Analysis of proton-density bias corrections based on T1 measurement for robust quantification of water content in the brain at 3 Tesla

Physics-guided self-supervised learning for retrospective T1 and T2 mapping from conventional weighted brain MRI: Technical developments and initial validation in glioblastoma

PURPOSE

To develop a self-supervised learning method to retrospectively estimate T1 and T2 values from clinical weighted MRI.

METHODS

A self-supervised learning approach was constructed to estimate T1, T2, and proton density maps from conventional T1- and T2-weighted images. MR physics models were employed to regenerate the weighted images from the network outputs, and the network was optimized based on loss calculated between the synthesized and input weighted images, alongside additional constraints based on prior information. The method was evaluated on healthy volunteer data, with conventional mapping as references. The reproducibility was examined on two 3.0T scanners. Performance in tumor characterization was inspected by applying the method to a public glioblastoma dataset.

RESULTS

For T1 and T2 estimation from three weighted images (T1 MPRAGE, T1 gradient echo sequences, and T2 turbo spin echo), the deep learning method achieved global voxel-wise error ≤9% in brain parenchyma and regional error ≤12.2% in six types of brain tissues. The regional measurements obtained from two scanners showed mean differences ≤2.4% and correlation coefficients >0.98, demonstrating excellent reproducibility. In the 50 glioblastoma patients, the retrospective quantification results were in line with literature reports from prospective methods, and the T2 values were found to be higher in tumor regions, with sensitivity of 0.90 and specificity of 0.92 in a voxel-wise classification task between normal and abnormal regions.

CONCLUSION

The self-supervised learning method is promising for retrospective T1 and T2 quantification from clinical MR images, with the potential to improve the availability of quantitative MRI and facilitate brain tumor characterization.

In Vivo Measurement of Rat Brain Water Content at 9.4 T MR Using Super-Resolution Reconstruction: Validation With Ex Vivo Experiments

BACKGROUND

Given that changes in brain water content are often correlated with disease, investigating water content non-invasively and in vivo could lead to a better understanding of the pathogenesis of several neurologic diseases.

PURPOSE

To adapt a super-resolution-based technique, previously developed for humans, to the rat brain and report in vivo high-resolution (HR) water content maps in comparison with ex vivo wet/dry methods.

STUDY TYPE

Prospective.

ANIMAL MODEL

Eight healthy male Wistar rats.

FIELD STRENGTH/SEQUENCE

9.4-T, multi-echo gradient-echo (mGRE) sequence.

ASSESSMENT

Using super-resolution reconstruction (SRR), a HR mGRE image (200 μm isotropic) was reconstructed from three low-resolution (LR) orthogonal whole-brain images in each animal, which was followed by water content mapping in vivo. The animals were subsequently sacrificed, the brains excised and divided into five regions (front left, front right, middle left, middle right, and cerebellum-brainstem regions), and the water content was measured ex vivo using wet/dry measurements as the reference standard. The water content values of the in vivo and ex vivo methods were then compared for the whole brain and also for the different regions separately.

STATISTICAL TESTS

Friedman's non-parametric test was used to test difference between the five regions, and Pearson's correlation coefficient was used for correlation between in vivo and ex vivo measurements. A P-value <0.05 was considered statistically significant.

RESULTS

Water content values derived from in vivo MR measurements showed strong correlations with water content measured ex vivo at a regional level (r = 0.902). Different brain regions showed significantly different water content values. Water content values were highest in the frontal brain, followed by the midbrain, and lowest in the cerebellum and brainstem regions.

DATA CONCLUSION

An in vivo technique to achieve HR isotropic water content maps in the rat brain using SRR was adopted in this study. The MRI-derived water content values obtained using the technique showed strong correlations with water content values obtained using ex vivo wet/dry methods.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1.

Age-related differences in macromolecular resonances observed in ultra-short-TE STEAM MR spectra at 7T

PURPOSE

To understand how macromolecular content varies in the human brain with age in a large cohort of healthy subjects.

METHODS

In-vivo 1H-MR spectra were acquired using ultra-short TE STEAM at 7T in the posterior cingulate cortex. Macromolecular content was studied in 147 datasets from a cohort ranging in age from 19 to 89 y. Three fitting approaches were used to evaluate the macromolecular content: (1) a macromolecular resonances model developed for this study; (2) LCModel-simulated macromolecules; and (3) a combination of measured and LCModel-simulated macromolecules. The effect of age on the macromolecular content was investigated by considering age both as a continuous variable (i.e., linear regressions) and as a categorical variable (i.e., multiple comparisons among sub-groups obtained by stratifying data according to age by decade).

RESULTS

While weak age-related effects were observed for macromolecular peaks at ˜0.9 (MM09), ˜1.2 (MM12), and ˜1.4 (MM14) ppm, moderate to strong effects were observed for peaks at ˜1.7 (MM17), and ˜2.0 (MM20) ppm. Significantly higher MM17 and MM20 content started from 30 to 40 y of age, while for MM09, MM12, and MM14, significantly higher content started from 60 to 70 y of age.

CONCLUSIONS

Our findings provide insights into age-related differences in macromolecular contents and strengthen the necessity of using age-matched measured macromolecules during quantification.

Muscular MRI and magnetic resonance neurography in spinal muscular atrophy

Spinal muscular atrophy (SMA) is an autosomal recessive genetic disease caused by the degeneration of the α-motor neurons in the anterior horn of the spinal cord. SMA is clinically characterized by progressive and symmetrical muscle weakness and muscle atrophy and ends up with systemic multisystem abnormalities. Quantitative MRI (qMRI) has the advantages of non-invasiveness, objective sensitivity, and high reproducibility, and has important clinical value in evaluating the severity of neuromuscular diseases and monitoring the efficacy of treatment. This article summarizes the clinical use of muscular MRI and magnetic resonance neurography in assessing the progress of SMA.

B1 mapping using pre-learned subspaces for quantitative brain imaging

PURPOSE

To develop a machine learning-based method for estimation of both transmitter and receiver B1 fields desired for correction of the B1 inhomogeneity effects in quantitative brain imaging.

THEORY AND METHODS

A subspace model-based machine learning method was proposed for estimation of B1t and B1r fields. Probabilistic subspace models were used to capture scan-dependent variations in the B1 fields; the subspace basis and coefficient distributions were learned from pre-scanned training data. Estimation of the B1 fields for new experimental data was achieved by solving a linear optimization problem with prior distribution constraints. We evaluated the performance of the proposed method for B1 inhomogeneity correction in quantitative brain imaging scenarios, including T1 and proton density (PD) mapping from variable-flip-angle spoiled gradient-echo (SPGR) data as well as neurometabolic mapping from MRSI data, using phantom, healthy subject and brain tumor patient data.

RESULTS

In both phantom and healthy subject data, the proposed method produced high-quality B1 maps. B1 correction on SPGR data using the estimated B1 maps produced significantly improved T1 and PD maps. In brain tumor patients, the proposed method produced more accurate and robust B1 estimation and correction results than conventional methods. The B1 maps were also applied to MRSI data from tumor patients and produced improved neurometabolite maps, with better separation between pathological and normal tissues.

CONCLUSION

This work presents a novel method to estimate B1 variations using probabilistic subspace models and machine learning. The proposed method may make correction of B1 inhomogeneity effects more robust in practical applications.

Quantification of the neurochemical profile of the human putamen using STEAM MRS in a cohort of elderly subjects at 3 T and 7 T: Ruminations on the correction strategy for the tissue voxel composition

The aim of this work is to quantify the metabolic profile of the human putamen in vivo in a cohort of elderly subjects using single-voxel proton magnetic resonance spectroscopy. To obtain metabolite concentrations specific to the putamen, we investigated a correction method previously proposed to account for the tissue composition of the volume of interest. We compared the method with the conventional approach, which a priori assumes equal metabolite concentrations in GM and WM. Finally, we compared the concentrations acquired at 3 Tesla (T) and 7 T MRI scanners. Spectra were acquired from 15 subjects (age: 67.7 ± 8.3 years) at 3 T and 7 T, using an ultra-short echo time, stimulated echo acquisition mode sequence. To robustly estimate the WM-to-GM metabolite concentration ratio, five additional subjects were measured for whom the MRS voxel was deliberately shifted from the putamen in order to increase the covered amount of surrounding WM. The concentration and WM-to-GM concentration ratio for 16 metabolites were reliably estimated. These ratios ranged from ~0.3 for γ-aminobutyric acid to ~4 for N-acetylaspartylglutamate. The investigated correction method led to significant changes in concentrations compared to the conventional method, provided that the ratio significantly differed from unity. Finally, we demonstrated that differences in tissue voxel composition cannot fully account for the observed concentration difference between field strengths. We provide not only a fully comprehensive quantification of the neurochemical profile of the putamen in elderly subjects, but also a quantification of the WM-to-GM concentration ratio. This knowledge may serve as a basis for future studies with varying tissue voxel composition, either due to tissue atrophy, inconsistent voxel positioning or simply when pooling data from different voxel locations.

Quantification of GABA concentration measured noninvasively in the human posterior cingulate cortex with 7 T ultra-short-TE MR spectroscopy

PURPOSE

The increased spectral dispersion achieved at ultra-high field permits quantification of γ-aminobutyric acid (GABA) concentrations at ultra-short-TE without editing. This work investigated the influence of spectral quality and different LCModel fitting approaches on quantification of GABA. Additionally, the sensitivity with which cross-sectional and longitudinal variations in GABA concentrations can be observed was characterized.

METHODS

In - vivo spectra were acquired in the posterior cingulate cortex of 10 volunteers at 7 T using a STEAM sequence. Synthetically altered spectra with different levels of GABA signals were used to investigate the reliability of GABA quantification with different LCModel fitting approaches and different realizations of SNR. The synthetically altered spectra were also used to characterize the sensitivity of GABA quantification.

RESULTS

The best LCModel fitting approach used stiff spline baseline, no soft constraints, and measured macromolecules in the basis set. With lower SNR, coefficients of variation increased dramatically. Longitudinal and cross-sectional variations in GABA of 10% could be detected with 79 and 48 participants per group, respectively. However, the small cohort may bias the calculation of the coefficients of variation and of the sample size that would be needed to detect variations in GABA.

CONCLUSION

Reliable quantification of normal and abnormal GABA concentrations was achieved for high quality 7 T spectra using LCModel fitting.

The distortions of the free water model for diffusion MRI data when assuming single compartment relaxometry and proton density

Objective.To document the bias of thesimplifiedfree water model of diffusion MRI (dMRI) signal vis-à-vis aspecificmodel which, in addition to diffusion, incorporates compartment-specific proton density (PD), T1 recovery during repetition time (TR), and T2 decay during echo time (TE).Approach.Both models assume that volume fractionfof the total signal in any voxel arises from the free water compartment (fw) such as cerebrospinal fluid or edema, and the remainder (1-f) from hindered water (hw) which is constrained by cellular structures such as white matter (WM). Thespecificandsimplifiedmodels are compared on a synthetic dataset, using a range of PD, T1 and T2 values. We then fit the models to anin vivohealthy brain dMRI dataset. For bothsyntheticandin vivodata we use experimentally feasible TR, TE, signal-to-noise ratio (SNR) and physiologically plausible diffusion profiles.Main results.From the simulations we see that the difference between the estimatedsimplified fandspecific fis largest for mid-range ground-truthf, and it increases as SNR increases. The estimation of volume fractionfis sensitive to the choice of model,simplifiedorspecific, but the estimated diffusion parameters are robust to small perturbations in the simulation.Specific fis more accurate and precise thansimplified f. In the white matter (WM) regions of thein vivoimages,specific fis lower thansimplified f.Significance.In dMRI models for free water, accounting for compartment specific PD, T1 and T2, in addition to diffusion, improves the estimation of model parameters. This extra model specification attenuates the estimation bias of compartmental volume fraction without affecting the estimation of other diffusion parameters.

Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques

This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling.

Whole-Brain Water Content Mapping Using Super-Resolution Reconstruction with MRI Acquisition in 3 Orthogonal Orientations

PURPOSE

Brain water content provides rich tissue contrast comparable to that of longitudinal relaxation time T₁ , but mapping is usually performed at modest resolution. In particular, the slice thickness in 2D mapping methods is limited. Here, we combine super-resolution reconstruction techniques with a fast water content mapping method to acquire high and isotropic resolution (0.75 mm) water content maps at 3 Tesla.

METHODS

A high-resolution multi-echo gradient echo image is super-resolution-reconstructed from 3 low-resolution, orthogonal multi-echo gradient echo image acquisitions, followed by water content mapping. The mapping accuracy and SNR of the proposed method are assessed using numerical simulations, phantom studies, and in vivo data acquired from 6 healthy volunteers at 3 Tesla. A high-resolution acquisition with an established mapping method is used as a reference.

RESULTS

Whole-brain water content maps with 0.75 mm isotropic resolution are demonstrated. No bias in the water content values was seen following super-resolution reconstruction. In the in vivo experiments, a lower SD of the mean water content values was observed with the proposed method compared to the reference method.

CONCLUSIONS

Super-resolution reconstruction of multi-echo gradient echo data is demonstrated, enabling whole-brain water content mapping with high and isotropic resolution. The accuracy of the proposed method is shown using phantoms and 6 healthy volunteers and was found to be unchanged compared to the conventional acquisition. The proposed method could increase the sensitivity of water content mapping sufficiently to enable the detection of very small lesions, such as cortical lesions in multiple sclerosis.

Repeated Sub-Concussive Impacts and the Negative Effects of Contact Sports on Cognition and Brain Integrity

Sports are yielding a wealth of benefits for cardiovascular fitness, for psychological resilience, and for cognition. The amount of practice, and the type of practiced sports, are of importance to obtain these benefits and avoid any side effects. This is especially important in the context of contact sports. Contact sports are not only known to be a major source of injuries of the musculoskeletal apparatus, they are also significantly related to concussion and sub-concussion. Sub-concussive head impacts accumulate throughout the active sports career, and thus can cause measurable deficits and changes to brain health. Emerging research in the area of cumulative sub-concussions in contact sports has revealed several associated markers of brain injury. For example, recent studies discovered that repeated headers in soccer not only cause measurable signs of cognitive impairment but are also related to a prolonged cortical silent period in transcranial magnetic stimulation measurements. Other cognitive and neuroimaging biomarkers are also pointing to adverse effects of heading. A range of fluid biomarkers completes the picture of cumulating effects of sub-concussive impacts. Those accumulating effects can cause significant cognitive impairment later in life of active contact sportswomen and men. The aim of this review is to highlight the current scientific evidence on the effects of repeated sub-concussive head impacts on contact sports athletes’ brains, identify the areas in need of further investigation, highlight the potential of advanced neuroscientific methods, and comment on the steps governing bodies have made to address this issue. We conclude that there are indeed neural and biofluid markers that can help better understand the effects of repeated sub-concussive head impacts and that some aspects of contact sports should be redefined, especially in situations where sub-concussive impacts and concussions can be minimized.

A Novel MRI-Based Quantitative Water Content Atlas of the Human Brain

The measurement of quantitative, tissue-specific MR properties, e.g., water content, longitudinal relaxation time (T₁) and effective transverse relaxation time (T₂*), using quantitative MRI at a clinical field strength (1.5 T to 3T) is a well-explored topic. However, none of the commonly used standard brain atlases, such as MNI or JHU, provide quantitative information. Within the framework of quantitative MRI of the brain, this work reports on the development of the first quantitative brain atlas for tissue water content at 3T. A methodology to create this quantitative atlas of in vivo brain water content based on healthy volunteers is presented, and preliminary, practical examples of its potential applications are also shown. Established methods for the fast and reliable measurement of the absolute water content were used to achieve high precision and accuracy. Water content and T₂* were mapped based on two different methods: an intermediate-TR, two-point method and a long-TR, single-scan method. Twenty healthy subjects (age 25.3 ± 2.5 years) were examined with these quantitative imaging protocols. The images were normalised to MNI stereotactic coordinates, and water content atlases of healthy volunteers were created for each method and compared. Regions-of-interest were generated with the help of a standard MNI template, and water content values averaged across the ROIs were compared to water content values from the literature. Finally, in order to demonstrate the strength of quantitative MRI, water content maps from patients with pathological changes in the brain due to stroke, tumour (glioblastoma) and multiple sclerosis were voxel-wise compared to the healthy brain. The water content atlases were largely independent of the method used to acquire the individual water maps. Global grey matter and white matter water content values between the methods agreed with each other to within 0.5 %. The feasibility of detecting abnormal water content in the brains of patients based on comparison to a healthy brain water content atlas was demonstrated. In summary, the first quantitative water content brain atlas in vivo has been developed and a voxel-wise assessment of pathology-related changes in the brain water content has been performed. These results suggest that qMRI, in combination with a water content atlas, allows for a quantitative interpretation of changes due to disease and could be used for disease monitoring.

Spatiotemporal characterisation of ischaemic lesions in transient stroke animal models using diffusion free water elimination and mapping MRI with echo time dependence

BACKGROUND AND PURPOSE

The excess fluid as a result of vasogenic oedema and the subsequent tissue cavitation obscure the microstructural characterisation of ischaemic tissue by conventional diffusion and relaxometry MRI. They lead to a pseudo-normalisation of the water diffusivity and transverse relaxation time maps in the subacute and chronic phases of stroke. Within the context of diffusion MRI, the free water elimination and mapping method (FWE) with echo time dependence has been proposed as a promising approach to measure the amount of free fluid in brain tissue robustly and to eliminate its biasing effect on other biomarkers. In this longitudinal study of transient middle cerebral artery occlusion (MCAo) in the rat brain, we investigated the use of FWE MRI with echo time dependence for the characterisation of the tissue microstructure and explored the potential of the free water fraction as a novel biomarker of ischaemic tissue condition.

METHODS

Adult rats received a transient MCAo. Diffusion- and transverse relaxation-weighted MRI experiments were performed longitudinally, pre-occlusion and on days 1, 3, 4, 5, 6, 7 and 10 after MCAo on four rats. Histology was performed for non-stroke and 1, 3 and 10 days after MCAo on three different rats at each time point.

RESULTS

The free water fraction was homogeneously increased in the ischaemic cortex one day after stroke. Between three and ten days after stroke, the core of the ischaemic tissue showed a progressive normalisation in the amount of free water, whereas the inner and outer border zones of the ischaemic cortex depicted a large, monotonous increase with time. The specific lesions in brain sections were verified by H&E and immunostaining. The tissue-specific diffusion and relaxometry MRI metrics in the ischaemic cortex were significantly different compared to their conventional counterpart.

CONCLUSIONS

Our results demonstrate that the free water fraction in FWE MRI with echo time dependence is a valuable biomarker, sensitive to the progressive degeneration in ischaemic tissue. We showed that part of the heterogeneity previously observed in conventional parameter maps can be accounted for by a heterogeneous distribution of free water in the tissue. Our results suggest that the temporal evolution of the free fluid fraction map at the core and inner border zone can be associated with the pathological changes linked to the evolution of vasogenic oedema. Namely, the homogeneous increase in free water one day after stroke and its tendency to normalise in the core of the ischaemic cortex starting three days after stroke, followed by a progressive increase in free water at the inner border zone from three to ten days after stroke. Finally, the monotonous increase in free fluid in the outer border zone of the cortex reflects the formation of fluid-filled cysts.

Magnetic Resonance Neurography: Improved Diagnosis of Peripheral Neuropathies

Peripheral neuropathies account for the most frequent disorders seen by neurologists, and causes are manifold. The traditional diagnostic gold-standard consists of clinical neurologic examinations supplemented by nerve conduction studies. Due to well-known limitations of standard diagnostics and atypical clinical presentations, establishing the correct diagnosis can be challenging but is critical for appropriate therapies. Magnetic resonance neurography (MRN) is a relatively novel technique that was developed for the high-resolution imaging of the peripheral nervous system. In focal neuropathies, whether traumatic or due to nerve entrapment, MRN has improved the diagnostic accuracy by directly visualizing underlying nerve lesions and providing information on the exact lesion localization, extension, and spatial distribution, thereby assisting surgical planning. Notably, the differentiation between distally located, complete cross-sectional nerve lesions, and more proximally located lesions involving only certain fascicles within a nerve can hold difficulties that MRN can overcome, when basic technical requirements to achieve sufficient spatial resolution are implemented. Typical MRN-specific pitfalls are essential to understand in order to prevent overdiagnosing neuropathies. Heavily T2-weighted sequences with fat saturation are the most established sequences for MRN. Newer techniques, such as T2-relaxometry, magnetization transfer contrast imaging, and diffusion tensor imaging, allow the quantification of nerve lesions and have become increasingly important, especially when evaluating diffuse, non-focal neuropathies. Innovative studies in hereditary, metabolic or inflammatory polyneuropathies, and motor neuron diseases have contributed to a better understanding of the underlying pathomechanism. New imaging biomarkers might be used for an earlier diagnosis and monitoring of structural nerve injury under causative treatments in the future.

Water content changes in new multiple sclerosis lesions have a minimal effect on the determination of myelin water fraction values

BACKGROUND AND PURPOSE

Myelin water fraction (MWF) is a histopathologically validated in vivo myelin marker. As MWF is the proportion of water with a short T₂ relative to the total water, increases in water from edema and inflammation may confound MWF determination in multiple sclerosis (MS) lesions. Total water content (TWC) measurement enables calculation of absolute myelin water content (MWC) and can be used to distinguish edema/inflammation from demyelination. We assessed what influence changes in total water might have on MWF by calculating MWC values in new MS lesions.

METHODS

3T 32-echo T₂ relaxation data were collected monthly for 6 months from six relapsing-remitting MS participants. TWC was determined and multiplied with MWF images to calculate corrected MWC images. The effect of this water content correction was examined in 20 new lesions by comparing mean MWF and MWC over time.

RESULTS

On average, at lesion first appearance, lesion TWC increased by 6.4% (p = .003; range: -1% to +21%), MWF decreased by 24% (p = .006; range: -70% to +12%), and MWC decreased by 20% (p = .026; range: -68% to +21%), relative to prelesion values. Average TWC in lesions then gradually decreased, whereas MWF and MWC remained low. The shape of the MWF and MWC lesion evolution curves was nearly identical, differing only by an offset.

CONCLUSION

MWF mirrors MWC and is able to monitor myelin in new lesions. Even after taking into account water content increases, MWC still decreased at lesion first appearance attributed to demyelination.

A dynamic susceptibility contrast MRI digital reference object for testing software with leakage correction: Effect of background simulation

PURPOSE

Dynamic susceptibility contrast (DSC)-MRI is a perfusion imaging technique from which useful quantitative imaging biomarkers can be derived. Relative cerebral blood volume (rCBV) is such a biomarker commonly used for evaluating brain tumors. To account for the extravasation of contrast agents in tumors, post-processing leakage correction is often applied to improve rCBV accuracy. Digital reference objects (DRO) are ideal for testing the post-processing software, because the biophysical model used to generate the DRO can be matched to the one that the software uses. This study aims to develop DROs to validate the leakage correction of software using Weisskoff model and to examine the effect of background signal time curves that are required by the model.

METHODS

Three DROs were generated using the Weisskoff model, each composed of nine foreground lesion objects with combinations of different levels of rCBV and contrast leakage parameter (K2). Three types of background were implemented for these DROs: (1) a multi-compartment brain-like background, (2) a sphere background with a constant signal time curve, and (3) a sphere background with signal time curve identical to that of the brain-like DRO's white matter (WM). The DROs were then analyzed with an FDA-cleared software with and without leakage correction. Leakage correction was tested with and without brain segmentation.

RESULTS

Accuracy of leakage correction was able to be verified using the brain-like phantom and the sphere phantom with WM background. The sphere with constant background did not perform well with leakage correction with or without brain segmentation. The DROs were able to verify that for the particular software tested, leakage correction with brain segmentation achieved the lowest error.

CONCLUSIONS

DSC-MRI DROs with biophysical model matched to that of the post-processing software can be well used for the software's validation, provided that the background signals are also properly simulated for generating the reference time curve required by the model. Care needs to be taken to consider the interaction of the design of the DRO with the software's implementation of brain segmentation to extract the reference time curve.

Do glia provide the link between low-grade systemic inflammation and normal cognitive ageing? A 1 H magnetic resonance spectroscopy study at 7 tesla

Low-grade systemic inflammation contributes to ageing-related cognitive decline, possibly by triggering a neuroinflammatory response through glial activation. Using proton magnetic resonance spectroscopy (¹ H-MRS) at 7T in normal human individuals from 18 to 79 years in a cross-sectional study, we previously observed higher regional levels of myo-inositol (mIns), total creatine (tCr) and total choline (tCho) in older than younger age groups. Moreover, visuo-spatial working memory (vsWM) correlated negatively with tCr and tCho in anterior cingulate cortex (ACC) and mIns in hippocampus and thalamus. As mIns, tCr and tCho are higher in glia than neurons, this suggest a potential in vivo connection between cognitive ageing and higher regional levels of glia-related metabolites. In the present study, we tested whether these metabolic differences may be related to low-grade systemic inflammation. In the same individuals, plasma concentrations of the proinflammatory markers C-reactive protein (CRP), interleukin 8 (IL-8), and tumour necrosis factor α (TNF-α) were measured on the same day as ¹ H-MRS assessments. We tested whether CRP, IL-8, and TNF-α concentrations correlated with the levels of glia-related metabolites. CRP and IL-8, but not TNF-α, were higher in older (69-79 years) than younger (18-26 years) individuals. CRP correlated positively with thalamic mIns and negatively with vsWM. IL-8 correlated positively with ACC tCho and hippocampal mIns, but not with vsWM. Mediation analysis revealed an indirect effect of IL-8 on vsWM via ACC tCho. Together, these findings corroborate the role of glial cells, perhaps via their role in neuroinflammation, as part of the neurobiological link between systemic inflammation and cognitive ageing.

MRI Analysis Of the Water Content Change In the Brain During Acute Ethanol Consumption Via Quantitative Water Mapping

AIMS

Alcohol consumption influences the water balance in the brain. While the impact of chronic alcohol misuse on cerebral water content has been the subject of several studies, less is known about the effects of acute alcohol misuse, with contradictory results in the literature. Therefore, we investigated the effects of acute alcohol intoxication on cerebral water content using a precise quantitative magnetic resonance imaging (MRI) sequence.

METHODS

In a prospective study, we measured cerebral water content in 20 healthy volunteers before alcohol consumption and after reaching a breath alcohol concentration of 1 ‰. A quantitative MRI water mapping sequence was conducted on a clinical 3 T system. Non-alcoholic fluid input and output were documented and accounted for. Water content was assessed for whole brain, grey and white matter and more specifically for regions known to be affected by acute or chronic alcohol misuse (occipital and frontal lobes, thalamus and pons). Changes in the volume of grey and white matter as well as the whole brain were examined.

RESULTS

Quantitative cerebral water content before and after acute alcohol consumption did not differ significantly (P ≥ 0.07), with changes often being within the range of measurement accuracy. Whole brain, white and grey matter volume did not change significantly (P ≥ 0.12).

CONCLUSION

The results of our study show no significant water content or volume change in the brain after recent alcohol intake in healthy volunteers. This accounts for the whole brain, grey and white matter, occipital and frontal lobes, thalamus and pons.

Influence of fitting approaches in LCModel on MRS quantification focusing on age-specific macromolecules and the spline baseline

Quantification of neurochemical concentrations from ¹ H MR spectra is challenged by incomplete knowledge of contributing signals. Some experimental conditions hinder the acquisition of artifact-free spectra and impede the acquisition of condition-specific macromolecule (MM) spectra. This work studies differences caused by fitting solutions routinely employed to manage resonances from MM and lipids. High quality spectra (free of residual water and lipid artifacts and for which condition-specific MM spectra are available) are used to understand the influences of spline baseline flexibility and noncondition-specific MM on neurochemical quantification. Fitting with moderate spline flexibility or using noncondition-specific MM led to quantification that differed from when an appropriate, fully specified model was used. This occurred for all neurochemicals to an extent that varied in magnitude among and within approaches. The spline baseline was more tortuous when less constrained and when used in combination with noncondition-specific MM. Increasing baseline flexibility did not reproduce concentrations quantified under appropriate conditions when spectra were fitted using a MM spectrum measured from a mismatched cohort. Using the noncondition-specific MM spectrum led to quantification differences that were comparable in size with using a fitting model that had moderate freedom, and these influences were additive. Although goodness of fit was better with greater fitting flexibility, quantification differed from when fitting with a fully specified model that is appropriate for low noise data. Notable GABA and PE concentration differences occurred with lower estimates of measurement error when fitting with greater spline flexibility or noncondition-specific MM. These data support the need for improved metrics of goodness of fit. Attempting to correct for artifacts or absence of a condition-specific MM spectrum via increased spline flexibility and usage of noncondition-specific MM spectra cannot replace artifact-free data quantified with a condition-specific MM spectrum.

A robust method for the detection of small changes in relaxation parameters and free water content in the vicinity of the substantia nigra in Parkinson's disease patients

Alterations in the substantia nigra are strongly associated with Parkinson's disease. However, due to low contrast and partial volume effects present in typical MRI images, the substantia nigra is not of sufficient size to obtain a reliable segmentation for region-of-interest based analysis. To combat this problem, the approach proposed here offers a method to investigate and reveal changes in quantitative MRI parameters in the vicinity of substantia nigra without any a priori delineation. This approach uses an alternative method of statistical, voxel-based analysis of quantitative maps and was tested on 18 patients and 15 healthy controls using a well-established, quantitative free water mapping protocol. It was possible to reveal the topology and the location of pathological changes in the substantia nigra and its vicinity. Moreover, a decrease in free water content, T1 and T2* in the vicinity of substantia nigra was indicated in the Parkinson's disease patients compared to the healthy controls. These findings reflect a disruption of grey matter and iron accumulation, which is known to lead to neurodegeneration. Consequently, the proposed method demonstrates an increased sensitivity for the detection of pathological changes-even in small regions-and can facilitate disease monitoring via quantitative MR parameters.

Accelerated white matter lesion analysis based on simultaneous T 1 and T 2 ∗ quantification using magnetic resonance fingerprinting and deep learning

PURPOSE

To develop an accelerated postprocessing pipeline for reproducible and efficient assessment of white matter lesions using quantitative magnetic resonance fingerprinting (MRF) and deep learning.

METHODS

MRF using echo-planar imaging (EPI) scans with varying repetition and echo times were acquired for whole brain quantification of T 1 and T 2 ∗ in 50 subjects with multiple sclerosis (MS) and 10 healthy volunteers along 2 centers. MRF T 1 and T 2 ∗ parametric maps were distortion corrected and denoised. A CNN was trained to reconstruct the T 1 and T 2 ∗ parametric maps, and the WM and GM probability maps.

RESULTS

Deep learning-based postprocessing reduced reconstruction and image processing times from hours to a few seconds while maintaining high accuracy, reliability, and precision. Mean absolute error performed the best for T 1 (deviations 5.6%) and the logarithmic hyperbolic cosinus loss the best for T 2 ∗ (deviations 6.0%).

CONCLUSIONS

MRF is a fast and robust tool for quantitative T 1 and T 2 ∗ mapping. Its long reconstruction and several postprocessing steps can be facilitated and accelerated using deep learning.

Investigating obesity-associated brain inflammation using quantitative water content mapping

There is growing evidence that obesity is associated with inflammation in the brain, which could contribute to the pathogenesis of obesity. In humans, it is challenging to detect brain inflammation in vivo. Recently, quantitative magnetic resonance imaging (qMRI) has emerged as a tool for characterising pathophysiological processes in the brain with reliable and reproducible measures. Proton density imaging provides quantitative assessment of the brain water content, which is affected in different pathologies, including inflammation. We enrolled 115 normal weight, overweight and obese men and women (body mass index [BMI] range 20.1-39.7 kg m^-2 , age range 20-75 years, 60% men) to acquire cerebral water content mapping in vivo using MRI at 3 Tesla. We investigated potential associations between brain water content with anthropometric measures of obesity, body fat distribution and whole-body metabolism. No global changes in water content were associated with obesity. However, higher water content values in the cerebellum, limbic lobe and sub-lobular region were detected in participants with higher BMI, independent of age. More specifically, the dorsal striatum, hypothalamus, thalamus, fornix, anterior limb of the internal capsule and posterior thalamic radiation showed the strongest relationship with BMI, independent of age. In a subgroup with available measurements (n = 50), we identified visceral adipose tissue to be the strongest tested link between higher water content values and obesity. Individuals with metabolic syndrome had the highest water content values in the hypothalamus and the fornix. There is accumulating evidence that inflammation of the hypothalamus contributed to obesity-associated insulin resistance in that area. Whether brain inflammation is a cause or consequence of obesity in humans still needs to be investigated using a longitudinal study design. Using qMRI, we were able to detect marked water content changes in young and older obese adults, which is most likely the result of chronic low-grade inflammation.

Regional Myo-Inositol, Creatine, and Choline Levels Are Higher at Older Age and Scale Negatively with Visuospatial Working Memory: A Cross-Sectional Proton MR Spectroscopy Study at 7 Tesla on Normal Cognitive Ageing

Proton MR spectroscopy (¹H-MRS) has been used to assess regional neurochemical brain changes during normal ageing, but results have varied. Exploiting the increased sensitivity at ultra-high field, we performed ¹H-MRS in 60 healthy human volunteers to asses age-related differences in metabolite levels and their relation to cognitive ageing. Sex was balanced, and participants were assigned to a younger, middle, and older group according to their age, ranging from 18 to 79 years. They underwent 7T ¹H-MRS of the ACC, DLPFC, hippocampus, and thalamus and performed a visuospatial working memory task outside the scanner. A multivariate ANCOVA revealed a significant overall effect of age group on metabolite levels in all regions. Higher levels in the middle than the younger group were observed for myo-inositol (mIns) in DLPFC and hippocampus and total choline (tCho) in ACC. Higher levels in the older than the younger group were observed for mIns in hippocampus and thalamus, total creatine (tCr) and tCho in ACC and hippocampus; lower levels of glutamate (Glu) were observed in DLPFC. Higher levels in the older than the middle group were observed for mIns in hippocampus, tCr in ACC and hippocampus, tCho in hippocampus, and total N-acetyl aspartate (tNAA) in hippocampus. Working memory performance correlated negatively with tCr and tCho levels in ACC and mIns levels in hippocampus and thalamus, but not with tNAA or glutamate levels. As NAA and Glu are commonly regarded to reflect neuronal health and function and concentrations of mIns, tCr, and tCho are higher in glia than neurons, the findings of this study suggest a potential in vivo connection between cognitive ageing and higher regional levels of glia-related metabolites.SIGNIFICANCE STATEMENT Neurochemical ageing is an integral component of age-related cognitive decline. Proton MR spectroscopy (¹H-MRS) studies of in vivo neurochemical changes across the lifespan have, however, yielded inconclusive results. ¹H-MRS at ultra-high field strength can potentially improve the consistency of findings. Using 7T ¹H-MRS, we assessed levels of mIns, tCr, and tCho (glia-related metabolites) and tNAA and Glu (neuron-related metabolites) in ACC, DLPFC, hippocampus, and thalamus. We found higher levels of glia-related metabolites in all brain regions in older individuals. Working memory performance correlated negatively with regional levels of glia-related metabolites. This study is the first to investigate normal ageing in these brain regions using 7T ¹H-MRS and findings indicate that glia-related metabolites could be valuable in cognitive ageing studies.

Dedicated diffusion phantoms for the investigation of free water elimination and mapping: insights into the influence of T2 relaxation properties

Conventional diffusion-weighted (DW) MRI suffers from free water contamination due to the finite voxel size. The most common case of free water contamination occurs with cerebrospinal fluid (CSF) in voxels located at the CSF-tissue interface, such as at the ventricles in the human brain. Another case refers to intra-tissue free water as in vasogenic oedema. In order to avoid the bias in diffusion metrics, several multi-compartment methods have been introduced, which explicitly model the presence of a free water compartment. However, fitting multi-compartment models in DW MRI represents a well known ill conditioned problem. Although during the last decade great effort has been devoted to mitigating this estimation problem, the research field remains active. The aim of this work is to introduce the design, characterise the NMR properties and demonstrate the use of two dedicated anisotropic diffusion fibre phantoms, useful for the study of free water elimination (FWE) and mapping models. In particular, we investigate the recently proposed FWE diffusion tensor imaging approach, which takes explicit account of differences in the transverse relaxation times between the free water and tissue compartments.

A Single-Scan, Rapid Whole-Brain Protocol for Quantitative Water Content Mapping With Neurobiological Implications

Water concentration is tightly regulated in the healthy human brain and changes only slightly with age and gender in healthy subjects. Consequently, changes in water content are important for the characterization of disease. MRI can be used to measure changes in brain water content, but as these changes are usually in the low percentage range, highly accurate and precise methods are required for detection. The method proposed here is based on a long-TR (10 s) multiple-echo gradient-echo measurement with an acquisition time of 7:21 min. Using such a long TR ensures that there is no T₁ weighting, meaning that the image intensity at zero echo time is only proportional to the water content, the transmit field, and to the receive field. The receive and transmit corrections, which are increasingly large at higher field strengths and for highly segmented coil arrays, are multiplicative and can be approached heuristically using a bias field correction. The method was tested on 21 healthy volunteers at 3T field strength. Calibration using cerebral-spinal fluid values (~100% water content) resulted in mean values and standard deviations of the water content distribution in white matter and gray matter of 69.1% (1.7%) and 83.7% (1.2%), respectively. Measured distributions were coil-independent, as seen by using either a 12-channel receiver coil or a 32-channel receiver coil. In a test-retest investigation using 12 scans on one volunteer, the variation in the mean value of water content for different tissue types was ~0.3% and the mean voxel variability was ~1%. Robustness against reduced SNR was assessed by comparing results for 5 additional volunteers at 1.5T and 3T. Furthermore, water content distribution in gray matter is investigated and regional contrast reported for the first time. Clinical applicability is illustrated with data from one stroke patient and one brain tumor patient. It is anticipated that this fast, stable, easy-to-use, high-quality mapping method will facilitate routine quantitative MR imaging of water content.

Sub-millimeter T1 mapping of rapidly relaxing compartments with gradient delay corrected spiral TAPIR and compressed sensing at 3T

PURPOSE

The TAPIR sequence is an accurate and efficient method for T₁ mapping. It combines a slice-interleaving Look-Locker read-out with an acquisition of multiple k-space lines in 1 shot. Whereas the acquisition of multiple lines per excitation increases imaging speed, the corresponding increase in TR and TE is detrimental to the T₁ fitting performance. This is especially problematic for substances exhibiting rapid T₂ ^* relaxation (e.g., myelin water).

METHODS

The T₁ fitting performance of TAPIR is enhanced by using an interleaved spiral read-out with shorter TE and TR. Furthermore, an improvement to a method for fast gradient delay estimation is presented. Whereas previous methods assume the gradient delay to be stationary, the presented approach corrects the spiral k-space trajectory by using a polynomial fit of the measured gradient delays.

RESULTS

Gradient delay artifacts are largely eliminated, requiring very little additional scanning time. The sampling efficiency of the spiral read-out allows for a significant reduction of the acquisition time in comparison to Cartesian TAPIR. Spiral TAPIR enables the sampling of more slices and an accurate measurement of rapidly relaxing compartments. Over a wide T₁ range (448-3115 ms), spiral TAPIR reduces the mean fitting error from -2.5% to -0.1%. Combining 50% undersampling with the shorter TR of spiral TAPIR, an increase in imaging speed by a factor of up to 3.3 was achieved.

CONCLUSION

Using a spiral read-out trajectory, the established TAPIR sequence enables measurement of rapidly relaxing T₁ compartments, while improving T₁ mapping performance and imaging speed.

Distinctive Neurochemistry in Alzheimer's Disease via 7 T In Vivo Magnetic Resonance Spectroscopy

This study's objective was to increase understanding of biological mechanisms underlying clinical Alzheimer's disease (AD) by noninvasively measuring an expanded neurochemical profile and exploring how well this advanced technology distinguishes AD from cognitively normal controls. We measured concentrations of 14 neurochemicals using ultra-high field (7 T) ultra-short echo time (8 ms) magnetic resonance spectroscopy (MRS) in 16 participants with mild to moderate clinical AD and 33 age- and gender-matched control participants. MRS was localized to the posterior cingulate cortex (PCC), a region known to be impacted by AD, and the occipital cortex (OCC), a control region. Participants with AD were recruited from dementia specialty clinics. Concentration of the antioxidant ascorbate was higher (p < 0.0007) in both brain regions. Concentrations of the glial marker myo-inositol and the choline-containing compounds involved in membrane turnover were higher (p≤0.0004) in PCC of participants with AD. Ascorbate and myo-inositol concentrations were strongly associated, especially in the PCC. Random forests, using the 14 neurochemicals in the two regions, distinguished participants with AD from controls: same-sample sensitivity and specificity were 88% and 97%, respectively, though out-of-sample-values would be lower. Ultra-high field ultra-short echo time MRS identified the co-occurrence of elevated ascorbate and myo-inositol in the PCC as markers that distinguish participants with mild to moderate AD from controls. While elevated myo-inositol may be a surrogate marker of neuroinflammation, the unexpected elevation of the antioxidant ascorbate may reflect infiltration of ascorbate-rich leukocytes.

Flexible proton density (PD) mapping using multi-contrast variable flip angle (VFA) data

Quantitative proton density (PD) maps measure the amount of free water, which is important for non-invasive tissue characterization in pathology and across lifespan. PD mapping requires the estimation and subsequent removal of factors influencing the signal intensity other than PD. These factors include the T1, T2* relaxation effects, transmit field inhomogeneities, receiver coil sensitivity profile (RP) and the spatially invariant factor that is required to scale the data. While the transmit field can be reliably measured, the RP estimation is usually based on image post-processing techniques due to limitations of its measurement at magnetic fields higher than 1.5 T. The post-processing methods are based on unified bias-field/tissue segmentation, fitting the sensitivity profile from images obtained with different coils, or on the linear relationship between T1 and PD. The scaling factor is derived from the signal within a specific tissue compartment or reference object. However, these approaches for calculating the RP and scaling factor have limitations particularly in severe pathology or over a wide age range, restricting their application. We propose a new approach for PD mapping based on a multi-contrast variable flip angle acquisition protocol and a data-driven estimation method for the RP correction and map scaling. By combining all the multi-contrast data acquired at different echo times, we are able to fully correct the MRI signal for T2* relaxation effects and to decrease the variance and the entropy of PD values within tissue class of the final map. The RP is determined from the corrected data applying a non-parametric bias estimation, and the scaling factor is based on the median intensity of an external calibration object. Finally, we compare the signal intensity and homogeneity of the multi-contrast PD map with the well-established effective PD (PD*) mapping, for which the RP is based on concurrent bias field estimation and tissue classification, and the scaling factor is estimated from the mean white matter signal. The multi-contrast PD values homogeneity and accuracy within the cerebrospinal fluid (CSF) and deep brain structures are increased beyond that obtained using PD* maps. We demonstrate that the multi-contrast RP approach is insensitive to anatomical or a priori tissue information by applying it in a patient with extensive brain abnormalities and for whole body PD mapping in post-mortem foetal imaging.

A 3D two-point method for whole-brain water content and relaxation time mapping: Comparison with gold standard methods

Quantitative imaging of the human brain is of great interest in clinical research as it enables the identification of a range of MR biomarkers useful in diagnosis, treatment and prognosis of a wide spectrum of diseases. Here, a 3D two-point method for water content and relaxation time mapping is presented and compared to established gold standard methods. The method determines free water content, H2O, and the longitudinal relaxation time, T1, quantitatively from a two-point fit to the signal equation including corrections of the transmit and receive fields. In addition, the effective transverse relaxation time, T2*, is obtained from an exponential fit to the multi-echo signal train and its influence on H2O values is corrected. The phantom results obtained with the proposed method show good agreement for H2O and T1 values with known and spectroscopically measured values, respectively. The method is compared in vivo to already established gold standard quantitative methods. For H2O and T2* mapping, the 3D two-point results were compared to a measurement conducted with a multiple-echo GRE with long TR and T1 is compared to results from a Look-Locker method, TAPIR. In vivo results show good overall agreement between the methods, but some systematic deviations are present. Besides an expected dependence of T2* on voxel size, T1 values are systematically larger in the 3D approach than those obtained with the gold standard method. This behaviour might be due to imperfect spoiling, influencing each method differently. Results for H2O differ due to differences in the saturation of cerebrospinal fluid and partial volume effects. In addition, ground truth values of in vivo studies are unknown, even when comparing to in vivo gold standard methods. A detailed region-of-interest analysis for H2O and T1 matches well published literature values.

Microstructural imaging in the spinal cord and validation strategies

In vivo histology using magnetic resonance imaging (MRI) is a newly emerging research field that aims to non-invasively characterize tissue microstructure. The implications of in vivo histology are many, from discovering novel biomarkers to studying human development, to providing tools for disease diagnosis and monitoring the effects of novel treatments on tissue. This review focuses on quantitative MRI (qMRI) techniques that are used to map spinal cord microstructure. Opening with a rationale for non-invasive imaging of the spinal cord, this article continues with a brief overview of the existing MRI techniques for axon and myelin imaging, followed by the specific challenges and potential solutions for acquiring and processing such data. The final part of this review focuses on histological validation, with suggested tissue preparation, acquisition and processing protocols for large-scale microscopy.

Altered macromolecular pattern and content in the aging human brain

The resonances originating from proteins underlie those of metabolites in brain ¹ H nuclear magnetic resonance (NMR) spectra. These resonances have different physical properties from those of metabolites, such as shorter T₁ and T₂ relaxation time constants. The age dependence of the macromolecular pattern and content in the human brain was investigated with a focus on adults over 66 years of age using ultrahigh-field in vivo magnetic resonance spectroscopy. Eighteen young and 23 cognitively normal older adults were studied at 7 T. Metabolite spectra were acquired in the occipital cortex and the posterior cingulate cortex with single-voxel stimulated echo acquisition mode (STEAM) spectroscopy in 14 young and 20 older adults. Macromolecular spectra were acquired in the occipital cortex using an inversion recovery STEAM sequence in four young and three older adults. The macromolecular pattern was apparent over the 0.5-4.5-ppm range in the inversion recovery spectra and the 0.5-2-ppm range in the metabolite spectra. Macromolecular content was quantified from metabolite spectra using LCModel and from inversion recovery spectra using integration. Age-associated differences in the macromolecular pattern were apparent via both types of spectra, with the largest difference observed for the 1.7- and 2-ppm macromolecular resonances. A higher macromolecular content was observed in the older adults for both brain regions. Age-specific macromolecular spectra are needed when comparing metabolite spectra from subjects of differing ages because of age-associated differences in macromolecular pattern. Age-associated pattern and content differences may provide information about the aging process.

Accelerated Parameter Mapping of Multiple-Echo Gradient-Echo Data Using Model-Based Iterative Reconstruction

A new reconstruction method, coined MIRAGE, is presented for accurate, fast, and robust parameter mapping of multiple-echo gradient-echo (MEGE) imaging, the basis sequence of novel quantitative magnetic resonance imaging techniques such as water content and susceptibility mapping. Assuming that the temporal signal can be modeled as a sum of damped complex exponentials, MIRAGE performs model-based reconstruction of undersampled data by minimizing the rank of local Hankel matrices. It further incorporates multi-channel information and spatial prior knowledge. Finally, the parameter maps are estimated using nonlinear regression. Simulations and retrospective undersampling of phantom and in vivo data affirm robustness, e.g., to strong inhomogeneity of the static magnetic field and partial volume effects. MIRAGE is compared with a state-of-the-art compressed sensing method, -ESPIRiT. Parameter maps estimated from reconstructed data using MIRAGE are shown to be accurate, with the mean absolute error reduced by up to 50% for in vivo results. The proposed method has the potential to improve the diagnostic utility of quantitative imaging techniques that rely on MEGE data.

Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations

PURPOSE

To implement a statistical framework for assessing the precision of several quantitative MRI metrics sensitive to myelin in the human spinal cord: T1, Magnetization Transfer Ratio (MTR), saturation imposed by an off-resonance pulse (MTsat) and Macromolecular Tissue Volume (MTV).

METHODS

Thirty-three healthy subjects within two age groups (young, elderly) were scanned at 3T. Among them, 16 underwent the protocol twice to assess repeatability. Statistical reliability indexes such as the Minimal Detectable Change (MDC) were compared across metrics quantified within different cervical levels and white matter (WM) sub-regions. The differences between pathways and age groups were quantified and interpreted in context of the test-retest repeatability of the measurements.

RESULTS

The MDC was respectively 105.7ms, 2.77%, 0.37% and 4.08% for T1, MTR, MTsat and MTV when quantified over all WM, while the standard-deviation across subjects was 70.5ms, 1.34%, 0.20% and 2.44%. Even though particular WM regions did exhibit significant differences, these differences were on the same order as test-retest errors. No significant difference was found between age groups for all metrics.

CONCLUSION

While T1-based metrics (T1 and MTV) exhibited better reliability than MT-based measurements (MTR and MTsat), the observed differences between subjects or WM regions were comparable to (and often smaller than) the MDC. This makes it difficult to determine if observed changes are due to variations in myelin content, or simply due to measurement error. Measurement error remains a challenge in spinal cord myelin imaging, but this study provides statistical guidelines to standardize the field and make it possible to conduct large-scale multi-center studies.

STrategically Acquired Gradient Echo (STAGE) imaging, part II: Correcting for RF inhomogeneities in estimating T1 and proton density

PURPOSE

To develop a method for mapping the B₁ transmit (B_1t) and B₁ receive (B_1r) fields from two gradient echo datasets each with a different flip angle and from these two images obtain accurate T₁ and proton density (PD) maps of the brain.

METHODS

A strategically acquired gradient echo (STAGE) data set is collected using two flip angles each with multiple echoes. The B_1t field extraction was based on forcing cortical gray matter and white matter to have specific T₁ values and fitting the resulting B_1t field to a quadratic function. The B_1r field extraction was based on synthesizing isointense images despite there being two or three tissue types present in the brain. This method was tested on 10 healthy volunteers and 20 stroke patients from data acquired at 3.0Tesla.

RESULTS

With the knowledge of the B_1t and B_1r fields, the uniformity of tissue T₁ and PD maps was considerably improved. T₁ values were measured for both the midbrain and basal ganglia and found to be in good agreement with the literature.

DISCUSSION AND CONCLUSIONS

STAGE provides a practical way to assess the B_1t and the B_1r fields which can then be used to correct for spatial variations in the images.

A new algebraic method for quantitative proton density mapping using multi-channel coil data

A difficult problem in quantitative MRI is the accurate determination of the proton density, which is an important quantity in measuring brain tissue organization. Recent progress in estimating proton density in vivo has been based on using the inverse linear relationship between the longitudinal relaxation rate T₁ and proton density. In this study, the same type of relationship is being used, however, in a more general framework by constructing 3D basis functions to model the receiver bias field. The novelty of this method is that the basis functions developed are suitable to cover an entire range of inverse linearities between T₁ and proton density. The method is applied by parcellating the human brain into small cubes with size 30mm x 30mm x 30mm. In each cube the optimal set of basis functions is determined to model the receiver coil sensitivities using multi-channel (32 element) coil data. For validation, we use arbitrary data from a numerical phantom where the data satisfy the conventional MR signal equations. Using added noise of different magnitude and realizations, we show that the proton densities obtained have a bias close to zero and also low noise sensitivity. The obtained root-mean-square-error rate is less than 0.2% for the estimated proton density in a realistic 3D simulation. As an application, the method is used in a small cohort of MS patients, and proton density values for specific brain structures are determined.

Evaluating g-ratio weighted changes in the corpus callosum as a function of age and sex

Recent years have seen a growing interest in relating MRI measurements to the structural-biophysical properties of white matter fibers. The fiber g-ratio, defined as the ratio between the inner and outer radii of the axon myelin sheath, is an important structural property of white matter, affecting signal conduction. Recently proposed modeling methods that use a combination of quantitative-MRI signals, enable a measurement of the fiber g-ratio in vivo. Here we use an MRI-based g-ratio estimation to observe the variance of the g-ratio within the corpus callosum, and evaluate sex and age related differences. To estimate the g-ratio we used a model (Stikov et al., 2011; Duval et al., 2017) based on two different WM microstructure parameters: the relative amounts of myelin (myelin volume fraction, MVF) and fibers (fiber volume fraction, FVF) in a voxel. We derived the FVF from the fractional anisotropy (FA), and estimated the MVF by using the lipid and macromolecular tissue volume (MTV), calculated from the proton density (Mezer et al., 2013). In comparison to other methods of estimating the MVF, MTV represents a stable parameter with a straightforward route of acquisition. To establish our model, we first compared histological MVF measurements (West et al., 2016) with the MRI derived MTV. We then implemented our model on a large database of 92 subjects (44 males), aged 7 to 81, in order to evaluate age and sex related changes within the corpus callosum. Our results show that the MTV provides a good estimation of MVF for calculating g-ratio, and produced values from the corpus callosum that correspond to those found in animals ex vivo and are close to the theoretical optimum, as well as to published in vivo data. Our results demonstrate that the MTV derived g-ratio provides a simple and reliable in vivo g-ratio-weighted (GR*) measurement in humans. In agreement with theoretical predictions, and unlike other tissue parameters measured with MRI, the g-ratio estimations were found to be relatively stable with age, and we found no support for a significant sexual dimorphism with age.

Region-specific aging of the human brain as evidenced by neurochemical profiles measured noninvasively in the posterior cingulate cortex and the occipital lobe using 1H magnetic resonance spectroscopy at 7 T

The concentrations of fourteen neurochemicals associated with metabolism, neurotransmission, antioxidant capacity, and cellular structure were measured noninvasively from two distinct brain regions using ¹H magnetic resonance spectroscopy. Seventeen young adults (age 19-22years) and sixteen cognitively normal older adults (age 70-88years) were scanned. To increase sensitivity and specificity, ¹H magnetic resonance spectra were obtained at the ultra-high field of 7T and at ultra-short echo time. The concentrations of neurochemicals were determined using water as an internal reference and accounting for gray matter, white matter, and cerebrospinal fluid content of the volume of interest. In the posterior cingulate cortex (PCC), the concentrations of neurochemicals associated with energy (i.e., creatine plus phosphocreatine), membrane turnover (i.e., choline containing compounds), and gliosis (i.e., myo-inositol) were higher in the older adults while the concentrations of N-acetylaspartylglutamate (NAAG) and phosphorylethanolamine (PE) were lower. In the occipital cortex (OCC), the concentration of N-acetylaspartate (NAA), a marker of neuronal viability, concentrations of the neurotransmitters Glu and NAAG, antioxidant ascorbate (Asc), and PE were lower in the older adults while the concentration of choline containing compounds was higher. Altogether, these findings shed light on how the human brain ages differently depending on region.

Diffusion-weighted DESS protocol optimization for simultaneous mapping of the mean diffusivity, proton density and relaxation times at 3 Tesla

PURPOSE

To design a general framework for the optimization of an MRI protocol based on the the diffusion-weighted dual-echo steady-state (DW-DESS) sequence, enabling quantitative and simultaneous mapping of proton density (PD), relaxation times T1 and T2 and diffusion coefficient D.

METHODS

A parameterization of the DW-DESS sequence minimizing the Cramér-Rao lower bound of each parameter estimate was proposed and tested in a phantom experiment. An extension of the protocol was implemented for brain imaging to return the rotationally invariant mean diffusivity (MD).

RESULTS

In an NiCl₂ -doped agar gel phantom wherein T1/T2=920/65 ms, the parameter estimation errors were below 3% for PD and T1 and below 7% for T2 and D while the measured signal-to-noise ratio always exceeded 20. In the human brain, the in vivo parametric maps obtained were overall in reasonable agreement with gold standard measurements, despite a broadening of the distributions due to physiological motion.

CONCLUSION

Within the optimization framework presented here, DW-DESS images can be quantitatively interpreted to yield four intrinsic parameters of the tissue. Currently, the method is limited by the sensitivity of the DW-DESS sequence in terms of physiological motion. Magn Reson Med 78:130-141, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

MRI Appearance of Intracerebral Iodinated Contrast Agents: Is It Possible to Distinguish Extravasated Contrast Agent from Hemorrhage?

BACKGROUND AND PURPOSE

Hyperattenuated cerebral areas on postinterventional CT are a common finding after endovascular stroke treatment. There is uncertainty about the extent to which these hyperattenuated areas correspond to hemorrhage or contrast agent that extravasated into infarcted parenchyma during angiography. We evaluated whether it is possible to distinguish contrast extravasation from blood on MR imaging.

MATERIALS AND METHODS

We examined the influence of iodinated contrast agents on T1, T2, and T2* and magnetic susceptibility in a phantom model and an ex vivo animal model. We determined T1, T2, and T2* relaxation times and magnetic susceptibility of iopamidol and iopromide in dilutions of 1:1; 1:2; 1:4; 1:10; and 1:100 with physiologic saline solution. We then examined the appearance of intracerebral iopamidol on MR imaging in an ex vivo animal model. To this end, we injected iopamidol into the brain of a deceased swine.

RESULTS

Iopamidol and iopromide cause a negative susceptibility shift and T1, T2, and T2* shortening. The effects, however, become very small in dilutions of 1:10 and higher. Undiluted iopamidol, injected directly into the brain parenchyma, did not cause visually distinctive signal changes on T1-weighted spin-echo, T2-weighted turbo spin-echo, and T2*-weighted gradient recalled-echo imaging.

CONCLUSIONS

It is unlikely that iodinated contrast agents extravasated into infarcted brain parenchyma cause signal changes that mimic hemorrhage on T1WI, T2WI, and T2*WI. Our results imply that extravasated contrast agents can be distinguished from hemorrhage on MR imaging.

Evaluating quantitative proton-density-mapping methods

Quantitative magnetic resonance imaging (qMRI) aims to quantify tissue parameters by eliminating instrumental bias. We describe qMRI theory, simulations, and software designed to estimate proton density (PD), the apparent local concentration of water protons in the living human brain. First, we show that, in the absence of noise, multichannel coil data contain enough information to separate PD and coil sensitivity, a limiting instrumental bias. Second, we show that, in the presence of noise, regularization by a constraint on the relationship between T1 and PD produces accurate coil sensitivity and PD maps. The ability to measure PD quantitatively has applications in the analysis of in-vivo human brain tissue and enables multisite comparisons between individuals and across instruments. Hum Brain Mapp 37:3623-3635, 2016. © 2016 Wiley Periodicals, Inc.

Effects of formalin fixation and temperature on MR relaxation times in the human brain

Post-mortem MRI of the brain is increasingly applied in neuroscience for a better understanding of the contrast mechanisms of disease induced tissue changes. However, the influence of chemical processes caused by formalin fixation and differences in temperature may hamper the comparability with results from in vivo MRI. In this study we investigated how formalin fixation and temperature affect T1, T2 and T2* relaxation times of brain tissue. Fixation effects were examined with respect to changes in water content and crosslinking. Relaxometry was performed in brain slices from five deceased subjects at different temperatures. All measurements were repeated after 190 days of formaldehyde immersion. The water content of unfixed and fixed tissue was determined using the wet-to-dry ratio following drying. Protein weight was determined with sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Fixation caused a strong decrease of all relaxation times, the strongest effect being seen on T1, with a reduction of up to 76%. The temperature coefficient of T1 was lower in the fixed than unfixed tissue, which was in contrast to T2, where an increase of the temperature coefficient was observed following fixation. The reduction of the water content after fixation was in the range of 1-6% and thus not sufficient to explain the changes in relaxation time. Results from SDS-PAGE indicated a strong increase of the protein size above 260 kDa in all brain structures examined. Our results suggest that crosslinking induced changes of the macromolecular matrix are responsible for T1 shortening and a decreased temperature dependency. The relaxation times provided in this work should allow optimization of post-mortem MRI protocols for the brain.

Magnetic resonance neurography detects diabetic neuropathy early and with Proximal Predominance

Objective

The aim of this work was to localize and quantify alterations of nerve microstructure in diabetic polyneuropathy (DPN) by magnetic resonance (MR) neurography with large anatomical coverage.

Methods

Patients (N = 25) with mild‐to‐moderate (Neuropathy‐Symptom‐Score [NSS]/Neuropathy Deficit Score [NDS] 3.8 ± 0.3/2.6 ± 0.5) and patients (n = 10) with severe DPN (6.2 ± 0.6/7.4 ± 0.5) were compared to patients (n = 15) with diabetes but no DPN and to age‐/sex‐matched nondiabetic controls (n = 25). All subjects underwent MR neurography with large spatial coverage and high resolution from spinal nerve to ankle level: four slabs per leg, each with 35 axial slices (T2‐ and proton‐density–weighted two dimensional turbo‐spin‐echo sequences; voxel size: 0.4 × 0.3 × 3.5 mm³) and a three‐dimensional T2‐weighted sequence to cover spinal nerves and plexus. Nerve segmentation was performed on a total of 280 slices per subject. Nerve lesion voxels were determined independently from operator input by statistical classification against the nondiabetic cohort. At the site with highest lesion‐voxel burden, signal quantification was performed by calculating nerve proton spin density and T2 relaxation time.

Results

Total burden of nerve lesion voxels was significantly increased in DPN (p = 0.003) with strong spatial predominance at thigh level, where average lesion voxel load was significantly higher in severe (57 ± 18.4; p = 0.0022) and in mild‐to‐moderate DPN (35 ± 4.0; p < 0.001) than in controls (18 ± 3.6). Signal quantification at the site of predominant lesion burden (thigh) revealed a significant increase of nerve proton spin density in severe (360 ± 22.9; p = 0.043) and in mild‐to‐moderate DPN (365 ± 15.2; p = 0.001) versus controls (288 ± 13.4), but not of T2 relaxation time (p = 0.49). Nerve proton spin density predicted severity of DPN with an odds ratio of 2.9 (95% confidence interval: 2.4–3.5; p < 0.001) per 100 proton spins.

Interpretation

In DPN, the predominant site of microstructural nerve alteration is at the thigh level with a strong proximal‐to‐distal gradient. Nerve proton spin density at the thigh level is a novel quantitative imaging biomarker of early DPN and increases with neuropathy severity. Ann Neurol 2015;78:939–948

Increased cerebral water content in hemodialysis patients

Little information is available on the impact of hemodialysis on cerebral water homeostasis and its distribution in chronic kidney disease. We used a neuropsychological test battery, structural magnetic resonance imaging (MRI) and a novel technique for quantitative measurement of localized water content using 3T MRI to investigate ten hemodialysis patients (HD) on a dialysis-free day and after hemodialysis (2.4±2.2 hours), and a matched healthy control group with the same time interval. Neuropsychological testing revealed mainly attentional and executive cognitive dysfunction in HD. Voxel-based-morphometry showed only marginal alterations in the right inferior medial temporal lobe white matter in HD compared to controls. Marked increases in global brain water content were found in the white matter, specifically in parietal areas, in HD patients compared to controls. Although the global water content in the gray matter did not differ between the two groups, regional increases of brain water content in particular in parieto-temporal gray matter areas were observed in HD patients. No relevant brain hydration changes were revealed before and after hemodialysis. Whereas longer duration of dialysis vintage was associated with increased water content in parieto-temporal-occipital regions, lower intradialytic weight changes were negatively correlated with brain water content in these areas in HD patients. Worse cognitive performance on an attention task correlated with increased hydration in frontal white matter. In conclusion, long-term HD is associated with altered brain tissue water homeostasis mainly in parietal white matter regions, whereas the attentional domain in the cognitive dysfunction profile in HD could be linked to increased frontal white matter water content.

Vascular endothelial growth factor blockade alters magnetic resonance imaging biomarkers of vascular function and decreases barrier permeability in a rat model of lung cancer brain metastasis

Background

Blockade of vascular endothelial growth factor (VEGF) to promote vascular normalization and inhibit angiogenesis has been proposed for the treatment of brain metastases; however, vascular normalization has not been well-characterized in this disease. We investigated the effect of treatment with bevacizumab anti-VEGF antibody on magnetic resonance imaging (MRI) biomarkers of brain tumor vascular characteristics in comparison to small molecule delivery in a rat model of human lung cancer brain metastasis.

Methods

Athymic rats with A549 human lung adenocarcinoma intracerebral xenografts underwent MRI at 11.75 T before and one day after treatment with bevacizumab (n = 8) or saline control (n = 8) to evaluate tumor volume, free water content (edema), blood volume and vascular permeability (K^trans). One day later, permeability to ¹⁴C-aminoisobutyric acid (AIB) was measured in tumor and brain to assess the penetration of a small drug-like molecule.

Results

In saline control animals, tumor volume, edema and permeability increased over the two day assessment period. Compared to controls, bevacizumab treatment slowed the rate of tumor growth (P = 0.003) and blocked the increase in edema (P = 0.033), but did not alter tumor blood volume. Bevacizumab also significantly reduced K^trans (P = 0.033) and AIB passive permeability in tumor (P = 0.04), but not to peritumoral tissue or normal brain. Post-treatment K^trans correlated with AIB levels in the bevacizumab-treated rats but not in the saline controls.

Conclusions

The correlation of an MRI biomarker for decreased vascular permeability with decreased AIB concentration in tumor after antiangiogenic treatment suggests that bevacizumab partially restored the normal low permeability characteristics of the blood–brain barrier in a model of human lung cancer brain metastasis.