Fast and robust measurement of microstructural dimensions using temporal diffusion spectroscopy

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.

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

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Diffusion MRI with pulsed and free gradient waveforms: Effects of restricted diffusion and exchange

Monitoring time dependence with diffusion MRI yields observables sensitive to compartment sizes (restricted diffusion) and membrane permeability (water exchange). However, restricted diffusion and exchange have opposite effects on the diffusion-weighted signal, which can lead to errors in parameter estimates. In this work, we propose a signal representation that incorporates the effects of both restricted diffusion and exchange up to second order in b-value and is compatible with gradient waveforms of arbitrary shape. The representation features mappings from a gradient waveform to two scalars that separately control the sensitivity to restriction and exchange. We demonstrate that these scalars span a two-dimensional space that can be used to choose waveforms that selectively probe restricted diffusion or exchange, eliminating the correlation between the two phenomena. We found that waveforms with specific but unconventional shapes provide an advantage over conventional pulsed and oscillating gradient acquisitions. We also show that parametrization of waveforms into a two-dimensional space can be used to understand protocols from other approaches that probe restricted diffusion and exchange. For example, we found that the variation of mixing time in filter-exchange imaging corresponds to variation of our exchange-weighting scalar at a fixed value of the restriction-weighting scalar. The proposed signal representation was evaluated using Monte Carlo simulations in identical parallel cylinders with hexagonal and random packing as well as parallel cylinders with gamma-distributed radii. Results showed that the approach is sensitive to sizes in the interval 4-12 μm and exchange rates in the simulated range of 0 to 20 s - 1 , but also that there is a sensitivity to the extracellular geometry. The presented theory constitutes a simple and intuitive description of how restricted diffusion and exchange influence the signal as well as a guide to protocol design capable of separating the two effects.

Time-dependent diffusion MRI probes cerebellar microstructural alterations in a mouse model of Down syndrome

The cerebellum is a complex system with distinct cortical laminar organization. Alterations in cerebellar microstructure are common and associated with many factors such as genetics, cancer and ageing. Diffusion MRI (dMRI) provides a non-invasive tool to map the brain structural organization, and the recently proposed diffusion-time (td )-dependent dMRI further improves its capability to probe the cellular and axonal/dendritic microstructures by measuring water diffusion at multiple spatial scales. The td -dependent diffusion profile in the cerebellum and its utility in detecting cerebellar disorders, however, are not yet elucidated. Here, we first deciphered the spatial correspondence between dMRI contrast and cerebellar layers, based on which the cerebellar layer-specific td -dependent dMRI patterns were characterized in both euploid and Ts65Dn mice, a mouse model of Down syndrome. Using oscillating gradient dMRI, which accesses diffusion at short td 's by modulating the oscillating frequency, we detected subtle changes in the apparent diffusivity coefficient of the cerebellar internal granular layer and Purkinje cell layer of Ts65Dn mice that were not detectable by conventional pulsed gradient dMRI. The detection sensitivity of oscillating gradient dMRI increased with the oscillating frequency at both the neonatal and adult stages. The td -dependence, quantified by ΔADC map, was reduced in Ts65Dn mice, likely associated with the reduced granule cell density and abnormal dendritic arborization of Purkinje cells as revealed from histological evidence. Our study demonstrates superior sensitivity of short-td diffusion using oscillating gradient dMRI to detect cerebellar microstructural changes in Down syndrome, suggesting the potential application of this technique in cerebellar disorders.

The sensitivity of diffusion MRI to microstructural properties and experimental factors

Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.

Diffusion-prepared 3D gradient spin-echo sequence for improved oscillating gradient diffusion MRI

PURPOSE

Oscillating gradient (OG) enables the access of short diffusion times for time-dependent diffusion MRI (dMRI); however, it poses several technical challenges for clinical use. This study proposes a 3D oscillating gradient-prepared gradient spin-echo (OGprep-GRASE) sequence to improve SNR and shorten acquisition time for OG dMRI on clinical scanners.

METHODS

The 3D OGprep-GRASE sequence consisted of global saturation, diffusion encoding, fat saturation, and GRASE readout modules. Multiplexed sensitivity-encoding reconstruction was used to correct the phase errors between multiple shots. We compared the scan time and SNR of the proposed sequence and the conventional 2D-EPI sequence for OG dMRI at 30-90-mm slice coverage. We also examined the time-dependent diffusivity changes with OG dMRI acquired at frequencies of 50 Hz and 25 Hz and pulsed-gradient dMRI at diffusion times of 30 ms and 60 ms.

RESULTS

The OGprep-GRASE sequence reduced the scan time by a factor of 1.38, and increased the SNR by 1.74-2.27 times compared with 2D EPI for relatively thick slice coverage (60-90 mm). The SNR gain led to improved diffusion-tensor reconstruction in the multishot protocols. Image distortion in 2D-EPI images was also reduced in GRASE images. Diffusivity measurements from the pulsed-gradient dMRI and OG dMRI showed clear diffusion-time dependency in the white matter and gray matter of the human brain, using both the GRASE and EPI sequences.

CONCLUSION

The 3D OGprep-GRASE sequence improved scan time and SNR and reduced image distortion compared with the 2D multislice acquisition for OG dMRI on a 3T clinical system, which may facilitate the clinical translation of time-dependent dMRI.

In vivo magnetic resonance imaging of treatment-induced apoptosis

Imaging apoptosis could provide an early and specific means to monitor tumor responses to treatment. To date, despite numerous attempts to develop molecular imaging approaches, there is still no widely-accepted and reliable method for in vivo imaging of apoptosis. We hypothesized that the distinct cellular morphologic changes associated with treatment-induced apoptosis, such as cell shrinkage, cytoplasm condensation, and DNA fragmentation, can be detected by temporal diffusion spectroscopy imaging (TDSI). Cetuximab-induced apoptosis was assessed in vitro and in vivo with cetuximab-sensitive (DiFi) and insensitive (HCT-116) human colorectal cancer cell lines by TDSI. TDSI findings were complemented by flow cytometry and immunohistochemistry. Cell cycle analysis and flow cytometry detected apoptotic cell shrinkage in cetuximab-treated DiFi cells, and significant apoptosis was confirmed by histology. TDSI-derived parameters quantified key morphological changes including cell size decreases during apoptosis in responsive tumors that occurred earlier than gross tumor volume regression. TDSI provides a unique measurement of apoptosis by identifying cellular characteristics, particularly cell shrinkage. The method will assist in understanding the underlying biology of solid tumors and predict tumor response to therapies. TDSI is free of any exogenous agent or radiation, and hence is very suitable to be incorporated into clinical applications.

Imaging brain microstructure with diffusion MRI: practicality and applications

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term.

Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook

Phantoms, both numerical (software) and physical (hardware), can serve as a gold standard for the validation of MRI methods probing the brain microstructure. This review aims to provide guidelines on how to build, implement, or choose the right phantom for a particular application, along with an overview of the current state-of-the-art of phantoms dedicated to study brain microstructure with MRI. For physical phantoms, we discuss the essential requirements and relevant characteristics of both the (NMR visible) liquid and (NMR invisible) phantom materials that induce relevant microstructural features detectable via MRI, based on diffusion, intra-voxel incoherent motion, magnetization transfer or magnetic susceptibility weighted contrast. In particular, for diffusion MRI, many useful phantoms have been proposed, ranging from simple liquids to advanced biomimetic phantoms consisting of hollow or plain microfibers and capillaries. For numerical phantoms, the focus is on Monte Carlo simulations of random walk, for which the basic principles, along with useful criteria to check and potential pitfalls are reviewed, in addition to a literature overview highlighting recent advances. While many phantoms exist already, the current review aims to stimulate further research in the field and to address remaining needs.

A biomimetic tumor tissue phantom for validating diffusion-weighted MRI measurements

PURPOSE

To develop a biomimetic tumor tissue phantom which more closely reflects water diffusion in biological tissue than previously used phantoms, and to evaluate the stability of the phantom and its potential as a tool for validating diffusion-weighted (DW) MRI measurements.

METHODS

Coaxial-electrospraying was used to generate micron-sized hollow polymer spheres, which mimic cells. The bulk structure was immersed in water, providing a DW-MRI phantom whose apparent diffusion coefficient (ADC) and microstructural properties were evaluated over a period of 10 months. Independent characterization of the phantom's microstructure was performed using scanning electron microscopy (SEM). The repeatability of the construction process was investigated by generating a second phantom, which underwent high resolution synchrotron-CT as well as SEM and MR scans.

RESULTS

ADC values were stable (coefficients of variation (CoVs) < 5%), and varied with diffusion time, with average values of 1.44 ± 0.03 µm2 /ms (Δ = 12 ms) and 1.20 ± 0.05 µm2 /ms (Δ = 45 ms). Microstructural parameters showed greater variability (CoVs up to 13%), with evidence of bias in sphere size estimates. Similar trends were observed in the second phantom.

CONCLUSION

A novel biomimetic phantom has been developed and shown to be stable over 10 months. It is envisaged that such phantoms will be used for further investigation of microstructural models relevant to characterizing tumor tissue, and may also find application in evaluating acquisition protocols and comparing DW-MRI-derived biomarkers obtained from different scanners at different sites. Magn Reson Med 80:147-158, 2018. © 2017 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Inferring diameters of spheres and cylinders using interstitial water

OBJECT

Most early methods to infer axon diameter distributions using magnetic resonance imaging (MRI) used single diffusion encoding sequences such as pulsed gradient spin echo (SE) and are thus sensitive to axons of diameters > 5 μm. We previously simulated oscillating gradient (OG) SE sequences for diffusion spectroscopy to study smaller axons including the majority constituting cortical connections. That study suggested the model of constant extra-axonal diffusion breaks down at OG accessible frequencies. In this study we present data from phantoms to test a time-varying interstitial apparent diffusion coefficient.

MATERIALS AND METHODS

Diffusion spectra were measured in four samples from water packed around beads of diameters 3, 6 and 10 μm; and 151 μm diameter tubes. Surface-to-volume ratios, and diameters were inferred.

RESULTS

The bead pore radii estimates were 0.60±0.08 μm, 0.54±0.06 μm and 1.0±0.1 μm corresponding to bead diameters ranging from 2.9±0.4 μm to 5.3±0.7 μm, 2.6±0.3 μm to 4.8±0.6 μm, and 4.9±0.7 μm to 9±1 μm. The tube surface-to-volume ratio estimate was 0.06±0.02 μm^-1 corresponding to a tube diameter of 180±70 μm.

CONCLUSION

Interstitial models with OG inferred 3-10 μm bead diameters from 0.54±0.06 μm to 1.0±0.1 μm pore radii and 151 μm tube diameters from 0.06±0.02 μm^-1 surface-to-volume ratios.

Oscillating gradient diffusion kurtosis imaging of normal and injured mouse brains

Recent advances in diffusion MRI employ multiple diffusion encoding schemes with varying diffusion direction, weighting, and diffusion time to investigate specific microstructural properties in biological tissues. In this study, we examined time-dependent diffusion kurtosis contrast in adult mouse brains and in neonatal mouse brains after hypoxic-ischemic (HI) injury. In vivo diffusion kurtosis maps were acquired with a short diffusion time using an oscillating gradient spin echo (OGSE) sequence at 100 Hz and with a relatively long diffusion time (20 ms) using a pulsed gradient spin echo (PGSE) sequence. In the adult mouse brain, we found that the cortex and hippocampus showed larger differences between OGSE kurtosis and PGSE kurtosis than major white matter tracts. In neonatal mouse brains with unilateral HI injury, the OGSE kurtosis map overall provided stronger edema contrast than the PGSE kurtosis map, and the differences between OGSE and PGSE kurtosis measurements in the edema region reflected heterogeneity of injury. This is the first in vivo study that has demonstrated multi-direction OGSE kurtosis contrasts in the mouse brain. Comparing PGSE and OGSE kurtosis measures may provide additional information on microstructural changes after ischemic stroke.

Diffusion tensor imaging of human Achilles tendon by stimulated echo readout-segmented EPI (ste-RS-EPI)

PURPOSE

Healing, regeneration, and remodeling of the injured Achilles tendon are associated with notable changes in tendon architecture. However, assessing Achilles microstructural properties with conventional diffusion tension imaging (DTI) remains a challenge because of very short T₂ / <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msubsup><mml:mi>T</mml:mi> <mml:mn>2</mml:mn> <mml:mo>*</mml:mo></mml:msubsup> </mml:mrow> </mml:math> values of the tendon. Hence, the objective of this study was to develop a novel Achilles tendon DTI protocol for a non-invasive investigation of the changes of microstructural integrity in tendinopathy.

METHODS

A novel stimulated echo readout-segmented EPI (ste-RS-EPI) DTI sequence was proposed to achieve a TE of ∼14-20 ms for typical b-values of 400-800 s/mm² on clinical 3T MRI scanners. To further boost tendon MR signal, the Achilles was positioned at the magic angle (∼55 °) with respect to the scanner B₀ field. The sensitivity of the developed protocol was evaluated in 19 healthy participants and 6 patients with clinically confirmed tendinopathy.

RESULTS

Compared to spin echo RS-EPI DTI protocol, ste-RS-EPI provided an ∼100-200% increase in Achilles MR signal. Tendinopathic Achilles demonstrated a high degree of microstructural disruption based on DTI tractography analysis, with significantly lower (P < 0.05) axial diffusivity (1.20 ± 0.19 vs. 1.39 ± 0.10 × 10^-3 mm² /s), radial diffusivity (0.72 ± 0.11 vs. 0.81 ± 0.08 × 10^-3 mm² /s), and mean diffusivity (0.87 ± 0.14 vs. 1.00 ± 0.07 × 10^-3 mm² /s), but no significant difference in fractional anisotropy (0.38 ± 0.04 vs. 0.38 ± 0.05; P = 0.86).

CONCLUSION

Achilles tendon ste-RS-EPI DTI can non-invasively detect the tendinopathy-induced changes to microstructural integrity, consistent with the disruption of collagen arrangement and increased cellularity. This study demonstrated the robustness and sensitivity of the proposed protocol in Achilles tendinopathy.

In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy

PURPOSE

A temporal diffusion MRI spectroscopy based approach has been developed to quantify cancer cell size and density in vivo.

METHODS

A novel imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) method selects a specific limited diffusion spectral window for an accurate quantification of cell sizes ranging from 10 to 20 μm in common solid tumors. In practice, it is achieved by a combination of a single long diffusion time pulsed gradient spin echo (PGSE) and three low-frequency oscillating gradient spin echo (OGSE) acquisitions. To validate our approach, hematoxylin and eosin staining and immunostaining of cell membranes, in concert with whole slide imaging, were used to visualize nuclei and cell boundaries, and hence, enabled accurate estimates of cell size and cellularity.

RESULTS

Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes were obtained in vivo for three types of human colon cancers. The IMPULSED-derived apparent cellularities showed a stronger correlation (r = 0.81; P < 0.0001) with histology-derived cellularities than conventional ADCs (r = -0.69; P < 0.03).

CONCLUSION

The IMPULSED approach samples a specific region of temporal diffusion spectra with enhanced sensitivity to length scales of 10-20 μm, and enables measurements of cell sizes and cellularities in solid tumors in vivo. Magn Reson Med 78:156-164, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Anisotropic diffusion phantoms based on microcapillaries

Diffusion MRI is an efficient and widely used technique for the investigation of tissue structure and organisation in vivo. Multiple phenomenological and biophysical diffusion models are intensively exploited for the analysis of the diffusion experiments. However, the verification of the applied diffusion models remains challenging. In order to provide a "gold standard" and to assess the accuracy of the derived parameters and the limitations of the diffusion models, anisotropic diffusion phantoms with well known architecture are demanded. In the present work we built four anisotropic diffusion phantoms consisting of hollow microcapillaries with very small inner diameters of 5, 10 and 20μm and outer diameters of 90 and 150μm. For testing the suitability of these phantoms, we performed diffusion measurements on all of them and evaluated the resulting data with a set of popular diffusion models, such as diffusion tensor and diffusion kurtosis imaging, a two compartment model with intra- and extra-capillary water spaces using bi-exponential fitting, and time-dependent diffusion coefficients in Mitra's limit. The perspectives and limitations of these diffusion phantoms are presented and discussed.

Impact of transcytolemmal water exchange on estimates of tissue microstructural properties derived from diffusion MRI

PURPOSE

To investigate the influence of transcytolemmal water exchange on estimates of tissue microstructural parameters derived from diffusion MRI using conventional PGSE and IMPULSED methods.

METHODS

Computer simulations were performed to incorporate a broad range of intracellular water life times τin (50-∞ ms), cell diameters d (5-15 μm), and intrinsic diffusion coefficient Din (0.6-2 μm2 /ms) for different values of signal-to-noise ratio (SNR) (10 to 50). For experiments, murine erythroleukemia (MEL) cancer cells were cultured and treated with saponin to selectively change cell membrane permeability. All fitted microstructural parameters from simulations and experiments in vitro were compared with ground-truth values.

RESULTS

Simulations showed that, for both PGSE and IMPULSED methods, cell diameter d can be reliably fit with sufficient SNR (≥ 50), whereas intracellular volume fraction fin is intrinsically underestimated due to transcytolemmal water exchange. Din can be reliably fit only with sufficient SNR and using the IMPULSED method with short diffusion times. These results were confirmed with those obtained in the cell culture experiments in vitro.

CONCLUSION

For the sequences and models considered in this study, transcytolemmal water exchange has minor effects on the fittings of d and Din with physiologically relevant membrane permeabilities if the SNR is sufficient (> 50), but fin is intrinsically underestimated. Magn Reson Med 77:2239-2249, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Early Detection of Treatment-Induced Mitotic Arrest Using Temporal Diffusion Magnetic Resonance Spectroscopy

PURPOSE: A novel quantitative magnetic resonance imaging (MRI) method, namely, temporal diffusion spectroscopy (TDS), was used to detect the response of tumor cells (notably, mitotic arrest) to a specific antimitotic treatment (Nab-paclitaxel) in culture and human ovarian xenografts and evaluated as an early imaging biomarker of tumor responsiveness. METHODS: TDS measures a series of apparent diffusion coefficients (ADCs) of tissue water over a range of effective diffusion times, which may correspond to diffusion distances ranging from subcellular to cellular levels (~ 3-20 μm). By fitting the measured ADC data to a tissue model, parameters reflecting structural properties such as restriction size in solid tumors can be extracted. Two types of human ovarian cell lines (OVCAR-8 as a responder to Nab-paclitaxel and NCI/ADR-RES as a resistant type) were treated with either vehicle (PBS) or Nab-paclitaxel, and treatment responses of both in vitro and in vivo cases were investigated using TDS. RESULTS: Acute cell size increases induced by Nab-paclitaxel in responding tumors were confirmed by flow cytometry and light microscopy in cell culture. Nab-paclitaxel–induced mitotic arrest in treated tumors/cells was quantified histologically by measuring the mitotic index in vivo using a mitosis-specific marker (anti-phosphohistone H3). Changes in the fitted restriction size, one of the parameters obtained from TDS, were able to detect and quantify increases in tumor cell sizes. All the MR results had a high degree of consistency with other flow, microscopy, and histological data. Moreover, with an appropriate analysis, the Nab-paclitaxel–responsive tumors in vivo could be easily distinguished from all the other vehicle-treated and Nab-paclitaxel–resistant tumors. CONCLUSION: TDS detects increases in cell sizes associated with antimitotic-therapy–induced mitotic arrest in solid tumors in vivo which occur before changes in tissue cellularity or conventional diffusion MRI metrics. By quantifying changes in cell size, TDS has the potential to improve the specificity of MRI methods in the evaluation of therapeutic response and enable a mechanistic understanding of therapy-induced changes in tumors.

1D and 2D diffusion pore imaging on a preclinical MR system using adaptive rephasing: Feasibility and pulse sequence comparison

Diffusion pore imaging (DPI) has recently been proposed as a means to acquire images of the average pore shape in an image voxel or region of interest. The highly asymmetric gradient scheme of its sequence makes it substantially demanding in terms of the hardware of the NMR system. The aim of this work is to show the feasibility of DPI on a preclinical 9.4T animal scanner. Using water-filled capillaries with an inner radius of 10μm, four different variants of the DPI sequence were compared in 1D and 2D measurements. The pulse sequences applied cover the basic implementation using one long and one temporally narrow gradient pulse, a CPMG-like variant with multiple refocusing RF pulses as well as two variants splitting up the long gradient and distributing it on either side of the refocusing pulse. Substantial differences between the methods were found in terms of signal-to-noise ratio, contrast, blurring, deviations from the expected results and sensitivity to gradient imperfections. Each of the tested sequences was found to produce characteristic gradient mismatches dependent on the absolute value, direction and sign of the applied q-value. Read gradients were applied to compensate these mismatches translating them into time shifts, which enabled 1D DPI yielding capillary radius estimations within the tolerances specified by the manufacturer. For a successful DPI application in 2D, a novel gradient amplitude adaption scheme was implemented to correct for the occurring time shifts. Using this adaption, higher conformity to the expected pore shape, reduced blurring and enhanced contrast were achieved. Images of the phantom's pore shape could be acquired with a nominal resolution of 2.2μm.

Diffusion MRI of the spinal cord: from structural studies to pathology

Diffusion MRI is extensively used to study brain microarchitecture and pathologies, and water diffusion appears highly anisotropic in the white matter (WM) of the spinal cord (SC). Despite these facts, the use of diffusion MRI to study the SC, which has increased in recent years, is much less common than that in the brain. In the present review, after a brief outline of early studies of diffusion MRI (DWI) and diffusion tensor MRI (DTI) of the SC, we provide a short survey on DTI and on diffusion MRI methods beyond the tensor that have been used to study SC microstructure and pathologies. After introducing the porous view of WM and describing the q-space approach and q-space diffusion MRI (QSI), we describe other methodologies that can be applied to study the SC. Selected applications of the use of DTI, QSI, and other more advanced diffusion MRI methods to study SC microstructure and pathologies are presented, with some emphasis on the use of less conventional diffusion methodologies. Because of length constraints, we concentrate on structural studies and on a few selected pathologies. Examples of the use of diffusion MRI to study dysmyelination, demyelination as in experimental autoimmune encephalomyelitis and multiple sclerosis, amyotrophic lateral sclerosis, and traumatic SC injury are presented. We conclude with a brief summary and a discussion of challenges and future directions for diffusion MRI of the SC. Copyright © 2016 John Wiley & Sons, Ltd.

A comparative assessment of preclinical chemotherapeutic response of tumors using quantitative non-Gaussian diffusion MRI

BACKGROUND

Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear.

METHODS

Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy. Bayesian Information Criterion (BIC) was used for model selection among all three non-Gaussian models.

RESULTS

All of tumor volume, histology, conventional ADC, and three non-Gaussian DWI models could show significant differences between control and treatment groups after four days of treatment. However, only the non-Gaussian models detected significant changes after two days of treatment. For any treatment or control group, over 65.7% of tumor voxels indicate the bi-exponential model is strongly or very strongly preferred.

CONCLUSION

Non-Gaussian DWI model-derived biomarkers are capable of detecting tumor earlier chemotherapeutic response of tumors compared with conventional ADC and tumor volume. The bi-exponential model provides better fitting compared with statistical and stretched exponential models for the tumor and treatment models used in the current work.

Double oscillating diffusion encoding and sensitivity to microscopic anisotropy

Purpose

To introduce a novel diffusion pulse sequence, namely double oscillating diffusion encoding (DODE), and to investigate whether it adds sensitivity to microscopic diffusion anisotropy (µA) compared to the well‐established double diffusion encoding (DDE) methodology.

Methods

We simulate measurements from DODE and DDE sequences for different types of microstructures exhibiting restricted diffusion. First, we compare the effect of varying pulse sequence parameters on the DODE and DDE signal. Then, we analyse the sensitivity of the two sequences to the microstructural parameters (pore diameter and length) which determine µA. Finally, we investigate specificity of measurements to particular substrate configurations.

Results

Simulations show that DODE sequences exhibit similar signal dependence on the relative angle between the two gradients as DDE sequences, however, the effect of varying the mixing time is less pronounced. The sensitivity analysis shows that in substrates with elongated pores and various orientations, DODE sequences increase the sensitivity to pore diameter, while DDE sequences are more sensitive to pore length. Moreover, DDE and DODE sequence parameters can be tailored to enhance/suppress the signal from a particular range of substrates.

Conclusions

A combination of DODE and DDE sequences maximize sensitivity to µA, compared to using just the DDE method. Magn Reson Med 78:550–564, 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Fast and simplified mapping of mean axon diameter using temporal diffusion spectroscopy

Mapping axon diameter is of interest for the potential diagnosis and monitoring of various neuronal pathologies. Advanced diffusion-weighted MRI methods have been developed to measure mean axon diameters non-invasively, but suffer major drawbacks that prevent their direct translation into clinical practice, such as complex non-linear data fitting and, more importantly, long scanning times that are usually not tolerable for most human subjects. In the current study, temporal diffusion spectroscopy using oscillating diffusion gradients was used to measure mean axon diameters with high sensitivity to small axons in the central nervous system. Axon diameters have been found to be correlated with a novel metric, DDR⊥ (the rate of dispersion of the perpendicular diffusion coefficient with gradient frequency), which is a model-free quantity that does not require complex data analyses and can be obtained from two diffusion coefficient measurements in clinically relevant times with conventional MRI machines. A comprehensive investigation including computer simulations and animal experiments ex vivo showed that measurements of DDR⊥ agree closely with histological data. In humans in vivo, DDR⊥ was also found to correlate well with reported mean axon diameters in human corpus callosum, and the total scan time was only about 8 min. In conclusion, DDR⊥ may have potential to serve as a fast, simple and model-free approach to map the mean axon diameter of white matter in clinics for assessing axon diameter changes.

PGSE, OGSE, and sensitivity to axon diameter in diffusion MRI: Insight from a simulation study

PURPOSE

To identify optimal pulsed gradient spin-echo (PGSE) and oscillating gradient spin-echo (OGSE) sequence settings for maximizing sensitivity to axon diameter in idealized and practical conditions.

METHODS

Simulations on a simple two-compartment white matter model (with nonpermeable cylinders) are used to investigate a wide space of clinically plausible PGSE and OGSE sequence parameters with trapezoidal diffusion gradient waveforms. Signal sensitivity is measured as a derivative of the signal with respect to axon diameter. Models of parallel and dispersed fibers are investigated separately to represent idealized and practical conditions.

RESULTS

Simulations show that, for the simple case of gradients perfectly perpendicular to straight parallel fibers, PGSE always gives maximum sensitivity. However, in real-world scenarios where fibers have unknown and dispersed orientation, low-frequency OGSE provides higher sensitivity. Maximum sensitivity results show that on current clinical scanners (Gmax  = 60 mT/m, signal to noise ratio (SNR) = 20) axon diameters below 6 µm are indistinguishable from zero. Scanners with stronger gradient systems such as the Massachusetts General Hospital (MGH) Connectom scanner (Gmax  = 300 mT/m) can extend this sensitivity limit down to 2-3 µm, probing a much greater proportion of the underlying axon diameter distribution.

CONCLUSION

Low-frequency OGSE provides additional sensitivity to PGSE in practical situations. OGSE is particularly advantageous for systems with high performance gradients.

Including diffusion time dependence in the extra-axonal space improves in vivo estimates of axonal diameter and density in human white matter

Axonal density and diameter are two fundamental properties of brain white matter. Recently, advanced diffusion MRI techniques have made these two parameters accessible in vivo. However, the techniques available to estimate such parameters are still under development. For example, current methods to map axonal diameters capture relative trends over different structures, but consistently over-estimate absolute diameters. Axonal density estimates are more accessible experimentally, but different modeling approaches exist and the impact of the experimental parameters has not been thoroughly quantified, potentially leading to incompatibility of results obtained in different studies using different techniques. Here, we characterise the impact of diffusion time on axonal density and diameter estimates using Monte Carlo simulations and STEAM diffusion MRI at 7 T on 9 healthy volunteers. We show that axonal density and diameter estimates strongly depend on diffusion time, with diameters almost invariably overestimated and density both over and underestimated for some commonly used models. Crucially, we also demonstrate that these biases are reduced when the model accounts for diffusion time dependency in the extra-axonal space. For axonal density estimates, both upward and downward bias in different situations are removed by modeling extra-axonal time-dependence, showing increased accuracy in these estimates. For axonal diameter estimates, we report increased accuracy in ground truth simulations and axonal diameter estimates decreased away from high values given by earlier models and towards known values in the human corpus callosum when modeling extra-axonal time-dependence. Axonal diameter feasibility under both advanced and clinical settings is discussed in the light of the proposed advances.

Structural information revealed by the dispersion of ADC with frequency

Diffusion MRI provides a non-invasive means to characterize tissue microstructure at varying length scales. Temporal diffusion spectra reveal how the apparent diffusion coefficient (ADC) varies with frequency. When measured using oscillating gradient spin echo sequences, the manner in which ADC disperses with gradient frequency (which is related to the reciprocal of diffusion time) provides information on the characteristic dimensions of restricting structures within the medium. For example, the dispersion of ADC with oscillating gradient frequency (ΔfADC) has been shown to correlate with axon sizes in white matter and provide novel tissue contrast in images of mouse hippocampus and cerebellum. However, despite increasing interest in applying frequency-dependent ADC to derive novel information on tissue, the interpretations of ADC spectra are not always clear. In this study, the relation between ADC spectra and restricting dimensions are further elucidated and used to derive novel image contrast related to the sizes of intrinsic microstructures.

Microstructural parameter estimation in vivo using diffusion MRI and structured prior information

Purpose

Diffusion MRI has recently been used with detailed models to probe tissue microstructure. Much of this work has been performed ex vivo with powerful scanner hardware, to gain sensitivity to parameters such as axon radius. By contrast, performing microstructure imaging on clinical scanners is extremely challenging.

Methods

We use an optimized dual spin‐echo diffusion protocol, and a Bayesian fitting approach, to obtain reproducible contrast (histogram overlap of up to 92%) in estimated maps of axon radius index in healthy adults at a modest, widely‐available gradient strength (35 mT m −1). A key innovation is the use of influential priors.

Results

We demonstrate that our priors can improve precision in axon radius estimates—a 7‐fold reduction in voxelwise coefficient of variation in vivo—without significant bias. Our results may reflect true axon radius differences between white matter regions, but this interpretation should be treated with caution due to the complexity of the tissue relative to our model.

Conclusions

Some sensitivity to relatively large axons (3–15 μm) may be available at clinical field and gradient strengths. Future applications at higher gradient strength will benefit from the favorable eddy current properties of the dual spin‐echo sequence, and greater precision available with suitable priors. Magn Reson Med, 2015. © 2015 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Magn Reson Med 75:1787–1796, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.

Quantification of cell size using temporal diffusion spectroscopy

PURPOSE

A new approach has been developed to quantify cell sizes and intracellular volume fractions using temporal diffusion spectroscopy with diffusion-weighted acquisitions.

METHODS

Temporal diffusion spectra may be used to characterize tissue microstructure by measuring the effects of restrictions over a range of diffusion times. Oscillating gradients have been used previously to probe variations on cellular and subcellular scales, but their ability to accurately measure cell sizes larger than 10 μm is limited. By combining measurements made using oscillating gradient spin echo (OGSE) and a conventional pulsed gradient spin echo (PGSE) acquisition with a single, relatively long diffusion time, we can accurately quantify cell sizes and intracellular volume fractions.

RESULTS

Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes and intracellular volume fractions were obtained in vitro for (i) different cell types with sizes ranging from 10 to 20 μm, (ii) different cell densities, and (iii) before and after anticancer treatment.

CONCLUSION

Hybrid OGSE-PGSE acquisitions sample a larger region of temporal diffusion spectra and can accurately quantify cell sizes over a wide range. Moreover, the maximum gradient strength used was lower than 15 G/cm, suggesting that this approach is translatable to practical MR imaging.

PGSE, OGSE, and sensitivity to axon diameter in diffusion MRI: Insight from a simulation study

Purpose

To identify optimal pulsed gradient spin‐echo (PGSE) and oscillating gradient spin‐echo (OGSE) sequence settings for maximizing sensitivity to axon diameter in idealized and practical conditions.

Methods

Simulations on a simple two‐compartment white matter model (with nonpermeable cylinders) are used to investigate a wide space of clinically plausible PGSE and OGSE sequence parameters with trapezoidal diffusion gradient waveforms. Signal sensitivity is measured as a derivative of the signal with respect to axon diameter. Models of parallel and dispersed fibers are investigated separately to represent idealized and practical conditions.

Results

Simulations show that, for the simple case of gradients perfectly perpendicular to straight parallel fibers, PGSE always gives maximum sensitivity. However, in real‐world scenarios where fibers have unknown and dispersed orientation, low‐frequency OGSE provides higher sensitivity. Maximum sensitivity results show that on current clinical scanners (G_max = 60 mT/m, signal to noise ratio (SNR) = 20) axon diameters below 6 µm are indistinguishable from zero. Scanners with stronger gradient systems such as the Massachusetts General Hospital (MGH) Connectom scanner (G_max = 300 mT/m) can extend this sensitivity limit down to 2–3 µm, probing a much greater proportion of the underlying axon diameter distribution.

Conclusion

Low‐frequency OGSE provides additional sensitivity to PGSE in practical situations. OGSE is particularly advantageous for systems with high performance gradients. Magn Reson Med 75:688–700, 2016. © 2015 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Mapping mean axon diameter and axonal volume fraction by MRI using temporal diffusion spectroscopy

Mapping mean axon diameter and intra-axonal volume fraction may have significant clinical potential because nerve conduction velocity is directly dependent on axon diameter, and several neurodegenerative diseases affect axons of specific sizes and alter axon counts. Diffusion-weighted MRI methods based on the pulsed gradient spin echo (PGSE) sequence have been reported to be able to assess axon diameter and volume fraction non-invasively. However, due to the relatively long diffusion times used, e.g. >20ms, the sensitivity to small axons (diameter<2μm) is low, and the derived mean axon diameter has been reported to be overestimated. In the current study, oscillating gradient spin echo (OGSE) diffusion sequences with variable frequency gradients were used to assess rat spinal white matter tracts with relatively short effective diffusion times (1-5ms). In contrast to previous PGSE-based methods, the extra-axonal diffusion cannot be modeled as hindered (Gaussian) diffusion when short diffusion times are used. Appropriate frequency-dependent rates are therefore incorporated into our analysis and validated by histology-based computer simulation of water diffusion. OGSE data were analyzed to derive mean axon diameters and intra-axonal volume fractions of rat spinal white matter tracts (mean axon diameter of ~1.27-5.54μm). The estimated values were in good agreement with histology, including the small axon diameters (<2.5μm). This study establishes a framework for the quantification of nerve morphology using the OGSE method with high sensitivity to small axons.