Rapid whole brain 3D T2 mapping respiratory-resolved Double-Echo Steady State (DESS) sequence with improved repeatability

PURPOSE

To propose a quantitative 3D double-echo steady-state (DESS) sequence that offers rapid and repeatable T2 mapping of the human brain using different encoding schemes that account for respiratory B0 variation.

METHODS

A retrospective self-gating module was firstly implemented into the standard DESS sequence in order to suppress the respiratory artifact via data binning. A compressed-sensing trajectory (CS-DESS) was then optimized to accelerate the acquisition. Finally, a spiral Cartesian encoding (SPICCS-DESS) was incorporated to further disrupt the coherent respiratory artifact. These different versions were compared to a standard DESS sequence (fully DESS) by assessing the T2 distribution and repeatability in different brain regions of eight volunteers at 3 T.

RESULTS

The respiratory artifact correction was determined to be optimal when the data was binned into seven respiratory phases. Compared to the fully DESS, T2 distribution was improved for the CS-DESS and SPICCS-DESS with interquartile ranges reduced significantly by a factor ranging from 2 to 12 in the caudate, putamen, and thalamus regions. In the gray and white matter areas, average absolute test-retest T2 differences across all volunteers were respectively 3.5 ± 2% and 3.1 ± 2.1% for the SPICCS-DESS, 4.6 ± 4.6% and 4.9 ± 5.1% for the CS-DESS, and 15% ± 13% and 7.3 ± 5.6% for the fully DESS. The SPICCS-DESS sequence's acquisition time could be reduced by half (<4 min) while maintaining its efficient T2 mapping.

CONCLUSION

The respiratory-resolved SPICCS-DESS sequence offers rapid, robust, and repeatable 3D T2 mapping of the human brain, which can be especially effective for longitudinal monitoring of cerebral pathologies.

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.

Statistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans

BACKGROUND

Consistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses.

NEW METHOD

The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2 * , which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2 * , and MTsat, computed from multiple sets of images.

RESULTS

QUIQI restores homoscedasticity in analyses of quantitative MRI data computed from multiple scans. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy.

COMPARISON WITH EXISTING METHODS

QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis.

CONCLUSION

QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.

Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling

PURPOSE

The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

METHODS

We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.

RESULTS

R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.

CONCLUSION

We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

The Compressed Sensing MP2RAGE as a Surrogate to the MPRAGE for Neuroimaging at 3 T

OBJECTIVES

The magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequence provides quantitative T1 maps in addition to high-contrast morphological images. Advanced acceleration techniques such as compressed sensing (CS) allow its acquisition time to be compatible with clinical applications. To consider its routine use in future neuroimaging protocols, the repeatability of the segmented brain structures was evaluated and compared with the standard morphological sequence (magnetization-prepared rapid gradient echo [MPRAGE]). The repeatability of the T1 measurements was also assessed.

MATERIALS AND METHODS

Thirteen healthy volunteers were scanned either 3 or 4 times at several days of interval, on a 3 T clinical scanner, with the 2 sequences (CS-MP2RAGE and MPRAGE), set with the same spatial resolution (0.8-mm isotropic) and scan duration (6 minutes 21 seconds). The reconstruction time of the CS-MP2RAGE outputs (including the 2 echo images, the MP2RAGE image, and the T1 map) was 3 minutes 33 seconds, using an open-source in-house algorithm implemented in the Gadgetron framework.Both precision and variability of volume measurements obtained from CAT12 and VolBrain were assessed. The T1 accuracy and repeatability were measured on phantoms and on humans and were compared with literature.Volumes obtained from the CS-MP2RAGE and the MPRAGE images were compared using Student t tests (P < 0.05 was considered significant).

RESULTS

The CS-MP2RAGE acquisition provided morphological images of the same quality and higher contrasts than the standard MPRAGE images. Similar intravolunteer variabilities were obtained with the CS-MP2RAGE and the MPRAGE segmentations. In addition, high-resolution T1 maps were obtained from the CS-MP2RAGE. T1 times of white and gray matters and several deep gray nuclei are consistent with the literature and show very low variability (<1%).

CONCLUSIONS

The CS-MP2RAGE can be used in future protocols to rapidly obtain morphological images and quantitative T1 maps in 3-dimensions while maintaining high repeatability in volumetry and relaxation times.

Correcting inter-scan motion artifacts in quantitative R1 mapping at 7T

PURPOSE

Inter-scan motion is a substantial source of error in R 1 estimation methods based on multiple volumes, for example, variable flip angle (VFA), and can be expected to increase at 7T where B 1 fields are more inhomogeneous. The established correction scheme does not translate to 7T since it requires a body coil reference. Here we introduce two alternatives that outperform the established method. Since they compute relative sensitivities they do not require body coil images.

THEORY

The proposed methods use coil-combined magnitude images to obtain the relative coil sensitivities. The first method efficiently computes the relative sensitivities via a simple ratio; the second by fitting a more sophisticated generative model.

METHODS

R 1 maps were computed using the VFA approach. Multiple datasets were acquired at 3T and 7T, with and without motion between the acquisition of the VFA volumes. R 1 maps were constructed without correction, with the proposed corrections, and (at 3T) with the previously established correction scheme. The effect of the greater inhomogeneity in the transmit field at 7T was also explored by acquiring B 1 + maps at each position.

RESULTS

At 3T, the proposed methods outperform the baseline method. Inter-scan motion artifacts were also reduced at 7T. However, at 7T reproducibility only converged on that of the no motion condition if position-specific transmit field effects were also incorporated.

CONCLUSION

The proposed methods simplify inter-scan motion correction of R 1 maps and are applicable at both 3T and 7T, where a body coil is typically not available. The open-source code for all methods is made publicly available.

Restoring statistical validity in group analyses of motion-corrupted MRI data

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data‐driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.

Imperfect spoiling in variable flip angle T1 mapping at 7T: Quantifying and minimizing impact

Purpose

The variable flip angle (VFA) approach to T₁ mapping assumes perfectly spoiled transverse magnetisation at the end of each repetition time (TR). Despite radiofrequency (RF) and gradient spoiling, this condition is rarely met, leading to erroneous T₁ estimates (T1app). Theoretical corrections can be applied but make assumptions about tissue properties, for example, a global T₂ time. Here, we investigate the effect of imperfect spoiling at 7T and the interaction between the RF and gradient spoiling conditions, additionally accounting for diffusion. We provide guidance on the optimal approach to maximise the accuracy of the T₁ estimate in the context of 3D multi‐echo acquisitions.

Methods

The impact of the spoiling regime was investigated through numerical simulations, phantom and invivo experiments.

Results

The predicted dependence of T1app on tissue properties, system settings, and spoiling conditions was observed in both phantom and in vivo experiments. Diffusion effects modulated the dependence of T1app on both B1+ efficiency and T₂ times.

Conclusion

Error in T1app can be minimized by using an RF spoiling increment and gradient spoiler moment combination that minimizes T₂‐dependence and safeguards image quality. Although the diffusion effect was comparatively small at 7T, correction factors accounting for this effect are recommended.

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Robust 3D Bloch-Siegert based B 1 + mapping using multi-echo general linear modeling

PURPOSE

Quantitative MRI applications, such as mapping the T₁ time of tissue, puts high demands on the accuracy and precision of transmit field ( B 1 + ) estimation. A candidate approach to satisfy these requirements exploits the difference in phase induced by the Bloch-Siegert frequency shift (BSS) of 2 acquisitions with opposite off-resonance frequency radiofrequency pulses. Interleaving these radiofrequency pulses ensures robustness to motion and scanner drifts; however, here we demonstrate that doing so also introduces a bias in the B 1 + estimates.

THEORY AND METHODS

It is shown here by means of simulation and experiments that the amplitude of the error depends on MR pulse sequence parameters, such as repetition time and radiofrequency spoiling increment, but more problematically, on the intrinsic properties, T₁ and T₂ , of the investigated tissue. To solve these problems, a new approach to BSS-based B 1 + estimation that uses a multi-echo acquisition and a general linear model to estimate the correct BSS-induced phase is presented.

RESULTS

In line with simulations, phantom and in vivo experiments confirmed that the general linear model-based method removed the dependency on tissue properties and pulse sequence settings.

CONCLUSION

The general linear model-based method is recommended as a more accurate approach to BSS-based B 1 + mapping.

A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI

Dynamic Causal Modelling (DCM) is the predominant method for inferring effective connectivity from neuroimaging data. In the 15 years since its introduction, the neural models and statistical routines in DCM have developed in parallel, driven by the needs of researchers in cognitive and clinical neuroscience. In this guide, we step through an exemplar fMRI analysis in detail, reviewing the current implementation of DCM and demonstrating recent developments in group-level connectivity analysis. In the appendices, we detail the theory underlying DCM and the assumptions (i.e., priors) in the models. In the first part of the guide (current paper), we focus on issues specific to DCM for fMRI. This is accompanied by all the necessary data and instructions to reproduce the analyses using the SPM software. In the second part (in a companion paper), we move from subject-level to group-level modelling using the Parametric Empirical Bayes framework, and illustrate how to test for commonalities and differences in effective connectivity across subjects, based on imaging data from any modality.

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This guide walks through a group effective connectivity study using DCM and PEB.

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Part 1, presented here, covers first level analysis using DCM for fMRI.

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It clarifies the specific neural and haemodynamic models in DCM and their priors.

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An accompanying dataset is provided with step-by-step analysis instructions.

Accurate modeling of temporal correlations in rapidly sampled fMRI time series

Rapid imaging techniques are increasingly used in functional MRI studies because they allow a greater number of samples to be acquired per unit time, thereby increasing statistical power. However, temporal correlations limit the increase in functional sensitivity and must be accurately accounted for to control the false‐positive rate. A common approach to accounting for temporal correlations is to whiten the data prior to estimating fMRI model parameters. Models of white noise plus a first‐order autoregressive process have proven sufficient for conventional imaging studies, but more elaborate models are required for rapidly sampled data. Here we show that when the “FAST” model implemented in SPM is used with a well‐controlled number of parameters, it can successfully prewhiten 80% of grey matter voxels even with volume repetition times as short as 0.35 s. We further show that the temporal signal‐to‐noise ratio (tSNR), which has conventionally been used to assess the relative functional sensitivity of competing imaging approaches, can be augmented to account for the temporal correlations in the time series. This amounts to computing the t‐score testing for the mean signal. We show in a visual perception task that unlike the tSNR weighted by the number of samples, the t‐score measure is directly related to the t‐score testing for activation when the temporal correlations are correctly modeled. This score affords a more accurate means of evaluating the functional sensitivity of different data acquisition options.

An automatic differentiation-based gradient method for inversion of the shear wave equation in magnetic resonance elastography: specific application in fibrous soft tissues

Quantitative and accurate measurement of in vivo mechanical properties using dynamic elastography has been the scope of many research efforts over the past two decades. Most of the shear-wave-based inverse approaches for magnetic resonance elastography (MRE) make the assumption of isotropic viscoelasticity. In this paper, we propose a quantitative gradient method for inversion of the shear wave equation in anisotropic media derived from a full waveform description using analytical viscoelastic Green formalism and automatic differentiation. The abilities and performances of the proposed identification method are first evaluated on numerical phantoms calculated in a transversely isotropic medium, and subsequently on experimental MRE data measured on an isotropic hydrogel phantom, on an anisotropic cryogel phantom and on an ex vivo fibrous muscle. The experiments are carried out by coupling circular shear wave profiles generated by acoustic radiation force and MRE acquisition of the wave front. Shear modulus values obtained by our MRE method are compared to those obtained by rheometry in the isotropic hydrogel phantom, and are found to be in good agreement despite non-overlapping frequency ranges. Both the cryogel and the ex vivo muscle are found to be anisotropic. Stiffness values in the longitudinal direction are found to be 1.8 times and 1.9 times higher than those in the transverse direction for the cryogel and the muscle, respectively. The proposed method shows great perspectives and substantial benefits for the in vivo quantitative investigation of complex mechanical properties in fibrous soft tissues.

Investigations on the viscoelastic behaviour of a human healthy heel pad: In vivo compression tests and numerical analysis

The aim of this study was to investigate the viscoelastic behaviour of the human heel pad by comparing the stress–relaxation curves obtained from a compression device used on an in vivo heel pad with those obtained from a three-dimensional computer-based subject-specific heel pad model subjected to external compression. The three-dimensional model was based on the anatomy revealed by magnetic resonance imaging of a 31-year-old healthy female. The calcaneal fat pad tissue was described with a viscohyperelastic model, while a fibre-reinforced hyperelastic model was formulated for the skin. All numerical analyses were performed to interpret the mechanical response of heel tissues, with loading conditions and displacement rate in agreement with experimental tests. The heel tissues showed a non-linear, viscoelastic behaviour described by characteristic hysteretic curves, stress–relaxation and viscous recovery phenomena. The reliability of the investigations was validated by the interpretation of the mechanical response of heel tissues under the application of three pistons with diameter of 15, 20 and 40 mm, at the same displacement rate of about 1.7 mm/s. The maximum and minimum relative errors were found to be less than 0.95 and 0.064, respectively.

Transmission Electron Microscopy Studies of Silicon Nitride / Silicon Carbide Interfaces

Microstructural investigations of HIP'ed silicon nitride reinforced with silicon carbide whiskers were performed using a 400 kV high resolution analytical transmission electron microscope. Two different whisker sources as well as uncoated and carbon coated whiskers were evaluated for their effectiveness in improving mechanical properties.

This paper focuses on microstructural and microchemical analysis of interface and grain boundary regions within the composites. Combined HREM and AEM investigations reveal that variations in fracture toughness are mainly influenced by the microstructural and chemical development of the interface. Fracture toughness can be related to the surface chemistry of the reinforcements.

Evaluation of fibrocartilage regeneration and bone response at full-thickness cartilage defects in articulation with pyrolytic carbon or cobalt-chromium alloy hemiarthroplasties

Hemiarthroplasty is one method used to treat osteoarthritic joints. Often, however, an adverse response of the articular cartilage to the metal implants occurs. The purpose of this study was to evaluate and compare the response of a surgically created defect to pyrolytic carbon and cobalt-based alloy hemiarthroplasties. The cartilage on the lateral side of the tibial plateau of a canine knee joint was abraded to create a full-thickness defect. Two small holes were drilled into the exposed subchondral bone. Next, either a carbon or metal implant was placed in the lateral femoral condyle. The implantation period was 1 year. Histologic examination of the tibial defects revealed a smooth bony surface for both implant groups. In addition, there was no evidence of a residual adverse inflammatory response nor of a significant increase in subchondral bone formation for either group. Surface cracks resulting from the presence of the implant were seen in 14% of the carbon implant specimens and in 100% of the metal implants. Fibrocartilage regeneration was seen in 86% of the carbon implants and in 25% of the metal implants. Thus the carbon appears to be better tolerated mechanically compared to wrought cobalt-chromium alloy. Pyrolytic carbon shows promise for use in hemiarthroplasty.

The hairless mouse as a model for quantitating skin deposition of 3,4,4'-trichlorocarbanilide in bar soap

A method is described for quantitating the deposition of the germicide 3,4,4'-trichlorocarbanilide (TCC) via direct application of bar soap to the skin. The soap contained 1.5% [14C]TCC. Quantitating the skin deposition of biologically active materials is important in the safety evaluation of these ingredients as well as the finished products. In the case of rinse-off products such as soaps, the residue remaining after rinsing constitutes the major portion of material available for penetration. The hairless mouse and the clipped albino Sprague-Dawley rat were evaluated as models for human skin deposition. Little TCC remained on the skin of either species following the wash and rinse procedure. The amount deposited on rat skin was 1.5% of the applied dose or 0.87 micrograms TCC/cm2 while the amount deposited on hairless mouse skin was 1.1% or 0.18 micrograms TCC/cm2. The greater deposition of TCC onto rat skin was likely to be due to the presence of a greater amount of hair. Results obtained using the hairless mouse were consistent and reproducible. The hairless mouse does not require shaving and is easy to handle. Since, like man, it has little hair, it appears to be an excellent model for use in predicting the deposition of TCC on human skin.

Deposition of 3,4,4'-trichlorocarbanilide on human skin

For rinse-off products such as soaps, quantitating the deposition of ingredients left behind on the skin following rinsing may be important particularly if the ingredient is biologically active, e.g. germicides, perfumes. The residue comprises the major portion of material which is available for percutaneous penetration. A method is described for quantitating the deposition of the soap germicide, 3,4,4'-trichlorocarbanilide (TCC) as the result of direct application of bar soap on human skin. A soap pellet containing 1.5% [14C]TCC was gently rubbed on a small area of the volar forearm for 30 s. 90 s after soap application the site was thoroughly rinsed with water. After rinsing, 1.4% of the applied [14C]TCC, or 0.33 micrograms/cm2, remained on the treated site as determined by cellophane tape stripping followed by scintillation counting. The amount of TCC deposited from a simulated wash with a bar soap onto human skin is compared to the amount deposited onto the skin of other species.