Oscillating Gradient Spin Echo Research Articles

Improving Microstructural Estimation in Time-Dependent Diffusion MRI With a Bayesian Method.

Accurately fitting diffusion-time-dependent diffusion MRI (td-dMRI) models poses challenges due to complex and nonlinear formulas, signal noise, and limited clinical data acquisition. Introduce a Bayesian methodology to refine microstructural fitting within the IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) model and optimize the prior distribution within the Bayesian framework. Retrospective. Involving 69 pediatric patients (median age 6 years, interquartile range [IQR] 3-9 years, 61% male) with 41 low-grade and 28 high-grade gliomas, of which 76.8% were identified within the brainstem or cerebellum. 3 T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE). The Bayesian method's performance in fitting cell diameter ( ), intracellular volume fraction ( ), and extracellular diffusion coefficient ( ) was compared against the NLLS method, considering simulated and experimental data. The tumor region-of-interest (ROI) were manually delineated on the b0 images. The diagnostic performance in distinguishing high- and low-grade gliomas was assessed, and fitting accuracy was validated against H&E-stained pathology. T-test, receiver operating curve (ROC), area under the curve (AUC) and DeLong's test were conducted. Significance considered at P < 0.05. Bayesian methodology manifested increased accuracy with robust estimates in simulation (RMSE decreased by 29.6%, 40.9%, 13.6%, and STD decreased by 29.2%, 43.5%, and 24.0%, respectively for , , and compared to NLLS), indicating fewer outliers and reduced error. Diagnostic performance for tumor grade was similar in both methods, however, Bayesian method generated smoother microstructural maps (outliers ratio decreased by 45.3% ± 19.4%) and a marginal enhancement in correlation with H&E staining result (r = 0.721 for compared to r = 0.698 using NLLS, P = 0.5764). The proposed Bayesian method substantially enhances the accuracy and robustness of IMPULSED model estimation, suggesting its potential clinical utility in characterizing cellular microstructure. 3 TECHNICAL EFFICACY: Stage 1.

Restricted diffusion characteristics in oscillating gradient spin echo with mesoscopic phantom

In diffusion magnetic resonance imaging, oscillating gradient spin echo (OGSE) has an extremely short diffusion time if motion probing gradient (MPG) is applied to the waveform. Further, it can detect microstructural specificity. OGSE changes sensitivity to spin displacement velocity based on the MPG phase. The current study aimed to investigate the restricted diffusion characteristics of each OGSE waveform using the capillary phantom with various b-values, frequencies, and MPG phases. We performed OGSE (b-value = 300, 500, 800, 1200, 1600, and 2000 s/mm2) for the sine and cosine waveforms using the capillary phantom (6, 12, 25, 50, and 100 μm and free water) with a 9.4-T experimental magnetic resonance imaging system and a solenoid coil. We evaluated the axial and radial diffusivity (AD, RD) of each structure size. The output current of the MPG was assessed with an oscilloscope and analyzed with the gradient modulation power spectra by fast Fourier transform.In sine, the sidelobe spectrum was enhanced with increasing frequency, and the central spectrum slightly increased. The difference in RD was detected at 6 and 12 μm; however, it did not depend on the structure scale at 50 or 100 μm and free water. In cosine, the diffusion spectrum was enhanced, whereas the central spectrum decreased with increasing frequency. Both AD and RD in cosine had a frequency dependence, and AD and RD increased with a higher frequency regardless of structure size. AD and RD in either sine or cosine had no evident b-value dependence. We evaluated the OGSE-restricted diffusion characteristics. The measurements obtained diffusion information similar to the pulsed gradient spin echo. Hence, the cosine measurements indicated that a higher frequency could capture faster diffusion within the diffusion phenomena.

Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient

BackgroundThis study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters.MethodsA retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices.ResultsIn enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs.ConclusionsEffective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.

Oscillating Gradient Diffusion-Weighted MRI for Risk Stratification of Uterine Endometrial Cancer.

Oscillating gradient diffusion-weighted imaging (DWI) enables elucidation of microstructural characteristics in cancers; however, there are limited data to evaluate its utility in patients with endometrial cancer. To investigate the utility of oscillating gradient DWI for risk stratification in patients with uterine endometrial cancer compared with conventional pulsed gradient DWI. Retrospective. Sixty-three women (mean age: 58 [range: 32-85] years) with endometrial cancer. 3 T MRI including DWI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) research sequences. Mean value of the apparent diffusion coefficient (ADC) values for OGSE (ADCOGSE) and PGSE (ADCPGSE) as well as the ADC ratio (ADCOGSE/ADCPGSE) within endometrial cancer were measured using regions of interest. Prognostic factors (histological grade, deep myometrial invasion, lymphovascular invasion, International Federation of Gynecology and Obstetrics [FIGO] stage, and prognostic risk classification) were tabulated. Interobserver agreement was analyzed by calculating the intraclass correlation coefficient. The associations of ADCOGSE, ADCPGSE, and ADCOGSE/ADCPGSE with prognostic factors were examined using the Kendall rank correlation coefficient, Mann-Whitney U test, and receiver operating characteristic (ROC) curve. A P value of <0.05 was statistically significant. Compared with ADCOGSE and ADCPGSE, ADCOGSE/ADCPGSE was significantly and strongly correlated with histological grade (observer 1, τ = 0.563; observer 2, τ = 0.456), FIGO stage (observer 1, τ = 0.354; observer 2, τ = 0.324), and prognostic risk classification (observer 1, τ = 0.456; observer 2, τ = 0.385). The area under the ROC curves of ADCOGSE/ADCPGSE for histological grade (observer 1, 0.92, 95% confidence intervals [CIs]: 0.83-0.98; observer 2, 0.84, 95% CI: 0.73-0.92) and prognostic risk (observer 1, 0.80, 95% CI: 0.68-0.89; observer 2, 0.76, 95% CI: 0.63-0.86) were significantly higher than that of ADCOGSE and ADCPGSE. The ADC ratio obtained via oscillating gradient and pulsed gradient DWIs might be useful imaging biomarkers for risk stratification in patients with endometrial cancer. 3 TECHNICAL EFFICACY: Stage 2.

Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI

BackgroundThis study was designed to investigate the use of time-dependent diffusion magnetic resonance imaging (MRI) parameters in distinguishing between glioblastomas and brain metastases.MethodsA retrospective study was conducted involving 65 patients with glioblastomas and 27 patients with metastases using a diffusion-weighted imaging sequence with oscillating gradient spin-echo (OGSE, 50 Hz) and a conventional pulsed gradient spin-echo (PGSE, 0 Hz) sequence. In addition to apparent diffusion coefficient (ADC) maps from two sequences (ADC50Hz and ADC0Hz), we generated maps of the ADC change (cADC): ADC50Hz − ADC0Hz and the relative ADC change (rcADC): (ADC50Hz − ADC0Hz)/ ADC0Hz × 100 (%).ResultsThe mean and the fifth and 95th percentile values of each parameter in enhancing and peritumoral regions were compared between glioblastomas and metastases. The area under the receiver operating characteristic curve (AUC) values of the best discriminating indices were compared. In enhancing regions, none of the indices of ADC0Hz and ADC50Hz showed significant differences between metastases and glioblastomas. The mean cADC and rcADC values of metastases were significantly higher than those of glioblastomas (0.24 ± 0.12 × 10−3mm2/s vs. 0.14 ± 0.03 × 10−3mm2/s and 23.3 ± 9.4% vs. 14.0 ± 4.7%; all p < 0.01). In peritumoral regions, no significant difference in all ADC indices was observed between metastases and glioblastomas. The AUC values for the mean cADC (0.877) and rcADC (0.819) values in enhancing regions were significantly higher than those for ADC0Hz5th (0.595; all p < 0.001).ConclusionsThe time-dependent diffusion MRI parameters may be useful for differentiating brain metastases from glioblastomas.

Revealing tumor microstructure with oscillating diffusion encoding MRI in pre-surgical and post-treatment glioma patients.

We hypothesized that the time-dependent diffusivity at short diffusion times, as measured by oscillating gradient spin echo (OGSE) diffusion MRI, can characterize tissue microstructures in glioma patients. Five adult patients with known diffuse glioma, including two pre-surgical and three with new enhancing lesions after treatment for high-grade glioma, were scanned in an ultra-high-performance gradient 3.0T MRI system. OGSE diffusion MRI at 30-100 Hz and pulsed gradient spin echo diffusion imaging (approximated as 0 Hz) were obtained. The ADC and trace-diffusion-weighted image at each acquired frequency were calculated, that is, ADC (f) and TraceDWI (f). In pre-surgical patients, biopsy-confirmed solid enhancing tumor in a high-grade glioblastoma showed higher and lower , compared to that at same OGSE frequency in a low-grade astrocytoma. In post-treatment patients, the enhancing lesions of two patients who were diagnosed with tumor progression contained more voxels with high and low , compared to the enhancing lesions of a patient who was diagnosed with treatment effect. Non-enhancing T2 signal abnormality lesions in both the pre-surgical high-grade glioblastoma and post-treatment tumor progressions showed regions with high and low , consistent with infiltrative tumor. The solid tumor of the glioblastoma, the enhancing lesions of post-treatment tumor progressions, and the suspected infiltrative tumors showed high diffusion time-dependency from 30 to 100 Hz, consistent with high intra-tumoral volume fraction (cellular density). Different characteristics of OGSE-based time-dependent diffusivity can reveal heterogenous tissue microstructures that indicate cellular density in glioma patients.

Detection of Treatment Response in Triple-Negative Breast Tumors to Paclitaxel Using MRI Cell Size Imaging.

Breast cancer treatment response evaluation using the response evaluation criteria in solid tumors (RECIST) guidelines, based on tumor volume changes, has limitations, prompting interest in novel imaging markers for accurate therapeutic effect determination. To use MRI-measured cell size as a new imaging biomarker for assessing chemotherapy response in breast cancer. Longitudinal; animal model. Triple-negative human breast cancer cell (MDA-MB-231) pellets (4 groups, n = 7) treated with dimethyl sulfoxide (DMSO) or 10 nM of paclitaxel for 24, 48, and 96 hours, and 29 mice with MDA-MB-231 tumors in right hind limbs treated with paclitaxel (n = 16) or DMSO (n = 13) twice weekly for 3 weeks. Oscillating gradient spin echo and pulsed gradient spin echo sequences at 4.7 T. MDA-MB-231 cells were analyzed using flowcytometry and light microscopy to assess cell cycle phases and cell size distribution. MDA-MB-231 cell pellets were MR imaged. Mice were imaged weekly, with 9, 6, and 14 being sacrificed for histology after MRI at weeks 1, 2, and 3, respectively. Microstructural parameters of tumors/cell pellets were derived by fitting diffusion MRI data to a biophysical model. One-way ANOVA compared cell sizes and MR-derived parameters between treated and control samples. Repeated measures 2-way ANOVA with Bonferroni post-tests compared temporal changes in MR-derived parameters. A P-value <0.05 was considered statistically significant. In vitro experiments showed that the mean MR-derived cell sizes of paclitaxel-treated cells increased significantly with a 24-hours treatment and decreased (P = 0.06) with a 96-hour treatment. For in vivo xenograft experiments, the paclitaxel-treated tumors showed significant decreases in cell size at later weeks. MRI observations were supported by flowcytometry, light microscopy, and histology. MR-derived cell size may characterize the cell shrinkage during treatment-induced apoptosis, and may potentially provide new insights into the assessment of therapeutic response. 2 TECHNICAL EFFICACY STAGE: 4.

A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla

Multimodal microstructural MRI has shown increased sensitivity and specificity to changes in various brain disease and injury models in the preclinical setting. Here, we present an in vivo longitudinal dataset, including a subset of ex vivo data, acquired as control data and to investigate microstructural changes in the healthy mouse brain. The dataset consists of structural T2-weighted imaging, magnetization transfer ratio and saturation imaging, and advanced quantitative diffusion MRI (dMRI) methods. The dMRI methods include oscillating gradient spin echo (OGSE) dMRI and microscopic anisotropy (μA) dMRI, which provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The technical skills required to analyze microstructural MRI data are complex and include MRI sequence development, acquisition, and computational neuroimaging expertise. Here, we share unprocessed and preprocessed data, and scalar maps of quantitative MRI metrics. We envision utility of this dataset in the microstructural MRI field to develop and test biophysical models, methods that model temporal brain dynamics, and registration and preprocessing pipelines.

Fourier transform temporal diffusion spectroscopy

Temporal diffusion spectroscopy (TDS) currently uses the oscillating gradient spin echo (OGSE) experiment to measure the spectral density of translational velocity autocorrelation at single frequencies. Due to timing restrictions imposed by the transverse relaxation, the frequency selectivity and the sampling density of OGSE are limited, especially at low frequencies. We propose to overcome this problem by adopting the principles of Fourier transform spectroscopy. The new method of Fourier transform TDS (FTDS) uses two broadband gradient waveforms with different relative delays to make the spin echo attenuation sensitive to a broad range of diffusion frequencies with different harmonic modulations and calculates the spectrum by discrete Fourier transform. The method was validated by a measurement of diffusion spectra in highly restrictive tissues of a celery stalk and provided results consistent with OGSE, however, on a denser frequency grid.

Investigation of time-dependent diffusion in extra-axial brain tumors using oscillating-gradient spin-echo

Oscillating gradient spin-echo (OGSE) sequences provide access to short diffusion times and may provide insight into micro-scale internal structures of pathologic lesions based on an analysis of changes in diffusivity with differing diffusion times. We hypothesized that changes in diffusivity acquired with a shorter diffusion time may permit elucidation of properties related to the internal structure of extra-axial brain tumors. This study aimed to investigate the utility of changes in diffusivity between short and long diffusion times for characterizing extra-axial brain tumors. In total, 12 patients with meningothelial meningiomas, 13 patients with acoustic neuromas, and 11 patients with pituitary adenomas were scanned with a 3 T magnetic resonance imaging (MRI) scanner with diffusion-weighted imaging (DWI) using OGSE and pulsed gradient spin-echo (PGSE) (effective diffusion times [Δeff]: 6.5 ms and 35.2 ms) with b-values of 0 and 1000 s/mm2. Relative percentage changes between shorter and longer diffusion times were calculated using region-of-interest (ROI) analysis of brain tumors on λ1, λ2, λ3, and mean diffusivity (MD) maps. The diffusivities of PGSE, OGSE, and relative percentage changes were compared among each tumor type using a multiple comparisons Steel-Dwass test. The mean (standard deviation) MD at Δeff of 6.5 ms was 1.07 ± 0.23 10−3 mm2/s, 1.19 ± 0.18 10−3 mm2/s, 1.19 ± 0.21 10−3 mm2/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) MD at Δeff of 35.2 ms was 0.93 ± 0.22 10−3 mm2/s, 1.07 ± 0.19 10−3 mm2/s, 0.82 ± 0.21 10−3 mm2/s for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. The mean (standard deviation) of the relative percentage change was 15.7 ± 4.4%, 12.4 ± 8.2%, 46.8 ± 11.3% for meningothelial meningiomas, acoustic neuromas, and pituitary adenomas, respectively. Compared to meningiomas and acoustic neuromas, pituitary adenoma exhibited stronger diffusion time-dependence with diffusion times between 6.5 ms and 35.2 ms (P < 0.05). In conclusion, differences in diffusion time-dependence may be attributed to differences in the internal structures of brain tumors. DWI with a short diffusion time may provide additional information on the microstructure of each tumor and contribute to tumor diagnosis.

Better neural images by combining ultrahigh field strength MRI with innovative MRI sequences

Better MRI scanning technologies and protocols can provide insights into neurological disorders. In this review, we describe the basic concepts of MRI and, in the process, we convey to the reader the relevance of MRI as a high-resolution imaging modality of tissue structure and metabolism. We outline the main parameters for improving MRI resolution and sensitivity for the ultimate goal of optimizing the diagnosis of neurological diseases. A key to obtaining high-resolution images by MRI is the strength of the magnet’s external field strength (Bo). The higher the field strength, the better the signal-to-noise (SNR) of acquired signals. Hence, this results in improved sensitivity and resolution of the reconstructed images. This article recapitulates the advancement of MRI technology towards Ultra-High-Field Strength (UHF) apparatus and the consequent benefits in SNR. Other keys towards improving MRI images include deftly modifying the parameters of longitudinal magnetization relaxation time (T1), transverse magnetization relaxation time (T2), repetition times between radiofrequency (RF) pulses (TR), and the time of reading post-pulse (TE). Such parameters can be controlled through acquisition software associated with the MRI machines. The review profiles the cumulative efforts by researchers to complement UHF-MRI hardware with innovative RF pulse sequences protocols such as Diffusion Weighted Imaging (DWI), Pulse Gradient Spin Echo (PGSE), Oscillating Gradient Spin Echo (OGSE), Blood Oxygen Level Dependent (BOLD)-MRI and Arterial Spin Label (ASL)-MRI. Collectively, these advances in both MRI hardware and software have pushed the field to attain a mesoscopic level of resolution. Further enhancements in analyzing MRI images through Artificial Intelligence (AI) algorithms may advance resolutions beyond the mesoscopic stage and perhaps even toward the microscopic resolution of living tissue.

Tuned bipolar oscillating gradients for mapping frequency dispersion of diffusion kurtosis in the human brain.

Oscillating gradient spin-echo (OGSE) sequences have demonstrated an ability to probe time-dependent microstructural features, although they often suffer from low SNR due to increased TEs. In this work we introduce frequency-tuned bipolar (FTB) gradients as a variation of oscillating gradients with reduced TE and demonstrate their utility by mapping the frequency dispersion of kurtosis in human subjects. An FTB oscillating gradient waveform is presented that provides encoding of 1.5 net oscillation periods, thereby reducing the TE of the acquisition. Simulations were performed to determine an optimal protocol based on the SNR of kurtosis frequency dispersion-defined as the difference in kurtosis between pulsed and oscillating gradient acquisitions. Healthy human subjects were scanned at 7T using pulsed gradient and an optimized 23 Hz FTB protocol, which featured a maximum b-value of 2500 s/mm2 . In addition, to directly compare existing methods, measurements using traditional cosine OGSE were also acquired. FTB oscillating gradients demonstrated equivalent frequency-dependent diffusion measurements compared with cosine-modulated OGSE while enabling a significant reduction in TE. Optimization and in vivo results suggest that FTB gradients provide increased SNR of kurtosis dispersion maps compared with traditional cosine OGSE. The optimized FTB gradient protocol demonstrated consistent reductions in apparent kurtosis values and increased diffusivity in generated frequency dispersion maps. This work presents an alternative to traditional cosine OGSE sequences, enabling more time-efficient acquisitions of frequency-dependent diffusion quantities as demonstrated through in vivo kurtosis frequency dispersion maps.

Impact of tissue properties on time-dependent alterations in apparent diffusion coefficient: a phantom study using oscillating-gradient spin-echo and pulsed-gradient spin-echo sequences

PurposeThe purpose of this study was to investigate whether the changes in apparent diffusion coefficients (ADCs) due to differences in diffusion time reflect tissue properties in actual measurements of phantoms.Materials and methodsVarious n-alkane phantoms and sucrose/collagen phantoms with various collagen densities were set up with and without polyvinyl alcohol (PVA) foam with an average pore diameter of 300 μm. Thus, n-alkanes or sucrose/collagen represented substrate viscosity and the presence of PVA foam represented tissue structure with septum. Diffusion-weighted images with various diffusion times (7.71–60 ms) were acquired using pulsed-gradient spin-echo (PGSE) and oscillating-gradient spin-echo (OGSE) sequences. The ADCs of the phantoms with and without PVA foam were calculated.ResultsThe ADCs of some of the phantoms without PVA decreased with diffusion times decreased. In the n-alkane phantoms, only C8H18 showed significantly different ADCs depending on the use of PVA foam in the OGSE sequence. On the other hand, sucrose/collagen phantoms showed significant differences according to diffusion time. The ADCs of the phantoms decreased as the molecular size of the n-alkanes or collagen density of the sucrose/collagen phantom increased. Compared to phantoms without PVA foam, the ADC of the phantoms with PVA foam decreased as the diffusion time increased.ConclusionChanges in ADCs due to differences in diffusion time reflect tissue properties in actual measurements of phantoms. These changes in ADCs can be used for tissue characterization in vivo.

Evaluating diffusion dispersion across an extended range of b-values and frequencies: Exploiting gap-filled OGSE shapes, strong gradients, and spiral readouts.

PurposeTo address the long echo times and relatively weak diffusion sensitization that typically limit oscillating gradient spin‐echo (OGSE) experiments, an OGSE implementation combining spiral readouts, gap‐filled oscillating gradient shapes providing stronger diffusion encoding, and a high‐performance gradient system is developed here and utilized to investigate the tradeoff between b‐value and maximum OGSE frequency in measurements of diffusion dispersion (i.e., the frequency dependence of diffusivity) in the in vivo human brain. In addition, to assess the effects of the marginal flow sensitivity introduced by these OGSE waveforms, flow‐compensated variants are devised for experimental comparison.MethodsUsing DTI sequences, OGSE acquisitions were performed on three volunteers at b‐values of 300, 500, and 1000 s/mm2 and frequencies up to 125, 100, and 75 Hz, respectively; scans were performed for gap‐filled oscillating gradient shapes with and without flow sensitivity. Pulsed gradient spin‐echo DTI acquisitions were also performed at each b‐value. Upon reconstruction, mean diffusivity (MD) maps and maps of the diffusion dispersion rate were computed.ResultsThe power law diffusion dispersion model was found to fit best to MD measurements acquired at b = 1000 s/mm2 despite the associated reduction of the spectral range; this observation was consistent with Monte Carlo simulations. Furthermore, diffusion dispersion rates without flow sensitivity were slightly higher than flow‐sensitive measurements.ConclusionThe presented OGSE implementation provided an improved depiction of diffusion dispersion and demonstrated the advantages of measuring dispersion at higher b‐values rather than higher frequencies within the regimes employed in this study.

Time-dependent Diffusion in Brain Abscesses Investigated with Oscillating-gradient Spin-echo.

Oscillating-gradient spin-echo sequences enable the measurement of diffusion weighting with a short diffusion time and can provide indications of internal structures. We report two cases of brain abscess in which the apparent diffusion coefficient (ADC) values appear higher at short diffusion times in comparison with those at long diffusion times. Diffusion time dependence of the ADC in brain abscesses suggests not only substrate viscosity but also restricted diffusion due to the structure within the lesions.

Characterization and correction of time-varying eddy currents for diffusion MRI.

To develop and test a method for reducing artifacts due to time-varying eddy currents in oscillating gradient spin-echo (OGSE) diffusion images. An in-house algorithm (TVEDDY), that for the first time retrospectively models eddy current decay, was tested on pulsed gradient spin echo and OGSE brain images acquired at 7 T. Image pairs were acquired using opposite polarity diffusion gradients. A three-parameter exponential decay model (two amplitudes and a time constant) was used to characterize and correct eddy current distortions by minimizing the intensity difference between image pairs. Correction performance was compared with conventional correction methods by evaluating the mean squared error (MSE) between diffusion-weighted images acquired with opposite polarity diffusion gradients. As a ground-truth comparison, images were corrected using field dynamics up to third order in space, measured using a field monitoring system. Time-varying eddy currents were observed for OGSE, which introduced blurring that was not reduced using the traditional approach but was diminished considerably with TVEDDY and field monitoring-informed model-based reconstruction. No MSE difference was observed between the conventional approach and TVEDDY for pulsed gradient spin echo, but for OGSE TVEDDY resulted in significantly lower MSE than the conventional approach. The field-monitoring reconstruction had the lowest MSE for both pulsed gradient spin echo and OGSE. This work establishes that it is possible to estimate time-varying eddy currents from the actual diffusion data, which provides substantial image-quality improvements for gradient-intensive diffusion MRI acquisitions like OGSE.

Test-retest reproducibility of in vivo oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla.

Microstructure imaging with advanced diffusion MRI (dMRI) techniques have shown increased sensitivity and specificity to microstructural changes in various disease and injury models. Oscillating gradient spin echo (OGSE) dMRI, implemented by varying the oscillating gradient frequency, and microscopic anisotropy (μA) dMRI, implemented via tensor valued diffusion encoding, may provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The aims of this study were to characterize the test-retest reproducibility of in vivo OGSE and μA dMRI metrics in the mouse brain at 9.4 Tesla and provide estimates of required sample sizes for future investigations. Twelve adult C57Bl/6 mice were scanned twice (5 days apart). Each imaging session consisted of multifrequency OGSE and μA dMRI protocols. Metrics investigated included μA, linear diffusion kurtosis, isotropic diffusion kurtosis, and the diffusion dispersion rate (Λ), which explores the power-law frequency dependence of mean diffusivity. The dMRI metric maps were analyzed with mean region-of-interest (ROI) and whole brain voxel-wise analysis. Bland-Altman plots and coefficients of variation (CV) were used to assess the reproducibility of OGSE and μA metrics. Furthermore, we estimated sample sizes required to detect a variety of effect sizes. Bland-Altman plots showed negligible biases between test and retest sessions. ROI-based CVs revealed high reproducibility for most metrics (CVs < 15%). Voxel-wise CV maps revealed high reproducibility for μA (CVs ~ 10%), but low reproducibility for OGSE metrics (CVs ~ 50%). Most of the μA dMRI metrics are reproducible in both ROI-based and voxel-wise analysis, while the OGSE dMRI metrics are only reproducible in ROI-based analysis. Given feasible sample sizes (10-15), μA metrics and OGSE metrics may provide sensitivity to subtle microstructural changes (4-8%) and moderate changes (> 6%), respectively.

Axon diameter inferences in the human corpus callosum using oscillating gradient spin echo sequences

Previous methods used to infer axon diameter distributions using magnetic resonance imaging (MRI) primarily use single diffusion encoding sequences such as pulsed gradient spin echo (PGSE) and are thus sensitive to axons of diameters >5 μm. We applied oscillating gradient spin echo (OGSE) sequences to study human axons in the 1–2 μm range in the corpus callosum, which include the majority of axons constituting cortical connections. The ActiveAx model was applied to calculate the fitted mean effective diameter for axons (AxD) and was compared with values found using histology. Axon diameters from histological data were calculated using three different datasets; true diameters (minimum diameter), a combination of minimum and maximum diameters, and diameters measured across a consistent diffusion direction. The AxD estimates from MRI were 1.8 ± 0.1 μm to 2.34 ± 0.04 μm with an average of 2.0 ± 0.2 μm for the ActiveAx model. The histology AxD values were 1.43 ± 0.02 μm when using the true minimum axon diameters, 5.52 ± 0.02 μm when using the combination of minimum and maximum axon diameters, and 2.20 ± 0.02 μm when collecting measurements across a consistent diffusion direction. This experiment demonstrates the first known usage of OGSE to calculate axon diameters in the human corpus callosum on a 1–2 μm scale. The importance for the model to account for axonal orientation dispersion is indicated by histological results which more closely match the MRI model results depending on the direction of axon diameter measurements. These initial steps using this non-invasive imaging method can be applied to future methodology to develop in vivo axon diameter measurements in human brain tissue.

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 β. 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.

Oscillating-gradient spin-echo diffusion-weighted imaging (OGSE-DWI) with a limited number of oscillations: I. Signal equation

The oscillating-gradient spin-echo (OGSE) sequence has been promoted as a promising diffusion-weighted magnetic resonance imaging (DWI) technique for probing in vivo tissue microstructure in the frequency domain. However, due to practical restrictions on the duration and number of oscillations that a motion-probing gradient can have, the technique has limited spectral resolution and range. This work re-examines the OGSE-DWI method to clarify how these limitations are reflected in the signal model. There are several aspects of the revised framework that distinguish it from the conventional description employed for OGSE DWI. In particular, while the conventional OGSE signal model implies that the spectral density of molecular diffusion may be directly sampled in experiments, in practice information about the spectral density can be only indirectly obtained.