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Background: Diffusion-weighted imaging (DWI) provides quantitative measurement of random water displacement in tissue as calculated by the apparent diffusion coefficient (ADC). While heavily utilized in stroke and oncology applications, DWI is a promising tool to map microstructural changes in musculoskeletal applications including evaluation of synovial reactions resulting from total hip arthroplasty (THA). One major challenge facing the application of DWI in THA is the significant artifacts related to the conventional echo-planar imaging (EPI) readout used. Multispectral imaging (MSI) techniques, including the multiacquisition with variable resonance image combination (MAVRIC), have been shown to effectively reduce metallic susceptibility artifacts around total joint replacements to render clinically useful images. Recently, a 2D periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) FSE acquisition that incorporates a diffusion preparation pulse with 2D-MAVRIC has been developed to mitigate both distortion and dropout artifacts. While there have been some preliminary assessments of DWI-MAVRIC, the repeatability of DWI-MAVRIC and the effects of key parameters, such as the number of spectral bins, are unknown., Purpose: To evaluate the quantitative accuracy of DWI-MAVRIC as compared to conventional diffusion sequences., Methods: A diffusion phantom with different reference diffusivities (ADC = 113-1123 μm 2 /s) was used. Scans were performed on two 1.5T MRI scanners. DWI-EPI and DWI-MAVRIC were acquired in both the axial and coronal planes. Three spatial offsets (0 cm, 10 cm left, and 10 cm right off iso-center) were used to evaluate effects of off-isocenter positioning. To assess intraday and interday repeatability, DWI-EPI and DWI-MAVRIC acquisitions were repeated on one scanner at same-day and 9-month intervals. To assess inter-scanner repeatability, DWI-EPI and DWI-MAVRIC acquisitions were compared between two scanners. ADC maps were generated with and without gradient nonlinearity correction (GNC). Linear regression, correlation, and error statistics were determined between calculated and reference ADC values. Bland-Altman plots were generated to evaluate intraday, interday, and interscanner repeatability., Results: DWI-MAVRIC had excellent correlation to reference values but at reduced linearity (r = 1.00, slope = 0.91-0.94) as compared to DWI-EPI (r = 1.00, slope = 0.99-1.01). A greater than 5% ADC bias was observed at the lowest ADC values, predominantly in the DWI-MAVRIC scans. ADC values did not vary with DWI-MAVRIC parameters. DWI-EPI acquisitions had intraday, interday, and interscanner repeatability of 3.18 μm 2 /s, 19.2 μm 2 /s, and 20.2 μm 2 /s, respectively. DWI-MAVRIC acquisitions had inferior intraday, interday, and interscanner repeatability of 13.3 μm 2 /s, 44.7 μm 2 /s, 110 μm 2 /s, respectively. Lower ADC errors were found at isocenter, as compared to the left and right positions. GNC reduced the absolute error by 0.31% ± 0.89%, 3.6% ± 1.4%, 0.65% ± 2.4% for the center, left, and right positions, respectively., Conclusions: DWI-MAVRIC provides good linearity with respect to reference values and good intra- and interday repeatability., (© 2022 American Association of Physicists in Medicine.)

The study aims to test the long-term stability of gradient characteristics for model-based correction of diffusion weighting (DW) bias in an apparent diffusion coefficient (ADC) for multisite imaging trials. Single spin echo (SSE) DWI of a long-tube ice-water phantom was acquired quarterly on six MR scanners over two years for individual diffusion gradient channels, along with B0 mapping, as a function of right-left (RL) and superior-inferior (SI) offsets from the isocenter. Additional double spin-echo (DSE) DWI was performed on two systems. The offset dependences of derived ADC were fit to 4th-order polynomials. Chronic shim gradients were measured from spatial derivatives of B0 maps along the tube direction. Gradient nonlinearity (GNL) was modeled using vendor-provided gradient field descriptions. Deviations were quantified by root-mean-square differences (RMSD), normalized to reference ice-water ADC, between the model and reference (RMSDREF), measurement and model (RMSDEXP), and temporal measurement variations (RMSDTMP). Average RMSDREF was 4.9 ± 3.2 (%RL) and -14.8 ± 3.8 (%SI), and threefold larger than RMSDEXP. RMSDTMP was close to measurement errors (~3%). GNL-induced bias across gradient systems varied up to 20%, while deviation from the model accounted at most for 6.5%, and temporal variation for less than 3% of ADC reproducibility error. Higher SSE RMSDEXP = 7.5-11% was reduced to 2.5-4.8% by DSE, consistent with the eddy current origin. Measured chronic shim gradients below 0.1 mT/m had a minor contribution to ADC bias. The demonstrated long-term stability of spatial ADC profiles and consistency with system GNL models justifies retrospective and prospective DW bias correction based on system gradient design models. Residual errors due to eddy currents and shim gradients should be corrected independent of GNL.

Purpose: To empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations., Methods: Spatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients. To illustrate spatial impact of GNL on ADC, diffusion weighted imaging using three orthogonal gradient directions was performed on a volunteer brain positioned at isocenter (as a reference) and offset superiorly by 10-17 cm (>10% predicted GNL bias). The SPH tensor-based GNL correction was applied to individual DWI gradient directions, and derived ADC was compared with low-bias reference for human brain white matter (WM) ROIs., Results: Empiric and predicted GNL errors were comparable for all three studied 3T MR systems, with <1.0% differences in the median and width of spatial histograms for individual GNL tensor elements. Median (±width) of ADC (10 -3 mm 2 /s) histograms measured at isocenter in WM reference ROIs from three MR systems were: 0.73 ± 0.11, 0.71 ± 0.14, 0.74 ± 0.17, and at off-isocenters (before versus after GNL correction) were respectively 0.63 ± 0.14 versus 0.72 ± 0.11, 0.53 ± 0.16 versus 0.74 ± 0.18, and 0.65 ± 0.16 versus 0.76 ± 0.18., Conclusion: The phantom-based spatial distortion measurements validated vendor-provided gradient fields, and accurate WM ADC was recovered regardless of spatial locations and clinical MR platforms using system-specific tensor-based GNL correction for routine DWI., (Crown Copyright © 2021. Published by Elsevier Ltd. All rights reserved.)

Background: Multi-b-valued/multi-shell diffusion provides potentially valuable metrics in breast MRI but suffers from low signal-to-noise ratio and has potentially long scan times., Purpose: To investigate the effects of model-based denoising with no loss of spatial resolution on multi-shell breast diffusion MRI; to determine the effects of downsampling on multi-shell diffusion; and to quantify these effects in multi-b-valued (three directions per b-value) acquisitions., Study Type: Prospective ("fully-sampled" multi-shell) and retrospective longitudinal (multi-b)., Subjects: One normal subject (multi-shell) and 10 breast cancer subjects imaging at four timepoints (multi-b)., Field Strength/sequence: 3T multi-shell acquisition and 1.5T multi-b acquisition., Assessment: The "fully-sampled" multi-shell acquisition was retrospectively downsampled to determine the bias and error from downsampling. Mean, axial/parallel, radial diffusivity, and fractional anisotropy (FA) were analyzed. Denoising was applied retrospectively to the multi-b-valued breast cancer subject dataset and assessed subjectively for image noise level and tumor conspicuity., Statistical Tests: Parametric paired t-test (P < 0.05 considered statistically significant) on mean and coefficient of variation of each metric-the apparent diffusion coefficient (ADC) from all b-values, fast ADC, slow ADC, and perfusion fraction. Paired and two-sample t-tests for each metric comparing normal and tumor tissue., Results: In the multi-shell data, denoising effectively suppressed FA (-45% to -78%), with small biases in mean diffusivity (-5% in normal, +23% in tumor, and -4% in vascular compartments). In the multi-b data, denoising resulted in small biases to the ADC metrics in tumor and normal contralateral tissue (by -3% to +11%), but greatly reduced the coefficient of variation for every metric (by -1% to -24%). Denoising improved differentiation of tumor and normal tissue regions in most metrics and timepoints; subjectively, image noise level and tumor conspicuity were improved in the fast ADC maps., Data Conclusion: Model-based denoising effectively suppressed erroneously high FA and improved the accuracy of diffusivity metrics., Evidence Level: 3 TECHNICAL EFFICACY STAGE: 1., (© 2020 International Society for Magnetic Resonance in Medicine.)

Purpose: We investigate the importance of high gradient-amplitude and high slew-rate on oscillating gradient spin echo (OGSE) diffusion imaging for human brain imaging and evaluate human brain imaging with OGSE on the MAGNUS head-gradient insert (200 mT/m amplitude and 500 T/m/s slew rate)., Methods: Simulations with cosine-modulated and trapezoidal-cosine OGSE at various gradient amplitudes and slew rates were performed. Six healthy subjects were imaged with the MAGNUS gradient at 3T with OGSE at frequencies up to 100 Hz and b = 450 s/mm 2 . Comparisons were made against standard pulsed gradient spin echo (PGSE) diffusion in vivo and in an isotropic diffusion phantom., Results: Simulations show that to achieve high frequency and b-value simultaneously for OGSE, high gradient amplitude, high slew rates, and high peripheral nerve stimulation limits are required. A strong linear trend for increased diffusivity (mean: 8-19%, radial: 9-27%, parallel: 8-15%) was observed in normal white matter with OGSE (20 Hz to 100 Hz) as compared to PGSE. Linear fitting to frequency provided excellent correlation, and using a short-range disorder model provided radial long-term diffusivities of D ∞,MD = 911 ± 72 µm 2 /s, D ∞,PD = 1519 ± 164 µm 2 /s, and D ∞,RD = 640 ± 111 µm 2 /s and correlation lengths of l c ,MD = 0.802 ± 0.156 µm, l c ,PD = 0.837 ± 0.172 µm, and l c ,RD = 0.780 ± 0.174 µm. Diffusivity changes with OGSE frequency were negligible in the phantom, as expected., Conclusion: The high gradient amplitude, high slew rate, and high peripheral nerve stimulation thresholds of the MAGNUS head-gradient enables OGSE acquisition for in vivo human brain imaging., (© 2020 International Society for Magnetic Resonance in Medicine.)

The presented analysis of multisite, multiplatform clinical oncology trial data sought to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric, derived from diffusion-weighted magnetic resonance imaging, by reducing technical interplatform variability owing to systematic gradient nonlinearity (GNL). This study tested the feasibility and effectiveness of a retrospective GNL correction (GNC) implementation for quantitative quality control phantom data, as well as in a representative subset of 60 subjects from the ACRIN 6698 breast cancer therapy response trial who were scanned on 6 different gradient systems. The GNL ADC correction based on a previously developed formalism was applied to trace-DWI using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. For quantitative DWI phantom images acquired in typical breast imaging positions, the GNC improved interplatform accuracy from a median of 6% down to 0.5% and reproducibility of 11% down to 2.5%. Across studied trial subjects, GNC increased low ADC (<1 µm 2 /ms) tumor volume by 16% and histogram percentiles by 5%-8%, uniformly shifting percentile-dependent ADC thresholds by ∼0.06 µm 2 /ms. This feasibility study lays the grounds for retrospective GNC implementation in multiplatform clinical imaging trials to improve accuracy and reproducibility of ADC metrics used for breast cancer treatment response prediction., (© 2020 The Authors. Published by Grapho Publications, LLC.)

Background: Gradient nonlinearity (GNL) leads to biased apparent diffusion coefficients (ADCs) in diffusion-weighted imaging. A gradient nonlinearity correction (GNLC) method has been developed for whole body systems, but is yet to be tested for the new compact 3T (C3T) scanner, which exhibits more complex GNL due to its asymmetrical design., Purpose: To assess the improvement of ADC quantification with GNLC for the C3T scanner., Study Type: Phantom measurements and retrospective analysis of patient data., Phantom/subjects: A diffusion quality control phantom with vials containing 0-30% polyvinylpyrrolidone in water was used. For in vivo data, 12 patient exams were analyzed (median age, 33)., Field Strength/sequence: Imaging was performed on the C3T and two commercial 3T scanners. A clinical DWI (repetition time [TR] = 10,000 msec, echo time [TE] = minimum, b = 1000 s/mm 2 ) sequence was used for phantom imaging and 10 patient cases and a clinical DTI (TR = 6000-10,000 msec, TE = minimum, b = 1000 s/mm 2 ) sequence was used for two patient cases., Assessment: The 0% vial was measured along three orthogonal axes, and at two different temperatures. The ADC for each concentration was compared between the C3T and two whole-body scanners. Cerebrospinal fluid and white matter ADCs were quantified for each patient and compared to values in literature., Statistical Tests: Paired t-test and two-way analysis of variance (ANOVA)., Results: For all PVP concentrations, the corrected ADC was within 2.5% of the reference ADC. On average, the ADC of cerebrospinal fluid and white matter post-GNLC were within 1% and 6%, respectively, of values reported in the literature and were significantly different from the uncorrected data (P < 0.05)., Data Conclusion: This study demonstrated that GNL effects were more severe for the C3T due to the asymmetric gradient design, but our implementation of a GNLC compensated for these effects, resulting in ADC values that are in good agreement with values from the literature., Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1498-1507., (© 2018 International Society for Magnetic Resonance in Medicine.)

Purpose: To investigate the feasibility of substantially reducing acoustic noise while performing diffusion tensor imaging (DTI) on a compact 3T (C3T) MRI scanner equipped with a 42-cm inner-diameter asymmetric gradient., Methods: A-weighted acoustic measurements were made using 10 mT/m-amplitude sinusoidal waveforms, corresponding to echo-planar imaging (EPI) echo spacing of 0.25 to 5.0 ms, on a conventional, whole-body 3T MRI and on the C3T. Acoustic measurements of DTI with trapezoidal EPI waveforms were then made at peak gradient performance on the C3T (80 mT/m amplitude, 700 T/m/s slew rate) and at derated performance (33 mT/m, 10 to 50 T/m/s) for acoustic noise reduction. DTI was acquired in two different phantoms and in seven human subjects, with and without gradient-derating corresponding to multi- and single-shot acquisitions, respectively., Results: Sinusoidal waveforms on the C3T were quieter by 8.5 to 15.6 A-weighted decibels (dBA) on average as compared to the whole-body MRI. The derated multishot DTI acquisition noise level was only 8.7 dBA (at 13 T/m/s slew rate) above ambient, and was quieter than non-derated, single-shot DTI by 22.3 dBA; however, the scan time was almost quadrupled. Although derating resulted in negligible diffusivity differences in the phantoms, small biases in diffusivity measurements were observed in human subjects (apparent diffusion coefficient = +9.3 ± 8.8%, fractional anisotropy = +3.2 ± 11.2%, radial diffusivity = +9.4 ± 16.8%, parallel diffusivity = +10.3 ± 8.4%)., Conclusion: The feasibility of achieving reduced acoustic noise levels with whole-brain DTI on the C3T MRI was demonstrated. Magn Reson Med 79:2902-2911, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: Diffusion MRI often suffers from low signal-to-noise ratio, especially for high b-values. This work proposes a model-based denoising technique to address this limitation., Methods: A generalization of the multi-shell spherical deconvolution model using a Richardson-Lucy algorithm is applied to noisy data. The reconstructed coefficients are then used in the forward model to compute denoised diffusion-weighted images (DWIs). The proposed method operates in the diffusion space and thus is complementary to image-based denoising methods., Results: We demonstrate improved image quality on the DWIs themselves, maps of neurite orientation dispersion and density imaging, and diffusional kurtosis imaging (DKI), as well as reduced spurious peaks in deterministic tractography. For DKI in particular, we observe up to 50% error reduction and demonstrate high image quality using just 30 DWIs. This corresponds to greater than fourfold reduction in scan time if compared to the widely used 140-DWI acquisitions. We also confirm consistent performance in pathological data sets, namely in white matter lesions of a multiple sclerosis patient., Conclusion: The proposed denoising technique termed generalized spherical deconvolution has the potential of significantly improving image quality in diffusion MRI. Magn Reson Med 78:2428-2438, 2017. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: To compare the effectiveness of prospective, retrospective, and combined (prospective + retrospective) EPI distortion correction methods in bilateral breast diffusion-weighted imaging (DWI) scans., Methods: Five healthy female subjects underwent an axial bilateral breast DWI exam with and without prospective B 0 inhomogeneity correction using slice-by-slice linear shimming. In each case, an additional b=0 DWI scan was performed with the polarity of the phase-encoding gradient reversed, to generate an estimated B 0 map; this map or a separately acquired B 0 map was used for retrospective correction, either alone or in combination with the prospective correction. The alignment between an undistorted, anatomical reference scan with similar contrast and the corrected b=0 DWI images with different correction schemes was assessed., Results: The average cross-correlation coefficient between the DWI images and the anatomical reference scan was increased from 0.82 to 0.92 over the five volunteers when combined prospective and retrospective distortion correction was applied. Furthermore, such correction substantially reduced patient-to-patient variation of the image alignment and the variability of the average apparent diffusion coefficient in normal glandular tissue., Conclusion: Combined prospective and retrospective distortion correction can provide an efficient way to reduce susceptibility-induced image distortions and enhance the reliability of breast DWI exams. Magn Reson Med 78:247-253, 2017. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: To compare compressed diffusion spectrum imaging (CS-DSI) with diffusion tensor imaging (DTI) in patients with intracranial masses. We hypothesized that CS-DSI would provide superior visualization of the motor and language tracts., Materials and Methods: We retrospectively analyzed 25 consecutive patients with intracranial masses who underwent DTI and CS-DSI for preoperative planning. Directionally-encoded anisotropy maps, and streamline hand corticospinal motor tracts and arcuate fasciculus language tracts were graded according to a 3-point scale. Tract counts, anisotropy, and lengths were also calculated. Comparisons were made using exact marginal homogeneity, McNemar's and Wilcoxon signed-rank tests., Results: Readers preferred the CS-DSI over DTI anisotropy maps in 92% of the cases, and the CS-DSI over DTI tracts in 84%. The motor tracts were graded as excellent in 80% of cases for CS-DSI versus 52% for DTI; 58% of the motor tracts graded as acceptable in DTI were graded as excellent in CS-DSI (p=0.02). The language tracts were graded as excellent in 68% for CS-DSI versus none for DTI; 78% of the language tracts graded as acceptable by DTI were graded as excellent by CS-DSI (p<0.001). CS-DSI demonstrated smaller normalized mean differences than DTI for motor tract counts, anisotropy and language tract counts (p≤0.01)., Conclusion: CS-DSI was preferred over DTI for the evaluation of motor and language white matter tracts in patients with intracranial masses. Results suggest that CS-DSI may be more useful than DTI for preoperative planning purposes., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: Diffusional kurtosis imaging (DKI) is an approach to characterizing the non-Gaussian fraction of water diffusion in biological tissue. However, DKI is highly susceptible to the low signal-to-noise ratio of diffusion-weighted images, causing low precision and a significant bias due to Rician noise distribution. Here, we evaluate precision and bias using weighted linear least squares fitting of different acquisition schemes including several multishell schemes, a diffusion spectrum imaging (DSI) scheme, as well as a compressed sensing reconstruction of undersampled DSI scheme., Methods: Monte Carlo simulations were performed to study the three-dimensional distribution of the apparent kurtosis coefficient (AKC). Experimental data were acquired from one healthy volunteer with multiple repetitions, using the same acquisition schemes as for the simulations., Results: The angular distribution of the bias and precision were very inhomogeneous. While axial kurtosis was significantly overestimated, radial kurtosis was underestimated. The precision of radial kurtosis was up to 10-fold lower than axial kurtosis., Conclusion: The noise bias behavior of DKI is highly complex and can cause overestimation as well as underestimation of the AKC even within one voxel. The acquisition scheme with three shells, suggested by Poot et al, provided overall the best performance. Magn Reson Med 76:1684-1696, 2016. © 2016 International Society for Magnetic Resonance in Medicine., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: To evaluate a gradient nonlinearity correction (GNC) program for quantitative apparent diffusion coefficient (ADC) measurements on phantom and human subject diffusion-weighted (DW) magnetic resonance imaging (MRI) scans in a multicenter breast cancer treatment response study, Materials and Methods: A GNC program using fifth-order spherical harmonics for gradient modeling was applied retrospectively to qualification phantom and human subject scans. Ice-water phantoms of known diffusion coefficient were scanned at five different study centers with different scanners and receiver coils. Human in vivo data consisted of baseline and early-treatment exams on 54 patients from four sites. ADC maps were generated with and without GNC. Regions of interest were defined to quantify absolute errors and changes with GNC over breast imaging positions., Results: Phantom ADC errors varied with region of interest (ROI) position and scanner configuration; the mean error by configuration ranged from 1.4% to 19.9%. GNC significantly reduced the overall mean error for all sites from 9.9% to 0.6% (P = 0.016). Spatial dependence of GNC was highest in the right-left (RL) and anterior-posterior (AP) directions. Human subject mean tumor ADC was reduced 0.2 to 12% by GNC at different sites. By regression, every 1-cm change in tumor ROI position between baseline and follow-up visits resulted in an estimated change of 2.4% in the ADC early-treatment response measurement., Conclusion: GNC is effective for removing large, system-dependent errors in quantitative breast DWI. GNC may be important in ensuring reproducibility in multicenter studies and in reducing errors in longitudinal treatment response measures arising from spatial variations in tumor position between visits., (© 2015 Wiley Periodicals, Inc.)

Purpose: To provide an improved correction for gradient nonlinearity (GN) effects in diffusion-weighted imaging (DWI). These effects produce spatially varying apparent diffusion coefficient (ADC), a result that will be significant in large field-of-view imaging, and may be confounded by distortion and concomitant fields related to the DWI acquisition., Materials and Methods: The effect of more accurate gradient field maps on GN correction (GNC) of ADC was evaluated. A simulation compared GN effects in commonly imaged anatomy. A temperature-controlled phantom was imaged at positions 0 cm and 11 cm from isocenter and in two whole-body MRI systems at 1.5T with different patient bore diameters (55 cm and 60 cm). Varying correction methods were applied to determine the errors from spatial variance and interscanner reproducibility., Results: As compared to conventional fifth-order spherical harmonics, a seventh-order GNC improved ADC accuracy by 1%. The combination of GNC with a dual-spin-echo pulse sequence and a retrospective concomitant field correction reduced ADC error due to spatial variance from 9.5% to 1.8% (55 cm bore) and from 4.2% to 1.8% (60 cm bore). The error in ADC attributed to interscanner reproducibility was reduced from 5.8% to 0.15% (at isocenter) and from 10% to 0.63% (11 cm from isocenter)., Conclusion: GNC in DWI improved spatial accuracy and interscanner reproducibility of ADC., (Copyright © 2012 Wiley Periodicals, Inc.)

Conventional quantitative diffusion-weighted imaging (DWI) is sensitive to changes in tissue microstructure, but its application to evaluating patients with orthopaedic hardware has generally been limited due to metallic susceptibility artifacts. The apparent diffusion coefficient (ADC) and T 2 -values from a multi-spectral imaging (MSI) DWI combined with 2D multi-spectral imaging with a 2D periodically rotated overlapping parallel lines with enhanced reconstruction (2D-MSI PROPELLER DWI) based sequence and a MAVRIC based T 2 mapping sequence, respectively, may mitigate the artifact and provide additional quantitative information on synovial reactions in individuals with total hip arthroplasty (THA). The aim of this pilot study is to utilize a 2D-MSI PROPELLER DWI and a MAVRIC-based T 2 mapping to evaluate ADC and T 2 -values of synovial reactions in patients with THA. Coronal morphologic MRIs from THA patients underwent evaluation of the synovium and were assigned a synovial classification of 'normal', or 'grouped abnormal' (consisting of sub-groups 'infection', 'polymeric', 'metallosis', 'adverse local tissue reaction' [ALTR], or 'non-specific') and type of synovial reaction present (fluid-like, solid-like, or mixed). Regions of interest (ROIs) were placed in synovial reactions for measurement of ADC and T 2 -values, obtained from the 2D-MSI PROPELLER DWI and T 2 -MAVRIC sequences, respectively. A one-way analysis of variance (ANOVA) and Kruskal-Wallis rank sum tests were used to compare the differences in ADC and T 2 -values across the different synovial reaction classifications. A Kruskal-Wallis test was used to compare the ROI areas for the ADC and T 2 -values. A principal component analysis (PCA) was performed to evaluate the possible effects of ADC values, size of the ADC ROI, T 2 -values, and size of the T 2 ROI with respect to synovial reaction classification. Differences of ADC and T 2 among the individual synovial reactions were not found. A difference of ADC between 'normal' and 'grouped abnormal' synovial reactions was also not detected even as the ADC area of 'grouped abnormal' synovial reactions were significantly larger (p = 0.02). The 'grouped abnormal' synovial reactions had significantly shorter T 2 -values than 'normal' synovial reactions (p = 0.02), and that the T 2 area of 'grouped abnormal' synovial reactions were significantly larger (p = 0.01). A larger ROI area on the T 2 -maps was observed in the mixed synovial reaction type as compared to the fluid-like reaction type area (p = 0.01). Heterogeneity was noted in calculated ADC and T 2 maps. PCA analysis revealed obvious clustering by the 'normal' and 'grouped abnormal' classifications. 2D-MSI PROPELLER DWI and MAVRIC-T 2 generate quantitative images of periprosthetic tissues within clinically feasible scan times. The combination of derived ADC and T 2 -values with area of synovial reaction may aid in differentiating normal from abnormal synovial reactions between types of synovial reactions in patients with THA. [ABSTRACT FROM AUTHOR]

Background: Quantitative diffusion MRI is a promising technique for evaluating peripheral nerve integrity but low signal-to-noise ratio (SNR) can impede measurement accuracy.Purpose: To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to improve within-subject reproducibility and peripheral nerve conspicuity.Study Type: Prospective.Subjects: Seven healthy volunteers and three peripheral neuropathy patients.Field Strength/sequence: 3T/multiband single-shot echo planar diffusion sequence using multishell 55-direction scheme.Assessment: Images were processed using four methods: "original" (no denoising), "average" (10 repetitions), "PCA-only," and "PCA + genSD." Tibial and common peroneal nerve segmentations and masks were generated from volunteer diffusion data. Quantitative (SNR and contrast-to-noise ratio [CNR]) values were calculated. Three radiologists qualitatively evaluated nerve conspicuity for each method. The two denoising methods were also performed in three patients with peripheral neuropathies.Statistical Tests: For healthy volunteers, calculations included SNR and CNRFA (computed using FA values). Coefficient of variation (CV%) of CNRFA quantified within-subject reproducibility. Groups were compared with two-sample t-tests (significance P < 0.05; two-tailed, Bonferroni-corrected). Odds ratios (ORs) quantified the relative rates of each of three radiologists confidently identifying a nerve, per slice, for the four methods.Results: "PCA + genSD" yielded the highest SNR (meanoverall = 14.83 ± 1.99) and tibial and common peroneal nerve CNRFA (meantibial = 3.45, meanperoneal = 2.34) compared to "original" (P SNR < 0.001; P CNR = 0.011) and "PCA-only" (P SNR < 0.001, P CNR < 0.001). "PCA + genSD" had higher within-subject reproducibility (low CV%) for tibial (6.04 ± 1.98) and common peroneal nerves (8.27 ± 2.75) compared to "original" and "PCA-only." The mean FA was higher for "original" than "average" (P < 0.001), but did not differ significantly between "average" and "PCA + genSD" (P = 0.14). "PCA + genSD" had higher tibial and common peroneal nerve conspicuity than "PCA-only" (ORtibial = 2.50, P < 0.001; ORperoneal = 1.86, P < 0.001) and "original" (ORtibial = 2.73, P < 0.001; ORperoneal = 2.43, P < 0.001).Data Conclusion: PCA + genSD denoising method improved SNR, CNRFA , and within-subject reproducibility (CV%) without biasing FA and nerve conspicuity. This technique holds promise for facilitating more reliable, unbiased diffusion measurements of peripheral nerves.Level Of Evidence: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1128-1137. [ABSTRACT FROM AUTHOR]

• Simultaneously high b -value and frequency OGSE diffusion encoding are achieved. • The frequency dependences of diffusivity and kurtosis are studied for human brains. • The effects of gradient nonlinearity on frequency-dependent DKI measures are studied. • A trend of decreasing kurtosis over frequency is captured for in vivo human brains. Measuring the time/frequency dependence of diffusion MRI is a promising approach to distinguish between the effects of different tissue microenvironments, such as membrane restriction, tissue heterogeneity, and compartmental water exchange. In this study, we measure the frequency dependence of diffusivity (D) and kurtosis (K) with oscillating gradient diffusion encoding waveforms and a diffusion kurtosis imaging (DKI) model in human brains using a high-performance, head-only MAGNUS gradient system, with a combination of b -values, oscillating frequencies (f), and echo time that has not been achieved in human studies before. Frequency dependence of diffusivity and kurtosis are observed in both global and local white matter (WM) and gray matter (GM) regions and characterized with a power-law model ∼Λ* f θ. The frequency dependences of diffusivity and kurtosis (including changes between f min and f max , Λ, and θ) vary over different WM and GM regions, indicating potential microstructural differences between regions. A trend of decreasing kurtosis over frequency in the short-time limit is successfully captured for in vivo human brains. The effects of gradient nonlinearity (GNL) on frequency-dependent diffusivity and kurtosis measurements are investigated and corrected. Our results show that the GNL has prominent scaling effects on the measured diffusivity values (3.5∼5.5% difference in the global WM and 6∼8% difference in the global cortex) and subsequently affects the corresponding power-law parameters (Λ, θ) while having a marginal influence on the measured kurtosis values (<0.05% difference) and power-law parameters (Λ, θ). This study expands previous OGSE studies and further demonstrates the translatability of frequency-dependent diffusivity and kurtosis measurements to human brains, which may provide new opportunities to probe human brain microstructure in health and disease. [ABSTRACT FROM AUTHOR]