Real-time reconstruction of sensitivity encoded radial magnetic resonance imaging using a graphics processing unit

MRI-guided endovascular intervention: current methods and future potential

INTRODUCTION

Image-guided endovascular interventions, performed using the insertion and navigation of catheters through the vasculature, have been increasing in number over the years, as minimally invasive procedures continue to replace invasive surgical procedures. Such endovascular interventions are almost exclusively performed under x-ray fluoroscopy, which has the best spatial and temporal resolution of all clinical imaging modalities. Magnetic resonance imaging (MRI) offers unique advantages and could be an attractive alternative to conventional x-ray guidance, but also brings with it distinctive challenges.

AREAS COVERED

In this review, the benefits and limitations of MRI-guided endovascular interventions are addressed, systems and devices for guiding such interventions are summarized, and clinical applications are discussed.

EXPERT OPINION

MRI-guided endovascular interventions are still relatively new to the interventional radiology field, since significant technical hurdles remain to justify significant costs and demonstrate safety, design, and robustness. Clinical applications of MRI-guided interventions are promising but their full potential may not be realized until proper tools designed to function in the MRI environment are available. Translational research and further preclinical studies are needed before MRI-guided interventions will be practical in a clinical interventional setting.

Continuous cardiac thermometry via simultaneous catheter tracking and undersampled radial golden angle acquisition for radiofrequency ablation monitoring

The complexity of the MRI protocol is one of the factors limiting the clinical adoption of MR temperature mapping for real-time monitoring of cardiac ablation procedures and a push-button solution would ease its use. Continuous gradient echo golden angle radial acquisition combined with intra-scan motion correction and undersampled temperature determination could be a robust and more user-friendly alternative than the ultrafast GRE-EPI sequence which suffers from sensitivity to magnetic field susceptibility artifacts and requires ECG-gating. The goal of this proof-of-concept work is to establish the temperature uncertainty as well as the spatial and temporal resolutions achievable in an Agar-gel phantom and in vivo using this method. GRE radial golden angle acquisitions were used to monitor RF ablations in a phantom and in vivo in two sheep hearts with different slice orientations. In each case, 2D rigid motion correction based on catheter micro-coil signal, tracking its motion, was performed and its impact on the temperature imaging was assessed. The temperature uncertainty was determined for three spatial resolutions (1 × 1 × 3 mm³, 2 × 2 × 3 mm³, and 3 × 3 × 3 mm³) and three temporal resolutions (0.48, 0.72, and 0.97 s) with undersampling acceleration factors ranging from 2 to 17. The combination of radial golden angle GRE acquisition, simultaneous catheter tracking, intra-scan 2D motion correction, and undersampled thermometry enabled temperature monitoring in the myocardium in vivo during RF ablations with high temporal (< 1 s) and high spatial resolution. The temperature uncertainty ranged from 0.2 ± 0.1 to 1.8 ± 0.2 °C for the various temporal and spatial resolutions and, on average, remained superior to the uncertainty of an EPI acquisition while still allowing clinical monitoring of the RF ablation process. The proposed method is a robust and promising alternative to EPI acquisition to monitor in vivo RF cardiac ablations. Further studies remain required to improve the temperature uncertainty and establish its clinical applicability.

Real-Time Magnetic Resonance Imaging

Real-time magnetic resonance imaging (RT-MRI) allows for imaging dynamic processes as they occur, without relying on any repetition or synchronization. This is made possible by modern MRI technology such as fast-switching gradients and parallel imaging. It is compatible with many (but not all) MRI sequences, including spoiled gradient echo, balanced steady-state free precession, and single-shot rapid acquisition with relaxation enhancement. RT-MRI has earned an important role in both diagnostic imaging and image guidance of invasive procedures. Its unique diagnostic value is prominent in areas of the body that undergo substantial and often irregular motion, such as the heart, gastrointestinal system, upper airway vocal tract, and joints. Its value in interventional procedure guidance is prominent for procedures that require multiple forms of soft-tissue contrast, as well as flow information. In this review, we discuss the history of RT-MRI, fundamental tradeoffs, enabling technology, established applications, and current trends. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

A System for Real-Time, Online Mixed-Reality Visualization of Cardiac Magnetic Resonance Images

Image-guided cardiovascular interventions are rapidly evolving procedures that necessitate imaging systems capable of rapid data acquisition and low-latency image reconstruction and visualization. Compared to alternative modalities, Magnetic Resonance Imaging (MRI) is attractive for guidance in complex interventional settings thanks to excellent soft tissue contrast and large fields-of-view without exposure to ionizing radiation. However, most clinically deployed MRI sequences and visualization pipelines exhibit poor latency characteristics, and spatial integration of complex anatomy and device orientation can be challenging on conventional 2D displays. This work demonstrates a proof-of-concept system linking real-time cardiac MR image acquisition, online low-latency reconstruction, and a stereoscopic display to support further development in real-time MR-guided intervention. Data are acquired using an undersampled, radial trajectory and reconstructed via parallelized through-time radial generalized autocalibrating partially parallel acquisition (GRAPPA) implemented on graphics processing units. Images are rendered for display in a stereoscopic mixed-reality head-mounted display. The system is successfully tested by imaging standard cardiac views in healthy volunteers. Datasets comprised of one slice (46 ms), two slices (92 ms), and three slices (138 ms) are collected, with the acquisition time of each listed in parentheses. Images are displayed with latencies of 42 ms/frame or less for all three conditions. Volumetric data are acquired at one volume per heartbeat with acquisition times of 467 ms and 588 ms when 8 and 12 partitions are acquired, respectively. Volumes are displayed with a latency of 286 ms or less. The faster-than-acquisition latencies for both planar and volumetric display enable real-time 3D visualization of the heart.

MRIReco.jl: An MRI reconstruction framework written in Julia

PURPOSE

The aim of this work is to develop a high-performance, flexible, and easy-to-use MRI reconstruction framework using the scientific programming language Julia.

METHODS

Julia is a modern, general purpose programming language with strong features in the area of signal/image processing and numerical computing. It has a high-level syntax but still generates efficient machine code that is usually as fast as comparable C/C++ applications. In addition to the language features itself, Julia has a sophisticated package management system that makes proper modularization of functionality across different packages feasible. Our developed MRI reconstruction framework MRIReco.jl can therefore reuse existing functionality from other Julia packages and concentrate on the MRI-related parts. This includes common imaging operators and support for MRI raw data formats.

RESULTS

MRIReco.jl is a simple to use framework with a high degree of accessibility. While providing a simple-to-use interface, many of its components can easily be extended and customized. The performance of MRIReco.jl is compared to the Berkeley Advanced Reconstruction Toolbox (BART) and we show that the Julia framework achieves comparable reconstruction speed as the popular C/C++ library.

CONCLUSIONS

Modern programming languages can bridge the gap between high performance and accessible implementations. MRIReco.jl leverages this fact and contributes a promising environment for future algorithmic development in MRI reconstruction.

Automatic needle tracking using Mask R-CNN for MRI-guided percutaneous interventions

PURPOSE

Accurate needle tracking provides essential information for MRI-guided percutaneous interventions. Passive needle tracking using MR images is challenged by variations of the needle-induced signal void feature in different situations. This work aimed to develop an automatic needle tracking algorithm for MRI-guided interventions based on the Mask Region Proposal-Based Convolutional Neural Network (R-CNN).

METHODS

Mask R-CNN was adapted and trained to segment the needle feature using 250 intra-procedural images from 85 MRI-guided prostate biopsy cases and 180 real-time images from MRI-guided needle insertion in ex vivo tissue. The segmentation masks were passed into the needle feature localization algorithm to extract the needle feature tip location and axis orientation. The proposed algorithm was tested using 208 intra-procedural images from 40 MRI-guided prostate biopsy cases, and 3 real-time MRI datasets in ex vivo tissue. The algorithm results were compared with human-annotated references.

RESULTS

In prostate datasets, the proposed algorithm achieved needle feature tip localization error with median Euclidean distance (dxy) of 0.71 mm and median difference in axis orientation angle (dθ) of 1.28°, respectively. In 3 real-time MRI datasets, the proposed algorithm achieved consistent dynamic needle feature tracking performance with processing time of 75 ms/image: (a) median dxy = 0.90 mm, median dθ = 1.53°; (b) median dxy = 1.31 mm, median dθ = 1.9°; (c) median dxy = 1.09 mm, median dθ = 0.91°.

CONCLUSIONS

The proposed algorithm using Mask R-CNN can accurately track the needle feature tip and axis on MR images from in vivo intra-procedural prostate biopsy cases and ex vivo real-time MRI experiments with a range of different conditions. The algorithm achieved pixel-level tracking accuracy in real time and has potential to assist MRI-guided percutaneous interventions.

Beyond T2 and 3T: New MRI techniques for clinicians

Technological advances in Magnetic Resonance Imaging (MRI) in terms of field strength and hybrid MR systems have led to improvements in tumor imaging in terms of anatomy and functionality. This review paper discusses the applications of such advances in the field of radiation oncology with regards to treatment planning, therapy guidance and monitoring tumor response and predicting outcome.

Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging

PURPOSE

To develop and evaluate a parallel imaging and convolutional neural network combined image reconstruction framework for low-latency and high-quality accelerated real-time MR imaging.

METHODS

Conventional Parallel Imaging reconstruction resolved as gradient descent steps was compacted as network layers and interleaved with convolutional layers in a general convolutional neural network. All parameters of the network were determined during the offline training process, and applied to unseen data once learned. The proposed network was first evaluated for real-time cardiac imaging at 1.5 T and real-time abdominal imaging at 0.35 T, using threefold to fivefold retrospective undersampling for cardiac imaging and threefold retrospective undersampling for abdominal imaging. Then, prospective undersampling with fourfold acceleration was performed on cardiac imaging to compare the proposed method with standard clinically available GRAPPA method and the state-of-the-art L1-ESPIRiT method.

RESULTS

Both retrospective and prospective evaluations confirmed that the proposed network was able to images with a lower noise level and reduced aliasing artifacts in comparison with the single-coil based and L1-ESPIRiT reconstructions for cardiac imaging at 1.5 T, and the GRAPPA and L1-ESPIRiT reconstructions for abdominal imaging at 0.35 T. Using the proposed method, each frame can be reconstructed in less than 100 ms, suggesting its clinical compatibility.

CONCLUSION

The proposed Parallel Imaging and convolutional neural network combined reconstruction framework is a promising technique that allows low-latency and high-quality real-time MR imaging.

A survey of GPU-based acceleration techniques in MRI reconstructions

Image reconstruction in magnetic resonance imaging (MRI) clinical applications has become increasingly more complicated. However, diagnostic and treatment require very fast computational procedure. Modern competitive platforms of graphics processing unit (GPU) have been used to make high-performance parallel computations available, and attractive to common consumers for computing massively parallel reconstruction problems at commodity price. GPUs have also become more and more important for reconstruction computations, especially when deep learning starts to be applied into MRI reconstruction. The motivation of this survey is to review the image reconstruction schemes of GPU computing for MRI applications and provide a summary reference for researchers in MRI community.

Accelerated Computing in Magnetic Resonance Imaging: Real-Time Imaging Using Nonlinear Inverse Reconstruction

Purpose

To develop generic optimization strategies for image reconstruction using graphical processing units (GPUs) in magnetic resonance imaging (MRI) and to exemplarily report on our experience with a highly accelerated implementation of the nonlinear inversion (NLINV) algorithm for dynamic MRI with high frame rates.

Methods

The NLINV algorithm is optimized and ported to run on a multi-GPU single-node server. The algorithm is mapped to multiple GPUs by decomposing the data domain along the channel dimension. Furthermore, the algorithm is decomposed along the temporal domain by relaxing a temporal regularization constraint, allowing the algorithm to work on multiple frames in parallel. Finally, an autotuning method is presented that is capable of combining different decomposition variants to achieve optimal algorithm performance in different imaging scenarios.

Results

The algorithm is successfully ported to a multi-GPU system and allows online image reconstruction with high frame rates. Real-time reconstruction with low latency and frame rates up to 30 frames per second is demonstrated.

Conclusion

Novel parallel decomposition methods are presented which are applicable to many iterative algorithms for dynamic MRI. Using these methods to parallelize the NLINV algorithm on multiple GPUs, it is possible to achieve online image reconstruction with high frame rates.

A review of GPU-based medical image reconstruction

Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing.

Recent advances in parallel imaging for MRI

Magnetic Resonance Imaging (MRI) is an essential technology in modern medicine. However, one of its main drawbacks is the long scan time needed to localize the MR signal in space to generate an image. This review article summarizes some basic principles and recent developments in parallel imaging, a class of image reconstruction techniques for shortening scan time. First, the fundamentals of MRI data acquisition are covered, including the concepts of k-space, undersampling, and aliasing. It is demonstrated that scan time can be reduced by sampling a smaller number of phase encoding lines in k-space; however, without further processing, the resulting images will be degraded by aliasing artifacts. Nearly all modern clinical scanners acquire data from multiple independent receiver coil arrays. Parallel imaging methods exploit properties of these coil arrays to separate aliased pixels in the image domain or to estimate missing k-space data using knowledge of nearby acquired k-space points. Three parallel imaging methods-SENSE, GRAPPA, and SPIRiT-are described in detail, since they are employed clinically and form the foundation for more advanced methods. These techniques can be extended to non-Cartesian sampling patterns, where the collected k-space points do not fall on a rectangular grid. Non-Cartesian acquisitions have several beneficial properties, the most important being the appearance of incoherent aliasing artifacts. Recent advances in simultaneous multi-slice imaging are presented next, which use parallel imaging to disentangle images of several slices that have been acquired at once. Parallel imaging can also be employed to accelerate 3D MRI, in which a contiguous volume is scanned rather than sequential slices. Another class of phase-constrained parallel imaging methods takes advantage of both image magnitude and phase to achieve better reconstruction performance. Finally, some applications are presented of parallel imaging being used to accelerate MR Spectroscopic Imaging.

Compressed sensing MRI reconstruction from 3D multichannel data using GPUs

PURPOSE

To accelerate iterative reconstructions of compressed sensing (CS) MRI from 3D multichannel data using graphics processing units (GPUs).

METHODS

The sparsity of MRI signals and parallel array receivers can reduce the data acquisition requirements. However, iterative CS reconstructions from data acquired using an array system may take a significantly long time, especially for a large number of parallel channels. This paper presents an efficient method for CS-MRI reconstruction from 3D multichannel data using GPUs. In this method, CS reconstructions were simultaneously processed in a channel-by-channel fashion on the GPU, in which the computations of multiple-channel 3D-CS reconstructions are highly parallelized. The final image was then produced by a sum-of-squares method on the central processing unit. Implementation details including algorithm, data/memory management, and parallelization schemes are reported in the paper.

RESULTS

Both simulated data and in vivo MRI array data were tested. The results showed that the proposed method can significantly improve the image reconstruction efficiency, typically shortening the runtime by a factor of 30.

CONCLUSIONS

Using low-cost GPUs and an efficient algorithm allowed the 3D multislice compressive-sensing reconstruction to be performed in less than 1 s. The rapid reconstructions are expected to help bring high-dimensional, multichannel parallel CS MRI closer to clinical applications. Magn Reson Med 78:2265-2274, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Feasibility of through-time spiral generalized autocalibrating partial parallel acquisition for low latency accelerated real-time MRI of speech

PURPOSE

To evaluate the feasibility of through-time spiral generalized autocalibrating partial parallel acquisition (GRAPPA) for low-latency accelerated real-time MRI of speech.

METHODS

Through-time spiral GRAPPA (spiral GRAPPA), a fast linear reconstruction method, is applied to spiral (k-t) data acquired from an eight-channel custom upper-airway coil. Fully sampled data were retrospectively down-sampled to evaluate spiral GRAPPA at undersampling factors R = 2 to 6. Pseudo-golden-angle spiral acquisitions were used for prospective studies. Three subjects were imaged while performing a range of speech tasks that involved rapid articulator movements, including fluent speech and beat-boxing. Spiral GRAPPA was compared with view sharing, and a parallel imaging and compressed sensing (PI-CS) method.

RESULTS

Spiral GRAPPA captured spatiotemporal dynamics of vocal tract articulators at undersampling factors ≤4. Spiral GRAPPA at 18 ms/frame and 2.4 mm² /pixel outperformed view sharing in depicting rapidly moving articulators. Spiral GRAPPA and PI-CS provided equivalent temporal fidelity. Reconstruction latency per frame was 14 ms for view sharing and 116 ms for spiral GRAPPA, using a single processor. Spiral GRAPPA kept up with the MRI data rate of 18ms/frame with eight processors. PI-CS required 17 minutes to reconstruct 5 seconds of dynamic data.

CONCLUSION

Spiral GRAPPA enabled 4-fold accelerated real-time MRI of speech with a low reconstruction latency. This approach is applicable to wide range of speech RT-MRI experiments that benefit from real-time feedback while visualizing rapid articulator movement. Magn Reson Med 78:2275-2282, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Quantification of Left Ventricular Function With Premature Ventricular Complexes Reveals Variable Hemodynamics

BACKGROUND

Premature ventricular complexes (PVCs) are prevalent in the general population and are sometimes associated with reduced ventricular function. Current echocardiographic and cardiovascular magnetic resonance imaging techniques do not adequately address the effect of PVCs on left ventricular function.

METHODS AND RESULTS

Fifteen subjects with a history of frequent PVCs undergoing cardiovascular magnetic resonance imaging had real-time slice volume quantification performed using a 2-dimensional (2D) real-time cardiovascular magnetic resonance imaging technique. Synchronization of 2D real-time imaging with patient ECG allowed for different beats to be categorized by the loading beat RR duration and beat RR duration. For each beat type, global volumes were quantified via summation over all slices covering the entire ventricle. Different patterns of ectopy, including isolated PVCs, bigeminy, trigeminy, and interpolated PVCs, were observed. Global functional measurement of the different beat types based on timing demonstrated differences in preload, stroke volume, and ejection fraction. An average of hemodynamic function was quantified for each subject depending on the frequency of each observed beat type.

CONCLUSIONS

Application of real-time cardiovascular magnetic resonance imaging in patients with PVCs revealed differential contribution of PVCs to hemodynamics.

Recommendations for real-time speech MRI

Real-time magnetic resonance imaging (RT-MRI) is being increasingly used for speech and vocal production research studies. Several imaging protocols have emerged based on advances in RT-MRI acquisition, reconstruction, and audio-processing methods. This review summarizes the state-of-the-art, discusses technical considerations, and provides specific guidance for new groups entering this field. We provide recommendations for performing RT-MRI of the upper airway. This is a consensus statement stemming from the ISMRM-endorsed Speech MRI summit held in Los Angeles, February 2014. A major unmet need identified at the summit was the need for consensus on protocols that can be easily adapted by researchers equipped with conventional MRI systems. To this end, we provide a discussion of tradeoffs in RT-MRI in terms of acquisition requirements, a priori assumptions, artifacts, computational load, and performance for different speech tasks. We provide four recommended protocols and identify appropriate acquisition and reconstruction tools. We list pointers to open-source software that facilitate implementation. We conclude by discussing current open challenges in the methodological aspects of RT-MRI of speech.

Magnetic Resonance Sequences and Rapid Acquisition for MR-Guided Interventions

Interventional MR uses rapid imaging to guide diagnostic and therapeutic procedures. One of the attractions of MR-guidance is the abundance of inherent contrast mechanisms available. Dynamic procedural guidance with real-time imaging has pushed the limits of MR technology, demanding rapid acquisition and reconstruction paired with interactive control and device visualization. This article reviews the technical aspects of real-time MR sequences that enable MR-guided interventions.

User-initialized active contour segmentation and golden-angle real-time cardiovascular magnetic resonance enable accurate assessment of LV function in patients with sinus rhythm and arrhythmias

BACKGROUND

Data obtained during arrhythmia is retained in real-time cardiovascular magnetic resonance (rt-CMR), but there is limited and inconsistent evidence to show that rt-CMR can accurately assess beat-to-beat variation in left ventricular (LV) function or during an arrhythmia.

METHODS

Multi-slice, short axis cine and real-time golden-angle radial CMR data was collected in 22 clinical patients (18 in sinus rhythm and 4 patients with arrhythmia). A user-initialized active contour segmentation (ACS) software was validated via comparison to manual segmentation on clinically accepted software. For each image in the 2D acquisitions, slice volume was calculated and global LV volumes were estimated via summation across the LV using multiple slices. Real-time imaging data was reconstructed using different image exposure times and frame rates to evaluate the effect of temporal resolution on measured function in each slice via ACS. Finally, global volumetric function of ectopic and non-ectopic beats was measured using ACS in patients with arrhythmias.

RESULTS

ACS provides global LV volume measurements that are not significantly different from manual quantification of retrospectively gated cine images in sinus rhythm patients. With an exposure time of 95.2 ms and a frame rate of > 89 frames per second, golden-angle real-time imaging accurately captures hemodynamic function over a range of patient heart rates. In four patients with frequent ectopic contractions, initial quantification of the impact of ectopic beats on hemodynamic function was demonstrated.

CONCLUSION

User-initialized active contours and golden-angle real-time radial CMR can be used to determine time-varying LV function in patients. These methods will be very useful for the assessment of LV function in patients with frequent arrhythmias.

Real-Time Image Reconstruction for Pulse EPR Oxygen Imaging Using a GPU and Lookup Table Parameter Fitting

The importance of tissue oxygenation has led to a great interest in methods for imaging pO₂ in vivo. Electron paramagnetic resonance imaging (EPRI) provides noninvasive, near absolute 1 mm-resolved 3D images of pO₂ in the tissues and tumors of living animals. Current EPRI image reconstruction methods tend to be time consuming and preclude real-time visualization of information. Methods are presented to significantly accelerate the reconstruction process in order to enable real-time reconstruction of EPRI pO₂ images. These methods are image reconstruction using graphics processing unit (GPU)-based 3D filtered back-projection and lookup table parameter fitting. The combination of these methods leads to acceleration factors of over 650 compared to current methods and allows for real-time reconstruction of EPRI images of pO₂ in vivo.

Three-dimensional liver motion tracking using real-time two-dimensional MRI

PURPOSE

Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution.

METHODS

The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (or tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions.

RESULTS

Axial, sagittal, and coronal 2D MRI series yielded 3D respiratory motion curves for all volunteers. The motion directionality and amplitude were very similar when measured directly as in-plane motion or estimated indirectly as through-plane motion. The mean peak-to-peak breathing amplitude was 1.6 mm (left-right), 11.0 mm (craniocaudal), and 2.5 mm (anterior-posterior). The position of the watermelon structure was estimated in 2D MRI images with a root-mean-square error of 0.52 mm (in-plane) and 0.87 mm (through-plane).

CONCLUSIONS

A method for 3D tracking in 2D MRI series was developed and demonstrated for liver tracking in volunteers. The method would allow real-time 3D localization with integrated MR-Linac systems.

An augmented Lagrangian based compressed sensing reconstruction for non-Cartesian magnetic resonance imaging without gridding and regridding at every iteration

Background

Non-Cartesian trajectories are used in a variety of fast imaging applications, due to the incoherent image domain artifacts they create when undersampled. While the gridding technique is commonly utilized for reconstruction, the incoherent artifacts may be further removed using compressed sensing (CS). CS reconstruction is typically done using conjugate-gradient (CG) type algorithms, which require gridding and regridding to be performed at every iteration. This leads to a large computational overhead that hinders its applicability.

Methods

We sought to develop an alternative method for CS reconstruction that only requires two gridding and one regridding operation in total, irrespective of the number of iterations. This proposed technique is evaluated on phantom images and whole-heart coronary MRI acquired using 3D radial trajectories, and compared to conventional CS reconstruction using CG algorithms in terms of quantitative vessel sharpness, vessel length, computation time, and convergence rate.

Results

Both CS reconstructions result in similar vessel length (P = 0.30) and vessel sharpness (P = 0.62). The per-iteration complexity of the proposed technique is approximately 3-fold lower than the conventional CS reconstruction (17.55 vs. 52.48 seconds in C++). Furthermore, for in-vivo datasets, the convergence rate of the proposed technique is faster (60±13 vs. 455±320 iterations) leading to a ∼23-fold reduction in reconstruction time.

Conclusions

The proposed reconstruction provides images of similar quality to the conventional CS technique in terms of removing artifacts, but at a much lower computational complexity.

Spiral tissue phase velocity mapping in a breath-hold with non-cartesian SENSE

PURPOSE

Tissue phase velocity mapping (TPVM) is capable of reproducibly measuring regional myocardial velocities. However acquisition durations of navigator gated techniques are long and unpredictable while current breath-hold techniques have low temporal resolution. This study presents a spiral TPVM technique which acquires high resolution data within a clinically acceptable breath-hold duration.

METHODS

Ten healthy volunteers are scanned using a spiral sequence with temporal resolution of 24 ms and spatial resolution of 1.7 × 1.7 mm. Retrospective cardiac gating is used to acquire data over the entire cardiac cycle. The acquisition is accelerated by factors of 2 and 3 by use of non-Cartesian SENSE implemented on the Gadgetron GPU system resulting in breath-holds of 17 and 13 heartbeats, respectively. Systolic, early diastolic, and atrial systolic global and regional longitudinal, circumferential, and radial velocities are determined.

RESULTS

Global and regional velocities agree well with those previously reported. The two acceleration factors show no significant differences for any quantitative parameter and the results also closely match previously acquired higher spatial resolution navigator-gated data in the same subjects.

CONCLUSION

By using spiral trajectories and non-Cartesian SENSE high resolution, TPVM data can be acquired within a clinically acceptable breath-hold.

Image reconstruction: an overview for clinicians

Image reconstruction plays a critical role in the clinical use of magnetic resonance imaging (MRI). The MRI raw data is not acquired in image space and the role of the image reconstruction process is to transform the acquired raw data into images that can be interpreted clinically. This process involves multiple signal processing steps that each have an impact on the image quality. This review explains the basic terminology used for describing and quantifying image quality in terms of signal-to-noise ratio and point spread function. In this context, several commonly used image reconstruction components are discussed. The image reconstruction components covered include noise prewhitening for phased array data acquisition, interpolation needed to reconstruct square pixels, raw data filtering for reducing Gibbs ringing artifacts, Fourier transforms connecting the raw data with image space, and phased array coil combination. The treatment of phased array coils includes a general explanation of parallel imaging as a coil combination technique. The review is aimed at readers with no signal processing experience and should enable them to understand what role basic image reconstruction steps play in the formation of clinical images and how the resulting image quality is described.

Real-time imaging with radial GRAPPA: Implementation on a heterogeneous architecture for low-latency reconstructions

Combination of non-Cartesian trajectories with parallel MRI permits to attain unmatched acceleration rates when compared to traditional Cartesian MRI during real-time imaging. However, computationally demanding reconstructions of such imaging techniques, such as k-space domain radial generalized auto-calibrating partially parallel acquisitions (radial GRAPPA) and image domain conjugate gradient sensitivity encoding (CG-SENSE), lead to longer reconstruction times and unacceptable latency for online real-time MRI on conventional computational hardware. Though CG-SENSE has been shown to work with low-latency using a general purpose graphics processing unit (GPU), to the best of our knowledge, no such effort has been made for radial GRAPPA. Radial GRAPPA reconstruction, which is robust even with highly undersampled acquisitions, is not iterative, requiring only significant computation during initial calibration while achieving good image quality for low-latency imaging applications. In this work, we present a very fast, low-latency, reconstruction framework based on a heterogeneous system using multi-core CPUs and GPUs. We demonstrate an implementation of radial GRAPPA that permits reconstruction times on par with or faster than acquisition of highly accelerated datasets in both cardiac and dynamic musculoskeletal imaging scenarios. Acquisition and reconstruction times are reported.

Real-time magnetic resonance imaging technique for determining left ventricle pressure-volume loops

BACKGROUND

Rapid determination of the left ventricular (LV) pressure-volume (PV) relationship as loading conditions are varied is the gold standard for assessment of LV function. Cine magnetic resonance imaging (MRI) does not have sufficient spatiotemporal resolution to assess beat-to-beat changes of the LV PV relationship required to measure the LV end-systolic elastance (EES) or preload-recruitable stroke work (PRSW). Our aim was to investigate real-time MRI and semiautomated LV measurement of LV volume to measure PV relations in large animals under normal and inotropically stressed physiologic conditions.

METHODS

We determined that PV relationships could be accurately measured using an image exposure time Tex less than 100 ms and frame rate Tfr less than 50 ms at elevated heart rates (∼140 beats per minute) using a golden angle radial MRI k-space trajectory and active contour segmentation.

RESULTS

With an optimized exposure time (Tex=95 ms and frame rate Tfr=2.8 ms), we found that there was no significant difference between cine and real-time MRI at rest in end-diastolic volume, end-systolic volume, ejection fraction, stroke volume, or cardiac output (n=5, p<0.05) at either normal or elevated heart rates. We found EES increased from 1.9±0.7 to 3.1±0.3 mm Hg/mL and PRSW increased from 6.2±1.2 to 9.1±0.9 mm Hg during continuous intravenous dobutamine infusion (n=5, p<0.05).

CONCLUSIONS

Real-time MRI can assess LV volumes, EES, and PRSW at baseline and elevated inotropic states.

Medical image processing on the GPU - past, present and future

Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges.

More IMPATIENT: A Gridding-Accelerated Toeplitz-based Strategy for Non-Cartesian High-Resolution 3D MRI on GPUs

Several recent methods have been proposed to obtain significant speed-ups in MRI image reconstruction by leveraging the computational power of GPUs. Previously, we implemented a GPU-based image reconstruction technique called the Illinois Massively Parallel Acquisition Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI) for reconstructing data collected along arbitrary 3D trajectories. In this paper, we improve IMPATIENT by removing computational bottlenecks by using a gridding approach to accelerate the computation of various data structures needed by the previous routine. Further, we enhance the routine with capabilities for off-resonance correction and multi-sensor parallel imaging reconstruction. Through implementation of optimized gridding into our iterative reconstruction scheme, speed-ups of more than a factor of 200 are provided in the improved GPU implementation compared to the previous accelerated GPU code.

Self-navigated tissue phase mapping using a golden-angle spiral acquisition-proof of concept in patients with pulmonary hypertension

PURPOSE

To create a high temporal- and spatial-resolution retrospectively cardiac-gated, tissue phase mapping (TPM) sequence, using an image-based respiratory navigator calculated from the data itself.

METHODS

The sequence was based on a golden-angle spiral acquisition. Reconstruction of real-time images allowed creation of an image-based navigator. The expiratory spiral interleaves were then retrospectively cardiac-gated using data binning. TPM data were acquired in 20 healthy volunteers and 10 patients with pulmonary hypertension. Longitudinal and radial myocardial velocities were calculated in the left ventricle and right ventricle.

RESULTS

The image-based navigator was shown to correlate well with simultaneously acquired airflow data in 10 volunteers(r=0.93±0.04). The TPM navigated images had a significantly higher subjective image quality and edge sharpness (P<0.0001) than averaged spiral TPM. No significant differences in myocardial velocities were seen between conventional Cartesian TPM with navigator respiratory-gating and the proposed self-navigated TPM technique, in 10 volunteers. Significant differences in the velocities were seen between the volunteers and patients in the left ventricle at systole and end diastole and in the right ventricle at end diastole.

CONCLUSION

The feasibility of measuring myocardial motion using a golden-angle spiral TPM sequence was demonstrated, with an image-based respiratory navigator calculated from the TPM data itself.

Compressed sensing reconstruction for whole-heart imaging with 3D radial trajectories: a graphics processing unit implementation

A disadvantage of three-dimensional (3D) isotropic acquisition in whole-heart coronary MRI is the prolonged data acquisition time. Isotropic 3D radial trajectories allow undersampling of k-space data in all three spatial dimensions, enabling accelerated acquisition of the volumetric data. Compressed sensing (CS) reconstruction can provide further acceleration in the acquisition by removing the incoherent artifacts due to undersampling and improving the image quality. However, the heavy computational overhead of the CS reconstruction has been a limiting factor for its application. In this article, a parallelized implementation of an iterative CS reconstruction method for 3D radial acquisitions using a commercial graphics processing unit is presented. The execution time of the graphics processing unit-implemented CS reconstruction was compared with that of the C++ implementation, and the efficacy of the undersampled 3D radial acquisition with CS reconstruction was investigated in both phantom and whole-heart coronary data sets. Subsequently, the efficacy of CS in suppressing streaking artifacts in 3D whole-heart coronary MRI with 3D radial imaging and its convergence properties were studied. The CS reconstruction provides improved image quality (in terms of vessel sharpness and suppression of noise-like artifacts) compared with the conventional 3D gridding algorithm, and the graphics processing unit implementation greatly reduces the execution time of CS reconstruction yielding 34-54 times speed-up compared with C++ implementation.

Fast direct fourier reconstruction of radial and PROPELLER MRI data using the chirp transform algorithm on graphics hardware

PURPOSE

To develop and test a new algorithm for fast direct Fourier transform (DrFT) reconstruction of MR data on non-Cartesian trajectories composed of lines with equally spaced points.

THEORY AND METHODS

The DrFT, which is normally used as a reference in evaluating the accuracy of other reconstruction methods, can reconstruct images directly from non-Cartesian MR data without interpolation. However, DrFT reconstruction involves substantially intensive computation, which makes the DrFT impractical for clinical routine applications. In this article, the Chirp transform algorithm was introduced to accelerate the DrFT reconstruction of radial and Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI data located on the trajectories that are composed of lines with equally spaced points. The performance of the proposed Chirp transform algorithm-DrFT algorithm was evaluated by using simulation and in vivo MRI data.

RESULTS

After implementing the algorithm on a graphics processing unit, the proposed Chirp transform algorithm-DrFT algorithm achieved an acceleration of approximately one order of magnitude, and the speed-up factor was further increased to approximately three orders of magnitude compared with the traditional single-thread DrFT reconstruction.

CONCLUSION

Implementation the Chirp transform algorithm-DrFT algorithm on the graphics processing unit can efficiently calculate the DrFT reconstruction of the radial and PROPELLER MRI data.

Real-time MRI-guided right heart catheterization in adults using passive catheters

AIMS

Real-time MRI creates images with superb tissue contrast that may enable radiation-free catheterization. Simple procedures are the first step towards novel interventional procedures. We aim to perform comprehensive transfemoral diagnostic right heart catheterization in an unselected cohort of patients entirely using MRI guidance.

METHODS AND RESULTS

We performed X-ray and MRI-guided transfemoral right heart catheterization in consecutive patients undergoing clinical cardiac catheterization. We sampled both cavae and both pulmonary arteries. We compared success rate, time to perform key steps, and catheter visibility among X-ray and MRI procedures using air-filled or gadolinium-filled balloon-tipped catheters. Sixteen subjects (four with shunt, nine with coronary artery disease, three with other) underwent paired X-ray and MRI catheterization. Complete guidewire-free catheterization was possible in 15 of 16 under both. MRI using gadolinium-filled balloons was at least as successful as X-ray in all procedure steps, more successful than MRI using air-filled balloons, and better than both in entering the left pulmonary artery. Total catheterization time and individual procedure steps required approximately the same amount of time irrespective of image guidance modality. Catheter conspicuity was best under X-ray and next-best using gadolinium-filled MRI balloons.

CONCLUSION

In this early experience, comprehensive transfemoral right heart catheterization appears feasible using only MRI for imaging guidance. Gadolinium-filled balloon catheters were more conspicuous than air-filled ones. Further workflow and device enhancement are necessary for clinical adoption.

Fast l₁-SPIRiT compressed sensing parallel imaging MRI: scalable parallel implementation and clinically feasible runtime

We present l₁-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and compressed sensing (CS) that permits an efficient implementation with clinically-feasible runtimes. We propose a CS objective function that minimizes cross-channel joint sparsity in the wavelet domain. Our reconstruction minimizes this objective via iterative soft-thresholding, and integrates naturally with iterative self-consistent parallel imaging (SPIRiT). Like many iterative magnetic resonance imaging reconstructions, l₁-SPIRiT's image quality comes at a high computational cost. Excessively long runtimes are a barrier to the clinical use of any reconstruction approach, and thus we discuss our approach to efficiently parallelizing l₁-SPIRiT and to achieving clinically-feasible runtimes. We present parallelizations of l₁-SPIRiT for both multi-GPU systems and multi-core CPUs, and discuss the software optimization and parallelization decisions made in our implementation. The performance of these alternatives depends on the processor architecture, the size of the image matrix, and the number of parallel imaging channels. Fundamentally, achieving fast runtime requires the correct trade-off between cache usage and parallelization overheads. We demonstrate image quality via a case from our clinical experimentation, using a custom 3DFT spoiled gradient echo (SPGR) sequence with up to 8× acceleration via Poisson-disc undersampling in the two phase-encoded directions.

Retrospective reconstruction of high temporal resolution cine images from real-time MRI using iterative motion correction

Cardiac function has traditionally been evaluated using breath-hold cine acquisitions. However, there is a great need for free breathing techniques in patients who have difficulty in holding their breath. Real-time cardiac MRI is a valuable alternative to the traditional breath-hold imaging approach, but the real-time images are often inferior in spatial and temporal resolution. This article presents a general method for reconstruction of high spatial and temporal resolution cine images from a real-time acquisition acquired over multiple cardiac cycles. The method combines parallel imaging and motion correction based on nonrigid registration and can be applied to arbitrary k-space trajectories. The method is demonstrated with real-time Cartesian imaging and Golden Angle radial acquisitions, and the motion-corrected acquisitions are compared with raw real-time images and breath-hold cine acquisitions in 10 (N = 10) subjects. Acceptable image quality was obtained in all motion-corrected reconstructions, and the resulting mean image quality score was (a) Cartesian real-time: 2.48, (b) Golden Angle real-time: 1.90 (1.00-2.50), (c) Cartesian motion correction: 3.92, (d) Radial motion correction: 4.58, and (e) Breath-hold cine: 5.00. The proposed method provides a flexible way to obtain high-quality, high-resolution cine images in patients with difficulty holding their breath.

GPU computing in medical physics: a review

The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

Combined prospective and retrospective motion correction to relax navigator requirements

Prospective motion correction can prevent motion artifacts in magnetic resonance imaging of the brain. However, for high-resolution imaging, the technique relies on precise tracking of head motion. This precision is often limited by tracking noise, which leads to residual errors in the prospectively-corrected k-space data and artifacts in the image. This work shows that it is possible to estimate these tracking errors, and hence the true k-space sample locations, by applying a two-sided filter to the tracking data after imaging. A conjugate gradient reconstruction is compared to gridding as a means of using this information to retrospectively correct for the effects of the residual errors.