Compartmental study of diffusion and relaxation measured in vivo in normal and ischemic rat brain and trigeminal nerve

Probing brain tissue microstructure with MRI: principles, challenges, and the role of multidimensional diffusion-relaxation encoding

Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells. Microstructure modeling techniques aim to estimate these properties from acquired data by separating the signal between virtual tissue 'compartments' such as the intra-neurite and the extra-cellular space. A key challenge is that the diffusion MRI signal is relatively featureless compared with the complexity of brain tissue. Another challenge is that the tissue microstructure is wildly different within the gray and white matter of the brain. In this review, we use results from multidimensional diffusion encoding techniques to discuss these challenges and their tentative solutions. Multidimensional encoding increases the information content of the data by varying not only the b-value and the encoding direction but also additional experimental parameters such as the shape of the b-tensor and the echo time. Three main insights have emerged from such encoding. First, multidimensional data contradict common model assumptions on diffusion and T2 relaxation, and illustrates how the use of these assumptions cause erroneous interpretations in both healthy brain and pathology. Second, many model assumptions can be dispensed with if data are acquired with multidimensional encoding. The necessary data can be easily acquired in vivo using protocols optimized to minimize Cramér-Rao lower bounds. Third, microscopic diffusion anisotropy reflects the presence of axons but not dendrites. This insight stands in contrast to current 'neurite models' of brain tissue, which assume that axons in white matter and dendrites in gray matter feature highly similar diffusion. Nevertheless, as an axon-based contrast, microscopic anisotropy can differentiate gray and white matter when myelin alterations confound conventional MRI contrasts.

The impact of head orientation with respect to B0 on diffusion tensor MRI measures

Diffusion tensor MRI (DT-MRI) remains the most commonly used approach to characterise white matter (WM) anisotropy. However, DT estimates may be affected by tissue orientation w.r.t. B → 0 due to local gradients and intrinsic T 2 orientation dependence induced by the microstructure. This work aimed to investigate whether and how diffusion tensor MRI-derived measures depend on the orientation of the head with respect to the static magnetic field, B → 0 . By simulating WM as two compartments, we demonstrated that compartmental T 2 anisotropy can induce the dependence of diffusion tensor measures on the angle between WM fibres and the magnetic field. In in vivo experiments, reduced radial diffusivity and increased axial diffusivity were observed in white matter fibres perpendicular to B → 0 compared to those parallel to B → 0 . Fractional anisotropy varied by up to 20 % as a function of the angle between WM fibres and the orientation of the main magnetic field. To conclude, fibre orientation w.r.t. B → 0 is responsible for up to 7 % variance in diffusion tensor measures across the whole brain white matter from all subjects and head orientations. Fibre orientation w.r.t. B → 0 may introduce additional variance in clinical research studies using diffusion tensor imaging, particularly when it is difficult to control for (e.g., fetal or neonatal imaging, or when the trajectories of fibres change due to, e.g., space occupying lesions).

Fiber-orientation independent component of R2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm

The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects.

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

PURPOSE

To develop a DWI sequence with multiple readout echo-trains in a single shot (multi-readout DWI) over a reduced FOV, and to demonstrate its ability to achieve high data acquisition efficiency in the study of coupling between diffusion and relaxation in the human prostate.

METHODS

The proposed multi-readout DWI sequence plays out multiple EPI readout echo-trains after a Stejskal-Tanner diffusion preparation module. Each EPI readout echo-train corresponded to a distinct effective TE. To maintain a high spatial resolution with a relatively short echo-train for each readout, a 2D RF pulse was used to limit the FOV. Experiments were performed on the prostate of six healthy subjects to acquire a set of images with three b values (0, 500, and 1000 s/mm² ) and three TEs (63.0, 78.8, and 94.6 ms), producing three ADC maps at different TEs and three T 2 * $$ {T}_2^{\ast } $$ maps at different b values.

RESULTS

Multi-readout DWI enabled a threefold acceleration without compromising the spatial resolution when compared with a conventional single-readout sequence. Images with three b values and three TEs were obtained in 3 min 40 s with an adequate SNR (≥ 26.9). The ADC values (1.45 ± 0.13, 1.52 ± 0.14, and 1.58 ± 0.15  μm 2 / ms $$ {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ; P < 0.01) exhibited an increasing trend as TEs increased (63.0 ms, 78.8 ms, and 94.6 ms), whereas T 2 * $$ {T}_2^{\ast } $$ values (74.78 ± 13.21, 63.21 ± 7.84, and 56.61 ± 5.05 ms; P < 0.01) decreases as the b values increased (0, 500, and 1000 s/mm² ).

CONCLUSION

The multi-readout DWI sequence over a reduced FOV provides a time-efficient technique to study the coupling between diffusion and relaxation times.

Mapping the Human Connectome using Diffusion MRI at 300 mT/m Gradient Strength: Methodological Advances and Scientific Impact

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in Continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength dMRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for dMRI and where the field is headed in the coming years.

Histological validation of prostate tissue composition measurement using hybrid multi-dimensional MRI: agreement with pathologists' measures

PURPOSE

To validate prostate tissue composition measured using hybrid multi-dimensional MRI (HM-MRI) by comparing with reference standard (ground truth) results from pathologists' interpretation of clinical histopathology slides following whole mount prostatectomy.

MATERIALS AND METHODS

36 prospective participants with biopsy-confirmed prostate cancer underwent 3 T MRI prior to radical prostatectomy. Axial HM-MRI was acquired with all combinations of echo times of 57, 70, 150, 200 ms and b-values of 0, 150, 750, 1500 s/mm² and data were fitted using a 3-compartment signal model using custom software to generate volumes for each tissue component (stroma, epithelium, lumen). Three experienced genitourinary pathologists independently as well as in consensus reviewed each histology image and provide an estimate of percentage of epithelium and lumen for regions-of-interest corresponding to MRI (n = 165; 64 prostate cancers and 101 benign tissue). Agreement statistics using total deviation index (TDI_0.9) was performed for tissue composition measured using HM-MRI and reference standard results from pathologists' consensus.

RESULTS

Based on the initial results showing typical variation among pathologists TDI_0.9 = 25%, we determined we will declare acceptable agreement if the 95% one-sided upper confident limit of TDI_0.9 is less than 30%. The results of tissue composition measurement from HM-MRI compared to ground truth results from the consensus of 3 pathologists, reveal that ninety percent of absolute paired differences (TDI_0.9) were within 18.8% and 22.4% in measuring epithelium and lumen, respectively. We are 95% confident that 90% of absolute paired differences were within 20.6% and 24.2% in measuring epithelium and lumen, respectively. These were less than our criterion of 30% and inter-pathologists' agreement (22.3% for epithelium and 24.2% for lumen) and therefore we accept the agreement performance of HM-MRI. The results revealed excellent area under the ROC curve for differentiating cancer from benign tissue based on epithelium (HM-MRI: 0.87, pathologists: 0.97) and lumen volume (HM-MRI: 0.85, pathologists: 0.77).

CONCLUSION

The agreement in tissue composition measurement using hybrid multidimensional MRI and consensus of pathologists is on par with the inter-raters (pathologists) agreement.

Combined diffusion-relaxometry microstructure imaging: Current status and future prospects

Microstructure imaging seeks to noninvasively measure and map microscopic tissue features by pairing mathematical modeling with tailored MRI protocols. This article reviews an emerging paradigm that has the potential to provide a more detailed assessment of tissue microstructure-combined diffusion-relaxometry imaging. Combined diffusion-relaxometry acquisitions vary multiple MR contrast encodings-such as b-value, gradient direction, inversion time, and echo time-in a multidimensional acquisition space. When paired with suitable analysis techniques, this enables quantification of correlations and coupling between multiple MR parameters-such as diffusivity, T 1 , T 2 , and T 2 ∗ . This opens the possibility of disentangling multiple tissue compartments (within voxels) that are indistinguishable with single-contrast scans, enabling a new generation of microstructural maps with improved biological sensitivity and specificity.

Validation of Prostate Tissue Composition by Using Hybrid Multidimensional MRI: Correlation with Histologic Findings

Background Tissue estimates obtained by using microstructure imaging techniques, such as hybrid multidimensional (HM) MRI, may improve prostate cancer diagnosis but require histologic validation. Purpose To validate prostate tissue composition measured by using HM MRI, with quantitative histologic evaluation from whole-mount prostatectomy as the reference standard. Materials and Methods In this HIPAA-compliant study, from December 2016 to July 2018, prospective participants with biopsy-confirmed prostate cancer underwent 3-T MRI before radical prostatectomy. Axial HM MRI was performed with all combinations of echo times (57, 70, 150, and 200 msec) and b values (0, 150, 750, and 1500 sec/mm²). Data were fitted by using a three-compartment signal model to generate volumes for each tissue component (stroma, epithelium, lumen). Quantitative histologic evaluation was performed to calculate volume fractions for each tissue component for regions of interest corresponding to MRI. Tissue composition measured by using HM MRI and quantitative histologic evaluation were compared (paired t test) and correlated (Pearson correlation coefficient), and agreement (concordance correlation) was assessed. Receiver operating characteristic curve analysis for cancer diagnosis was performed. Results Twenty-five participants (mean age, 60 years ± 7 [standard deviation]; 30 cancers and 45 benign regions of interest) were included. Prostate tissue composition measured with HM MRI and quantitative histologic evaluation did not differ (stroma, 45% ± 11 vs 44% ± 11 [P = .23]; epithelium, 31% ± 15 vs 34% ± 15 [P = .08]; and lumen, 24% ± 13 vs 22% ± 11 [P = .80]). Between HM MRI and histologic evaluation, there was excellent correlation (Pearson r: overall, 0.91; stroma, 0.82; epithelium, 0.93; lumen, 0.90 [all P < .05]) and agreement (concordance correlation coefficient: overall, 0.91; stroma, 0.81; epithelium, 0.90; and lumen, 0.87). High areas under the receiver operating characteristic curve obtained with HM MRI (0.96 for epithelium and 0.94 for lumen, P < .001) and histologic evaluation (0.94 for epithelium and 0.88 for lumen, P < .001) were found for differentiation between benign tissue and prostate cancer. Conclusion Tissue composition measured by using hybrid multidimensional MRI had excellent correlation with quantitative histologic evaluation as the reference standard. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Muglia in this issue.

New prostate MRI techniques and sequences

Prostate MRI has seen increasing interest in recent years and has led to the development of new MRI techniques and sequences to improve prostate cancer (PCa) diagnosis which are reviewed in this article. Numerous studies have focused on improving image quality (segmented DWI) and faster acquisition (compressed sensing, k-t-SENSE, PROPELLER). An increasing number of studies have developed new quantitative and computer-aided diagnosis methods including artificial intelligence (PROSTATEx challenge) that mitigate the subjective nature of mpMRI interpretation. MR fingerprinting allows rapid, simultaneous generation of quantitative maps of multiple physical properties (T1, T2), where PCa are characterized by lower T1 and T2 values. New techniques like luminal water imaging (LWI), restriction spectrum imaging (RSI), VERDICT and hybrid multi-dimensional MRI (HM-MRI) have been developed for microstructure imaging, which provide information similar to histology. The distinct MR properties of tissue components and their change with the presence of cancer is used to diagnose prostate cancer. LWI is a T2-based imaging technique where long T2-component corresponding to luminal water is reduced in PCa. RSI and VERDICT are diffusion-based techniques where PCa is characterized by increased signal from intra-cellular restricted water and increased intracellular volume fraction, respectively, due to increased cellularity. VERDICT also reveal loss of extracellular-extravascular space in PCa due to loss of glandular structure. HM-MRI measures volumes of prostate tissue components, where PCa has reduced lumen and stromal and increased epithelium volume similar to results shown in histology. Similarly, molecular imaging using hyperpolarized ¹³C imaging has been utilized.

Denoising and Multiple Tissue Compartment Visualization of Multi-b-Valued Breast Diffusion MRI

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.

Oscillating diffusion-encoding with a high gradient-amplitude and high slew-rate head-only gradient for human brain imaging

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/mm² . 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 µm² /s, D_∞,PD = 1519 ± 164 µm² /s, and D_∞,RD = 640 ± 111 µm² /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.

Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling

In vivo mapping of the neurite density with diffusion MRI (dMRI) is a high but challenging aim. First, it is unknown whether all neurites exhibit completely anisotropic ("stick-like") diffusion. Second, the "density" of tissue components may be confounded by non-diffusion properties such as T2 relaxation. Third, the domain of validity for the estimated parameters to serve as indices of neurite density is incompletely explored. We investigated these challenges by acquiring data with "b-tensor encoding" and multiple echo times in brain regions with low orientation coherence and in white matter lesions. Results showed that microscopic anisotropy from b-tensor data is associated with myelinated axons but not with dendrites. Furthermore, b-tensor data together with data acquired for multiple echo times showed that unbiased density estimates in white matter lesions require data-driven estimates of compartment-specific T2 values. Finally, the "stick" fractions of different biophysical models could generally not serve as neurite density indices across the healthy brain and white matter lesions, where outcomes of comparisons depended on the choice of constraints. In particular, constraining compartment-specific T2 values was ambiguous in the healthy brain and had a large impact on estimated values. In summary, estimating neurite density generally requires accounting for different diffusion and/or T2 properties between axons and dendrites. Constrained "index" parameters could be valid within limited domains that should be delineated by future studies.

Combined diffusion-relaxometry MRI to identify dysfunction in the human placenta

Purpose

A combined diffusion‐relaxometry MR acquisition and analysis pipeline for in vivo human placenta, which allows for exploration of coupling between T2* and apparent diffusion coefficient (ADC) measurements in a sub 10‐minute scan time.

Methods

We present a novel acquisition combining a diffusion prepared spin echo with subsequent gradient echoes. The placentas of 17 pregnant women were scanned in vivo, including both healthy controls and participants with various pregnancy complications. We estimate the joint T2*‐ADC spectra using an inverse Laplace transform.

Results

T2*‐ADC spectra demonstrate clear quantitative separation between normal and dysfunctional placentas.

Conclusions

Combined T2*‐diffusivity MRI is promising for assessing fetal and maternal health during pregnancy. The T2*‐ADC spectrum potentially provides additional information on tissue microstructure, compared to measuring these two contrasts separately. The presented method is immediately applicable to the study of other organs.

Comparing diagnostic accuracy of luminal water imaging with diffusion-weighted and dynamic contrast-enhanced MRI in prostate cancer: A quantitative MRI study

Luminal water imaging (LWI) is a new MRI T₂ mapping technique that has been developed with the aim of diagnosis of prostate carcinoma (PCa). This technique measures the fractional amount of luminal water in prostate tissue, and has shown promising preliminary results in detection of PCa. To include LWI in clinical settings, further investigation on the accuracy of this technique is required. In this study, we compare the diagnostic accuracy of LWI with those of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI in detection and grading of PCa. Fifteen patients with biopsy-proven PCa consented to participate in this ethics-board-approved prospective study. Patients were examined with LWI, DWI, and DCE sequences at 3 T prior to radical prostatectomy. Maps of MRI parameters were generated and registered to whole-mount histology. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of individual and combined MR parameters. Correlation with Gleason score (GS) was evaluated using Spearman's rank correlation test. The results show that area under the ROC curve (AUC) obtained from LWI was equal to or higher than the AUC obtained from DWI, DCE, or their combination, in peripheral zone (0.98 versus 0.90, 0.89, and 0.91 respectively), transition zone (0.99 versus 0.98, n/a, and 0.98), and the entire prostate (0.85 versus 0.81, 0.75, and 0.84). The strongest correlation with GS was achieved from LWI (ρ = -0.81 ± 0.09, P < 0.001). Results of this pilot study show that LWI performs equally well as, or better than, DWI and DCE in detection of PCa. LWI provides significantly higher correlation with GS than DWI and DCE. This technique can potentially be included in clinical MRI protocols to improve characterization of tumors. However, considering the small size of the patient population in this study, a further study with a larger cohort of patients and broader range of GS is required to confirm the findings and draw a firm conclusion on the applicability of LWI in clinical settings.

MRI gradient-echo phase contrast of the brain at ultra-short TE with off-resonance saturation

Larmor-frequency shift or image phase measured by gradient-echo sequences has provided a new source of MRI contrast. This contrast is being used to study both the structure and function of the brain. So far, phase images of the brain have been largely obtained at long echo times as maximum phase signal-to-noise ratio (SNR) is achieved at TE = T2* (∼40 ms at 3T). The structures of the brain, however, are compartmentalized and complex with a wide range of signal relaxation times. At such long TE, the short-T2 components are largely attenuated and contribute minimally to phase contrast. The purpose of this study was to determine whether proton gradient-echo images of the brain exhibit phase contrast at ultra-short TE (UTE). Our data showed that UTE images acquired at 7 T without off-resonance saturation do not contain significant phase contrast between gray and white matter. However, UTE images of the brain can attain strong phase contrast even at a nominal TE of 106 μs by using off-resonance RF saturation pulses, which provide direct saturation of ultra-short-T2 components and indirect saturation of longer-T2 components via magnetization transfer. In addition, phase contrast between gray and white matter acquired at UTE with off-resonance saturation is reversed compared to that of the long-T2 signals acquired at long TEs. This finding opens up a potential new way to manipulate image phase contrast of the brain. By accessing short and ultra-short-T2 species, MRI phase images may further improve the characterization of tissue microstructure in the brain.

A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization

Purpose

The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill‐posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free‐water component.

Theory and Methods

Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization.

Results

Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free‐water contamination and to estimate tissue parameters.

Conclusion

Formulation of the diffusion‐relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free‐water elimination.

Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study

Purpose To evaluate whether compartmental analysis by using hybrid multidimensional magnetic resonance (MR) imaging can be used to diagnose prostate cancer and determine its aggressiveness. Materials and Methods Twenty-two patients with prostate cancer underwent preoperative 3.0-T MR imaging. Axial images were obtained with hybrid multidimensional MR imaging by using all combinations of echo times (47, 75, 100 msec) and b values of 0, 750, 1500 sec/mm², resulting in a 3 × 3 array of data associated with each voxel. Volumes of the tissue components stroma, epithelium, and lumen were calculated by fitting the hybrid data to a three-compartment signal model, with distinct, paired apparent diffusion coefficient (ADC) and T2 values associated with each compartment. Volume fractions and conventional ADC and T2 were measured for regions of interest in sites of prostatectomy-verified malignancy (n = 28) and normal tissue (n = 71). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of various parameters in differentiating prostate cancer from benign tissue. Results Compared with normal tissue, prostate cancer showed significantly increased fractional volumes of epithelium (23.2% ± 7.1 vs 48.8% ± 9.2, respectively) and reduced fractional volumes of lumen (26.4% ± 14.1 vs 14.0% ± 5.2) and stroma (50.5% ± 15.7 vs 37.2% ± 9.1) by using hybrid multidimensional MR imaging. The fractional volumes of tissue components show a significantly higher Spearman correlation coefficient with Gleason score (epithelium: ρ = 0.652, P = .0001; stroma: ρ = -0.439, P = .020; lumen: ρ = -0.390, P = .040) compared with traditional T2 values (ρ = -0.292, P = .132) and ADCs (ρ = -0.315, P = .102). The area under the ROC curve for differentiation of cancer from normal prostate was highest for fractional volume of epithelium (0.991), followed by fractional volumes of lumen (0.800) and stroma (0.789). Conclusion Fractional volumes of prostatic lumen, stroma, and epithelium change significantly when cancer is present. These parameters can be measured noninvasively by using hybrid multidimensional MR imaging and have the potential to improve the diagnosis of prostate cancer and determine its aggressiveness. ^© RSNA, 2018 Online supplemental material is available for this article.

7.0 Tesla MRI tractography in patients with trigeminal neuralgia

7.0 Tesla (T) high-resolution diffusion tensor imaging (DTI) can supply information on changing microstructures in cranial nerves. We investigated DTI parameters and the feasibility of DTI criteria for diagnosing trigeminal neuralgia (TN). In this study, 14 patients (28 hemispheres) of mean age 49.0 years (range, 31-64) with TN underwent DTI using 7.0 TMRI. We compared fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) of affected-side and unaffected-side trigeminal nerves using DTI. We examined associations between DTI parameters and clinical characteristics for patients with TN. In patients with TN, affected sides showed significantly decreased FA and significantly increased MD, and RD compared with unaffected sides of trigeminal nerves. Nuclei were not significantly different among patients with TN. Barrow Neurological Institute (BNI) pain scores did not correlate with affected sides. 7.0 T DTI was useful for detecting neurovascular compression in patients with TN. The increased signal-to-noise ratio provided by 7 T MRI should be advantageous for increasing spatial resolution to detect microstructure changes to trigeminal nerves in patients with TN.

Relationships between tissue microstructure and the diffusion tensor in simulated skeletal muscle

PURPOSE

To establish a series of relationships defining how muscle microstructure and diffusion tensor imaging (DTI) are related.

METHODS

The relationship among key microstructural features of skeletal muscle (fiber size, fibrosis, edema, and permeability) and the diffusion tensor were systematically simulated over physiologically relevant dimensions individually, and in combination, using a numerical simulation application. Stepwise multiple regression was used to identify which microstructural features of muscle significantly predict the diffusion tensor using single-echo and multi-echo DTI pulse sequences. Simulations were also performed in models with histology-informed geometry to investigate the relationship between fiber size and the diffusion tensor in models with real muscle geometry.

RESULTS

Fiber size is the strongest predictor of λ2, λ3, mean diffusivity, and fractional anisotropy in skeletal muscle, accounting for approximately 40% of the variance in the diffusion model when calculated with single-echo DTI. This increased to approximately 70% when diffusion measures were calculated from the short T₂ component of the multi-echo DTI sequence. This nonlinear relationship begins to plateau in fibers with greater than 60-μm diameter.

CONCLUSIONS

As the normal fiber size of a human muscle fiber is 40 to 60 μm, this suggests that DTI is a sensitive tool to monitor muscle atrophy, but may be limited in measurements of muscle with larger fibers. Magn Reson Med 80:317-329, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Effect of myelin water exchange on DTI-derived parameters in diffusion MRI: Elucidation of TE dependence

PURPOSE

Water exchange exists between different neuronal compartments of brain tissue but is often ignored in most diffusion models. The goal of the current study was to demonstrate the dependence of diffusion measurements on echo time (TE) in the human brain and to investigate the underlying effects of myelin water exchange.

METHODS

Five healthy subjects were examined with single-shot pulsed-gradient spin-echo echo-planar imaging with fixed duration (δ) and separation (Δ) of diffusion gradient pulses and a set of varying TEs. The effects of water exchange and intrinsic T₂ difference in cellular environments were investigated with Monte Carlo simulations.

RESULTS

Both in vivo measurements and simulations showed that fractional anisotropy (FA) and axial diffusivity (AD) had positive correlations with TE, while radial diffusivity (RD) showed a negative correlation, which is consistent with a previous study. The simulation results further indicated the sensitivity of TE dependence to the change of g-ratio.

CONCLUSION

The exchange between myelin and intra/extra-axonal water pools often plays a non-negligible role in the observed TE dependence of diffusion parameters, which may accompany or alter the effect of intrinsic T₂ in causing such dependence. The TE dependence may potentially serve as a biomarker for demyelination processes (e.g., in multiple sclerosis and Alzheimer's disease). Magn Reson Med 79:1650-1660, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Pilot Study of the Use of Hybrid Multidimensional T2-Weighted Imaging-DWI for the Diagnosis of Prostate Cancer and Evaluation of Gleason Score

OBJECTIVE

The objective of our study was to evaluate the role of a hybrid T2-weighted imaging-DWI sequence for prostate cancer diagnosis and differentiation of aggressive prostate cancer from nonaggressive prostate cancer.

MATERIALS AND METHODS

Twenty-one patients with prostate cancer who underwent preoperative 3-T MRI and prostatectomy were included in this study. Patients underwent a hybrid T2-weighted imaging-DWI examination consisting of DW images acquired with TEs of 47, 75, and 100 ms and b values of 0 and 750 s/mm(2). The apparent diffusion coefficient (ADC) and T2 were calculated for cancer and normal prostate ROIs at each TE and b value. Changes in ADC and T2 as a function of increasing the TE and b value, respectively, were analyzed. A new metric termed "PQ4" was defined as the percentage of voxels within an ROI that has increasing T2 with increasing b value and has decreasing ADC with increasing TE.

RESULTS

ADC values were significantly higher in normal ROIs than in cancer ROIs at all TEs (p < 0.0001). With increasing TE, the mean ADC increased 3% in cancer ROIs and increased 12% in normal ROIs. T2 was significantly higher in normal ROIs than in cancer ROIs at both b values (p ≤ 0.0002). The mean T2 decreased with increasing b value in cancer ROIs (ΔT2 = -17 ms) and normal ROIs (ΔT2 = -52 ms). PQ4 clearly differentiated normal ROIs from prostate cancer ROIs (p = 0.0004) and showed significant correlation with Gleason score (ρ = 0.508, p < 0.0001).

CONCLUSION

Hybrid MRI measures the response of ADC and T2 to changing TEs and b values, respectively. This approach shows promise for detecting prostate cancer and determining its aggressiveness noninvasively.

Simulations on the influence of myelin water in diffusion-weighted imaging

While myelinated axons present an important barrier to water diffusion, many models used to interpret DWI signal neglect other potential influences of myelin. In this work, Monte Carlo simulations were used to test the sensitivity of DWI results to the diffusive properties of water within myelin. Within these simulations, the apparent diffusion coefficient (D app) varied slowly over several orders of magnitude of the coefficient of myelin water diffusion (D m), but exhibited important differences compared to D app values simulated that neglect D m (=0). Compared to D app, the apparent diffusion kurtosis (K app) was generally more sensitive to D m. Simulations also tested the sensitivity of D app and K app to the amount of myelin present. Unique variations in D app and K app caused by differences in the myelin volume fraction were diminished when myelin water diffusion was included. Also, expected trends in D app and K app with experimental echo time were reduced or inverted when accounting for myelin water diffusion, and these reduced/inverted trends were seen experimentally in ex vivo rat brain DWI experiments. In general, myelin water has the potential to subtly influence DWI results and bias models of DWI that neglect these components of white matter.

Metabolite diffusion up to very high b in the mouse brain in vivo: Revisiting the potential correlation between relaxation and diffusion properties

PURPOSE

To assess the potential correlation between metabolites diffusion and relaxation in the mouse brain, which is of importance for interpreting and modeling metabolite diffusion based on pure geometry, irrespective of relaxation properties (multicompartmental relaxation or surface relaxivity).

METHODS

A new diffusion-weighted magnetic resonance spectroscopy sequence is introduced, dubbed "STE-LASER," which presents several nice properties, in particular the absence of cross-terms with selection gradients and a very clean localization. Metabolite diffusion is then measured in a large voxel in the mouse brain at 11.7 Tesla using a cryoprobe, resulting in excellent signal-to-noise ratio, up to very high b-values under different echo time, mixing time, and diffusion time combinations.

RESULTS

Our results suggest that the correlation between relaxation and diffusion properties is extremely small or even nonexistent for metabolites in the mouse brain.

CONCLUSION

The present work strongly supports the interpretation and modeling of metabolite diffusion primarily based on geometry, irrespective of relaxation properties, at least under current experimental conditions. Magn Reson Med 77:1390-1398, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Degeneracy in model parameter estimation for multi-compartmental diffusion in neuronal tissue

The ultimate promise of diffusion MRI (dMRI) models is specificity to neuronal microstructure, which may lead to distinct clinical biomarkers using noninvasive imaging. While multi-compartment models are a common approach to interpret water diffusion in the brain in vivo, the estimation of their parameters from the dMRI signal remains an unresolved problem. Practically, even when q space is highly oversampled, nonlinear fit outputs suffer from heavy bias and poor precision. So far, this has been alleviated by fixing some of the model parameters to a priori values, for improved precision at the expense of accuracy. Here we use a representative two-compartment model to show that fitting fails to determine the five model parameters from over 60 measurement points. For the first time, we identify the reasons for this poor performance. The first reason is the existence of two local minima in the parameter space for the objective function of the fitting procedure. These minima correspond to qualitatively different sets of parameters, yet they both lie within biophysically plausible ranges. We show that, at realistic signal-to-noise ratio values, choosing between the two minima based on the associated objective function values is essentially impossible. Second, there is an ensemble of very low objective function values around each of these minima in the form of a pipe. The existence of such a direction in parameter space, along which the objective function profile is very flat, explains the bias and large uncertainty in parameter estimation, and the spurious parameter correlations: in the presence of noise, the minimum can be randomly displaced by a very large amount along each pipe. Our results suggest that the biophysical interpretation of dMRI model parameters crucially depends on establishing which of the minima is closer to the biophysical reality and the size of the uncertainty associated with each parameter.

The interaction between apparent diffusion coefficients and transverse relaxation rates of human brain metabolites and water studied by diffusion-weighted spectroscopy at 7 T

The dependence of apparent diffusion coefficients (ADCs) of molecules in biological tissues on an acquisition-specific timescale is a powerful mechanism for studying tissue microstructure. Unlike water, metabolites are confined mainly to intracellular compartments, thus providing higher specificity to tissue microstructure. Compartment-specific structural and chemical properties may also affect molecule transverse relaxation times (T₂). Here, we investigated the correlation between diffusion and relaxation for N-acetylaspartate, creatine and choline compounds in human brain white matter in vivo at 7 T, and compared them with those of water under the same experimental conditions. Data were acquired in a volume of interest in parietal white matter at two different diffusion times, Δ = 44 and 246 ms, using a matrix of three echo times (T(E)) and five diffusion weighting values (up to 4575 s/mm²). Significant differences in the dependence of the ADCs on T(E) were found between water and metabolites, as well as among the different metabolites. A significant decrease in water ADC as a function of TE was observed only at the longest diffusion time (p < 0.001), supporting the hypothesis that at least part of the restricted water pool can be associated with longer T₂, as suggested by previous studies in vitro. Metabolite data showed an increase of creatine (p < 0.05) and N-acetylaspartate (p < 0.05) ADCs with TE at Δ = 44 ms, and a decrease of creatine (p < 0.05) and N-acetylaspartate (p = 0.1) ADCs with TE at Δ = 246 ms. No dependence of choline ADC on TE was observed. The metabolite results suggest that diffusion and relaxation properties are dictated not only by metabolite distribution in different cell types, but also by other mechanisms, such as interactions with membranes, exchange between "free" and "bound" states or interactions with microsusceptibility gradients.

Hybrid multidimensional T(2) and diffusion-weighted MRI for prostate cancer detection

PURPOSE

To study the dependence of apparent diffusion coefficient (ADC) and T2 on echo time (TE) and b-value, respectively, in normal prostate and prostate cancer, using two-dimensional MRI sampling, referred to as "hybrid multidimensional imaging."

MATERIALS AND METHODS

The study included 10 patients with biopsy-proven prostate cancer who underwent 3 Tesla prostate MRI. Diffusion-weighted MRI (DWI) data were acquired at b = 0, 750, and 1500 s/mm(2) . For each b-value, data were acquired at TEs of 47, 75, and 100 ms. ADC and T2 were measured as a function of b-value and TE, respectively, in 15 cancer and 10 normal regions of interest (ROIs). The Friedman test was used to test the significance of changes in ADC as a function of TE and of T2 as a function of b-value.

RESULTS

In normal prostate ROIs, the ADC at TE of 47 ms is significantly smaller than ADC at TE of 100 ms (P = 0.0003) and T2 at b-value of 0 s/mm(2) is significantly longer than T2 at b-value of 1500 s/mm(2) (P = 0.001). In cancer ROIs, average ADC and T2 values do not change as a function of TE and b-value, respectively. However, in many cancer pixels, there are large decreases in the ADC as a function of TE and large increases in T2 as a function of b-value. Cancers are more conspicuous in ADC maps at longer TEs.

CONCLUSION

Parameters derived from hybrid imaging that depend on coupled/associated values of ADC and T2 may improve the accuracy of MRI in diagnosing prostate cancer.

The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.

The effect of age and cerebral ischemia on diffusion-weighted proton MR spectroscopy of the human brain

BACKGROUND AND PURPOSE

DW-MRS is a promising tool for the noninvasive identification of the cellular response to cerebral ischemia. To date, the potential confounding effects of aging and the stage of ischemia are unknown. We, therefore, examined the cross-sectional effects of age and different stages of cerebral ischemia on the diffusion of brain metabolites.

MATERIALS AND METHODS

The ADCs of 3 major metabolites, including Cho, Cr, and NAA were measured by DW-MRS in healthy younger (n = 26, 24 ± 2.2 years of age) and older (n = 17, 63 ± 7.0 years of age) adults, as well as in patients with acute (n = 7, 57 ± 4.0 years of age) and subacute (n = 12, 62 ± 7.8 years of age) cerebral ischemia.

RESULTS

Compared with younger adults, healthy older adults presented with significantly reduced ADC values of NAA (P = .000052), Cr (P = .000018), and Cho (P = .00075). Meanwhile, the ADC values of NAA (F(2,36) = 6.057, P = .006), Cr (F(2,36) = 5.634, P = .008), and Cho (F(2,36) = 8.167, P = .001) were significantly different among the acute cerebral ischemia group, subacute cerebral ischemia group, and healthy older controls. These metabolites decreased in the acute stage of cerebral ischemia but increased in the subacute stage, compared with age-matched controls.

CONCLUSIONS

The effect of age should be considered when analyzing diffusion of cerebral metabolites with DW-MRS. Our observations also suggest that metabolite diffusion data may be used to reveal changes in the intracellular environment, depending on the pathologic status of ischemia.

Assessment of the effects of cellular tissue properties on ADC measurements by numerical simulation of water diffusion

The apparent diffusion coefficient (ADC), as measured by diffusion-weighted MRI, has proven useful in the diagnosis and evaluation of ischemic stroke. The ADC of tissue water is reduced by 30-50% following ischemia and provides excellent contrast between normal and affected tissue. Despite its clinical utility, there is no consensus on the biophysical mechanism underlying the reduction in ADC. In this work, a numerical simulation of water diffusion is used to predict the effects of cellular tissue properties on experimentally measured ADC. The model indicates that the biophysical mechanisms responsible for changes in ADC postischemia depend upon the time over which diffusion is measured. At short diffusion times, the ADC is dependent upon the intrinsic intracellular diffusivity, while at longer, clinically relevant diffusion times, the ADC is highly dependent upon the cell volume fraction. The model also predicts that at clinically relevant diffusion times, the 30-50% drop in ADC after ischemia can be accounted for by cell swelling alone when intracellular T(2) is allowed to be shorter than extracellular T(2).

How does water diffusion in human white matter change following ischemic stroke?

PURPOSE

Temporal evolution of the water apparent diffusion coefficients (ADC) parallel (ADC parallel) and perpendicular (ADC perpendicular) to the human white matter tract following ischemia has not been investigated systematically. We attempted to quantify the evolution of ADC parallel and ADC perpendicular and examine whether it can be interpreted by a model of ischemic edema.

METHODS

We retrospectively selected 53 patients with ischemic lesions involving the posterior limb of the internal capsule (PLIC) and placed regions of interest in the right and left PLIC on ADC maps. We performed regression analysis of lesion-to-contralateral ratios of ADC parallel and ADC perpendicular against the time (t = 1-1600 h) from onset. We then fitted the estimated time courses of ADC parallel and ADC perpendicular obtained from the analysis to a model of nerve tissue composed of cylinders (axons) and spheres corresponding to isotropic structures, particularly focal cytoplasmic swellings of glial cells and axons seen in ischemic white matter.

RESULTS

The evolution of ADC perpendicular and ADC parallel differed. The estimated time course of ADC parallel in microm(2)*ms(-1) was 0.64 + 0.88 exp (-0.24t) for 1 < t < 54 h and 0.00059t + 0.61 for t >or= 54 h (contralateral normal value, 1.52). That of ADC perpendicular was 0.19-0.063 exp (-0.24t) for 1 < t < 54 h and 0.00040t + 0.17 for t >or=54 h (normal value 0.22). The model fitted to these values showed that the volume of the cylinders decreased, that of the spheres increased, and extracellular volume changed little from one hour to approximately one day after stroke onset.

CONCLUSION

In the human PLIC, ADC parallel continued to decrease from one hour to a few days after stroke onset, and ADC perpendicular tended to increase. The temporal evolution could be interpreted by progression of the focal cytoplasmic swelling of glial cells and axons previously observed in animal studies.

Diffusion-Exchange Weighted Imaging

A method has been developed whereby diffusion and exchange in micro cellular structures in the human brain are correlated to produce a new type of image contrast leading to determination of water exchange rates in vivo. The diffusion method relies on differential apparent diffusion coefficients as detectable nuclei exchange between adjacent compartments marked with different apparent diffusion coefficient values (e.g. intra- and extra-cellular compartments). A new pulse sequence was developed, and used to calculate water intra/extra mean residence times in brain, and the signal dependence on various experimental parameters was analysed. The method was tested in vivo at 3T field strength and produced 160 ms and 550 ms for extra-cellular and intra-cellular mean residence times, respectively.

Effects of echo time on diffusion quantification of brain white matter at 1.5 T and 3.0 T

The aim was to investigate the effects of echo time (TE) on diffusion quantification of brain white matter. Seven rhesus monkeys (all males; age, 4-6 years; weight, 5-7 kg) underwent diffusion tensor imaging (DTI) with a series of TEs in 1.5 T and 3.0 T MR scanners. The mean diffusivity (MD), fractional anisotropy (FA), primary (lambda(1)), and transverse eigenvalues (lambda(23)) were measured in a region of interest at the bilateral internal capsule. Pearson correlation showed that the FA and lambda(1) increased and lambda(23) decreased with TE both at 1.5 T and 3.0 T except for the MD. Repeated measurement analysis of variance (ANOVA) also showed significantly higher FA and lower MD and lambda(23) at 3.0 T than those at 1.5 T (P<0.01), but no statistical differences were found in lambda(1) between these two field strengths (P=0.709). These findings implied that TE and field strength might influence diffusion quantification in brain white matter.

Compartment-specific q-space analysis of diffusion-weighted data from isolated rhesus optic and sciatic nerves

We investigated compartment-specific water diffusion properties in two widely structurally different isolated bovine nerves. Sciatic and optic nerves were immersed in saline containing Gd-DTPA(2+). Consequently, T(1) became non-monoexponential and fit well to a biexponential function. q-Space diffusion data were collected for each component. In the sciatic nerve, the slow-decaying component (T(1s)) was considerably more restricted and directional than the fast-decaying component (T(1f)). In the optic nerve, fractional anisotropy of both components was comparable and similar to that of the total H(2)O signal. The root mean square of the displacement distribution functions of T(1s) correlated well with the widely different axonal diameters of both nerves. Possibly, the source of T(1s) is the intra-axonal compartment and that of T(1f) is associated with the inter-axonal space. The compartment specificity of the method shown makes it useful for the investigation of the contribution of each nerve compartment to diffusion tensor imaging measurements and other diffusion-based methods.

Compartmental relaxation and diffusion tensor imaging measurements in vivo in lambda-carrageenan-induced edema in rat skeletal muscle

Integrated diffusion tensor T(2) measurements were made on normal and edematous rat muscle, and the data were fitted with one- and two-compartment models, respectively. Edematous muscle exhibited a short-lived component (T(2) = 28 +/- 6 ms), with diffusion characteristics similar to that of normal muscle, and a long-lived component (T(2) = 96 +/- 27 ms), with greater mean apparent diffusion coefficient (ADC) and lower fractional anisotropy (FA). With this two-component description of diffusion and relaxation, values of ADC and FA estimated with a conventional pulsed-gradient spin-echo sequence will depend on the echo time, relative fraction of short-lived and long-lived water signals, and the intrinsic ADC and FA values within the tissue. On the basis of the relative differences in water diffusion properties between long-lived and short-lived water signals, as well as the similarities between the short-lived component and normal tissue, it is postulated that these two signal components largely reflect intracellular and extracellular water.

Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study

Diffusion tensor imaging (DTI) studies of human ischemic stroke within 24 h of symptom onset have reported variable findings of changes in diffusion anisotropy. Serial DTI within 24 h may clarify these heterogeneous results. We characterized longitudinal changes of diffusion anisotropy by analyzing discrete ischemic white matter (WM) and gray matter (GM) regions during the hyperacute (2.5-7 h) and acute (21.5-29 h) scanning phases of ischemic stroke onset in 13 patients. Mean diffusivity (MD), fractional anisotropy (FA) and T2-weighted signal intensity were measured for deep and subcortical WM and deep and cortical GM areas in lesions outlined by a > or =30% decrease in MD. Average reductions of approximately 40% in relative (r) MD were observed in all four brain regions during both the hyperacute and acute phases post stroke. Overall, 9 of 13 patients within 7 h post symptom onset showed elevated FA in at least one of the four tissues, and within the same cohort, 11 of 13 patients showed reduced FA in at least one of the ischemic WM and GM regions at 21.5-29 h after stroke. The fractional anisotropy in the lesion relative to the contralateral side (rFA, mean+/-S.D.) was significantly elevated in some patients in the deep WM (1.10+/-0.11, n=4), subcortical WM (1.13+/-0.14, n=4), deep GM (1.07+/-0.06, n=1) and cortical GM (1.22+/-0.13, n=5) hyperacutely (< or =7 h); however, reductions of rFA at approximately 24 h post stroke were more consistent (rFA= 0.85+/-0.12).

Early beneficial effect of matrix metalloproteinase inhibition on blood-brain barrier permeability as measured by magnetic resonance imaging countered by impaired long-term recovery after stroke in rat brain

Proteolytic disruption of the extracellular matrix with opening of the blood-brain barrier (BBB) because of matrix metalloproteinases (MMPs) occurs in reperfusion injury after stroke. Matrix metalloproteinase inhibition blocks the early disruption of the BBB, but the long-term consequences of short-term MMP inhibition are not known. Recently, a method to quantify BBB permeability by graphical methods was described, which provides a way to study both early disruption of the BBB and long-term effects on recovery in the same animal. We used a broad-spectrum MMP inhibitor, BB1101, to determine both the usefulness of the Magnetic resonance imaging (MRI) method for treatment studies and the long-term effects on recovery. Magnetic resonance imaging studies were performed in control (N=6) and drug-treated (N=8) groups on a dedicated 4.7-T MRI scanner. Adult Wistar-Kyoto underwent a 2-h middle cerebral artery occlusion followed by an MRI study after 3 h of reperfusion, which consisted of T2- and diffusion-weighted techniques. Additionally, a rapid T1 mapping protocol was also implemented to acquire one pre-gadolinium-diethylenetriaminepentaacetic acid baseline data set followed by postinjection data sets at 3-min intervals for 45 mins. The same animal was imaged again at 48 h for lesion size estimation. Data was postprocessed pixel-wise to generate apparent diffusion coefficient and permeability coefficient maps. Treatment with BB-1101 significantly reduced BBB permeability at 3 h, but failed to reduce lesion size at 48 h. Behavioral studies showed impairment in recovery in treated rats. Magnetic resonance imaging allowed for the monitoring of multiple parameters in the same animal. Our studies showed that BB-1101 was an excellent inhibitor of the BBB damage. However, results show that BB-1101 may be responsible for significant deterioration in neurologic status of treated animals. Although these preliminary results suggest that BB-1101 is useful in reducing early BBB leakage owing to reperfusion injury in stroke, further studies will be needed to determine whether the later detrimental effects can be eliminated by shorter time course of drug delivery.

Correlated displacement-T2 MRI by means of a Pulsed Field Gradient-Multi Spin Echo Method

A method for correlated displacement-T2 imaging is presented. A Pulsed Field Gradient-Multi Spin Echo (PFG-MSE) sequence is used to record T2 resolved propagators on a voxel-by-voxel basis, making it possible to perform single voxel correlated displacement-T2 analyses. In spatially heterogeneous media the method thus gives access to sub-voxel information about displacement and T2 relaxation. The sequence is demonstrated using a number of flow conducting model systems: a tube with flowing water of variable intrinsic T2's, mixing fluids of different T2's in an "X"-shaped connector, and an intact living plant. PFG-MSE can be applied to yield information about the relation between flow, pore size and exchange behavior, and can aid volume flow quantification by making it possible to correct for T2 relaxation during the displacement labeling period Delta in PFG displacement imaging methods. Correlated displacement-T2 imaging can be of special interest for a number of research subjects, such as the flow of liquids and mixtures of liquids or liquids and solids moving through microscopic conduits of different sizes (e.g., plants, porous media, bioreactors, biomats).

Anisotropic diffusion of metabolites in peripheral nerve using diffusion weighted magnetic resonance spectroscopy at ultra-high field

Although the diffusivity and anisotropy of water has been investigated thoroughly in ordered axonal systems (i.e., nervous tissue), there have been very few studies on the directional dependence of diffusion of metabolites. In this study, the mean apparent diffusion coefficient (Trace/3 ADC) and fractional anisotropy (FA) values of the intracellular metabolites N-acetyl aspartate (NAA), creatine and phosphocreatine (tCr), choline (Cho), taurine (Tau), and glutamate and glutamine (Glx) were measured parallel and perpendicular to the length of excised frog sciatic nerve using a water suppressed, diffusion-weighted, spin-echo pulse sequence at 18.8T. The degree of anisotropy (FA) of NAA (0.41+/-0.09) was determined to be less than tCr (0.59+/-0.07) and Cho (0.61+/-0.11), which is consistent with previously reported human studies of white matter. In contrast, Glx diffusion was found to be almost isotropic with an FA value of 0.20+/-0.06. The differences of FA between the metabolites is most likely due to their differing micro-environments and could be beneficial as an indicator of compartment specific changes with disease, information not readily available with water diffusion.

Microstructural changes in ischemic cortical gray matter predicted by a model of diffusion-weighted MRI

PURPOSE

To understand the diffusion attenuated MR signal from normal and ischemic brain tissue in order to extract structural and physiological information using mathematical modeling, taking into account the transverse relaxation rates in gray matter.

MATERIALS AND METHODS

We fit our diffusion model to the diffusion-weighted MR signal obtained from cortical gray matter in healthy subjects. Our model includes variable volume fractions, intracellular restriction effects, and exchange between compartments in addition to individual diffusion coefficients and transverse relaxation rates for each compartment. A global optimum was found from a wide range of parameter permutations using cluster computing. We also present simulations of cell swelling and changes of exchange rate and intracellular diffusion as possible cellular mechanisms in ischemia.

RESULTS

Our model estimates an extracellular volume fraction of 0.19 in accordance with the accepted value from histology. The absolute apparent diffusion coefficient obtained from the model was similar to that of experiments. The model and the experimental results indicate significant differences in diffusion and transverse relaxation between the tissue compartments and slow water exchange. Our model reproduces the signal changes observed in ischemia via physiologically credible mechanisms.

CONCLUSION

Our modeling suggests that transverse relaxation has a profound influence on the diffusion attenuated MR signal. Our simulations indicate cell swelling as the primary cause of the diffusion changes seen in the acute phase of brain ischemia.

Magnetic resonance imaging and T2 relaxometry of human median nerve at 7 Tesla

Measurements of T2 relaxation times in tissues have provided a unique, noninvasive method to investigate the microenvironment of water molecules in vivo. As more clinical imaging is performed at higher field strengths, tissue relaxation times need to be reassessed in order to optimize tissue contrast. The purpose of this study was to investigate the water proton T2 relaxation time in human median nerve at 7 T. High-resolution images of the wrist were obtained using a home-built dedicated microstrip coil. Gradient echo images provided a good anatomical delineation of the wrist structure, with a clear definition of the median nerve, tendons, bone, and connective tissue within the wrist in an acquisition time of 2 min. Measurements of the T2 relaxation time were performed with a spin echo imaging sequence. The T2 relaxation time of the median nerve was 18.3 +/- 1.9 ms, which is significantly shorter than the T2 measured in previous studies performed at 1.5 T and 3 T. Further, the T2 relaxation time of the median nerve is shorter than the T2 relaxation time of other tissues, such as brain tissue, at the same field strength. Since the T2 relaxation time of water protons is sensitive to the water microenvironment, relaxation measurements and, in general, a more quantitative magnetic resonance imaging approach might help in detecting and investigating diseases of peripheral nervous system, such as compressive and inflammatory neuropathies, in humans.

Diffusion of myelin water

We studied compartmentally specific characteristics of water diffusion in excised frog sciatic nerve by combining T1 or T2 selective acquisitions with pulse-gradient spin-echo (PGSE) diffusion weighting, with the specific objective of characterizing myelin water diffusion. Combining a PGSE with a Carr-Purcell-Meiboom-Gill (CPMG) acquisition provided apparent diffusion coefficients (ADCs) for each of the three T2 components found in nerve, including the short-lived component believed to be derived from myelin water. Double-inversion-recovery (DIR) preparation provided an alternate means of discriminating myelin water, and in combination with PGSE provided somewhat different measures of ADC. The DIR measures yielded myelin water ADCs of 0.37 microm2/ms (parallel to nerve) and 0.13 microm2/ms (perpendicular to nerve). These ADC estimates were postulated to be more accurate than those based on T2 discrimination, although the difference between the two findings is not clear.

The relationship between diffusion anisotropy and time of onset after stroke

Diffusion anisotropy changes in stroke lesions less than 24 h after onset have been reported to be elevated, decreased, or both. To address these mixed findings, we sought to characterize temporal changes of diffusion anisotropy by analyzing anatomically distinct ischemic white matter (WM) regions at 3 time phases within the first 34 h of ischemic stroke onset in 26 stroke patients (2 to 5 h, N=7; 7 to 14 h, N=11; 18 to 34 h, N=8). Mean diffusivity (Trace/3 apparent diffusion coefficient (ADC)), fractional anisotropy (FA), and T2-weighted signal intensity were measured for major and subcortical WM in lesions defined by a >or=30% drop in Trace/3 ADC. Major WM tract lesions with mean decreases of approximately 40% in relative (r) Trace/3 ADC showed an increased rFA of 1.11+/-0.18 (P<0.01) during the hyperacute phase (2 to 5 h), whereas rFA declined to 0.90+/-0.20 (P<0.01) and 0.88+/-0.12 (P<0.01) in the acute (7 to 14 h) and subacute (18 to 34 h) phases, respectively. Of those patients with lesions in major WM, 4 of 8 patients <or=7 h showed elevated rFA as opposed to none of the remaining 13 patients after 7 h. A greater proportion of the evaluated WM regions-of-interest (ROI) in the hyperacute phase revealed increases in rFA (60%), whereas conversely large proportions of ROIs (55% and 59%) in the acute and subacute phases showed reduced rFA. Similar anisotropy changes were noted in subcortical WM regions in the gyri.

Extraction and validation of correlation lengths from interstitial velocity fields using diffusion-weighted MRI

Magnetic Resonance Imaging methods sensitive to individual molecular displacements (q-space MRI) provide a convenient means of measuring dispersion in complex interstitial spaces. Pressure-driven flow experiments through a water-saturated packed bed phantom have been conducted to prove the feasibility of using q-space MRI to measure the coherence length associated with the interstitial velocity field. The method involves measuring the dependence of the apparent dispersion coefficient on the distance along the mean flow by repeating a small number of pulsed-gradient stimulated-echo experiments with increasing gradient pulse separation times. Assuming homogeneous interstitial flow statistics inside the averaging volume, an integral spatial scale characterizing the Eulerian velocity auto-correlation coefficient is extracted via a stochastic convective model. The validity of the a priori statistical description of interstitial flow is verified by comparing with an independent MRI measurement of the Eulerian velocity field using phase contrast methods in the same phantom with pore-level resolution. The integral length scale obtained via q-space MRI agrees with the mean pore size in the present as well as in similar phantoms found in the literature. This method has direct applicability in the quantification of the interstitial morphology of fluid-saturated porous media with resolution independent of voxel size, assuming "perfectly reflecting pore walls" (no surface relaxation) and no contribution to the MR signal from outside the pore space.

Oscillating gradient measurements of water diffusion in normal and globally ischemic rat brain

Oscillating gradients were used to probe the diffusion-time/frequency dependence of water diffusion in the gray matter of normal and globally ischemic rat brain. In terms of a conventional definition of diffusion time, the oscillating gradient measurements provided the apparent diffusion coefficient (ADC) of water with diffusion times between 9.75 ms and 375 micros, an order of magnitude shorter than previously studied in vivo. Over this range, ADCs increased as much as 24% in vivo and 50% postmortem, depending on the nature of the oscillating gradient waveform used. Novel waveforms were employed to sample narrow frequency bands of the so-called diffusion spectrum. This spectral description of ADC includes the effects of restriction and/or flow, and is independent of experimental parameters, such as diffusion time. The results in rat brain were found to be consistent with restricted diffusion and the known micro-anatomy of gray matter. Differences between normal and postmortem data were consistent with an increase in water restriction and/or a decrease in flow, and tentatively suggest that physical changes following the onset of ischemia occur on a scale of about 2 microm, similar to a typical cellular dimension in gray matter.

The basis of anisotropic water diffusion in the nervous system - a technical review

Anisotropic water diffusion in neural fibres such as nerve, white matter in spinal cord, or white matter in brain forms the basis for the utilization of diffusion tensor imaging (DTI) to track fibre pathways. The fact that water diffusion is sensitive to the underlying tissue microstructure provides a unique method of assessing the orientation and integrity of these neural fibres, which may be useful in assessing a number of neurological disorders. The purpose of this review is to characterize the relationship of nuclear magnetic resonance measurements of water diffusion and its anisotropy (i.e. directional dependence) with the underlying microstructure of neural fibres. The emphasis of the review will be on model neurological systems both in vitro and in vivo. A systematic discussion of the possible sources of anisotropy and their evaluation will be presented followed by an overview of various studies of restricted diffusion and compartmentation as they relate to anisotropy. Pertinent pathological models, developmental studies and theoretical analyses provide further insight into the basis of anisotropic diffusion and its potential utility in the nervous system.

Modelling of self-diffusion and relaxation time NMR in multicompartment systems with cylindrical geometry

Multicompartment characteristics of relaxation and diffusion in a model for (plant) cells and tissues have been simulated as a means to test separating the signal into a set of these compartments. A numerical model of restricted diffusion and magnetization relaxation behavior in PFG-CPMG NMR experiments, based on Fick's second law of diffusion, has been extended for two-dimensional diffusion in systems with concentric cylindrical compartments separated by permeable walls. This model is applicable to a wide range of (cellular) systems and allows the exploration of temporal and spatial behavior of the magnetization with and without the influence of gradient pulses. Numerical simulations have been performed to show the correspondence between the obtained results and previously reported studies and to investigate the behavior of the apparent diffusion coefficients for the multicompartment systems with planar and cylindrical geometry. The results clearly demonstrate the importance of modelling two-dimensional diffusion in relation to the effect of restrictions, permeability of the membranes, and the bulk relaxation within the compartments. In addition, the consequences of analysis by multiexponential curve fitting are investigated.

Compartmental study of T(1) and T(2) in rat brain and trigeminal nerve in vivo

The integrated T(1)-T(2) characteristics of rat brain and trigeminal nerve water were studied in vivo using a rapid method for acquiring a series of images that depend on T(1) and T(2) relaxation times. Gray matter regions showed only one signal component in both the T(1) and T(2) domains. Trigeminal nerve, however, which has been shown previously to exhibit three T(2) components, was found to also exhibit three T(1) components. The correlations between these T(1) and T(2) components were demonstrated by uniquely filtering out each of the three T(2) components using an inversion-recovery preparation, as determined by the component T(1) values. Based on previous works, it is postulated that each of these three signal components is derived from a unique microanatomical region of the nerve. Knowledge of these T(1) components may thus prove valuable in devising novel methods of identifying the presence and quantifying the volume of tissue subtypes such as myelin.

Diffusion-weighted in vivo localized proton MR spectroscopy of human cerebral ischemia and tumor

The apparent diffusion coefficients (ADCs) of water and brain metabolites were determined by proton MR spectroscopy on a clinical MR scanner for healthy volunteers and for pathological changes in cases of acute cerebral infarction and brain tumor. The ADCs of N-acetyl aspartate (NAA) and creatines in tissue involved in acute infarction were decreased compared to normal control values, while in tumors they showed increased values. Since NAA is a neuronal marker, these findings suggest that neuronal cell viscosity changes according to the pathological status of the tissue. The lactate ADC was significantly larger than the values for other major metabolites in cases of ischemia and tumor, suggesting that lactate is present in a different compartment. These results indicate that metabolite diffusion data can be used to reveal changes in the intracellular environment depending on the pathological status.