Parallel Imaging Approaches Research Articles

Joint MAPLE: Accelerated joint T1 and mapping with scan-specific self-supervised networks.

Quantitative MRI finds important applications in clinical and research studies. However, it is encoding intensive and may suffer from prohibitively long scan times. Accelerated MR parameter mapping techniques have been developed to help address these challenges. Here, an accelerated joint T1, , frequency and proton density mapping technique with scan-specific self-supervised network reconstruction is proposed to synergistically combine parallel imaging, model-based, and deep learning approaches to speed up parameter mapping. Proposed framework, Joint MAPLE, includes parallel imaging, signal modeling, and data consistency blocks which are optimized jointly in a combined loss function. A scan-specific self-supervised reconstruction is embedded into the framework, which takes advantage of multi-contrast data from a multi-echo, multi-flip angle, gradient echo acquisition. In comparison with parallel reconstruction techniques powered by low-rank methods, emerging scan specific networks, and model-based estimation approaches, the proposed framework reduces the reconstruction error in parameter maps by approximately two-fold on average at acceleration rates as high as R = 16 with uniform sampling. It can outperform evaluated parallel reconstruction techniques up to four-fold on average in the presence of challenging sub-sampling masks. It is observed that Joint MAPLE performs well at extreme acceleration rates of R = 25 and R = 36 with error values less than 20%. Joint MAPLE enables higher fidelity parameter estimation at high acceleration rates by synergistically combining parallel imaging and model-based parameter mapping and exploiting multi-echo, multi-flip angle datasets. Utilizing a scan-specific self-supervised reconstruction obviates the need for large data sets for training while improving the parameter estimation ability.

An ultra‐fast MRI protocol in dementia enabled by Wave‐CAIPI

AbstractBackgroundStructural brain imaging is essential for the diagnostic workup in dementia and for safety monitoring of disease modifying therapies. MRI has several advantages over other imaging techniques, but its use is limited by cost and availability. Reducing acquisition time holds the potential for its democratisation. We developed a prototype ultra‐fast MRI protocol based on an optimised 3D parallel imaging approach. Here we present the finalised version, developed using a qualitative and quantitative approach to optimisation.MethodIn this ongoing real‐world study, participants are sequentially recruited from the cognitive disorders' clinics of a tertiary centre. Patients due to have a standard 3T MRI scan as part of their diagnostic pathway are eligible. The standard‐of‐care protocol includes T1w, T2w, FLAIR and T2*/SWI sequences [scan time ∼18mins]. The prototype rapid protocol utilises Siemens work‐in‐progress 3D Wave‐CAIPI (Controlled Aliasing in Parallel Imaging) sequences, enabling a reduction in scan time of more than 60% (table 1). For qualitative analysis, scans (of 9 individuals) were reviewed by six raters and assessed side‐by‐side against the gold‐standard scan for diagnostic utility. For a quantitative analysis, volumes were calculated from T1w scans using the default cortical reconstruction and volumetric segmentation pipeline in FreeSurfer 7.3.2. Key volumes (e.g., deep grey matter, cortical grey matter, white matter) for each participant were compared between the two protocols. Independent visual QC was performed on T1w datasets by an experienced clinical trials team.ResultSide‐by‐side visual assessment results of 9 participants is shown in figure 1. For all sequences bar FLAIR, raters scored the ultra‐fast sequences of comparable image quality in at least 67% of cases. For quantitative analysis, 10 T1w sequence pairs were reviewed, with 1 clinical scan failing QC due to motion. Bland‐Altman analyses (figure 2.) comparing volumes between the clinical and ultra‐fast sequences show little bias.ConclusionOur preliminary results demonstrate that for most contrasts the ultra‐fast sequences are diagnostically non‐inferior and quantitatively equivalent to the clinical protocol both for diagnosis and for safety monitoring.

A 3-slice cardiac quantitative native and post-contrast T1 and T2 MRI protocol requiring only four BHs using a 72-channel receive array coil

IntroductionCurrent practice to obtain left ventricular (LV) native and post-contrast T1 and T2 comprises single-slice readouts with multiple breath-holds (BHs). We propose a multi-slice parallel-imaging approach with a 72-channel receive-array to reduce BHs and demonstrate this in healthy subjects and hypertrophic cardiomyopathy (HCM) patients.MethodsA T1/T2 phantom was scanned at 3 T using a 16-channel and a novel 72-channel coil to assess the impact of different coils and acceleration factors on relaxation times. 16–18 healthy participants (8 female, age 28.4 ± 5.1 years) and 3 HCM patients (3 male, age 55.3 ± 4.2 years) underwent cardiac-MRI with the 72-channel coil, using a Modified Look-Locker scan with a shared inversion pulse across 3 slices and a Gradient-Spin-Echo scan. Acceleration was done by sensitivity encoding (SENSE) with accelerations 2, 4, and 6. LV T1 and T2 values were analyzed globally, per slice, and in 16 segments, with SENSE = 2 as the reference.ResultsThe phantom scans revealed no bias between coils and acceleration factors for T1 or T2, except for T2 with SENSE = 2, which resulted in a bias of 8.0 ± 6.7 ms (p < 0.001) between coils. SENSE = 4 and 6 enabled T1 mapping of three slices in a single BH, and T2 mapping of three slices within two BHs. In healthy subjects, T1 and T2 values varied. We found an average overestimation of T1 in 3 slices of 25 ± 87 ms for SENSE = 4 and 30 ± 103 ms using SENSE = 6, as compared to SENSE = 2. Acceleration resulted in decreased signal-to-noise; however, visually insignificant and without increased incidence of SENSE-artifacts. T2 was overestimated by 2.1 ± 5.0 ms for SENSE = 4 and 6.4 ± 9.7 ms using SENSE = 6, as compared to SENSE = 2. Native and post-contrast T1 measurements with SENSE = 4 and ECV quantification in HCM patients was successful.ConclusionThe 72-channel receiver-array coil with SENSE = 4 and 6, enabled LV-tissue characterization in three slices. Pre- and post-contrast T1 maps were obtained in a single BH, while T2 required two BHs.

The advantages of radial trajectories for vessel-selective dynamic angiography with arterial spin labeling

ObjectivesTo demonstrate the advantages of radial k-space trajectories over conventional Cartesian approaches for accelerating the acquisition of vessel-selective arterial spin labeling (ASL) dynamic angiograms, which are conventionally time consuming to acquire.Materials and methodsVessel-encoded pseudocontinuous ASL was combined with time-resolved balanced steady-state free precession (bSSFP) and spoiled gradient echo (SPGR) readouts to obtain dynamic vessel-selective angiograms arising from the four main brain-feeding arteries. Dynamic 2D protocols with acquisition times of one minute or less were achieved through radial undersampling or a Cartesian parallel imaging approach. For whole-brain dynamic 3D imaging, magnetic field inhomogeneity and the high acceleration factors required rule out the use of bSSFP and Cartesian trajectories, so the feasibility of acquiring 3D radial SPGR angiograms was tested.ResultsThe improved SNR efficiency of bSSFP over SPGR was confirmed for 2D dynamic imaging. Radial trajectories had considerable advantages over a Cartesian approach, including a factor of two improvements in the measured SNR (p < 0.00001, N = 6), improved distal vessel delineation and the lack of a need for calibration data. The 3D radial approach produced good quality angiograms with negligible artifacts despite the high acceleration factor (R = 13).ConclusionRadial trajectories outperform conventional Cartesian techniques for accelerated vessel-selective ASL dynamic angiography.

ENLIVE: An Efficient Nonlinear Method for Calibrationless and Robust Parallel Imaging

Robustness against data inconsistencies, imaging artifacts and acquisition speed are crucial factors limiting the possible range of applications for magnetic resonance imaging (MRI). Therefore, we report a novel calibrationless parallel imaging technique which simultaneously estimates coil profiles and image content in a relaxed forward model. Our method is robust against a wide class of data inconsistencies, minimizes imaging artifacts and is comparably fast, combining important advantages of many conceptually different state-of-the-art parallel imaging approaches. Depending on the experimental setting, data can be undersampled well below the Nyquist limit. Here, even high acceleration factors yield excellent imaging results while being robust to noise and the occurrence of phase singularities in the image domain, as we show on different data. Moreover, our method successfully reconstructs acquisitions with insufficient field-of-view. We further compare our approach to ESPIRiT and SAKE using spin-echo and gradient echo MRI data from the human head and knee. In addition, we show its applicability to non-Cartesian imaging on radial FLASH cardiac MRI data. Using theoretical considerations, we show that ENLIVE can be related to a low-rank formulation of blind multi-channel deconvolution, explaining why it inherently promotes low-rank solutions.

Accelerated magnetic resonance fingerprinting using soft-weighted key-hole (MRF-SOHO).

ObjectTo develop a novel approach for highly accelerated Magnetic Resonance Fingerprinting (MRF) acquisition.Materials and methodsThe proposed method combines parallel imaging, soft-gating and key-hole approaches to highly accelerate MRF acquisition. Slowly varying flip angles (FA), commonly used during MRF acquisition, lead to a smooth change in the signal contrast of consecutive time-point images. This assumption enables sharing of high frequency data between different time-points, similar to what is done in some dynamic MR imaging methods such as key-hole. The proposed approach exploits this information using a SOft-weighted key-HOle (MRF-SOHO) reconstruction to achieve high acceleration factors and/or increased resolution without compromising image quality or increasing scan time. MRF-SOHO was validated on a standard T1/T2 phantom and in in-vivo brain acquisitions reconstructing T1, T2 and proton density parametric maps.ResultsAccelerated MRF-SOHO using less data per time-point and less time-point images enabled a considerable reduction in scan time (up to 4.6x), while obtaining similar T1 and T2 accuracy and precision when compared to zero-filled MRF reconstruction. For the same number of spokes and time-points, the proposed method yielded an enhanced performance in quantifying parameters than the zero-filled MRF reconstruction, which was verified with 2, 1 and 0.7 (sub-millimetre) resolutions.ConclusionThe proposed MRF-SOHO enabled a 4.6x scan time reduction for an in-plane spatial resolution of 2x2 mm2 when compared to zero-filled MRF and enabled sub-millimetric (0.7x0.7 mm2) resolution MRF.

3D hyperpolarized C-13 EPI with calibrationless parallel imaging

With the translation of metabolic MRI with hyperpolarized 13C agents into the clinic, imaging approaches will require large volumetric FOVs to support clinical applications. Parallel imaging techniques will be crucial to increasing volumetric scan coverage while minimizing RF requirements and temporal resolution. Calibrationless parallel imaging approaches are well-suited for this application because they eliminate the need to acquire coil profile maps or auto-calibration data. In this work, we explored the utility of a calibrationless parallel imaging method (SAKE) and corresponding sampling strategies to accelerate and undersample hyperpolarized 13C data using 3D blipped EPI acquisitions and multichannel receive coils, and demonstrated its application in a human study of [1-13C]pyruvate metabolism.

Key clinical benefits of neuroimaging at 7 T

The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.

A combined Compressed Sensing Super-Resolution Diffusion and gSlider-SMS acquisition/reconstruction for rapid sub-millimeter whole-brain diffusion imaging.

Event Abstract Back to Event A combined Compressed Sensing Super-Resolution Diffusion and gSlider-SMS acquisition/reconstruction for rapid sub-millimeter whole-brain diffusion imaging. Kawin Setsompop1, Lipeng Ning2 and Yogesh Rathi2* 1 Harvard Medical School, Massachusetts General Hospital, United States 2 Harvard Medical School, Brigham and Women’s Hospital, United States Purpose: Submillimeter isotropic diffusion imaging (DI) is made difficult by long acquisition time and low SNR. Slider-SMS acquisition (1) has recently been proposed to provide large improvement to SNR efficiency for DI, by allowing a large number of imaging slices to be acquire simultaneously through the combined use of SMS parallel imaging and super-resolution approaches. Further improvement to this acquisition with a new generalized Slider approach (gSlider) is also being proposed (2), which utilizes RF encoding to improve the orthogonality of the slice-encoding basis for super-resolution, to enable high quality 5 simultaneous slice super-resolution, which when combines with SMS parallel imaging can achieve highly efficient 10 simultaneous slices DI (gSlider x MB = 5x2). In this work, we provide further improvement to this acquisition by incorporating the framework of Compressed Sensing for Super-Resolution Diffusion (CS-RSD) proposed in (3) to gSlider-SMS. This enables acquisition acceleration through undersampling of the gSlider slice-encoded super-resolution acquisitions needed for super-resolution reconstruction of each diffusion direction (with different random undersampling for different diffusion directions). Such acquisition undersampling is made possible through sparsity enforce reconstruction where the diffusion signal in each voxel of the final high-resolution image is enforced to be sparse in the basis of spherical ridgelets. We demonstrate that the incorporation of the CS-RSD approach enables a further 3x? efficiency gain to an already highly efficient 10 simultaneous slice gSlider-SMS acquisition. This permits, for the first time, high quality 860um whole-brain DI at high b-value to be perform in a relevant clinical timeframe of 8 minutes. Method: gSlider-SMS data with 10 simultaneous slice acquisition (gSlider×MB = 5×2) were acquired in a healthy volunteer on the 3T CONNECTOM system using custom-built 64-channel array. Imaging parameters were: 860μm iso; FOV 220×163.4×130 mm3; p.f. 6/8; TE = 64ms and TR per thick-slice volume = 4.2s; effective echo spacing = 0.32ms, 64 directions at b=2000 s/mm2 with interspersed b0 every 10 volumes, where for each diffusion direction, imaging were performed 5 times for different RF gSlider encoding, total scan-time ~25 min. Background phase removal was performed using real value diffusion algorithm (6). Reconstruction for full sampled Slider encoding data were performed using Tikhonov regularized super-resolution reconstruction to represent fullysampled acquisition for comparison. For incorporation of CS-RSD, the 5 different gSlider slice-encode imaging per diffusion direction were randomly undersampled to provide three times acceleration to result in an effective acquisition time of ~8 min. This accelerated acquisition is reconstructed using algorithm proposed in (3) and compared with the fully sampled reconstruction. Results: Figure (1) shows the acquired thick-slice images and the reconstructed high-resolution diffusion-weighted images obtained using the Tikhonov regularization and the compressed-sensing approach, respectively. The high-resolution image obtained using the compressed-sensing approach has the lowest noise level due to the sparse representation using spherical ridgelets. Figure (2) shows the corresponding colored-coded diffusion tensor images for the three diffusion MRI volumes, respectively.

Evaluation of cartilage repair and osteoarthritis with sodium MRI.

The growing need for early diagnosis and higher specificity than that which can be achieved with morphological MRI is a driving force in the application of methods capable of probing the biochemical composition of cartilage tissue, such as sodium imaging. Unlike morphological imaging, sodium MRI is sensitive to even small changes in cartilage glycosaminoglycan content, which plays a key role in cartilage homeostasis. Recent advances in high- and ultrahigh-field MR systems, gradient technology, phase-array radiofrequency coils, parallel imaging approaches, MRI acquisition strategies and post-processing developments have resulted in many clinical in vivo sodium MRI studies of cartilage, even at 3 T. Sodium MRI has great promise as a non-invasive tool for cartilage evaluation. However, further hardware and software improvements are necessary to complete the translation of sodium MRI into a clinically feasible method for 3-T systems. This review is divided into three parts: (i) cartilage composition, pathology and treatment; (ii) sodium MRI; and (iii) clinical sodium MRI studies of cartilage with a focus on the evaluation of cartilage repair tissue and osteoarthritis.

High resolution myocardial first-pass perfusion imaging with extended anatomic coverage

To evaluate and to compare Parallel Imaging and Compressed Sensing acquisition and reconstruction frameworks based on simultaneous multislice excitation for high resolution contrast-enhanced myocardial first-pass perfusion imaging with extended anatomic coverage. The simultaneous multislice imaging technique MS-CAIPIRINHA facilitates imaging with significantly extended anatomic coverage. For additional resolution improvement, equidistant or random undersampling schemes, associated with corresponding reconstruction frameworks, namely Parallel Imaging and Compressed Sensing can be used. By means of simulations and in vivo measurements, the two approaches were compared in terms of reconstruction accuracy. Comprehensive quality metrics were used, identifying statistical and systematic reconstruction errors. The quality measures applied allow for an objective comparison of the frameworks. Both approaches provide good reconstruction accuracy. While low to moderate noise enhancement is observed for the Parallel Imaging approach, the Compressed Sensing framework is subject to systematic errors and reconstruction induced spatiotemporal blurring. Both techniques allow for perfusion measurements with a resolution of 2.0 × 2.0 mm(2) and coverage of six slices every heartbeat. Being not affected by systematic deviations, the Parallel Imaging approach is considered to be superior for clinical studies.

Design of k‐space channel combination kernels and integration with parallel imaging

In this work, a new method is described for producing local k-space channel combination kernels using a small amount of low-resolution multichannel calibration data. Additionally, this work describes how these channel combination kernels can be combined with local k-space unaliasing kernels produced by the calibration phase of parallel imaging methods such as GRAPPA, PARS and ARC. Experiments were conducted to evaluate both the image quality and computational efficiency of the proposed method compared to a channel-by-channel parallel imaging approach with image-space sum-of-squares channel combination. Results indicate comparable image quality overall, with some very minor differences seen in reduced field-of-view imaging. It was demonstrated that this method enables a speed up in computation time on the order of 3-16X for 32-channel data sets. The proposed method enables high quality channel combination to occur earlier in the reconstruction pipeline, reducing computational and memory requirements for image reconstruction.

Slice accelerated diffusion‐weighted imaging at ultra‐high field strength

Diffusion magnetic resonance imaging (dMRI) data with very high isotropic resolution can be obtained at 7T. However, for extensive brain coverage, a large number of slices is required, resulting in long acquisition times (TAs). Recording multiple slices simultaneously (SMS) promises to reduce the TA. A combination of zoomed and parallel imaging is used to achieve high isotropic resolution dMRI data with a low level of distortions at 7T. The blipped-CAIPI (controlled aliasing in parallel imaging) approach is used to acquire several slices simultaneously. Due to their high radiofrequency (RF) power deposition and ensuing specific absorption rate (SAR) constraints, the commonly used multiband (MB) RF pulses for SMS imaging are inefficient at 7T and entail long repetition times, counteracting the usefulness of SMS acquisitions. To address this issue, low SAR multislice Power Independent of Number of Slices RF pulses are employed. In vivo dMRI results with and without SMS acceleration are presented at different isotropic spatial resolutions at ultra high field strength. The datasets are recorded at a high angular resolution to detect fiber crossings. From the results and compared with earlier studies at these resolutions, it can be seen that scan time is significantly reduced, while image quality is preserved.

MR spectroscopic imaging: Principles and recent advances

MR spectroscopic imaging (MRSI) has become a valuable tool for quantifying metabolic abnormalities in human brain, prostate, breast and other organs. It is used in routine clinical imaging, particularly for cancer assessment, and in clinical research applications. This article describes basic principles of commonly used MRSI data acquisition and analysis methods and their impact on clinical applications. It also highlights technical advances, such as parallel imaging and newer high-speed MRSI approaches that are becoming viable alternatives to conventional MRSI methods. Although the main focus is on (1) H-MRSI, the principles described are applicable to other MR-compatible nuclei. This review of the state-of-the-art in MRSI methodology provides a framework for critically assessing the clinical utility of MRSI and for defining future technical development that is expected to lead to increased clinical use of MRSI. Future technical development will likely focus on ultra-high field MRI scanners, novel hyperpolarized contrast agents using metabolically active compounds, and ultra-fast MRSI techniques because these technologies offer unprecedented sensitivity and specificity for probing tissue metabolic status and dynamics.

Cardiac proton spectroscopy using large coil arrays

Large coil arrays are widely used in clinical routine for cardiovascular imaging providing extended spatial coverage and enabling accelerated acquisition using parallel imaging approaches. This work investigates the use of large coil arrays in single-voxel cardiac spectroscopy for the detection of myocardial creatine and triglyceride content. For this purpose, a navigator-gated and cardiac-triggered point-resolved spectroscopy sequence was implemented, and data obtained in 11 healthy volunteers using 32- and 5-element coil arrays were compared. For combination of the individual coil element signals, four strategies were evaluated differing in the manner of estimation of the complex coil weights and the amount of additional information required for coil combination. In all volunteers, and with both the 32- and 5-channel coil arrays, triglyceride-to-water (0.44 ± 0.19% and 0.45 ± 0.17%) and total creatine-to-water (0.05 ± 0.02% and 0.05 ± 0.01%) contents were computed. The values were found to agree well, showing an intraclass correlation coefficient of 0.76 (p < 0.003). The results revealed a gain in signal-to-noise ratio of approximately 24% with the 32-channel coil relative to the 5-channel array. The findings may foster the integration of cardiac spectroscopy into clinical practice using large coil arrays, provided that appropriate reconstruction algorithms are implemented.

A parallel imaging approach to wide-field MR microscopy

Magnetic resonance microscopy, suggested in the earliest papers on MRI, has always been limited by the low signal-to-noise ratio resulting from the small voxel size. Magnetic resonance microscopy has largely been enabled by the use of microcoils that provide the signal-to-noise ratio improvement required to overcome this limitation. Concomitant with the small coils is a small field-of-view, which limits the use of magnetic resonance microscopy as a histological tool or for imaging large regions in general. This article describes initial results in wide field-of-view magnetic resonance microscopy using a large array of narrow, parallel coils, which provides a signal-to-noise ratio enhancement as well as the ability to use parallel imaging techniques. Comparison images made between a volume coil and the proposed technique demonstrate reductions in imaging time of more than 100 with no loss in signal-to-noise ratio or resolution.

Comparison of k‐t SENSE/k‐t BLAST with conventional SENSE applied to BOLD fMRI

To compare k-t BLAST (broad-use linear-acquisition speedup technique)/k-t SENSE (sensitivity encoding) with conventional SENSE applied to a simple fMRI paradigm. Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) was performed at 3 T using a displaced ultra-fast low-angle refocused echo (UFLARE) pulse sequence with a visual stimulus in a block paradigm. Conventional SENSE and k-t BLAST/k-t SENSE data were acquired. Also, k-t BLAST/k-t SENSE was simulated at different undersampling factors from fully sampled data after removal of lines of k-space data. Analysis was performed using SPM5. Sensitivity to the BOLD response in k-t BLAST/k-t SENSE was comparable with that of SENSE in images acquired at an undersampling factor of 2.3. Simulated k-t BLAST/k-t SENSE yielded reliable detection of activation-induced BOLD contrast at undersampling factors of 5 or less. Sensitivity increased significantly when training data were included in k-space before Fourier transformation (known as "plug-in"). k-t BLAST/k-t SENSE performs at least as well as conventional SENSE for BOLD fMRI at a modest undersampling factor. Results suggest that sufficient sensitivity to BOLD contrast may be achievable at higher undersampling factors with k-t BLAST/k-t SENSE than with conventional parallel imaging approaches, offering particular advantages at the highest magnetic field strengths.

Multiplexed Analysis of Proteins in Tissue Using Multispectral Fluorescence Imaging

We present a new application of multispectral analysis for subcellular measurement of multiple proteins in formalin-fixed paraffin embedded tissue and cells. Typically, the targets of interest are present in the same or spatially overlapping cellular compartments. Such co-localization can complicate analysis and interpretation of the images obtained using traditional fluorescence, especially when spectrally overlapping labels are present. The spectral properties of currently available fluorescent dyes set an upper limit to the number of molecules that can be detected simultaneously with traditional fluorescence. By exciting a set of fluorophores at the same wavelength and unmixing their emission signals from background autofluorescence, we were able to image three targets in a single channel. This parallel imaging approach provides significant advantages for multiplexed analysis of tissues and cells.

Ghost artifact removal using a parallel imaging approach

Parallel imaging techniques, which use several receive coils simultaneously, have been shown to enable a significant scan time reduction by subsampling k-space. Nevertheless, the data acquired with multiple coils in parallel exhibit some redundancy if the number of receive coils exceeds the subsampling factor. This redundancy leads to an overdetermination of the reconstruction problem, which is generally used to optimize the signal-to-noise ratio (SNR). However, it can yield further information about the quality of the reconstructed image, and can thus be used to identify and correct image artifacts. While some known approaches try to solve this problem in k-space, this study addresses it in the spatial domain and uses a modified SENSE reconstruction to reduce or completely remove ghost-type artifacts arising from processes such as motion or flow during data acquisition. Phantom and in vivo studies show significant improvements in image quality after correction, and serve as a basis for the discussion of the performance and limitations of this new approach.

3Parallel magnetic resonance imaging with adaptive radius in k‐space (PARS): Constrained image reconstruction using k‐space locality in radiofrequency coil encoded data

A parallel image reconstruction algorithm is presented that exploits the k-space locality in radiofrequency (RF) coil encoded data. In RF coil encoding, information relevant to reconstructing an omitted datum rapidly diminishes as a function of k-space separation between the omitted datum and the acquired signal data. The proposed method, parallel magnetic resonance imaging with adaptive radius in k-space (PARS), harnesses this physical property of RF coil encoding via a sliding-kernel approach. Unlike generalized parallel imaging approaches that might typically involve inverting a prohibitively large matrix for arbitrary sampling trajectories, the PARS sliding-kernel approach creates manageable and distributable independent matrices to be inverted, achieving both computational efficiency and numerical stability. An empirical method designed to measure total error power is described, and the total error power of PARS reconstructions is studied over a range of k-space radii and accelerations, revealing "minimal-error" conditions at comparatively modest k-space radii. PARS reconstructions of undersampled in vivo Cartesian and non-Cartesian data sets are shown and are compared selectively with traditional SENSE reconstructions. Various characteristics of the PARS k-space locality constraint (such as the tradeoff between signal-to-noise ratio and artifact power and the relationship with iterative parallel conjugate gradient approaches or nonparallel gridding approaches) are discussed.