Fast 3D fMRI acquisition with high spatial resolutions over a reduced FOV.

PURPOSE: To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k-t 3D reduced FOV imaging (3D-rFOVI). METHODS: Based on 3D gradient-echo EPI, k-t 3D-rFOVI used a 2D RF pulse to reduce the FOV in the in-plane phase-encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k-space region along the through-slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k-t 3D-rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k-t 3D-rFOVI and compare it with a commercial multiband EPI sequence. RESULTS: The simulation data showed that k-t 3D-rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5-mm spatial resolution and 800-ms volume TR (TRvol), k-t 3D-rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k-t 3D-rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation. CONCLUSIONS: k-t 3D-rFOVI can simultaneously achieve a high spatial resolution (1.5-mm isotropically) and short TRvol (480-ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume.

Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion.

PURPOSE: EPI with blip-up/down acquisition (BUDA) can provide high-quality images with minimal distortions by using two readout trains with opposing phase-encoding gradients. Because of the need for two separate acquisitions, BUDA doubles the scan time and degrades the temporal resolution when compared to single-shot EPI, presenting a major challenge for many applications, particularly fMRI. This study aims at overcoming this challenge by developing an echo-shifted EPI BUDA (esEPI-BUDA) technique to acquire both blip-up and blip-down datasets in a single shot. METHODS: A 3D esEPI-BUDA pulse sequence was designed by using an echo-shifting strategy to produce two EPI readout trains. These readout trains produced a pair of k-space datasets whose k-space trajectories were interleaved with opposite phase-encoding gradient directions. The two k-space datasets were separately reconstructed using a 3D SENSE algorithm, from which time-resolved B0 -field maps were derived using TOPUP in FSL and then input into a forward model of joint parallel imaging reconstruction to correct for geometric distortion. In addition, Hankel structured low-rank constraint was incorporated into the reconstruction framework to improve image quality by mitigating the phase errors between the two interleaved k-space datasets. RESULTS: The 3D esEPI-BUDA technique was demonstrated in a phantom and an fMRI study on healthy human subjects. Geometric distortions were effectively corrected in both phantom and human brain images. In the fMRI study, the visual activation volumes and their BOLD responses were comparable to those from conventional 3D echo-planar images. CONCLUSION: The improved imaging efficiency and dynamic distortion correction capability afforded by 3D esEPI-BUDA are expected to benefit many EPI applications.

Accelerating High b-Value Diffusion-Weighted MRI Using a Convolutional Recurrent Neural Network (CRNN-DWI).

PURPOSE: To develop a novel convolutional recurrent neural network (CRNN-DWI) and apply it to reconstruct a highly undersampled (up to six-fold) multi-b-value, multi-direction diffusion-weighted imaging (DWI) dataset. METHODS: A deep neural network that combines a convolutional neural network (CNN) and recurrent neural network (RNN) was first developed by using a set of diffusion images as input. The network was then used to reconstruct a DWI dataset consisting of 14 b-values, each with three diffusion directions. For comparison, the dataset was also reconstructed with zero-padding and 3D-CNN. The experiments were performed with undersampling rates (R) of 4 and 6. Standard image quality metrics (SSIM and PSNR) were employed to provide quantitative assessments of the reconstructed image quality. Additionally, an advanced non-Gaussian diffusion model was employed to fit the reconstructed images from the different approaches, thereby generating a set of diffusion parameter maps. These diffusion parameter maps from the different approaches were then compared using SSIM as a metric. RESULTS: Both the reconstructed diffusion images and diffusion parameter maps from CRNN-DWI were better than those from zero-padding or 3D-CNN. Specifically, the average SSIM and PSNR of CRNN-DWI were 0.750 ± 0.016 and 28.32 ± 0.69 (R = 4), and 0.675 ± 0.023 and 24.16 ± 0.77 (R = 6), respectively, both of which were substantially higher than those of zero-padding or 3D-CNN reconstructions. The diffusion parameter maps from CRNN-DWI also yielded higher SSIM values for R = 4 (>0.8) and for R = 6 (>0.7) than the other two approaches (for R = 4, <0.7, and for R = 6, <0.65). CONCLUSIONS: CRNN-DWI is a viable approach for reconstructing highly undersampled DWI data, providing opportunities to reduce the data acquisition burden.

Time-dependent diffusion MRI using multiple stimulated echoes.

PURPOSE: To develop a time-efficient pulse sequence that acquires multiple diffusion-weighted images with distinct diffusion times in a single shot by using multiple stimulated echoes (mSTE) with variable flip angles (VFA). METHODS: The proposed diffusion-weighted mSTE with VFA (DW-mSTE-VFA) sequence begins with two 90° RF pulses that straddle a diffusion gradient lobe (GD ) to excite and restore one half of the magnetization into the longitudinal axis. The restored longitudinal magnetization was successively re-excited by a series of RF pulses with VFA, each followed by another GD , to generate a set of stimulated echoes. Each of the multiple stimulated echoes was acquired with an EPI echo train. As such, the train of multiple stimulated echoes produced a set of diffusion-weighted images with varying diffusion times in a single shot. This technique was experimentally demonstrated on a diffusion phantom, a fruit, and healthy human brain and prostate at 3 T. RESULTS: In the phantom experiment, the mean ADC measured at different diffusion times using DW-mSTE-VFA were highly consistent (r = 0.999) with those from a commercial spin-echo diffusion-weighted EPI sequence. In the fruit and brain experiments, DW-mSTE-VFA exhibited similar diffusion-time dependence to a standard diffusion-weighted stimulated echo sequence. The ADC showed significant time dependence in the human brain (p = 0.003 in both white matter and gray matter) and prostate tissues (p = 0.003 in both peripheral zone and central gland). CONCLUSION: DW-mSTE-VFA offers a time-efficient tool for investigating the diffusion-time dependency in diffusion MRI studies.

Multi-readout DWI with a reduced FOV for studying the coupling between diffusion and T 2 * relaxation in the prostate.

PURPOSE: To develop a DWI sequence with multiple readout echo-trains in a single shot (multi-readout DWI) over a reduced FOV, and to demonstrate its ability to achieve high data acquisition efficiency in the study of coupling between diffusion and relaxation in the human prostate. METHODS: The proposed multi-readout DWI sequence plays out multiple EPI readout echo-trains after a Stejskal-Tanner diffusion preparation module. Each EPI readout echo-train corresponded to a distinct effective TE. To maintain a high spatial resolution with a relatively short echo-train for each readout, a 2D RF pulse was used to limit the FOV. Experiments were performed on the prostate of six healthy subjects to acquire a set of images with three b values (0, 500, and 1000 s/mm2 ) and three TEs (63.0, 78.8, and 94.6 ms), producing three ADC maps at different TEs and three T 2 * $$ {T}_2^{\ast } $$ maps at different b values. RESULTS: Multi-readout DWI enabled a threefold acceleration without compromising the spatial resolution when compared with a conventional single-readout sequence. Images with three b values and three TEs were obtained in 3 min 40 s with an adequate SNR (≥ 26.9). The ADC values (1.45 ± 0.13, 1.52 ± 0.14, and 1.58 ± 0.15  µm 2 / ms $$ {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ; P < 0.01) exhibited an increasing trend as TEs increased (63.0 ms, 78.8 ms, and 94.6 ms), whereas T 2 * $$ {T}_2^{\ast } $$ values (74.78 ± 13.21, 63.21 ± 7.84, and 56.61 ± 5.05 ms; P < 0.01) decreases as the b values increased (0, 500, and 1000 s/mm2 ). CONCLUSION: The multi-readout DWI sequence over a reduced FOV provides a time-efficient technique to study the coupling between diffusion and relaxation times.

Characterization of breast lesions using multi-parametric diffusion MRI and machine learning.

Objective. To investigate quantitative imaging markers based on parameters from two diffusion-weighted imaging (DWI) models, continuous-time random-walk (CTRW) and intravoxel incoherent motion (IVIM) models, for characterizing malignant and benign breast lesions by using a machine learning algorithm.Approach. With IRB approval, 40 women with histologically confirmed breast lesions (16 benign, 24 malignant) underwent DWI with 11b-values (50 to 3000 s/mm2) at 3T. Three CTRW parameters,Dm,α, andßand three IVIM parametersDdiff,Dperf, andfwere estimated from the lesions. A histogram was generated and histogram features of skewness, variance, mean, median, interquartile range; and the value of the 10%, 25% and 75% quantiles were extracted for each parameter from the regions-of-interest. Iterative feature selection was performed using the Boruta algorithm that uses the Benjamin Hochberg False Discover Rate to first determine significant features and then to apply the Bonferroni correction to further control for false positives across multiple comparisons during the iterative procedure. Predictive performance of the significant features was evaluated using Support Vector Machine, Random Forest, Naïve Bayes, Gradient Boosted Classifier (GB), Decision Trees, AdaBoost and Gaussian Process machine learning classifiers.Main Results. The 75% quantile, and median ofDm; 75% quantile off;mean, median, and skewness ofß;kurtosis ofDperf; and 75% quantile ofDdiffwere the most significant features. The GB differentiated malignant and benign lesions with an accuracy of 0.833, an area-under-the-curve of 0.942, and an F1 score of 0.87 providing the best statistical performance (p-value < 0.05) compared to the other classifiers.Significance. Our study has demonstrated that GB with a set of histogram features from the CTRW and IVIM model parameters can effectively differentiate malignant and benign breast lesions.

Simultaneous multi-segment (SMSeg) EPI over multiple focal regions.

Objective.This study aimed at developing a simultaneous multi-segment (SMSeg) imaging technique using a two-dimensional (2D) RF pulse in conjunction with echo planar imaging (EPI) to image multiple focal regions.Approach.The SMSeg technique leveraged periodic replicates of the excitation profile of a 2D RF pulse to simultaneously excite multiple focal regions at different locations. These locations were controlled by rotating and scaling transmit k-space trajectories. The resulting multiple isolated focal regions were projected into a composite 'slice' for display. GRAPPA-based parallel imaging was incorporated into SMSeg by taking advantage of coil sensitivity variations in both the phase-encoded and slice-selection directions. The SMSeg technique was implemented at 3 T in a single-shot gradient-echo EPI sequence and demonstrated in a phantom and human brains for both anatomic imaging and functional imaging.Main results.In both the phantom and the human brain, SMSeg images from three focal regions were simultaneously acquired. SMSeg imaging enabled up to a six-fold acceleration in parallel imaging without causing appreciable residual aliasing artifacts when compared with a conventional gradient-echo EPI sequence with the same acceleration factor. In the functional imaging experiment, BOLD activations associated with a visuomotor task were simultaneously detected in two non-coplanar segments (each with a size of 240 × 30 mm2), corresponding to visual and motor cortices, respectively.Significance.Our study has demonstrated that SMSeg imaging can be a viable method for studying multiple focal regions simultaneously.

Coupling and decoupling CH stretching vibration of methylene and methine in serine conformers.

In the molecules of the early Earth, as a building block of proteins, serine has enormous chemical and biological significance. The vibrational spectroscopy of CH bonds plays an important role in probing biomolecules. Whether the CH stretching vibration bands can be accurately assigned will affect the accuracy of the detection results. In this study, we employed the MP2/cc-pVTZ method to calculate the Raman spectra of 85 serine conformers and the corresponding species with deuterium in the CH stretching region from 2800 cm-1 to 3050 cm-1 and then recorded the movement of each atom and the dihedral angles, CH bond lengths, and Raman shifts before and after deuterium for each conformer. We directly observed that the stretching vibration of two CH bonds in the methylene group decoupled to vibrate independently in some conformers, and the stretching vibrations of methylene and methine could be strongly coupled in some conformers. Those results are inconsistent with the traditional understanding, which is generally believed that the CH stretching vibrations are mutually coupled in a single methyl or methylene group to generate symmetric and antisymmetric stretching vibrations, while for different methyl, methylene or methine groups, the CH stretching vibrations cannot be mutually coupled. Through the statistical analysis between several factors, we found that the level of local coupling in serine methylene was correlated with the bond length difference between two CH bonds. Our work provides a new understanding of the vibrational modes of hydrocarbon bonds and the coupling between different hydrocarbon groups.

In-plane simultaneous multisegment imaging using a 2D RF pulse.

PURPOSE: To develop an in-plane simultaneous multisegment (IP-SMS) imaging technique using a 2D-RF pulse and to demonstrate its ability to achieve high spatial resolution in EPI while reducing image distortion. METHODS: The proposed IP-SMS technique takes advantage of periodic replicates of the excitation profile of a 2D-RF pulse to simultaneously excite multiple segments within a slice. These segments were acquired over a reduced FOV and separated using a joint GRAPPA reconstruction by leveraging virtual coils that combined the physical coil sensitivity and 2D-RF pulse spatial response. Two excitations were used with complementary spatial response profiles to adequately cover a full FOV, producing a full-FOV image that had the benefits of reduced FOV with high spatial resolution and reduced distortion. The IP-SMS technique was implemented in a diffusion-weighted single-shot EPI sequence. Experimental demonstrations were performed on a phantom and healthy human brain. RESULTS: In the phantom experiment, IP-SMS enabled a four-fold acceleration using an eight-channel coil without causing residual aliasing artifacts. In the human brain experiment, diffusion-weighted images with high in-plane resolution (1 × 1 mm2 ) and substantially reduced image distortion were obtained in all imaging planes in comparison with a commercial diffusion-weighted EPI sequence. The capability of IP-SMS for contiguous whole-brain coverage was also demonstrated. CONCLUSION: The proposed IP-SMS technique can realize the benefits of reduced-FOV imaging while achieving a full-FOV coverage with good image quality and time efficiency.

Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma.

OBJECTIVES: To evaluate the feasibility of high b-value diffusion-weighted imaging (DWI) for distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC) and low- from high-grade bladder urothelial carcinoma using a fractional-order calculus (FROC) model as well as a combination of FROC DWI and bi-parametric Vesical Imaging-Reporting and Data System (VI-RADS). METHODS: Fifty-eight participants with bladder urothelial carcinoma were included in this IRB-approved prospective study. Diffusion-weighted images, acquired with 16 b-values (0-3600 s/mm2), were analyzed using the FROC model. Three FROC parameters, D, ß, and µ, were used for delineating NMIBC from MIBC and for tumor grading. A receiver operating characteristic (ROC) analysis was performed based on the individual FROC parameters and their combinations, followed by comparisons with apparent diffusion coefficient (ADC) and bi-parametric VI-RADS based on T2-weighted images and DWI. RESULTS: D and µ were significantly lower in the MIBC group than in the NMIBC group (p = 0.001 for each), and D, ß, and µ all exhibited significantly lower values in the high- than in the low-grade tumors (p ≤ 0.011). The combination of D, ß, and µ produced the highest specificity (85%), accuracy (78%), and the area under the ROC curve (AUC, 0.782) for distinguishing NMIBC and MIBC, and the best sensitivity (89%), specificity (86%), accuracy (88%), and AUC (0.892) for tumor grading, all of which outperformed the ADC. The combination of FROC parameters with bi-parametric VI-RADS improved the AUC from 0.859 to 0.931. CONCLUSIONS: High b-value DWI with a FROC model is useful in distinguishing NMIBC from MIBC and grading bladder tumors. KEY POINTS: • Diffusion parameters derived from a FROC diffusion model may differentiate NMIBC from MIBC and low- from high-grade bladder urothelial carcinomas. • Under the condition of a moderate sample size, higher AUCs were achieved by the FROC parameters D (0.842) and µ (0.857) than ADC (0.804) for bladder tumor grading with p ≤ 0.046. • The combination of the three diffusion parameters from the FROC model can improve the specificity over ADC (85% versus 67%, p = 0.031) for distinguishing NMIBC and MIBC and enhance the performance of bi-parametric VI-RADS.

Three-dimensional reduced field-of-view imaging (3D-rFOVI).

PURPOSE: This study aimed at developing a 3D reduced field-of-view imaging (3D-rFOVI) technique using a 2D radiofrequency (RF) pulse, and demonstrating its ability to achieve isotropic high spatial resolution and reduced image distortion in echo planar imaging (EPI). METHODS: The proposed 3D-rFOVI technique takes advantage of a 2D RF pulse to excite a slab along the conventional slice-selection direction (i.e., z-direction) while limiting the spatial extent along the phase-encoded direction (i.e., y-direction) within the slab. The slab is phase-encoded in both through-slab and in-slab phase-encoded directions. The 3D-rFOVI technique was implemented at 3T in gradient-echo and spin-echo EPI pulse sequences for functional MRI (fMRI) and diffusion-weighted imaging (DWI), respectively. 3D-rFOVI experiments were performed on a phantom and human brain to illustrate image distortion reduction, as well as isotropic high spatial resolution, in comparison with 3D full-FOV imaging. RESULTS: In both the phantom and the human brain, image voxel dislocation was substantially reduced by 3D-rFOVI when compared with full-FOV imaging. In the fMRI experiment with visual stimulation, 3D isotropic spatial resolution of (2 × 2 × 2 mm3 ) was achieved with an adequate signal-to-noise ratio (81.5) and blood oxygen level-dependent (BOLD) contrast (2.5%). In the DWI experiment, diffusion-weighted brain images with an isotropic resolution of (1 × 1 × 1 mm3 ) was obtained without appreciable image distortion. CONCLUSION: This study indicates that 3D-rFOVI is a viable approach to 3D neuroimaging over a zoomed region.

Diffusion in Sephadex Gel Structures: Time Dependency Revealed by Multi-Sequence Acquisition over a Broad Diffusion Time Range.

It has been increasingly reported that in biological tissues diffusion-weighted MRI signal attenuation deviates from mono-exponential decay, especially at high b-values. A number of diffusion models have been proposed to characterize this non-Gaussian diffusion behavior. One of these models is the continuous-time random-walk (CTRW) model, which introduces two new parameters: a fractional order time derivative α and a fractional order spatial derivative ß. These new parameters have been linked to intravoxel diffusion heterogeneities in time and space, respectively, and are believed to depend on diffusion times. Studies on this time dependency are limited, largely because the diffusion time cannot vary over a board range in a conventional spin-echo echo-planar imaging sequence due to the accompanying T2 decays. In this study, we investigated the time-dependency of the CTRW model in Sephadex gel phantoms across a broad diffusion time range by employing oscillating-gradient spin-echo, pulsed-gradient spin-echo, and pulsed-gradient stimulated echo sequences. We also performed Monte Carlo simulations to help understand our experimental results. It was observed that the diffusion process fell into the Gaussian regime at extremely short diffusion times whereas it exhibited a strong time dependency in the CTRW parameters at longer diffusion times.

Predicting the aggressiveness of peripheral zone prostate cancer using a fractional order calculus diffusion model.

PURPOSE: To evaluate the performance of parameters D, ß, µ from the Fractional Order Calculus (FROC) model at differentiating peripheral zone (PZ) prostate cancer (PCa) MATERIAL AND METHODS: 75 patients who underwent targeted MRI-guided TRUS prostate biopsy within 6 months of MRI were reviewed retrospectively. Regions of interest (ROI) were placed on suspicious lesions on MRI scans. ROIs were then correlated to pathological results based on core biopsy location. The final tumor count is a total: 23 of GS 6 (3 + 3), 36 of GS 7 (3 + 4), 18 of GS 7 (4 + 3), and 19 of GS ≥ 8. Diffusion-weighted imaging (DWI) scans were fitted into the FROC and monoexponential model to calculate ADC and FROC parameters: anomalous diffusion coefficient D, intravoxel diffusion heterogeneity ß, and spatial parameter µ. The performance of FROC parameters and ADC at differentiating PCa grade was evaluated with receiver operating characteristic (ROC) analysis. RESULTS: In differentiating low (GS 6) vs. intermediate (GS 7) risk PZ PCa, combination of (D, ß) provides the best performance with AUC of 0.829 with significance of p = 0.018 when compared to ADC (AUC of 0.655). In differentiating clinically significant (GS 6) vs. clinically significant (GS ≥ 7) PCa, combination of (D, ß, µ) provides highest AUC of 0.802 when compared to ADC (AUC of 0.671) with significance of p = 0.038. Stratification of intermediate (GS 7) and high (GS ≥ 8) risk PCa with FROC did not reach a significant difference when compared to ADC. CONCLUSION: Combination of FROC parameters shows greater performance than ADC at differentiating low vs. intermediate risk and clinically insignificant vs. significant prostate cancers in peripheral zone lesions. The FROC diffusion model holds promise as a quantitative imaging technique for non-invasive evaluation of PZ PCa.

MRI with sub-millisecond temporal resolution over a reduced field of view.

PURPOSE: To demonstrate an MRI pulse sequence-Sub-millisecond Periodic Event Encoded Dynamic Imaging with a reduced field of view (or rFOV-SPEEDI)-for decreasing the scan times while achieving sub-millisecond temporal resolution. METHODS: rFOV-SPEEDI was based on a variation of SPEEDI, known as get-SPEEDI, which used each echo in an echo-train to sample a distinct k-space raster by synchronizing with a cyclic event. This can produce a set of time-resolved images of the cyclic event with a temporal resolution determined by the echo spacing (typically < 1 ms). rFOV-SPEEDI incorporated a 2D radiofrequency (RF) pulse into get-SPEEDI to limit the field of view (FOV), leading to reduction in phase-encoding steps and subsequently decreased scan times without compromising the spatial resolution. Two experiments were performed at 3T to illustrate rFOV-SPEEDI's capability of capturing fast-changing electric currents in a phantom and the rapid opening and closing of aortic valve in human subjects over reduced FOVs. The results were compared with those from full FOV get-SPEEDI. RESULTS: In the first experiment, the rapidly varying currents (50-200 Hz) were successfully captured with a temporal resolution of 0.8 ms, and agreed well with the applied currents. In the second experiment, the rapid opening and closing processes of aortic valve were clearly visualized with a temporal resolution of 0.6 ms over a reduced FOV (12 × 12 cm2 ). In both experiments, the acquisition times of rFOV-SPEEDI were decreased by 33%-50% relative to full FOV get-SPEEDI acquisitions and the spatial resolution was maintained. CONCLUSION: Reducing the FOV is a viable approach to shortening the scan times in SPEEDI, which is expected to help stimulate SPEEDI applications for studying ultrafast, cyclic physiological and biophysical processes over a focal region.

Visualization of Human Aortic Valve Dynamics Using Magnetic Resonance Imaging with Sub-Millisecond Temporal Resolution.

BACKGROUND: Visualization of aortic valve dynamics is important in diagnosing valvular diseases but is challenging to perform with magnetic resonance imaging (MRI) due to the limited temporal resolution. PURPOSE: To develop an MRI technique with sub-millisecond temporal resolution and demonstrate its application in visualizing rapid aortic valve opening and closing in human subjects in comparison with echocardiography and conventional MRI techniques. STUDY TYPE: Prospective. POPULATION: Twelve healthy subjects. FIELD STRENGTH/SEQUENCE: 3 T; gradient-echo-train-based sub-millisecond periodic event encoded imaging (get-SPEEDI) and balanced steady-state free precession (bSSFP). ASSESSMENT: Images were acquired using get-SPEEDI with a temporal resolution of 0.6 msec. get-SPEEDI was triggered by an electrocardiogram so that each echo in the gradient echo train corresponded to an image at a specific time point, providing a time-resolved characterization of aortic valve dynamics. For comparison, bSSFP was also employed with 12 msec and 24 msec temporal resolutions, respectively. The durations of the aortic valve rapid opening (Tro ), rapid closing (Trc ), and the maximal aortic valve area (AVA) normalized to height were measured with all three temporal resolutions. M-mode echocardiograms with a temporal resolution of 0.8 msec were obtained for further comparison. STATISTICAL TEST: Parameters were compared between the three sequences, together with the echocardiography results, with a Mann-Whitney U test. RESULTS: Significantly shorter Tro (mean ± SD: 27.5 ± 6.7 msec) and Trc (43.8 ± 11.6 msec) and larger maximal AVA/height (2.01 ± 0.29 cm2 /m) were measured with get-SPEEDI compared to either bSSFP sequence (Tro of 56.3 ± 18.8 and 63.8 ± 20.2 msec; Trc of 68.2 ± 16.6 and 72.8 ± 18.2 msec; maximal AVA/height of 1.63 ± 0.28 and 1.65 ± 0.32 cm2 /m for 12 msec and 24 msec temporal resolutions, respectively, P < 0.05). In addition, the get-SPEEDI results were more consistent with those measured using echocardiography, especially for Tro (29.0 ± 4.1 msec, P = 0.79) and Trc (41.6 ± 4.3 msec, P = 0.16). DATA CONCLUSION: get-SPEEDI allows for visualization of human aortic valve dynamics and provided values closer to those measured using echocardiography than the bSSFP sequences. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.