Use of capillaries in the construction of an MRI phantom for the assessment of diffusion tensor imaging: demonstration of performance

Influence of Diffusion Time and Temperature on Restricted Diffusion Signal: A Phantom Study

PURPOSE

Diffusion MRI is a physical measurement method that quantitatively indicates the displacement of water molecules diffusing in voxels. However, there are insufficient data to characterize the diffusion process physically in a uniform structure such as a phantom. This study investigated the transitional relationship between structure scale, temperature, and diffusion time for simple restricted diffusion using a capillary phantom.

METHODS

We performed diffusion-weighted pulsed-gradient stimulated-echo acquisition mode (STEAM) MRI with a 9.4 Tesla MRI system (Bruker BioSpin, Ettlingen, Germany) and a quadrature coil with an inner diameter of 86 mm (Bruker BioSpin). We measured the diffusion coefficients (radial diffusivity [RD]) of capillary plates (pore sizes 6, 12, 25, 50, and 100 μm) with uniformly restricted structures at various temperatures (10ºC, 20ºC, 30ºC, and 40ºC) and multiple diffusion times (12-800 ms). We evaluated the characteristics of scale, temperature, and diffusion time for restricted diffusion.

RESULTS

The RD decayed and became constant depending on the structural scale. Diffusion coefficient fluctuations with temperature occurred mostly under conditions of a large structural scale and short diffusion time. We obtained data suggesting that temperature-dependent changes in the diffusion coefficients follow physical laws.

CONCLUSION

No water molecules were observed outside the glass tubes in the capillary plates, and the capillary plates only reflected a restricted diffusion process within the structure.We experimentally evaluated the characteristics of simple restricted diffusion to reveal the transitional relationship of the diffusion coefficient with diffusion time, structure scale, and temperature through composite measurement.

A critical review of connectome validation studies

Diffusion MRI tractography is the most widely used macroscale method for mapping connectomes in vivo. However, tractography is prone to various errors and biases, and thus tractography-derived connectomes require careful validation. Here, we critically review studies that have developed or utilized phantoms and tracer maps to validate tractography-derived connectomes, either quantitatively or qualitatively. We identify key factors impacting connectome reconstruction accuracy, including streamline seeding, propagation and filtering methods, and consider the strengths and limitations of state-of-the-art connectome phantoms and associated validation studies. These studies demonstrate the inherent limitations of current fiber orientation models and tractography algorithms and their impact on connectome reconstruction accuracy. Reconstructing connectomes with both high sensitivity and high specificity is challenging, given that some tractography methods can generate an abundance of spurious connections, while others can overlook genuine fiber bundles. We argue that streamline filtering can minimize spurious connections and potentially improve the biological plausibility of connectomes derived from tractography. We find that algorithmic choices such as the tractography seeding methodology, angular threshold, and streamline propagation method can substantially impact connectome reconstruction accuracy. Hence, careful application of tractography is necessary to reconstruct accurate connectomes. Improvements in diffusion MRI acquisition techniques will not necessarily overcome current tractography limitations without accompanying modeling and algorithmic advances.

Design and characterization of a 3D-printed axon-mimetic phantom for diffusion MRI

PURPOSE

To introduce and characterize inexpensive and easily produced 3D-printed axon-mimetic diffusion MRI phantoms in terms of pore geometry and diffusion kurtosis imaging metrics.

METHODS

Phantoms were 3D-printed with a composite printing material that, after the dissolution of the polyvinyl alcohol, exhibits microscopic fibrous pores. Confocal microscopy and synchrotron phase-contrast micro-CT imaging were performed to visualize and assess the pore sizes. Diffusion MRI scans of four identical phantoms and phantoms with varying print parameters in water were performed at 9.4 T. Diffusion kurtosis imaging was fit to both data sets and used to assess the reproducibility between phantoms and effects of print parameters on diffusion kurtosis imaging metrics. Identical scans were performed 25 and 76 days later, to test their stability.

RESULTS

Segmentation of pores in three microscopy images yielded a mean, median, and SD of equivalent pore diameters of 7.57 μm, 3.51 μm, and 12.13 μm, respectively. Phantoms had T₁ /T₂ = 2 seconds/180 ms, and those with identical parameters showed a low coefficient of variation (~10%) in mean diffusivity (1.38 × 10^-3 mm² /s) and kurtosis (0.52) metrics and radial diffusivity (1.01 × 10^-3 mm² /s) and kurtosis (1.13) metrics. Printing temperature and speed had a small effect on diffusion kurtosis imaging metrics (< 16%), whereas infill density had a larger and more variable effect (> 16%). The stability analysis showed small changes over 2.5 months (< 7%).

CONCLUSION

Three-dimension-printed axon-mimetic phantoms can mimic the fibrous structure of axon bundles on a microscopic scale, serving as complex, anisotropic diffusion MRI phantoms.

The reproducibility of measurements using a standardization phantom for the evaluation of fractional anisotropy (FA) derived from diffusion tensor imaging (DTI)

OBJECTIVES

It is necessary to standardize the examination procedure and diagnostic criteria of diffusion tensor imaging (DTI). Thus, the purpose of this study was to examine the reproducibility of measurements using a standardization phantom composed of different fibre materials with different fibre densities (FDs) for the evaluation of fractional anisotropy (FA) derived from DTI.

MATERIALS AND METHODS

Two types of fibre materials wrapped in heat-shrinkable tubes were used as fibre phantoms. We designed fibre phantoms with three different FDs of each fibre material. The standardization phantom was examined using DTI protocol six times a day, and each examination session was repeated once a month for 7 consecutive months. Fibre tracking was performed by setting regions of interest in the FA map, and FA was measured in each fibre phantom. Coefficients of variation (CVs) were used to evaluate the inter-examination reproducibility of FA values. Furthermore, Bland-Altman plots were used to evaluate the intra-operator reproducibility of FA measurements.

RESULTS

All CVs for each fibre phantom were within 2% throughout the 7-month study of repeated DTI sessions. The high intra-operator reproducibility of the FA measurement was confirmed.

DISCUSSION

High reproducibility of measurements using a standardization phantom for the evaluation of FA was achieved.

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.

Comparison of Glass Capillary Plates and Polyethylene Fiber Bundles as Phantoms to Assess the Quality of Diffusion Tensor Imaging

Purpose:

The purpose of this study was to evaluate the suitability of two phantoms, one made of capillary plates and the other polyethylene fibers, for assessing the quality of diffusion tensor imaging (DTI).

Methods:

The first phantom was a stack of glass capillary plates with many parallel micropores (CP). The second phantom was a bundle of polyethylene fiber Dyneema held together with a thermal shrinkage tube (Dy). High resolution multi-shot echo planar imaging (EPI) DTI acquisitions were performed at b-values of 0 and 1000 s/mm² and diffusion-times (T_diff) of 37.7 and 97.7 ms on a preclinical 7T MRI scanner. Thirty diffusion-encoding directions were used. The data were used to calculate the fractional anisotropy (FA), mean diffusivity (MD), and angular dispersion (AD). Further acquisitions were performed at b-values from 0 to 8000 s/mm² in 14 steps with the diffusion gradient applied parallel (axial) and perpendicular (radial) to the Z direction. On the other hand, the data acquired with a 3T MRI scanner were used to confirm that measurements on a clinical machine are consistent with the 7T MRI results.

Results:

The dependence of FA, MD and AD on T_diff was smaller for the Dy than for the CPs. The b-value-dependent signal attenuations in the axial direction at T_diff = 37.7 and 97.7 ms were similar for both phantoms. In the radial direction, Dy demonstrated similar b-value attenuation to that of in vivo tissue for both T_diffs, but the attenuation for the CPs was affected by the change in T_diff. Parameter estimates were similar for 3T and 7T MRI.

Conclusion:

The characteristics of the CP indicate that it can be used as a restricted-diffusion dominant phantom, while the characteristics of the Dy suggest that it can be used as a hindered-diffusion dominant phantom. Dy may be more suitable than CP for DTI quality control.

Liquid crystal phantom for validation of microscopic diffusion anisotropy measurements on clinical MRI systems

PURPOSE

To develop a phantom for validating MRI pulse sequences and data processing methods to quantify microscopic diffusion anisotropy in the human brain.

METHODS

Using a liquid crystal consisting of water, detergent, and hydrocarbon, we designed a 0.5-L spherical phantom showing the theoretically highest possible degree of microscopic anisotropy. Data were acquired on the Connectome scanner using echo-planar imaging signal readout and diffusion encoding with axisymmetric b-tensors of varying magnitude, anisotropy, and orientation. The mean diffusivity, fractional anisotropy (FA), and microscopic FA (µFA) parameters were estimated.

RESULTS

The phantom was observed to have values of mean diffusivity similar to brain tissue, and relaxation times compatible with echo-planar imaging echo times on the order of 100 ms. The estimated values of µFA were at the theoretical maximum of 1.0, whereas the values of FA spanned the interval from 0.0 to 0.8 as a result of varying orientational order of the anisotropic domains within each voxel.

CONCLUSIONS

The proposed phantom can be manufactured by mixing three widely available chemicals in volumes comparable to a human head. The acquired data are in excellent agreement with theoretical predictions, showing that the phantom is ideal for validating methods for measuring microscopic diffusion anisotropy on clinical MRI systems. Magn Reson Med 79:1817-1828, 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-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength

Diffusion microstructural imaging techniques have attracted great interest in the last decade due to their ability to quantify axon diameter and volume fraction in healthy and diseased human white matter. The estimates of compartment size and volume fraction continue to be debated, in part due to the lack of a gold standard for validation and quality control. In this work, we validate diffusion MRI estimates of compartment size and volume fraction using a novel textile axon ("taxon") phantom constructed from hollow polypropylene yarns with distinct intra- and extra-taxonal compartments to mimic white matter in the brain. We acquired a comprehensive set of diffusion MRI measurements in the phantom using multiple gradient directions, diffusion times and gradient strengths on a human MRI scanner equipped with maximum gradient strength (G_max) of 300 mT/m. We obtained estimates of compartment size and restricted volume fraction through a straightforward extension of the AxCaliber/ActiveAx frameworks that enables estimation of mean compartment size in fiber bundles of arbitrary orientation. The voxel-wise taxon diameter estimates of 12.2 ± 0.9 μm were close to the manufactured inner diameter of 11.8 ± 1.2 μm with G_max = 300 mT/m. The estimated restricted volume fraction demonstrated an expected decrease along the length of the fiber bundles in accordance with the known construction of the phantom. When G_max was restricted to 80 mT/m, the taxon diameter was overestimated, and the estimates for taxon diameter and packing density showed greater uncertainty compared to data with G_max = 300 mT/m. In conclusion, the compartment size and volume fraction estimates resulting from diffusion measurements on a human scanner were validated against ground truth in a phantom mimicking human white matter, providing confidence that this method can yield accurate estimates of parameters in simplified but realistic microstructural environments. Our work also demonstrates the importance of a biologically analogous phantom that can be applied to validate a variety of diffusion microstructural imaging methods in human scanners and be used for standardization of diffusion MRI protocols for neuroimaging research.

Histological validation of diffusion MRI fiber orientation distributions and dispersion

Diffusion magnetic resonance imaging (dMRI) is widely used to probe tissue microstructure, and is currently the only non-invasive way to measure the brain's fiber architecture. While a large number of approaches to recover the intra-voxel fiber structure have been utilized in the scientific community, a direct, 3D, quantitative validation of these methods against relevant histological fiber geometries is lacking. In this study, we investigate how well different high angular resolution diffusion imaging (HARDI) models and reconstruction methods predict the ground-truth histologically defined fiber orientation distribution (FOD), as well as investigate their behavior over a range of physical and experimental conditions. The dMRI methods tested include constrained spherical deconvolution (CSD), Q-ball imaging (QBI), diffusion orientation transform (DOT), persistent angular structure (PAS), and neurite orientation dispersion and density imaging (NODDI) methods. Evaluation criteria focus on overall agreement in FOD shape, correct assessment of the number of fiber populations, and angular accuracy in orientation. In addition, we make comparisons of the histological orientation dispersion with the fiber spread determined from the dMRI methods. As a general result, no HARDI method outperformed others in all quality criteria, with many showing tradeoffs in reconstruction accuracy. All reconstruction techniques describe the overall continuous angular structure of the histological FOD quite well, with good to moderate correlation (median angular correlation coefficient > 0.70) in both single- and multiple-fiber voxels. However, no method is consistently successful at extracting discrete measures of the number and orientations of FOD peaks. The major inaccuracies of all techniques tend to be in extracting local maxima of the FOD, resulting in either false positive or false negative peaks. Median angular errors are ∼10° for the primary fiber direction and ∼20° for the secondary fiber, if present. For most methods, these results did not vary strongly over a wide range of acquisition parameters (number of diffusion weighting directions and b value). Regardless of acquisition parameters, all methods show improved successes at resolving multiple fiber compartments in a voxel when fiber populations cross at near-orthogonal angles, with no method adequately capturing low to moderate angle (<60°) crossing fibers. Finally, most methods are limited in their ability to capture orientation dispersion, resulting in low to moderate, yet statistically significant, correlation with histologically-derived dispersion with both HARDI and NODDI methodologies. Together, these results provide quantitative measures of the reliability and limitations of dMRI reconstruction methods and can be used to identify relative advantages of competing approaches as well as potential strategies for improving accuracy.

Temperature and concentration calibration of aqueous polyvinylpyrrolidone (PVP) solutions for isotropic diffusion MRI phantoms

To use the "apparent diffusion coefficient" (Dapp) as a quantitative imaging parameter, well-suited test fluids are essential. In this study, the previously proposed aqueous solutions of polyvinylpyrrolidone (PVP) were examined and temperature calibrations were obtained. For example, at a temperature of 20°C, Dapp ranged from 1.594 (95% CI: 1.593, 1.595) μm2/ms to 0.3326 (95% CI: 0. 3304, 0.3348) μm2/ms for PVP-concentrations ranging from 10% (w/w) to 50% (w/w) using K30 polymer lengths. The temperature dependence of Dapp was found to be so strong that a negligence seems not advisable. The temperature dependence is descriptively modelled by an exponential function exp(c2 (T - 20°C)) and the determined c2 values are reported, which can be used for temperature calibration. For example, we find the value 0.02952 K-1 for 30% (w/w) PVP-concentration and K30 polymer length. In general, aqueous PVP solutions were found to be suitable to produce easily applicable and reliable Dapp-phantoms.

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.

Concerning the matching of magnetic susceptibility differences for the compensation of background gradients in anisotropic diffusion fibre phantoms

Artificial, anisotropic fibre phantoms are nowadays increasingly used in the field of diffusion-weighted MRI. Such phantoms represent useful tools for, among others, the calibration of pulse sequences and validation of diffusion models since they can mimic well-known structural features of brain tissue on the one hand, but exhibit a reduced complexity, on the other. Among all materials, polyethylene fibres have been widely used due to their excellent properties regarding the restriction of water diffusion and surface relaxation properties. Yet the magnetic susceptibility of polyethylene can be distinctly lower than that of distilled water. This difference produces strong microscopic, background field gradients in the vicinity of fibre bundles which are not parallel to the static magnetic field. This, in turn, modulates the MRI signal behaviour. In the present work we investigate an approach to reduce the susceptibility-induced background gradients via reducing the heterogeneity in the internal magnetic susceptibility. An aqueous solution of magnesium chloride hexahydrate (MgCl₂·6H₂O) is used for this purpose. Its performance is demonstrated in dedicated anisotropic fibre phantoms with different geometrical configurations.

* A 3D Tissue-Printing Approach for Validation of Diffusion Tensor Imaging in Skeletal Muscle

The ability to noninvasively assess skeletal muscle microstructure, which predicts function and disease, would be of significant clinical value. One method that holds this promise is diffusion tensor magnetic resonance imaging (DT-MRI), which is sensitive to the microscopic diffusion of water within tissues and has become ubiquitous in neuroimaging as a way of assessing neuronal structure and damage. However, its application to the assessment of changes in muscle microstructure associated with injury, pathology, or age remains poorly defined, because it is difficult to precisely control muscle microstructural features in vivo. However, recent advances in additive manufacturing technologies allow precision-engineered diffusion phantoms with histology informed skeletal muscle geometry to be manufactured. Therefore, the goal of this study was to develop skeletal muscle phantoms at relevant size scales to relate microstructural features to MRI-based diffusion measurements. A digital light projection based rapid 3D printing method was used to fabricate polyethylene glycol diacrylate based diffusion phantoms with (1) idealized muscle geometry (no geometry; fiber sizes of 30, 50, or 70 μm or fiber size of 50 μm with 40% of walls randomly deleted) or (2) histology-based geometry (normal and after 30-days of denervation) containing 20% or 50% phosphate-buffered saline (PBS). Mean absolute percent error (8%) of the printed phantoms indicated high conformity to templates when "fibers" were >50 μm. A multiple spin-echo echo planar imaging diffusion sequence, capable of acquiring diffusion weighted data at several echo times, was used in an attempt to combine relaxometry and diffusion techniques with the goal of separating intracellular and extracellular diffusion signals. When fiber size increased (30-70 μm) in the 20% PBS phantom, fractional anisotropy (FA) decreased (0.32-0.26) and mean diffusivity (MD) increased (0.44 × 10^-3 mm²/s-0.70 × 10^-3 mm²/s). Similarly, when fiber size increased from 30 to 70 μm in the 50% PBS diffusion phantoms, a small change in FA was observed (0.18-0.22), but MD increased from 0.86 × 10^-3 mm²/s to 1.79 × 10^-3 mm²/s. This study demonstrates a novel application of tissue engineering to understand complex diffusion signals in skeletal muscle. Through this work, we have also demonstrated the feasibility of 3D printing for skeletal muscle with relevant matrix geometries and physiologically relevant tissue characteristics.

Diffusion tensor imaging in abdominal organs

Initially, diffusion tensor imaging (DTI) was mainly applied in studies of the human brain to analyse white matter tracts. As DTI is outstanding for the analysis of tissue´s microstructure, the interest in DTI for the assessment of abdominal tissues has increased continuously in recent years. Tissue characteristics of abdominal organs differ substantially from those of the human brain. Further peculiarities such as respiratory motion and heterogenic tissue composition lead to difficult conditions that have to be overcome in DTI measurements. Thus MR measurement parameters have to be adapted for DTI in abdominal organs. This review article provides information on the technical background of DTI with a focus on abdominal imaging, as well as an overview of clinical studies and application of DTI in different abdominal regions. Copyright © 2015 John Wiley & Sons, Ltd.

Assessment of diffusion tensor image quality across sites and vendors using the American College of Radiology head phantom

The purpose of this study was to explore the feasibility of assessing quality of diffusion tensor imaging (DTI) from multiple sites and vendors using American College of Radiology (ACR) phantom. Participating sites (Siemens (n = 2), GE (n= 2), and Philips (n = 4)) reached consensus on parameters for DTI and used the widely available ACR phantom. Tensor data were processed at one site. B0 and eddy current distortions were assessed using grid line displacement on phantom Slice 5; signal-to-noise ratio (SNR) was measured at the center and periphery of the b = 0 image; fractional anisotropy (FA) and mean diffusivity (MD) were assessed using phantom Slice 7. Variations of acquisition parameters and deviations from specified sequence parameters were recorded. Nonlinear grid line distortion was higher with linear shimming and could be corrected using the 2nd order shimming. Following image registration, eddy current distortion was consistently smaller than acquisi-tion voxel size. SNR was consistently higher in the image periphery than center by a factor of 1.3-2.0. ROI-based FA ranged from 0.007 to 0.024. ROI-based MD ranged from 1.90 × 10-3 to 2.33 × 10-3 mm2/s (median = 2.04 × 10-3 mm2/s). Two sites had image void artifacts. The ACR phantom can be used to compare key qual-ity measures of diffusion images acquired from multiple vendors at multiple sites.

D-BRAIN: Anatomically Accurate Simulated Diffusion MRI Brain Data

Diffusion Weighted (DW) MRI allows for the non-invasive study of water diffusion inside living tissues. As such, it is useful for the investigation of human brain white matter (WM) connectivity in vivo through fiber tractography (FT) algorithms. Many DW-MRI tailored restoration techniques and FT algorithms have been developed. However, it is not clear how accurately these methods reproduce the WM bundle characteristics in real-world conditions, such as in the presence of noise, partial volume effect, and a limited spatial and angular resolution. The difficulty lies in the lack of a realistic brain phantom on the one hand, and a sufficiently accurate way of modeling the acquisition-related degradation on the other. This paper proposes a software phantom that approximates a human brain to a high degree of realism and that can incorporate complex brain-like structural features. We refer to it as a Diffusion BRAIN (D-BRAIN) phantom. Also, we propose an accurate model of a (DW) MRI acquisition protocol to allow for validation of methods in realistic conditions with data imperfections. The phantom model simulates anatomical and diffusion properties for multiple brain tissue components, and can serve as a ground-truth to evaluate FT algorithms, among others. The simulation of the acquisition process allows one to include noise, partial volume effects, and limited spatial and angular resolution in the images. In this way, the effect of image artifacts on, for instance, fiber tractography can be investigated with great detail. The proposed framework enables reliable and quantitative evaluation of DW-MR image processing and FT algorithms at the level of large-scale WM structures. The effect of noise levels and other data characteristics on cortico-cortical connectivity and tractography-based grey matter parcellation can be investigated as well.

Comparison of 3D orientation distribution functions measured with confocal microscopy and diffusion MRI

The ability of diffusion MRI (dMRI) fiber tractography to non-invasively map three-dimensional (3D) anatomical networks in the human brain has made it a valuable tool in both clinical and research settings. However, there are many assumptions inherent to any tractography algorithm that can limit the accuracy of the reconstructed fiber tracts. Among them is the assumption that the diffusion-weighted images accurately reflect the underlying fiber orientation distribution (FOD) in the MRI voxel. Consequently, validating dMRI's ability to assess the underlying fiber orientation in each voxel is critical for its use as a biomedical tool. Here, using post-mortem histology and confocal microscopy, we present a method to perform histological validation of orientation functions in 3D, which has previously been limited to two-dimensional analysis of tissue sections. We demonstrate the ability to extract the 3D FOD from confocal z-stacks, and quantify the agreement between the MRI estimates of orientation information obtained using constrained spherical deconvolution (CSD) and the true geometry of the fibers. We find an orientation error of approximately 6° in voxels containing nearly parallel fibers, and 10-11° in crossing fiber regions, and note that CSD was unable to resolve fibers crossing at angles below 60° in our dataset. This is the first time that the 3D white matter orientation distribution is calculated from histology and compared to dMRI. Thus, this technique serves as a gold standard for dMRI validation studies - providing the ability to determine the extent to which the dMRI signal is consistent with the histological FOD, and to establish how well different dMRI models can predict the ground truth FOD.

Strengths and weaknesses of state of the art fiber tractography pipelines--A comprehensive in-vivo and phantom evaluation study using Tractometer

Many different tractography approaches and corresponding isolated evaluation attempts have been presented over the last years, but a comparative and quantitative evaluation of tractography algorithms still remains a challenge, particularly in-vivo. The recently presented evaluation framework Tractometer is the first attempt to approach this challenge in a quantitative, comparative, persistent and open-access way. Tractometer is currently based on the evaluation of several global connectivity and tract-overlap metrics on hardware phantom data. The work presented in this paper focuses on extending Tractometer with a metric that enables the assessment of the local consistency of tractograms with the underlying image data that is not only applicable to phantom dataset but allows the quantitative and purely data-driven evaluation of in-vivo tractography. We furthermore present an extensive reference-based evaluation study of 25,000 tractograms obtained on phantom and in-vivo datasets using the presented local metric as well as all the methods already established in Tractometer. The experiments showed that the presented local metric successfully reflects the behavior of in-vivo tractography under different conditions and that it is consistent with the results of previous studies. Additionally our experiments enabled a multitude of conclusions with implications for fiber tractography in general, including recommendations regarding optimal choice of a local modeling technique, tractography algorithm, and parameterization, confirming and complementing the results of earlier studies.

Validation of High-Resolution Tractography Against In Vivo Tracing in the Macaque Visual Cortex

Diffusion magnetic resonance imaging (MRI) allows for the noninvasive in vivo examination of anatomical connections in the human brain, which has an important role in understanding brain function. Validation of this technique is vital, but has proved difficult due to the lack of an adequate gold standard. In this work, the macaque visual system was used as a model as an extensive body of literature of in vivo and postmortem tracer studies has established a detailed understanding of the underlying connections. We performed probabilistic tractography on high angular resolution diffusion imaging data of 2 ex vivo, in vitro macaque brains. Comparisons were made between identified connections at different thresholds of probabilistic connection “strength,” and with various tracking optimization strategies previously proposed in the literature, and known connections from the detailed visual system wiring map described by Felleman and Van Essen (1991; FVE91). On average, 74% of connections that were identified by FVE91 were reproduced by performing the most successfully optimized probabilistic diffusion MRI tractography. Further comparison with the results of a more recent tracer study ( Markov et al. 2012) suggests that the fidelity of tractography in estimating the presence or absence of interareal connections may be greater than this.

Effects of MR parameter changes on the quantification of diffusion anisotropy and apparent diffusion coefficient in diffusion tensor imaging: evaluation using a diffusional anisotropic phantom

Objective

To validate the usefulness of a diffusional anisotropic capillary array phantom and to investigate the effects of diffusion tensor imaging (DTI) parameter changes on diffusion fractional anisotropy (FA) and apparent diffusion coefficient (ADC) using the phantom.

Materials and Methods

Diffusion tensor imaging of a capillary array phantom was performed with imaging parameter changes, including voxel size, number of sensitivity encoding (SENSE) factor, echo time (TE), number of signal acquisitions, b-value, and number of diffusion gradient directions (NDGD), one-at-a-time in a stepwise-incremental fashion. We repeated the entire series of DTI scans thrice. The coefficients of variation (CoV) were evaluated for FA and ADC, and the correlation between each MR imaging parameter and the corresponding FA and ADC was evaluated using Spearman's correlation analysis.

Results

The capillary array phantom CoVs of FA and ADC were 7.1% and 2.4%, respectively. There were significant correlations between FA and SENSE factor, TE, b-value, and NDGD, as well as significant correlations between ADC and SENSE factor, TE, and b-value.

Conclusion

A capillary array phantom enables repeated measurements of FA and ADC. Both FA and ADC can vary when certain parameters are changed during diffusion experiments. We suggest that the capillary array phantom can be used for quality control in longitudinal or multicenter clinical studies.

Biomimetic phantom for the validation of diffusion magnetic resonance imaging

PURPOSE

A range of advanced diffusion MRI (dMRI) techniques are currently in development which characterize the orientation of white matter fibers using diffusion tensor imaging (DTI). There is a need for a physical phantom with microstructural features of the brain's white matter to help validate these methods.

METHODS

Hollow, co-electrospun, aligned fibers with a tuneable size distribution have been produced in bulk and with an MR visible solvent infused into the pores. The morphology and size of the phantoms was assessed using scanning electron microscopy (SEM) and compared with DTI results obtained on both a clinical and preclinical scanner.

RESULTS

By varying inner diameter of the phantom fibers (from SEM: 9.5 μm, 11.9 μm, 13.4 μm) the radial diffusivity and fractional anisotropy, calculated from DTI, vary between 0.38 ± 0.05 × 10(3) and 0.61 ± 0.06 × 10(3) cm s(-1) and between 0.45 ± 0.05 and 0.33 ± 0.04, respectively.

CONCLUSION

We envisage that these materials will be used for the validation of novel and established methods within the field of diffusion MRI, as well as for routine quality assurance purposes and for establishing scanner performance in multicenter trials.

FIBRASCAN: a novel method for 3D white matter tract reconstruction in MR space from cadaveric dissection

INTRODUCTION

Diffusion tractography relies on complex mathematical models that provide anatomical information indirectly, and it needs to be validated. In humans, up to now, tractography has mainly been validated by qualitative comparison with data obtained from dissection. No quantitative comparison was possible because Magnetic Resonance Imaging (MRI) and dissection data are obtained in different reference spaces, and because fiber tracts are progressively destroyed by dissection. Here, we propose a novel method and software (FIBRASCAN) that allow accurate reconstruction of fiber tracts from dissection in MRI reference space.

METHOD

Five human hemispheres, obtained from four formalin-fixed brains were prepared for Klingler's dissection, placed on a holder with fiducial markers, MR scanned, and then dissected to expose the main association tracts. During dissection, we performed iterative acquisitions of the surface and texture of the specimens using a laser scanner and two digital cameras. Each texture was projected onto the corresponding surface and the resulting set of textured surfaces was coregistered thanks to the fiducial holders. The identified association tracts were then interactively segmented on each textured surface and reconstructed from the pile of surface segments. Finally, the reconstructed tracts were coregistered onto ex vivo MRI space thanks to the fiducials. Each critical step of the process was assessed to measure the precision of the method.

RESULTS

We reconstructed six fiber tracts (long, anterior and posterior segments of the superior longitudinal fasciculus; Inferior fronto-occipital, Inferior longitudinal and uncinate fasciculi) from cadaveric dissection and ported them into ex vivo MRI reference space. The overall accuracy of the method was of the order of 1mm: surface-to-surface registration=0.138mm (standard deviation (SD)=0.058mm), deformation of the specimen during dissection=0.356mm (SD=0.231mm), and coregistration surface-MRI=0.6mm (SD=0.274mm). The spatial resolution of the method (distance between two consecutive surface acquisitions) was 0.345mm (SD=0.115mm).

CONCLUSION

This paper presents the robustness of a novel method, FIBRASCAN, for accurate reconstruction of fiber tracts from dissection in the ex vivo MR reference space. This is a major step toward quantitative comparison of MR tractography with dissection results.

Fiberfox: facilitating the creation of realistic white matter software phantoms

PURPOSE

Phantom-based validation of diffusion-weighted image processing techniques is an important key to innovation in the field and is widely used. Openly available and user friendly tools for the flexible generation of tailor-made datasets for the specific tasks at hand can greatly facilitate the work of researchers around the world.

METHODS

We present an open-source framework, Fiberfox, that enables (1) the intuitive definition of arbitrary artificial white matter fiber tracts, (2) signal generation from those fibers by means of the most recent multi-compartment modeling techniques, and (3) simulation of the actual MR acquisition that allows for the introduction of realistic MRI-related effects into the final image.

RESULTS

We show that real acquisitions can be closely approximated by simulating the acquisition of the well-known FiberCup phantom. We further demonstrate the advantages of our framework by evaluating the effects of imaging artifacts and acquisition settings on the outcome of 12 tractography algorithms.

CONCLUSION

Our findings suggest that experiments on a realistic software phantom might change the conclusions drawn from earlier hardware phantom experiments. Fiberfox may find application in validating and further developing methods such as tractography, super-resolution, diffusion modeling or artifact correction.

Simultaneous analysis and quality assurance for diffusion tensor imaging

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.

Manifestation and post hoc correction of gradient cross-term artifacts in DTI

Cross-terms between imaging and diffusion gradients, unaccounted for during tensor calculations, can lead to erroneous estimation of diffusivity and fractional anisotropy (FA) in regions of isotropic and anisotropic diffusion. Cross-term of magnitude 136.8±1.6 s/mm(2), artificially introduced in the slice-encode direction, caused an increase in FA in isotropic phantom from 0.0546±0.0001 to 0.0996±0.0001, while the change in chimpanzee brain depended on the orientation of the white matter (WM). Mean diffusivity (MD) remained unchanged in isotropic phantom, but increased by ∼20% in the WM due to cross-terms. A bias was observed in the principal eigenvectors in both phantom and chimpanzee brain, resulting in significant increase in midline crossing fibers along the bias than perpendicular to it in tractography in chimpanzee brain. Post hoc correction of these artifacts was achieved by estimating the cross-term factors using calibration scans on an isotropic phantom and modifying the b-matrix before tensor calculation. Upon correction, the FA and MD values closely resembled the values obtained from sequence without cross-terms, and the bias in principal eigenvectors was eliminated. Customized sequences involving large b-values, high-resolution imaging, or long diffusion or echo times should therefore be evaluated and any residual cross-terms corrected before implementation.

A quality assurance protocol for diffusion tensor imaging using the head phantom from American College of Radiology

PURPOSE

To propose a quality assurance procedure for routine clinical diffusion tensor imaging (DTI) using the widely available American College of Radiology (ACR) head phantom.

METHODS

Analysis was performed on the data acquired at 1.5 and 3.0 T on whole body clinical MRI scanners using the ACR phantom and included the following: (1) the signal-to-noise ratio (SNR) at the center and periphery of the phantom, (2) image distortion by EPI readout relative to spin echo imaging, (3) distortion of high-b images relative to the b= 0 image caused by diffusion encoding, and (4) determination of fractional anisotropy (FA) and mean diffusivity (MD) measured with region-of-interest (ROI) and pixel-based approaches. Reproducibility of the measurements was assessed by five repetitions of data acquisition on each scanner.

RESULTS

The SNR at the phantom center was approximately half of that near the periphery at both 1.5 and 3 T. The image distortion by the EPI readout was up to 7 mm at 1.5 T and 10 mm at 3 T. The typical distortion caused by eddy currents from diffusion encoding was on the order of 0.5 mm. The difference between ROI-based and pixel-based MD quantification was 1.4% at 1.5 T and 0.3% at 3 T. The ROI-based MD values were in close agreement (within 2%) with the reference values. The ROI-based FA values were approximately a factor of 10 smaller than pixel-based values and less than 0.01. The measurement reproducibility was sufficient for quality assurance (QA) purposes.

CONCLUSIONS

This QA approach is simple to perform and evaluates key aspects of the scanner performance for DTI data acquisition using a widely available phantom.

Novel spherical phantoms for Q-ball imaging under in vivo conditions

For the validation of complex diffusion imaging techniques like q-ball imaging that aim to resolve multiple fiber directions, appropriate phantoms are highly desirable. However, previous q-ball imaging phantoms had diffusion anisotropies well below those of in vivo white matter. In this work, fiber phantoms of well-defined geometry are presented. The fibers are wound on a spherical spindle yielding high packing densities and consequently high diffusion anisotropies (fractional anisotropy 0.93 ± 0.02 at b = 500 s/mm(2)). Phantoms with 90° and 45° crossing angle were constructed both with two crossing types. In the "stacked" crossing, two fiber strings were wound consecutively to simulate two touching fibers, in the "interleaved" crossing, fibers were wound alternately. The stacked crossing allows the alteration of partial volumes, whereas the interleaved crossing provides constant partial volumes, allowing e.g. the easy alteration of the SNR by varying the slice thickness. Exemplary q-ball imaging validation measurements using different b-values and slice thicknesses are presented.

Ground truth hardware phantoms for validation of diffusion-weighted MRI applications

PURPOSE

To quantitatively validate diffusion-weighted MRI (DW-MRI) applications, a hardware phantom containing crossing fibers at a sub-voxel level is presented. It is suitable for validation of a large spectrum of DW-MRI applications from acquisition to fiber tracking, which is an important recurrent issue in the field.

MATERIALS AND METHODS

Phantom properties were optimized to resemble properties of human white matter in terms of anisotropy, fractional anisotropy, and T(2). Sub-voxel crossings were constructed at angles of 30, 50, and 65 degrees, by wrapping polyester fibers, with a diameter close to axon diameter, into heat shrink tubes. We show our phantoms are suitable for the acquisition of DW-MRI data using a clinical protocol.

RESULTS

The phantoms can be used to successfully estimate both the diffusion tensor and non-Gaussian diffusion models, and perform streamline fiber tracking. DOT (Diffusion Orientation Transform) and q-ball reconstruction of the diffusion profiles acquired at b = 3000 s/mm(2) and 132 diffusion directions reveal multimodal diffusion profiles in voxels containing crossing yarn strands.

CONCLUSION

The highly purpose adaptable phantoms provide a DW-MRI validation platform: applications include optimisation of acquisition schemes, validation of non-Gaussian diffusion models, comparison and validation of fiber tracking algorithms, and quality control in multi-center DWI studies.

The use of novel gradient directions with DTI to synthesize data with complicated diffusion behavior

This study demonstrates a new technique for synthesizing diffusion tensor imaging (DTI) data sets that exhibit complex diffusion characteristics by performing operations on acquired DTI data of simple structures with anisotropic diffusive properties. The motivation behind this technique is to characterize the behavior of noise in complicated data using a phantom. Compared to simulations, an advantage to this approach is that the acquired data contain noise characteristic of the scanner and protocol. Using this technique, a simple capillary phantom is employed to infer the quality of data for more clinically realistic tissue structures (e.g., crossing fiber tracts). A water-filled phantom containing capillary arrays was constructed to demonstrate this technique, which uses a DTI protocol with typical clinical parameters. Eigenvalues and fractional anisotropy were calculated for the initial prolate data. Data were adjusted to synthesize different apparent diffusion coefficient (ADC) spatial distributions, which were compared to theoretical and analytical models. RMS differences and volumetric overlap between expected and measured ADC distributions were quantified for all synthesized distributions. Differences between synthesized and actual distributions were discussed.

Rigid diffusion phantom: acquisition and simulation

Diffusion tensor imaging has already been a popular imaging modality for clinical researches. However, to setup an imaging protocol is not straightforward. This problem is critical issue for multi-center studies. We developed anisotropy phantoms and examined the feasibility of using water-filled arrays of channeled silicon plates. Various channel sizes were tested to optimize the diffusion and anisotropy properties. We succeeded in producing a phantom with high anisotropy (FA=0.8). However, a reason of high axial diffusivity needs further investigations.

Quantitative bone matrix density measurement by water- and fat-suppressed proton projection MRI (WASPI) with polymer calibration phantoms

The density of the organic matrix of bone substance is a critical parameter necessary to clinically evaluate and distinguish structural and metabolic pathological conditions such as osteomalacia in adults and rickets in growing children. Water- and fat-suppressed proton projection MRI (WASPI) was developed as a noninvasive means to obtain this information. In this study, a density calibration phantom was developed to convert WASPI intensity to true bone matrix density. The phantom contained a specifically designed poly(ethylene oxide)/poly(methyl methacrylate) (PEO/PMMA) blend, whose MRI properties (T(1), T(2), and resonance linewidth) were similar to those of solid bone matrix (collagen, tightly bound water, and other immobile molecules), minimizing the need to correct for differences in T(1) and/or T(2) relaxation between the phantom and the subject. Cortical and trabecular porcine bone specimens were imaged using WASPI with the calibration phantom in the field of view (FOV) as a stable intensity reference. Gravimetric and amino acid analyses were carried out on the same specimens after WASPI, and the chemical results were found to be highly correlated (r(2) = 0.98 and 0.95, respectively) to the WASPI intensity. By this procedure the WASPI intensity can be used to obtain the true bone matrix mass density in g cm(-3).

New diffusion phantoms dedicated to the study and validation of high-angular-resolution diffusion imaging (HARDI) models

We present new diffusion phantoms dedicated to the study and validation of high-angular-resolution diffusion imaging (HARDI) models. The phantom design permits the application of imaging parameters that are typically employed in studies of the human brain. The phantoms were made of small-diameter acrylic fibers, chosen for their high hydrophobicity and flexibility that ensured good control of the phantom geometry. The polyurethane medium was filled under vacuum with an aqueous solution that was previously degassed, doped with gadolinium-tetraazacyclododecanetetraacetic acid (Gd-DOTA), and treated by ultrasonic waves. Two versions of such phantoms were manufactured and tested. The phantom's applicability was demonstrated on an analytical Q-ball model. Numerical simulations were performed to assess the accuracy of the phantom. The phantom data will be made accessible to the community with the objective of analyzing various HARDI models.

On the effects of dephasing due to local gradients in diffusion tensor imaging experiments: relevance for diffusion tensor imaging fiber phantoms

The effect of susceptibility differences between fluid and fibers on the properties of DTI fiber phantoms was investigated. Thereto, machine-made, easily producible and inexpensive DTI fiber phantoms were constructed by winding polyamide fibers of 15 microm diameter around a circular acrylic glass spindle. The achieved fractional anisotropy was 0.78+/-0.02. It is shown by phantom measurements and Monte Carlo simulations that the transversal relaxation time T(2) strongly depends on the angle between the fibers and the B(0) field if the susceptibilities of the fibers and fluid are not identical. In the phantoms, the measured T(2) time at 3 T decreased by 60% for fibers running perpendicular to B(0). Monte Carlo simulations confirmed this result and revealed that the exact relaxation time depends strongly on the exact packing of the fibers. In the phantoms, the measured diffusion was independent of fiber orientation. Monte Carlo simulations revealed that the measured diffusion strongly depends on the exact fiber packing and that field strength and -orientation dependencies of measured diffusion may be minimal for hexagonal packing while the diffusion can be underestimated by more than 50% for cubic packing at 3 T. To overcome these effects, the susceptibilities of fibers and fluid were matched using an aqueous sodium chloride solution (83 g NaCl per kilogram of water). This enables an orientation independent and reliable use of DTI phantoms for evaluation purposes.

Simulation and experimental verification of the diffusion in an anisotropic fiber phantom

Diffusion weighted magnetic resonance imaging enables the visualization of fibrous tissues such as brain white matter. The validation of this non-invasive technique requires phantoms with a well-known structure and diffusion behavior. This paper presents anisotropic diffusion phantoms consisting of parallel fibers. The diffusion properties of the fiber phantoms are measured using diffusion weighted magnetic resonance imaging and bulk NMR measurements. To enable quantitative evaluation of the measurements, the diffusion in the interstitial space between fibers is modeled using Monte Carlo simulations of random walkers. The time-dependent apparent diffusion coefficient and kurtosis, quantifying the deviation from a Gaussian diffusion profile, are simulated in 3D geometries of parallel fibers with varying packing geometries and packing densities. The simulated diffusion coefficients are compared to the theory of diffusion in porous media, showing a good agreement. Based on the correspondence between simulations and experimental measurements, the fiber phantoms are shown to be useful for the quantitative validation of diffusion imaging on clinical MRI-scanners.

Non-uniform gradient prescription for precise angular measurements using DTI

Diffusion Tensor Imaging (DTI) calculates a tensor for each voxel, representing the mean diffusive characteristics in volume-averaged tissue. Gradients that phase-encode spins according to the amount of their diffusion are usually applied uniformly over a sphere during a DTI procedure for minimal bias of tensor information. If prior knowledge of diffusion direction exists, the angular precision for determining the principle eigenvector of cylindrically-symmetric ("prolate") tensors can be improved by specifying gradients non-uniformly. Improvements in precision of 30-40% can be achieved using a restricted band of zenith angle values for gradient directions. Sensitivity to the a priori angular range of the principle eigenvector can be adjusted with the width of the band. Simulations and phantom data are in agreement; a preliminary validation is presented.

An empirical characterization of the quality of DTI data and the efficacy of dyadic sorting

Metrics calculated from images acquired using the diffusion tensor imaging (DTI) technique possess a systematic bias that depends on signal-to-noise ratio (SNR). Dyadic sorting provides a simple method for remediating some of this bias within a region(s) of interest (ROI). Although this bias and its removal using dyadic sorting have been studied previously within a theoretical framework, one can employ precise geometric knowledge of microstructures to perform an empirical comparison between expected DTI results and those measured with a scanner. In this project, the biasing effect of low SNR (approximately 1-10) on DTI eigenvalues was measured directly using water-filled capillary structures of two different sizes, and the magnitude of the corrective effect of dyadically sorting eigenvector-eigenvalue pairs was characterized. Multiple DTI series were acquired for determining DTI metrics at eight unique SNR values, using T(R) to vary signal intensity via T(1) contrast. Differences between the second and third eigenvalues, which should be equal for prolate geometry, ranged from approximately 23% to 45% and from 19% to 41% for large and small inner diameter capillaries after sorting eigenvalues by magnitude, and ranged from approximately 1% to 18% and from 1% to 4% after dyadic sorting. A high-resolution DTI series was used to observe the effect of ROI size on dyadic sorting. For restriction of diffusion on the scale of the small capillary at SNR approximately 18, an ROI with > or =50 pixels is adequate to determine fractional anisotropy to 99% accuracy, while larger ROI are required to resolve the two smaller eigenvalues to the same accuracy ( approximately 330-390 pixels). At low values of SNR, the iteration of dyadic sorting is suggested to achieve good accuracy. A method for the incorporation of empirical measurements into a bias-correction map, which would be useful for characterizing uncertainty and for reducing systematic bias in DTI data, is introduced.