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This paper updates and extends three previous papers on tissue property filters (TP-filters), Multiplied, Added, Divided and/or Subtracted Inversion Recovery (MASTIR) pulse sequences and synergistic contrast MRI (scMRI). It does this by firstly adding the central contrast theorem (CCT) to TP-filters, secondly including division with MASTIR sequences to make them Multiplied, Added, Subtracted and/or Divided IR (MASDIR) sequences, and thirdly incorporating division into the image processing needed for scMR to increase synergistic T1 contrast. These updated concepts are then used to explain and improve contrast at tissue boundaries, as well as to develop imaging regimes to detect and monitor small changes to the brain over time and quantify T1. The CCT is in two parts: the first part states that contrast produced by each TP is the product of the change in TP multiplied by the TP sequence weighting which is the first partial derivative of the TP-filter. The second part states that the overall fractional contrast is the algebraic sum of the fractional contrasts produced by each of the TPs. Subtraction of two IR sequences alone about doubles contrast relative to a conventional single IR sequence. Division of this subtraction can amplify contrast 5-15 times compared with conventional IR sequences. Dividing sequences can be problematic in areas where the signal is zero but this is avoided by dividing the difference in signal of two magnitude reconstructed IR sequences by the sum of their signals. The basis for the production of high contrast, high spatial resolution boundaries at white-gray matter junctions, between cerebral cortex and cerebrospinal fluid (CSF) and at other sites with subtracted IR (SIR) and divided subtracted IR (dSIR) sequences is explained and examples are shown. A key concept is the tissue fraction f, which is the proportion of a tissue in a mixture of two tissues within a voxel. Contrast at boundaries is a function of the partial derivative of the TP-filter, the partial derivative of the relevant TP with respect to f, and the partial derivative of f with respect to distance, x. Location of tissue boundaries is important for segmentation and is helpful in determining if inversion times have been chosen correctly. In small change regimes, the high sensitivity to small changes in T1 provided by dSIR images, together with the high definition boundaries, afford mechanisms for detecting small changes due to contrast agents, disease, perfusion and other causes. 3D isotropic rigid body registration provides a technique for following these changes over time in serial studies. Images showing high lesion contrast, high definition tissue and fluid boundaries, and the detection of small changes are included. T1 maps can be created by linearly scaling dSIR images.

PurposeDevelop a novel three-dimensional (3D) generative adversarial network (GAN)-based technique for simultaneous image reconstruction and respiratory motion compensation of 4D MRI. Our goal was to enable high-acceleration factors 10.7X-15.8X, while maintaining robust and diagnostic image quality superior to state-of-the-art self-gating (SG) compressed sensing wavelet (CS-WV) reconstruction at lower acceleration factors 3.5X-7.9X.MethodsOur GAN was trained based on pixel-wise content loss functions, adversarial loss function, and a novel data-driven temporal aware loss function to maintain anatomical accuracy and temporal coherence. Besides image reconstruction, our network also performs respiratory motion compensation for free-breathing scans. A novel progressive growing-based strategy was adapted to make the training process possible for the proposed GAN-based structure. The proposed method was developed and thoroughly evaluated qualitatively and quantitatively based on 3D cardiac cine data from 42 patients.ResultsOur proposed method achieved significantly better scores in general image quality and image artifacts at 10.7X-15.8X acceleration than the SG CS-WV approach at 3.5X-7.9X acceleration (4.53 ± 0.540 vs. 3.13 ± 0.681 for general image quality, 4.12 ± 0.429 vs. 2.97 ± 0.434 for image artifacts, P < .05 for both). No spurious anatomical structures were observed in our images. The proposed method enabled similar cardiac-function quantification as conventional SG CS-WV. The proposed method achieved faster central processing unit-based image reconstruction (6 s/cardiac phase) than the SG CS-WV (312 s/cardiac phase).ConclusionThe proposed method showed promising potential for high-resolution (1 mm3 ) free-breathing 4D MR data acquisition with simultaneous respiratory motion compensation and fast reconstruction time.

PurposeStandard balanced SSFP (bSSFP) cine MRI often suffers from blood outflow artifacts. We propose a method that spatially encodes these outflowing spins to reduce their effects in the intended slice.MethodsBloch simulations were performed to characterize through-plane flow and to investigate how the use of phase encoding along the slice select's direction ("slice encoding") could alleviate its issues. Phantom scans and in vivo cines were acquired on a 3T system, comparing the standard 2D acquisition to the proposed slice-encoding method. Nineteen healthy volunteers were recruited for short-axis and horizontal long-axis oriented scans. An expert radiologist evaluated each slice-encoded/standard cine pairs in a rank comparison test and graded their quality on a 1-5 scale. The grades were used for a nonparametric paired evaluation for independent samples with a null hypothesis that there was no statistical difference between the two quality-grade distributions for α = 0.05 significance.ResultsBloch simulation results demonstrated this technique's feasibility, showing a fully resolved slice profile given a sufficient number of slice encodes. These results were confirmed with the phantom experiments. Each in vivo slice-encoded cine had a higher quality than its corresponding standard acquisition. The nonparametric paired evaluation came to 0.01 significance, encouraging us to reject the null hypothesis and conclude that slice-encoding effectively works in reducing outflow effects.ConclusionThe slice-encoding balanced SSFP technique is helpful in mitigating outflow effects and is achievable within a single breath hold, being a useful alternative for cases in which the flow artifacts are significant.

PurposeChemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study.Theory and methodsA technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature.ResultsSimulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction.ConclusionCorrection for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.

Sampling k-space asymmetrically (ie, partial Fourier sampling) in the readout direction is a common way to reduce the echo time (TE) during magnetic resonance image acquisitions. This technique requires overlap around the center of k-space to provide a calibration region for reconstruction, which limits the minimum fractional echo to ~60% before artifacts are observed. The present study describes a method for reconstructing images from exact half echoes using two separate acquisitions with reversed readout polarity, effectively providing a full line of k-space without additional data around central k-space. This approach can benefit sequences or applications that prioritize short TE, short inter-echo spacing or short repetition time. An example of the latter is demonstrated to reduce banding artifacts in balanced steady-state free precession.

The aim of this study was to develop a deep neural network for respiratory motion compensation in free-breathing cine MRI and evaluate its performance. An adversarial autoencoder network was trained using unpaired training data from healthy volunteers and patients who underwent clinically indicated cardiac MRI examinations. A U-net structure was used for the encoder and decoder parts of the network and the code space was regularized by an adversarial objective. The autoencoder learns the identity map for the free-breathing motion-corrupted images and preserves the structural content of the images, while the discriminator, which interacts with the output of the encoder, forces the encoder to remove motion artifacts. The network was first evaluated based on data that were artificially corrupted with simulated rigid motion with regard to motion-correction accuracy and the presence of any artificially created structures. Subsequently, to demonstrate the feasibility of the proposed approach in vivo, our network was trained on respiratory motion-corrupted images in an unpaired manner and was tested on volunteer and patient data. In the simulation study, mean structural similarity index scores for the synthesized motion-corrupted images and motion-corrected images were 0.76 and 0.93 (out of 1), respectively. The proposed method increased the Tenengrad focus measure of the motion-corrupted images by 12% in the simulation study and by 7% in the in vivo study. The average overall subjective image quality scores for the motion-corrupted images, motion-corrected images and breath-held images were 2.5, 3.5 and 4.1 (out of 5.0), respectively. Nonparametric-paired comparisons showed that there was significant difference between the image quality scores of the motion-corrupted and breath-held images (P < .05); however, after correction there was no significant difference between the image quality scores of the motion-corrected and breath-held images. This feasibility study demonstrates the potential of an adversarial autoencoder network for correcting respiratory motion-related image artifacts without requiring paired data.

The divided subtracted inversion recovery (dSIR) is a high T1 contrast technique that shows changes in white matter in patients with traumatic brain injury and hypoxic injury. The changes can be explained by small differences in T1; however, to date, there has been no independent validation of the technique using a standard reference. The present study develops the theory of the dSIR signal and performs validation using the NIST/ISMRM T1 phantom. Non‐idealities are explored, including the influence of noise bias and finite repetition time (TR), which leads to the introduction of an optimally efficient TR for inversion recovery acquisitions. Results show excellent agreement with theoretical calculations. [ABSTRACT FROM AUTHOR]

Purpose: Balanced steady‐state free precession (bSSFP) imaging is susceptible to outflow effects where excited spins leaving the slice as part of the blood stream are misprojected back onto the imaging plane. Previous work proposed using slice‐encoding steps to localize these outflow effects from corrupting the target slice, at the expense of prolonged scan time. This present study extends this idea by proposing a means of significantly reducing most of the outflowing signal from the imaged slice using a coil localization method that acquires a slice‐encoded calibration scan in addition to the 2D data, without being nearly as time‐demanding as our previous method. This coil localization method is titled UNfolding Coil Localized Errors from an imperfect slice profile using a Structured Autocalibration Matrix (UNCLE SAM). Methods: Retrospective and prospective evaluations were carried out. Both featured a 2D acquisition and a separate slice‐encoded calibration of the center in‐plane k‐space lines across all desired slice‐encoding steps. Results: Retrospective results featured a slice‐by‐slice comparison of the slice‐encoded images with UNCLE SAM. UNCLE SAM's subtraction from the slice‐encoded image was compared with a subtraction from the flow‐corrupted 2D image, to demonstrate UNCLE SAM's capability to unfold outflowing spins. UNCLE SAM's comparison with slice encoding showed that UNCLE SAM was able to unfold up to 74% of what slice encoding achieved. Prospective results showed significant reduction in outflow effects with only a marginal increase in scan time from the 2D acquisition. Conclusions: We developed a method that effectively unfolds most outflowing spins from corrupting the target slice and does not require the explicit use of slice‐encoding gradients. This development offers a method to reduce most outflow effects from the target slice within a clinically feasible scan duration compared with the fully sampled slice‐encoding technique. [ABSTRACT FROM AUTHOR]

BackgroundImproving the signal-to-noise ratio (SNR) of chemical-shift-encoded MRI acquisition with complex reconstruction (MRI-C) may improve the accuracy and precision of noninvasive proton density fat fraction (PDFF) quantification in patients with hepatic steatosis.PurposeTo assess the accuracy of high SNR (Hi-SNR) MRI-C versus standard MRI-C acquisition to estimate hepatic PDFF in adult and pediatric nonalcoholic fatty liver disease (NAFLD) using an MR spectroscopy (MRS) sequence as the reference standard.Study typeProspective.Population/subjectsIn all, 231 adult and pediatric patients with known or suspected NAFLD.Field strength/sequencePDFF estimated at 3T by three MR techniques: standard MRI-C; a Hi-SNR MRI-C variant with increased slice thickness, decreased matrix size, and no parallel imaging; and MRS (reference standard).AssessmentMRI-PDFF was measured by image analysts using a region of interest coregistered with the MRS-PDFF voxel.Statistical testsLinear regression analyses were used to assess accuracy and precision of MRI-estimated PDFF for MRS-PDFF as a function of MRI-PDFF using the standard and Hi-SNR MRI-C for all patients and for patients with MRS-PDFF

The purpose of this work was to investigate sources of bias in magnetic resonance imaging (MRI) liver fat quantification that lead to a dependence of the proton density fat fraction (PDFF) on the number of echoes. This was a retrospective analysis of liver MRI data from 463 subjects. The magnitude signal variation with TE from spoiled gradient echo images was curve fitted to estimate the PDFF using a model that included monoexponential R2 * decay and a multi-peak fat spectrum. Additional corrections for non-exponential decay (Gaussian), bi-exponential decay, degree of fat saturation, water frequency shift and noise bias were introduced. The fitting error was minimized with respect to 463 × 3 = 1389 subject-specific parameters and seven additional parameters associated with these corrections. The effect on PDFF was analyzed, notably the dependence on the number of echoes. The effects on R2 * were also analyzed. The results showed that the inclusion of bias corrections resulted in an increase in the quality of fit (r2 ) in 427 of 463 subjects (i.e. 92.2%) and a reduction in the total fitting error (residual norm) of 43.6%. This was largely a result of the Gaussian decay (57.8% of the reduction), fat spectrum (31.0%) and biexponential decay (8.8%) terms. The inclusion of corrections was also accompanied by a decrease in the dependence of PDFF on the number of echoes. Similar analysis of R2 * showed a decrease in the dependence on the number of echoes. Comparison of PDFF with spectroscopy indicated excellent agreement before and after correction, but the latter exhibited lower bias on a Bland-Altman plot (1.35% versus 0.41%). In conclusion, correction for known and expected biases in PDFF quantification in liver reduces the fitting error, decreases the dependence on the number of echoes and increases the accuracy.

Purpose: To develop a new sequence to simultaneously acquire Cartesian sodium (23Na) MRI and accelerated Cartesian single (SQ) and triple quantum (TQ) sodium MRI of in vivo human brain at 7 T by leveraging two dedicated low‐rank reconstruction frameworks. Theory and Methods: The Double Half‐Echo technique enables short echo time Cartesian 23Na MRI and acquires two k‐space halves, reconstructed by a low‐rank coupling constraint. Additionally, three‐dimensional (3D) 23Na Multi‐Quantum Coherences (MQC) MRI requires multi‐echo sampling paired with phase‐cycling, exhibiting a redundant multidimensional space. Simultaneous Autocalibrating and k‐Space Estimation (SAKE) were used to reconstruct highly undersampled 23Na MQC MRI. Reconstruction performance was assessed against five‐dimensional (5D) CS, evaluating structural similarity index (SSIM), root mean squared error (RMSE), signal‐to‐noise ratio (SNR), and quantification of tissue sodium concentration and TQ/SQ ratio in silico, in vitro, and in vivo. Results: The proposed sequence enabled the simultaneous acquisition of fully sampled 23Na MRI while leveraging prospective undersampling for 23Na MQC MRI. SAKE improved TQ image reconstruction regarding SSIM by 6% and reduced RMSE by 35% compared to 5D CS in vivo. Thanks to prospective undersampling, the spatial resolution of 23Na MQC MRI was enhanced from 8×8×15$$ 8\times 8\times 15 $$ mm3 to 8×8×8$$ 8\times 8\times 8 $$ mm3 while reducing acquisition time from 2×31$$ 2\times 31 $$ min to 2×23$$ 2\times 23 $$ min. Conclusion: The proposed sequence, coupled with low‐rank reconstructions, provides an efficient framework for comprehensive whole‐brain sodium MRI, combining TSC, T2*, and TQ/SQ ratio estimations. Additionally, low‐rank matrix completion enables the reconstruction of highly undersampled 23Na MQC MRI, allowing for accelerated acquisition or enhanced spatial resolution. [ABSTRACT FROM AUTHOR]

PurposeTo investigate in adults the associations between histologic features of nonalcoholic fatty liver disease (NAFLD) and quantitative measures derived from diffusion-weighted imaging (DWI).Materials and methodsEighty-nine adults undergoing standard-of-care liver biopsy for NAFLD were recruited for DWI. Biopsies were scored for histologic features of NAFLD. DWI was performed using b-values of 0, 100, and 500 s/mm(2) . Images were reconstructed using either conventional magnitude averaging (CMA) or a method to address bulk motion artifacts (Beta*LogNormal, BLN). The apparent diffusion coefficient (ADC) and the diffusivity (D) and perfusion fraction (F) of the intravoxel incoherent motion (IVIM) model were measured in the right hepatic lobe using both reconstructions. Associations between histologic features and DWI-derived measures were tested statistically with several methods including multiple linear regression.ResultsUsing CMA and BLN reconstructions, respectively, the means (and ranges) were 1.7 (1.1-3.5) and 1.4 (1.0-3.2) × 10(-3) mm(2) /s for ADC, 1.1 (0.84-1.4) and 0.84 (0.53-1.1) × 10(-3) mm(2) /s for D, and 17 and 18 (2.3-35)% for F. For both reconstruction methods, D decreased with steatosis and F decreased with fibrosis (P < 0.05). ADC was not independently associated with any histologic feature.ConclusionSteatosis and fibrosis have significant independent effects on D and F in adults undergoing biopsy for NAFLD.

The purpose of this study was to evaluate a magnetic resonance imaging (MRI) technique for quantifying the proton density water fraction (PDWF) as a biomarker of bone marrow cellularity. Thirty-six human bone marrow specimens from 18 donors were excised and subjected to different measurements of tissue composition: PDWF quantification using a multiple gradient echo MRI technique, three biochemical assays (triglyceride, total lipid and water content) and a histological assessment of cellularity. Results showed a strong correlation between PDWF and bone marrow cellularity from histology (r=0.72). A strong correlation was also found between PDWF and the biochemical assay of water content (r=0.76). These results suggest the PDWF is a predictor of bone marrow cellularity in tissues and can provide a non-invasive assessment of bone marrow changes in clinical patients undergoing radiotherapy.

PurposeTo quantify changes in bone marrow fat fraction and determine associations with peripheral blood cell counts.Methods and materialsIn this prospective study, 19 patients received either highly myelotoxic treatment (radiation therapy plus cisplatin, 5-fluorouracil mitomycin C [FU/MMC], or cisplatin/5-FU/cetuximab) or less myelotoxic treatment (capecitabine-radiation therapy or no concurrent chemotherapy). Patients underwent MR imaging and venipuncture at baseline, midtreatment, and posttreatment visits. We performed mixed effects modeling of the mean proton density fat fraction (PDFF[%]) by linear time, treatment, and vertebral column region (lumbar [L]4-sacral [S]2 vs thoracic [T]10-L3 vs cervical[C]3-T9), while controlling for cumulative mean dose and other confounders. Spearman rank correlations were performed by white blood cell (WBC) counts versus the differences in PDFF(%) before and after treatment.ResultsCumulative mean dose was associated with a 0.43% per Gy (P=.004) increase in PDFF(%). In the highly myelotoxic group, we observed significant changes in PDFF(%) per visit within L4-S2 (10.1%, P

Ultra-high contrast (UHC) MRI describes forms of MRI in which little or no contrast is seen on conventional MRI images but very high contrast is seen with UHC techniques. One of these techniques uses the divided subtracted inversion recovery (dSIR) sequence, which, in modelling studies, can produce ten times the contrast of conventional inversion recovery (IR) sequences. When used in cases of mild traumatic brain injury (mTBI), the dSIR sequence frequently shows extensive abnormalities in white matter that appears normal when imaged with conventional T2-fluid-attenuated IR (T2-FLAIR) sequences. The changes are bilateral and symmetrical in white matter of the cerebral and cerebellar hemispheres. They partially spare the anterior and posterior central corpus callosum and peripheral white matter of the cerebral hemispheres and are described as the whiteout sign. In addition to mTBI, the whiteout sign has also been seen in methamphetamine use disorder and Grinker's myelinopathy (delayed post-hypoxic leukoencephalopathy) in the absence of abnormalities on T2-FLAIR images, and is a central component of post-insult leukoencephalopathy syndromes. This paper describes the concept of ultra-high contrast MRI, the whiteout sign, the theory underlying the use of dSIR sequences and post-insult leukoencephalopathy syndromes. [ABSTRACT FROM AUTHOR]