Sliding Window Reconstruction Research Articles

Reconstruction of multi-phase parametric maps in 4D-magnetic resonance fingerprinting (4D-MRF) by optimization of local T1 and T2 sensitivities.

Time-resolved magnetic resonance fingerprinting (MRF), or 4D-MRF, has been demonstrated its feasibility in motion management in radiotherapy (RT). However, the prohibitive long acquisition time is one of challenges of the clinical implementation of 4D-MRF. The shortening of acquisition time causes data insufficiency in each respiratory phase, leading to poor accuracies and consistencies of the predicted tissues' properties of each phase. To develop a technique for the reconstruction of multi-phase parametric maps in four-dimensional magnetic resonance fingerprinting (4D-MRF) through the optimization of local T1 and T2 sensitivities. The proposed technique employed an iterative optimization to tailor the data arrangement of each phase by manipulation of inter-phase frames, such that the T1 and T2 sensitivities, which were quantified by the modified Minkowski distance, of the truncated signal evolution curve was maximized. The multi-phase signal evolution curves were modified by sliding window reconstruction and inter-phase frame sharing (SWIFS). Motion correction (MC) and dot product matching were sequentially performed on the modified signal evolution and dictionary to reconstruct the multi-parametric maps. The proposed technique was evaluated by numerical simulations using the extended cardiac-torso (XCAT) phantom with regular and irregular breathing patterns, and by in vivo MRF data of three health volunteers and six liver cancer patients acquired at a 3.0 T scanner. In simulation study, the proposed SWIFS approach achieved the overall mean absolute percentage error (MAPE) of 8.62%±1.59% and 16.2%±3.88% for the eight-phases T1 and T2 maps, respectively, in the sagittal view with irregular breathing patterns. In contrast, the overall MAPE of T1 and T2 maps generated by the conventional approach with multiple MRF repetitions were 22.1%±11.0% and 30.8%±14.9%, respectively. For in-vivo study, the predicted mean T1 and T2 of liver by the proposed SWIFS approach were 795ms±38.9ms and 58.3ms±11.7ms, respectively. Both simulation and in vivo results showed that the approach empowered by T1 and T2 sensitivities optimization and sliding window under the shortened acquisition of MRF had superior performance in the estimation of multi-phase T1 and T2 maps as compared to the conventional approach with oversampling of MRF data.

Nonuniform sliding-window reconstruction for accelerated dual contrast agent quantification with MR fingerprinting

ObjectiveMR fingerprinting (MRF) can enable preclinical studies of cell tracking by quantifying multiple contrast agents simultaneously, but faster scan times are required for in vivo applications. Sliding window (SW)-MRF is one option for accelerating MRF, but standard implementations are not sufficient to preserve the accuracy of T2*, which is critical for tracking iron-labelled cells in vivo.PurposeTo develop a SW approach to MRF which preserves the T2* accuracy required for accelerated concentration mapping of iron-labelled cells on single-channel preclinical systems.MethodsA nonuniform SW was applied to the MRF sequence and dictionary. Segments of the sequence most sensitive to T2* were subject to a shorter window length, preserving the T2* sensitivity. Phantoms containing iron-labelled CD8+ T cells and gadolinium were used to compare 24× undersampled uniform and nonuniform SW-MRF parameter maps. Dual concentration maps were generated for both uniform and nonuniform MRF and compared.ResultsLin’s concordance correlation coefficient, compared to gold standard parameter values, was much greater for nonuniform SW-MRF than for uniform SW-MRF. A Wilcoxon signed-rank test showed no significant difference between nonuniform SW-MRF and gold standards. Nonuniform SW-MRF outperformed the uniform SW-MRF concentration maps for all parameters, providing a balance between T2* sensitivity of short window lengths, and SNR of longer window lengths.ConclusionsNonuniform SW-MRF improves the accuracy of matching compared to uniform SW-MRF, allowing higher accelerated concentration mapping for preclinical systems.

Deep-learning accelerated super-resolution radial fluctuations (SRRF) enables real-time live cell imaging

The Super-resolution radial fluctuations (SRRF) algorithm analyzes radial and temporal fluorescence intensity fluctuations in an image sequence, which typically includes tens or hundreds of raw images to generate one super-resolution image. At present, most of the SRRF applications rely on large amounts of raw images or tedious post-processing and computation, thus are not feasible for real-time live cell super-resolution imaging. Here, we developed a novel deep learning accelerated SRRF method, which significantly reduced the requirement of raw images for super-resolution reconstruction. Our results showed that by using only 5 low signal-to-noise ratio (SNR) images, we were able to achieve super-resolution SRRF reconstruction to a comparable resolution as the traditional method. We demonstrated that by integration of GPU computing and the sliding window reconstruction method, the dynamic contraction of microtubules and the interactions between microtubules and clathrin-coated pits (CCPs) can be visualized in real-time with super-resolution. In summary, we established the deep learning accelerated SRRF method, which permits real-time, long-term and multi-color live cell super-resolution imaging, and we anticipate it will have vast biomedical applications.

Dynamic lung water MRI during exercise stress.

Exercise-induced dyspnea caused by lung water is an early heart failure symptom. Dynamic lung water quantification during exercise is therefore of interest to detect early stage disease. This study developed a time-resolved 3D MRI method to quantify transient lung water dynamics during rest and exercise stress. The method was evaluated in 15 healthy subjects and 2 patients with heart failure imaged in transitions between rest and exercise, and in a porcine model of dynamic extravascular lung water accumulation through mitral regurgitation (n = 5). Time-resolved images were acquired at 0.55T using a continuous 3D stack-of-spirals proton density weighted sequence with 3.5 mm isotropic resolution, and derived using a motion corrected sliding-window reconstruction with 90-s temporal resolution in 20-s increments. A supine MRI-compatible pedal ergometer was used for exercise. Global and regional lung water density (LWD) and percent change in LWD (ΔLWD) were automatically quantified. A ΔLWD increase of 3.3 ± 1.5% was achieved in the animals. Healthy subjects developed a ΔLWD of 7.8 ± 5.0% during moderate exercise, peaked at 16 ± 6.8% during vigorous exercise, and remained unchanged over 10 min at rest (-1.4 ± 3.5%, p = 0.18). Regional LWD were higher posteriorly compared the anterior lungs (rest: 33 ± 3.7% vs 20 ± 3.1%, p < 0.0001; peak exercise: 36 ± 5.5% vs 25 ± 4.6%, p < 0.0001). Accumulation rates were slower in patients than healthy subjects (2.0 ± 0.1%/min vs 2.6 ± 0.9%/min, respectively), whereas LWD were similar at rest (28 ± 10% and 28 ± 2.9%) and peak exercise (ΔLWD 17 ± 10% vs 16 ± 6.8%). Lung water dynamics can be quantified during exercise using continuous 3D MRI and a sliding-window image reconstruction.

Motion-resolved and free-breathing liver MRF

PurposeTo develop a motion-resolved and free-breathing liver magnetic resonance fingerprinting (MRF) protocol. MethodsThe deformation maps were obtained from the first singular image of MRF data. The reconstruction method enforced the consistency of the MRF data with the deformation maps by adding the deformation maps to the encoding matrix. A sliding window reconstruction was inherently assumed, with a window size of 60 repetition times (TRs) and a step size of 30 TRs. L1 wavelet regularization was applied to reduce the undersampling artifact. MRF was tested on four healthy volunteers with parameters: 13 s/slice, 0.39 s/frame, and 33 time frames/slice. ResultsFor measuring the accuracy of the deformation map, the typical normalized root mean square error (NRMSE) of the first singular image after motion correction was 0.19. In the sagittal scan, the liver T1 and T2 were 808.7±96.8 ms and 52.7±11.6 ms, respectively. They agreed with our previously reported values, i.e., T1 = 759 ms and T2 = 51 ms at 3 T, using free-breathing liver MRF. Compared to breath-hold MRF, the NRMSEs for T1 and T2 maps (without considering vessel pixels) from the proposed method were 0.13 and 0.18, respectively. ConclusionWe demonstrated a motion-resolved MRF with a nominal frame rate of 2.5 Hz for free-breathing liver imaging.

Free-Breathing Phase-Resolved Oxygen-Enhanced Pulmonary MRI Based on 3D Stack-of-Stars UTE Sequence.

Compared with hyperpolarized noble gas MRI, oxygen-enhanced lung imaging is a cost-effective approach to investigate lung function. In this study, we investigated the feasibility of free-breathing phase-resolved oxygen-enhanced pulmonary MRI based on a 3D stack-of-stars ultra-short echo time (UTE) sequence. We conducted both computer simulation and in vivo experiments and calculated percent signal enhancement maps of four different respiratory phases on four healthy volunteers from the end of expiration to the end of inspiration. The phantom experiment was implemented to verify simulation results. The respiratory phase was segmented based on the extracted respiratory signal and sliding window reconstruction, providing phase-resolved pulmonary MRI. Demons registration algorithm was applied to compensate for respiratory motion. The mean percent signal enhancement of the average phase increases from anterior to posterior region, matching previous literature. More details of pulmonary tissues were observed on post-oxygen inhalation images through the phase-resolved technique. Phase-resolved UTE pulmonary MRI shows the potential as a valuable method for oxygen-enhanced MRI that enables the investigation of lung ventilation on middle states of the respiratory cycle.

Three dimensional radial echo planar imaging for functional MRI.

To demonstrate a novel 3D radial echo planar imaging (3D REPI) sequence for flexible, rapid, and motion-robust sampling in fMRI. The 3D REPI method expands on the recently described golden angle rotated EPI trajectory using radial batched internal navigator echoes (TURBINE) approach by exploiting the unused perpendicular direction in the EPI readout to form fast analogues of rotated stack of stars or spirals trajectories that cover all 3 dimensions of k-space. An iterative conjugate gradient algorithm with SENSE reconstruction and time-segmented non-uniform fast Fourier transform (FFT) was used for parallel imaging acceleration and to account for the effects of B0 inhomogeneity. The golden angle rotation allowed for sliding window reconstruction schemes to be applied in brain BOLD fMRI experiments. Combined whole brain visual and motor fMRI experiments were successfully carried out on a clinical 3T scanner at 2 mm isotropic and 1 × 1 × 2 mm3 resolutions using the 3D REPI design. Improved sampling characteristics and image quality were observed for twisted trajectories at the expense of prolonged readout times and off-resonance effects. The ability to correct for rigid motion correction was also demonstrated. 3D REPI presents a flexible approach for segmented volumetric fMRI with motion correction and high in-plane spatial resolutions. Improved BOLD fMRI brain activation maps were obtained using a sliding window reconstruction.

Improvement of sensitivity and specificity for laminar BOLD fMRI with double spin-echo EPI in humans at 7 T

Mapping mesoscopic cortical functional units such as columns or laminae is increasingly pursued by ultra-high field (UHF) functional magnetic resonance imaging (fMRI). The most popular approach for high-resolution fMRI is currently gradient-echo (GE) blood oxygenation level-dependent (BOLD) fMRI. However, its spatial accuracy is reduced due to its sensitivity to draining vessels, including pial veins, whereas spin-echo (SE) BOLD signal is expected to have higher spatial accuracy, albeit with lower sensitivity than the GE-BOLD signal. Here, we introduce a new double spin-echo (dSE) echo-planar imaging (EPI) method to improve the sensitivity of SE-BOLD contrast by averaging two spin-echoes using three radiofrequency pulses. Human fMRI experiments were performed with slices perpendicular to the central sulcus between motor and sensory cortices at 7 T during fist-clenching with touching. First, we evaluated the feasibility of single-shot dSE-EPI for BOLD fMRI with 1.5 mm isotropic resolution and found that dSE-BOLD fMRI has higher signal-to-noise ratio (SNR), temporal SNR (tSNR), and higher functional sensitivity than conventional SE-BOLD fMRI. Second, to investigate the laminar specificity of dSE-BOLD fMRI, we implemented a multi-shot approach to achieve 0.8-mm isotropic resolution with sliding-window reconstruction. Unlike GE-BOLD fMRI, the cortical profile of dSE-BOLD fMRI peaked at ~ 1.0 mm from the surface of the primary motor and sensory cortices, demonstrating an improvement of laminar specificity in humans over GE-BOLD fMRI. The proposed multi-shot dSE-EPI method is viable for high spatial resolution UHF-fMRI studies in the pursuit of resolving mesoscopic functional units.

Comparison of contrast-enhanced videofluoroscopy to unenhanced dynamic MRI in minor patients following surgical correction of velopharyngeal dysfunction.

To compare dynamic magnetic resonance imaging (MRI) with videofluoroscopy (VFS) regarding image quality and assessment of gap size between soft palate (SP) and posterior pharyngeal wall (PPW) in children and adolescents following surgical correction of velopharyngeal dysfunction (VPD). Twenty-one patients undergoing unenhanced 3-T MRI and contrast-enhanced VFS were included in this IRB-approved prospective study. The MRI scan protocol comprised refocused gradient-echo sequences in transverse and sagittal planes during speech, with TE 1.97ms, TR 3.95ms, flip angle 8°, matrix size 128 × 128, and 5-mm slice thickness. Radial k-space sampling and sliding window reconstruction were used to achieve an image acquisition rate of 28 frames per second (fps). VFS with 30 fps was similarly performed in both planes. Closure of the velopharyngeal port during phonation was evaluated by two experienced radiologists. Eleven (52.4%) patients displayed a complete closure, whereas ten (47.6%) patients showed a post-operative gap during speech. VFS and MRI equally identified the cases with persistent or recurrent VPD. Differences in SP-PPW distance between VFS (3.9 ± 1.6mm) and MRI (4.1 ± 1.5mm) were not statistically significant (p = 0.5). The subjective overall image quality of MRI was rated inferior (p < 0.001) compared with VFS, with almost perfect inter-rater agreement (κ= 0.90). The presence of susceptibility artifacts did not limit anatomical measurements. Dynamic MRI is equally reliable as VFS to assess persistent or recurrent inadequate velum closure in patients following surgical treatment of VPD. • Unenhanced 3-T dynamic MRI and contrast-enhanced videofluoroscopy are equally useful for the identification of patients with incomplete velopharyngeal closure during speech. • MRI using refocused gradient-echo acquisition with radial k-space sampling and sliding window reconstruction generates diagnostic images with 28 frames per second. • MRI can offer a radiation-free alternative to currently established videofluoroscopy for young patients.

Sliding window reduced FOV reconstruction for real-time cardiac imaging

BackgroundCurrent functional cardiovascular imaging protocols mostly rely on electrocardiogram (ECG) gating and breathholding. The resulting image quality can substantially suffer from insufficient patient cooperation or severe arrhythmia. Real-time imaging can mitigate these effects but requires highly accelerated techniques, usually relying on non-cartesian trajectories and Compressed Sensing (CS). MethodsWe investigate a sliding window reduced field of view (FOV) Echo Planar Imaging (EPI) technique for real-time cardiac MRI. Segmented EPI has been combined with a subtraction technique for reducing the FOV in cardiac applications to the region of the beating heart. Residual respiratory motion, potentially impairing the image quality, has been addressed by continuous update of the static image fraction, which is derived from a low-temporal resolution sliding window reconstruction. For further acceleration, the proposed technique was combined with parallel imaging. ResultsThe sliding window reduced FOV technique was proven feasible to reconstruct images of diagnostic image quality at a temporal resolution of 36.5ms per image. Semi-quantitative evaluation of image quality showed significant improvement over the existing rFOV method (p=0.039). Derived functional parameters show comparable results as with the BH-CINE reference. However, a trend to a slight underestimation of the largest and smallest in-plane volumes is observed. ConclusionThe proposed technique is feasible of providing real-time cardiac MRI with a temporal resolution better than 40ms without the need of computably complex reconstruction techniques.

Boosting Compressed Sensing Using Local Measurements and Sliding Window Reconstruction

In the framework of compressed sensing, image data is measured using less measurements than the total number of pixels. Each measurement consists of a (random) linear combination of all pixels. Since image data is approximately sparse in an appropriate transform domain, a reasonable reconstruction is possible for many measurement matrices, especially for i.i.d. Gaussian measurement matrices. In a seemingly different field, non-regular sampling techniques such as three-quarter sampling have shown promising results to enhance the resolution of an imaging sensor by effectively sub-sampling a higher resolution image. Here, the measurements can be described as linear combinations of only three pixels, which can also be seen as a (spectral) compressed sensing measurement. Since each measurement is spatially localized, the reconstruction can be performed in overlapping sliding windows. In this work, we show that compressed sensing reconstruction algorithms can greatly benefit from such an overlapping sliding window reconstruction. Compared to conventional block-wise compressed sensing with i.i.d. Gaussian measurement matrices, the reconstruction quality in terms of the PSNR increases up to +5dB using small, local i.d.d. Gaussian measurement blocks. Additionally, we propose a local joint sparse deconvolution and extrapolation (L-JSDE) to reconstruct images from arbitrary local measurements. For several applications with local measurements we show that L-JSDE increases the PSNR by +2.2dB relative to conventional block-wise i.i.d. Gaussian measurements reconstructed with the state-of-the-art reconstruction algorithm D-AMP using the same overall sampling density.

Sector-wise golden-angle phase contrast with high temporal resolution for evaluation of left ventricular diastolic dysfunction.

PurposeTo develop a high temporal resolution phase‐contrast pulse sequence for evaluation of diastolic filling patterns, and to evaluate it in comparison to transthoracic echocardiography.MethodsA phase‐contrast velocity‐encoded gradient‐echo pulse sequence was implemented with a sector‐wise golden‐angle radial ordering. Acquisitions were optimized for myocardial tissue (TE/TR: 4.4/6.8 ms, flip angle: 8º, velocity encoding: 30 cm/s) and transmitral flow (TE/TR: 4.0/6.6 ms, flip angle: 20º, velocity encoding: 150 cm/s). Shared velocity encoding was combined with a sliding‐window reconstruction that enabled up to 250 frames per cardiac cycle. Transmitral and myocardial velocities were measured in 35 patients. Echocardiographic velocities were obtained with pulsed‐wave Doppler using standard methods.ResultsMyocardial velocity showed a low difference and good correlation between MRI and Doppler (mean ± 95% limits of agreement 0.9 ± 3.7 cm/s, R2 = 0.63). Transmitral velocity was underestimated by MRI (P < .05) with a difference of −11 ± 28 cm/s (R2 = 0.45). The early‐to‐late ratio correlated well (R2 = 0.66) with a minimal difference (0.03 ± 0.6). Analysis of interobserver and intra‐observer variability showed excellent agreement for all measurements.ConclusionsThe proposed method enables the acquisition of phase‐contrast images during a single breath‐hold with a sufficiently high temporal resolution to match transthoracic echocardiography, which opens the possibility for many clinically relevant variables to be assessed by MRI.

Rigid motion correction for magnetic resonance fingerprinting with sliding-window reconstruction and image registration

Magnetic resonance fingerprinting (MRF) can be used to simultaneously obtain multiple parameter maps from a single pulse sequence. However, patient motion during MRF acquisition may result in blurring and artifacts in estimated parameter maps. In this work, a novel motion correction method was proposed to correct for rigid motion in MRF. The proposed method involved sliding-window reconstruction to obtain intermediate images followed by image registration to estimate rigid motion information between these images. Finally, the motion-corrupted k-space data were corrected with the estimated motion parameters and then reconstructed to obtain the parameter maps via the conventional MRF processing pipeline. The proposed method was evaluated using both simulations and in vivo MRF experiments with intently different types of motion. For motion-corrupted data, the proposed method yielded brain T1, T2 and proton density maps with obviously reduced blurring and artifacts and lower normalized root-mean-square error, compared to MRF without motion correction. In conclusion, motion-corrected MRF using the proposed method has the potential to produce accurate parameter maps in the presence of in-plane rigid motion.

Rigid motion-corrected magnetic resonance fingerprinting.

PurposeDevelop a method for rigid body motion‐corrected magnetic resonance fingerprinting (MRF).MethodsMRF has shown some robustness to abrupt motion toward the end of the acquisition. Here, we study the effects of different types of rigid body motion during the acquisition on MRF and propose a novel approach to correct for this motion. The proposed method (MC‐MRF) follows 4 steps: (1) sliding window reconstruction is performed to produce high‐quality auxiliary dynamic images; (2) rotation and translation motion is estimated from the dynamic images by image registration; (3) estimated motion is used to correct acquired k‐space data with corresponding rotations and phase shifts; and (4) motion‐corrected data are reconstructed with low‐rank inversion. MC‐MRF was validated in a standard T1/T2 phantom and 2D in vivo brain acquisitions in 7 healthy subjects. Additionally, the effect of through‐plane motion in 2D MC‐MRF was investigated.ResultsSimulation results show that motion in MRF can introduce artifacts in T1 and T2 maps, depending when it occurs. MC‐MRF improved parametric map quality in all phantom and in vivo experiments with in‐plane motion, comparable to the no‐motion ground truth. Reduced parametric map quality, even after motion correction, was observed for acquisitions with through‐plane motion, particularly for smaller structures in T2 maps.ConclusionHere, a novel method for motion correction in MRF (MC‐MRF) is proposed, which improves parametric map quality and accuracy in comparison to no‐motion correction approaches. Future work will include validation of 3D MC‐MRF to enable also through‐plane motion correction.

Simultaneous T1 and T2 mapping of the carotid plaque (SIMPLE) with T2 and inversion recovery prepared 3D radial imaging.

To propose a technique that can produce different T1 and T2 contrasts in a single scan for simultaneous T1 and T2 mapping of the carotid plaque (SIMPLE). An interleaved 3D golden angle radial trajectory was used in conjunction with T2 preparation with variable duration (TEprep ) and inversion recovery pulses. Sliding window reconstruction was adopted to reconstruct images at different inversion delay time and TEprep for joint T1 and T2 fitting. In the fitting procedure, a rapid B1 correction method was presented. The accuracy of SIMPLE was investigated in phantom experiments. In vivo scans were performed on 5 healthy volunteers with 2 scans each, and on 5 patients with carotid atherosclerosis. The phantom T1 and T2 estimations of SIMPLE agreed well with the standard methods with the percentage difference smaller than 7.1%. In vivo T1 and T2 for normal carotid vessel wall were 1213 ± 48.3 ms and 51.1 ± 1.7 ms, with good interscan repeatability. Alternations of T1 and T2 in plaque regions were in agreement with the conventional multicontrast imaging findings. The proposed SIMPLE allows simultaneous T1 and T2 mapping of the carotid artery in less than 10 minutes, serving as a quantitative tool with good accuracy and reproducibility for plaque characterization.

Pulmonary artery imaging under free-breathing using golden-angle radial bSSFP MRI: a proof of concept.

To evaluate the feasibility of an improved motion and flow robust methodology for imaging the pulmonary vasculature using non-contrast-enhanced, free-breathing, golden-angle radial MRI. Healthy volunteers (n = 10, age 46 ± 11 years, 50% female) and patients (n = 2, ages 27 and 84, both female) were imaged at 1.5 T using a Cartesian and golden-angle radial 2D balanced SSFP pulse sequence. The acquisitions were made under free breathing without contrast agent enhancement. The radial acquisitions were reconstructed at 3 temporal footprints. All series were scored from 1 to 5 for perceived diagnostic quality, artifact level, and vessel sharpness in multiple anatomical locations. In addition, vessel sharpness and blood-to-blood clot contrast were measured. Quantitative measurements showed higher vessel sharpness for golden-angle radial (n = 76, 0.79 ± 0.11 versus 0.71 ± 0.16, p < .05). Blood-to-blood clot contrast was found to be 23% higher in golden-angle radial in the 2 patients. At comparable temporal footprints, golden-angle radial was scored higher for diagnostic quality (mean ± SD, 2.3 ± 0.7 versus 2.2 ± 0.6, p < .01) and vessel sharpness (2.2 ± 0.8 versus 2.1 ± 0.5, p < .01), whereas the artifact level did not differ (3.0 ± 0.9 versus 3.0 ± 1.0, p = .80). The ability to retrospectively choose a temporal resolution and perform sliding-window reconstructions was demonstrated in patients. In pulmonary artery imaging, the motion and flow robustness of a radial trajectory does both improve image quality over Cartesian trajectory in healthy volunteers, and allows for flexible selection of temporal footprints and the ability to perform real-time sliding window reconstructions, which could potentially provide further diagnostic insight.

Carotid Intraplaque Hemorrhage Imaging with Quantitative Vessel Wall T1 Mapping: Technical Development and Initial Experience.

Purpose To develop a three-dimensional (3D) high-spatial-resolution time-efficient sequence for use in quantitative vessel wall T1 mapping. Materials and Methods A previously described sequence, simultaneous noncontrast angiography and intraplaque hemorrhage (SNAP) imaging, was extended by introducing 3D golden angle radial k-space sampling (GOAL-SNAP). Sliding window reconstruction was adopted to reconstruct images at different inversion delay times (different T1 contrasts) for voxelwise T1 fitting. Phantom studies were performed to test the accuracy of T1 mapping with GOAL-SNAP against a two-dimensional inversion recovery (IR) spin-echo (SE) sequence. In vivo studies were performed in six healthy volunteers (mean age, 27.8 years ± 3.0 [standard deviation]; age range, 24-32 years; five male) and five patients with atherosclerosis (mean age, 66.4 years ± 5.5; range, 60-73 years; five male) to compare T1 measurements between vessel wall sections (five per artery) with and without intraplaque hemorrhage (IPH). Statistical analyses included Pearson correlation coefficient, Bland-Altman analysis, and Wilcoxon rank-sum test with data permutation by subject. Results Phantom T1 measurements with GOAL-SNAP and IR SE sequences showed excellent correlation (R2 = 0.99), with a mean bias of -25.8 msec ± 43.6 and a mean percentage error of 4.3% ± 2.5. Minimum T1 was significantly different between sections with IPH and those without it (mean, 371 msec ± 93 vs 944 msec ± 120; P = .01). Estimated T1 of normal vessel wall and muscle were 1195 msec ± 136 and 1117 msec ± 153, respectively. Conclusion High-spatial-resolution (0.8 mm isotropic) time-efficient (5 minutes) vessel wall T1 mapping is achieved by using the GOAL-SNAP sequence. This sequence may yield more quantitative reproducible biomarkers with which to characterize IPH and monitor its progression. © RSNA, 2017.

Alternate update of shifted extended keyholes (AUSEK): A new accelerating strategy for interventional MRI

Real-time or near-real-time acquisition plays a key role in providing immediate image guidance for interventional magnetic resonance imaging (iMRI). However, the requirement of accurate needle tip localization has made several accelerating techniques, like Keyhole imaging or sliding window reconstruction, difficult to be applied to iMRI. The purpose of this work was to further explore the possible ways of applying view sharing techniques to iMRI. Inspired by Keyhole imaging, we present an easy-to-implement accelerating strategy called “Alternate update of shifted extended keyholes (AUSEK)”. In this method, the keyhole views are not only extended but also shifted towards either high-frequency edge to form two divisions in k-space. The divisions which are mirrored to each other along the center are alternately updated following a reference scan. By using simulations and experiments, we demonstrate that AUSEK could effectively preserve the spatial resolution of the image, especially of the needle, at a temporal acceleration rate of about 2.5. AUSEK was implemented online in an open-configuration low-field MR imaging system.

MPnRAGE: A technique to simultaneously acquire hundreds of differently contrasted MPRAGE images with applications to quantitative T1 mapping.

To introduce a new technique called MPnRAGE, which produces hundreds of images with different T1 contrasts and a B1 corrected T1 map. An interleaved three-dimensional radial k-space trajectory with a sliding window reconstruction is used in conjunction with magnetization preparation pulses. This work modifies the SNAPSHOT-FLASH T1 fitting equations for radial imaging with view-sharing and develops a new rapid B1 correction procedure. MPnRAGE is demonstrated in phantoms and volunteers, including two volunteers with eight scans each and eight volunteers with two scans each. T1 values from MPnRAGE were compared with those from fast spin echo inversion recovery (FSE-IR) in phantoms and a healthy human brain at 3 Tesla (T). The T1 fit for human white and gray matter was T1MPnRAGE = 1.00 · T1FSE-IR + 24 ms, r(2) = 0.990. Voxel-wise coefficient of variation in T1 measurements across eight time points was between 0.02 and 0.08. Region of interest-based T1 values were reproducible to within 2% and agree well with literature values. In the same amount of time as a traditional MPRAGE exam (7.5 min), MPnRAGE was shown to produce hundreds of images with alternate T1 contrasts as well as an accurate and reproducible T1 map that is robust to B1 errors.

A g-factor metric for k-t-GRAPPA- and PEAK-GRAPPA-based parallel imaging.

The aim of this work is to derive a theoretical framework for quantitative noise and temporal fidelity analysis of time-resolved k-space-based parallel imaging methods. An analytical formalism of noise distribution is derived extending the existing g-factor formulation for nontime-resolved generalized autocalibrating partially parallel acquisition (GRAPPA) to time-resolved k-space-based methods. The noise analysis considers temporal noise correlations and is further accompanied by a temporal filtering analysis. All methods are derived and presented for k-t-GRAPPA and PEAK-GRAPPA. A sliding window reconstruction and nontime-resolved GRAPPA are taken as a reference. Statistical validation is based on series of pseudoreplica images. The analysis is demonstrated on a short-axis cardiac CINE dataset. The superior signal-to-noise performance of time-resolved over nontime-resolved parallel imaging methods at the expense of temporal frequency filtering is analytically confirmed. Further, different temporal frequency filter characteristics of k-t-GRAPPA, PEAK-GRAPPA, and sliding window are revealed. The proposed analysis of noise behavior and temporal fidelity establishes a theoretical basis for a quantitative evaluation of time-resolved reconstruction methods. Therefore, the presented theory allows for comparison between time-resolved parallel imaging methods and also nontime-resolved methods. Magn Reson Med 74:125-135, 2015. © 2014 Wiley Periodicals, Inc.