to the first 4 subbands (LLL, HLL, LHL, and HHL), the intensity of the last 4 subbands (LLH, HLH, LHH, and HHH) was amplified by a factor of 8 for better visualization. The fraction of coefficients in each subband that is larger than 1% of the maximum value across all subbands is 0
Accelerated MRI for the assessment of cardiac function
The British Journal of Radiology, 2016
Heart disease is a worldwide public health problem; assessment of cardiac function is an important part of the diagnosis and management of heart disease. MRI of the heart can provide clinically useful information on cardiac function, although it is still not routinely used in clinical practice, in part because of limited imaging speed. New accelerated methods for performing cardiovascular MRI (CMR) have the potential to provide both increased imaging speed and robustness to CMR, as well as access to increased functional information. In this review, we will briefly discuss the main methods currently employed to accelerate CMR methods, such as parallel imaging, k-t undersampling and compressed sensing, as well as new approaches that extend the idea of compressed sensing and exploit sparsity to provide richer information of potential use in clinical practice.
Real-time cardiac MRI using low-rank and sparsity penalties
… Imaging: From Nano to Macro, 2010 …, 2010
We introduce a novel algorithm to reconstruct realtime cardiac MRI data from undersampled radial acquisitions. We exploit the fact that the spatio-temporal data can be represented as the linear combination of a few temporal basis functions. The current approaches that capitalize this property estimate the basis functions from central phase encodes, acquired with a fine temporal sampling rate. In contrast, we estimate the basis functions from the entire under-sampled data. By eliminating the need for training data, the proposed method can achieve potentially high acceleration factors. More importantly, the estimation of the temporal functions from the entire data significantly improves the quality of the basis functions, which inturn improves the quality of the reconstructions. Experiments on numerical phantoms show a significant reduction in artifacts at high acceleration factors, in comparison to current schemes.
Time-resolved parallel imaging with a reduced dynamic field of view
2008
Abstract This paper introduces a novel method for accelerated dynamic image acquisition for cardiac MRI. This method combines two different formalisms for reconstruction from sparse data by incorporation of prior information. Parallel imaging uses information about coil geometry in imaging systems with multiple receiver coils. Reduced field of view (rFOV) imaging exploits knowledge about static regions in a dynamic image scene.
Variable density incoherent spatiotemporal acquisition (VISTA) for highly accelerated cardiac MRI
Magnetic Resonance in Medicine, 2014
Purpose-For the application of compressive sensing to parallel MRI, Poisson disk sampling (PDS) has been shown to generate superior results compared with random sampling methods. However, due to its limited flexibility to incorporate additional constraints, PDS is not readily extendible to dynamic applications. Here, we propose and validate a pseudo-random sampling technique that allows incorporating constraints specific to dynamic imaging. Methods-The proposed sampling scheme, called variable density incoherent spatiotemporal acquisition (VISTA), is based on constrained minimization of Riesz energy on a spatiotemporal grid. Data from both a digital phantom and real-time cine were used to compare VISTA with uniform interleaved sampling (UIS) and variable density random sampling (VRS). The image quality was assessed qualitatively and quantitatively.
Temporally constrained reconstruction of dynamic cardiac perfusion MRI
Magnetic Resonance in Medicine, 2007
Dynamic contrast-enhanced (DCE) MRI is a powerful technique to probe an area of interest in the body. Here a temporally constrained reconstruction (TCR) technique that requires less k-space data over time to obtain good-quality reconstructed images is proposed. This approach can be used to improve the spatial or temporal resolution, or increase the coverage of the object of interest. The method jointly reconstructs the space-time data iteratively with a temporal constraint in order to resolve aliasing. The method was implemented and its feasibility tested on DCE myocardial perfusion data with little or no motion. The results obtained from sparse k-space data using the TCR method were compared with results obtained with a sliding-window (SW) method and from full data using the standard inverse Fourier transform (IFT) reconstruction. Acceleration factors of 5 (R ؍ 5) were achieved without a significant loss in image quality. Mean improvements of 28 ؎ 4% in the signal-to-noise ratio (SNR) and 14 ؎ 4% in the contrast-to-noise ratio (CNR) were observed in the images reconstructed using the TCR method on sparse data (R ؍ 5) compared to the standard IFT reconstructions from full data for the perfusion datasets. The method has the potential to improve dynamic myocardial perfusion imaging and also to reconstruct other sparse dynamic MR acquisitions. Magn Reson Med 57:1027-1036, 2007.
IEEE Transactions on Medical Imaging, 2016
A novel method for real-time magnetic resonance imaging for the assessment of cardiac function in mice at 9.4 T is proposed. The technique combines a highly undersampled radial gradient echo acquisition with an image reconstruction utilizing both parallel imaging and compressed sensing. Simulations on an in silico phantom were performed to determine the achievable acceleration factor and to optimize regularization parameters. Several parameters characterizing the quality of the reconstructed images (such as spatial and temporal image sharpness or compartment areas) were calculated for this purpose. Subsequently, double-gated segmented cine data as well as non-gated undersampled real-time data using only six projections per timeframe (temporal resolution) were acquired in a mid-ventricular slice of four normal mouse hearts in vivo. The highly accelerated data sets were then subjected to the introduced reconstruction technique and results were validated against the fully sampled references. Functional parameters obtained from real-time and fully sampled data agreed well with a comparable accuracy for left-ventricular volumes and a slightly larger scatter for mass. This study introduces and validates a real-time cine-MRI technique, which significantly reduces scan time in preclinical cardiac functional imaging and has the potential to investigate mouse models with abnormal heart rhythm.
Real-time cardiac MRI using prior spatial-spectral information
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2009
Cardiac MRI performed while the patient is breathing is typically achieved using non-real-time techniques such as ECG triggering with respiratory gating; however, modern dynamic imaging techniques are beginning to enable this type of imaging in real-time. One of these dynamic imaging techniques is based on forming a Partially Separable Function (PSF) model of the data, but the model fitting process is known to be sensitive even when truncated SVD regularization is used. As a result, physiologically meaningless artifacts can appear in the dynamic images when the total number of measurements is limited. To address this issue, the dynamic imaging problem is formulated as a generalized Tikhonov regularization problem with the PSF model as a component of the forward data model, and a penalty function is used to introduce spatial-spectral prior information. This new method both reduces data acquisition requirements and improves stability relative to the original PSF based method when appl...
High speed and high resolution cardiac MRI (parallel acquisition techniques & modular imaging)
An enormous array of technical and methodological challenges in cardiac MRI must be overcome to produce dynamic cardiac and coronary artery images with sufficient spatial resolution, contrast-to-noise ratio, and with minimal flow artifacts. In addition, the complex effects of cardiac and respiratory motion must be addressed. These factors explain why MRI still does not play a significant role as a clinically accepted cardiac imaging modality. However, over the last few years, an impressive number of technical and methodological developments have continued to provide enhancements to cardiac MRI. In particular, the advent of faster and stronger gradient systems and the development of improved imaging strategies have enormously boosted the acquisition speed. Based on this technology, faster cardiac imaging techniques have been developed which provide considerable time savings and increased flexibility. Today, it is possible to perform a comprehensive cardiac MR examination assessing cardiac anatomy and pathology, ventricular function, valvular function, wall motion, myocardial perfusion and coronary angiography. However, each of the current cardiac imaging approaches have their problems, such as limitations in sensitivity, long acquisition times, low image quality or reduced spatial resolution. Given the advantages and disadvantages of the various fast imaging methods, it is obvious that no single method will dominate the field of cardiac imaging. Thus, in many research groups, including our own, different dedicated approaches are currently being developed which optimize imaging efficiency for a given cardiac task.