Sources of variation in multi-centre brain MTR histogram studies: body-coil transmission eliminates inter-centre differences

Within-participants reliability and measurement error of magnetization transfer imaging determinations within the healthy cervical spinal cord

PURPOSE

To assess the within-participant reliability and measurement error in the determination of MTR in the healthy human cervical spinal cord.

METHODS AND MATERIALS

A total of twenty healthy controls (10 male, mean ± sd age: 33.9 ± 3.5 years, 10 females, mean ± sd age: 47.5 ± 14.4 years), with no family history of any neurological disorders or a contraindication to MRI scanning were recruited over a period of two months. Each participant was scanned twice with a 3T MRI scanner using standard MTI sequences. Spinal Cord Toolbox (v5.4) was used for image post-processing. Data were first segmented and then registered to a template and then MTR was computed. The within-participant coefficients of variation (CV%), single and average within-participants intraclass correlation coefficients (ICC) and Bland-Altman plots were determined for MT values over the volume between the 2nd and 5th cervical vertebrae for the total WM and for specific WM regions: dorsal column (DC), ventral column (VC) and lateral column (LC).

RESULTS

MTR showed poor to excellent within-participant reliability for the total WM, DC, VC and LC with single/average ICC values of 0.03/0.06, 0.10/0.18, 0.39/0.75, and 0.001/0.002, respectively, and the CV% reported an acceptable variation with values less than 10%. The Bland-Altman plots showed good within-participant agreement between the scan-rescan values.

CONCLUSION

This study demonstrates that clinical trials using MTI technique are feasible and shows that quantitative MTI can monitor tissue changes in degenerative WM patients.

IMPLICATIONS FOR PRACTICE

MTI with its MTR index provide broad assessment of the integrity of white matter tissue and are being studied widely in brain as a diagnostic tool for the assessment of different neurological diseases.

T1 relaxation time is prolonged in healthy aging: a whole brain study

BACKGROUND

: Measurement of tissue characteristics such as the longitudinal relaxation time (T1) provides complementary information to the volumetric and surface based structural analyses. We aimed to investigate T1 relaxation time characteristics in healthy aging via an exploratory design in the whole brain. The data processing pipeline was designed to minimize errors related to aging effects such as atrophy.

METHODS

Sixty healthy participants underwent MRI scanning (28 F, 32 M, age range: 18-78, 30 young and 30 old) in November 2017-March 2018 at the Bilkent University UMRAM Center. Four images with varying flip angles with FLASH (fast low angle shot magnetic resonance imaging) sequence and a high-resolution structural image with MP-RAGE (Magnetization Prepared - RApid Gradient Echo) were acquired. T1 relaxation times of the entire brain were mapped by using the region of interest (ROI) based method on 134 brain areas in young and old populations.

RESULTS

T1 prolongation was observed in various subcortical (bilateral hippocampus, caudate and thalamus) and cortical brain structures (bilateral precentral gyrus, bilateral middle frontal gyrus, bilateral supplementary motor area (SMA), left middle occipital gyrus, bilateral postcentral gyrus and bilateral Heschl's gyrus) as well as cerebellar regions (GM regions of cerebellum: bilateral cerebellum III, cerebellum IV V, cerebellum X, cerebellar vermis u 4 5, cerebellar vermis u 9 and WM cerebellar regions: left cerebellum IX, bilateral cerebellum X and cerebellar vermis u 4 5).

DISCUSSION

T1 mapping provides a practical quantitative MRI (qMRI) methodology for studying the tissue characteristics in healthy aging. T1 values are significantly increased in the aging group among half of the studied ROIs (57 ROIs out of 134).

Rapid whole-brain quantitative MT imaging

PURPOSE

To provide a robust whole-brain quantitative magnetization transfer (MT) imaging method that is not limited by long acquisition times.

METHODS

Two variants of a spiral 2D interleaved multi-slice spoiled gradient echo (SPGR) sequence are used for rapid quantitative MT imaging of the brain at 3 T. A dual flip angle, steady-state prepared, double-contrast method is used for combined B₁ and-T₁ mapping in combination with a single-contrast MT-prepared acquisition over a range of different saturation flip angles (50 deg to 850 deg) and offset frequencies (1 kHz and 10 kHz). Five sets (containing minimum 6 to maximum 18 scans) with different MT-weightings were acquired. In addition, main magnetic field inhomogeneities (ΔB₀) were measured from two Cartesian low-resolution 2D SPGR scans with different echo times. Quantitative MT model parameters were derived from all sets using a two-pool continuous-wave model analysis, yielding the pool-size ratio, F, their exchange rate, k_f, and their transverse relaxation time, T_2r.

RESULTS

Whole-brain quantitative MT imaging was feasible for all sets with total acquisition times ranging from 7:15 min down to 3:15 min. For accurate modeling, B₁-correction was essential for all investigated sets, whereas ΔB₀-correction showed limited bias for the observed maximum off-resonances at 3 T.

CONCLUSION

The combination of rapid B₁-T₁ mapping and MT-weighted imaging using a 2D multi-slice spiral SPGR research sequence offers excellent prospects for rapid whole-brain quantitative MT imaging in the clinical setting.

The perfect qMR machine: Measurement variance much less than biological variance

Implementing quantitative MR (qMR) methodology can be a time-consuming task, sometimes seemingly without an end. The concept of the Perfect qMR Machine offers the possibility that the implementation is complete and that no further improvements are needed. This is achieved by making the measurement repeatability variance much less than the biological variance. Thus the proposal is: A Perfect Quantitative MR machine is one that, in making a measurement, contributes no significant extra variation to that which already exists from biological variation. A medal system (platinum, gold, silver and bronze) recognises different sources of biological variance, depending on the type of measurement being carried out (whether a serial study or a group comparison), and different kinds of measurement variance (single machine or multi-centre). A perfect machine can in principle be demonstrated for each quantitative measure (T₁, ADC etc).

Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio

INTRODUCTION

Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS.

METHODS

Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values.

RESULTS

In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF.

DISCUSSION

G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility.

CONCLUSION

MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.

MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

•

Sharing data from cooperative studies is essential to develop new biomarkers in MS.

•

Differences in MRI acquisition, analysis, storage represent a substantial constraint.

•

We review the state of the art and developments in the harmonization of MRI.

•

We provide recommendations to harmonize large MRI datasets in the MS field.

There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.

Model-based multi-parameter mapping

Quantitative MR imaging is increasingly favoured for its richer information content and standardised measures. However, computing quantitative parameter maps, such as those encoding longitudinal relaxation rate (R1), apparent transverse relaxation rate (R2*) or magnetisation-transfer saturation (MTsat), involves inverting a highly non-linear function. Many methods for deriving parameter maps assume perfect measurements and do not consider how noise is propagated through the estimation procedure, resulting in needlessly noisy maps. Instead, we propose a probabilistic generative (forward) model of the entire dataset, which is formulated and inverted to jointly recover (log) parameter maps with a well-defined probabilistic interpretation (e.g., maximum likelihood or maximum a posteriori). The second order optimisation we propose for model fitting achieves rapid and stable convergence thanks to a novel approximate Hessian. We demonstrate the utility of our flexible framework in the context of recovering more accurate maps from data acquired using the popular multi-parameter mapping protocol. We also show how to incorporate a joint total variation prior to further decrease the noise in the maps, noting that the probabilistic formulation allows the uncertainty on the recovered parameter maps to be estimated. Our implementation uses a PyTorch backend and benefits from GPU acceleration. It is available at https://github.com/balbasty/nitorch.

Reliability and reproducibility of sciatic nerve magnetization transfer imaging and T2 relaxometry

Objectives

To assess the interreader and test-retest reliability of magnetization transfer imaging (MTI) and T2 relaxometry in sciatic nerve MR neurography (MRN).

Materials and methods

In this prospective study, 21 healthy volunteers were examined three times on separate days by a standardized MRN protocol at 3 Tesla, consisting of an MTI sequence, a multi-echo T2 relaxometry sequence, and a high-resolution T2-weighted sequence. Magnetization transfer ratio (MTR), T2 relaxation time, and proton spin density (PSD) of the sciatic nerve were assessed by two independent observers, and both interreader and test-retest reliability for all readout parameters were reported by intraclass correlation coefficients (ICCs) and standard error of measurement (SEM).

Results

For the sciatic nerve, overall mean ± standard deviation MTR was 26.75 ± 3.5%, T2 was 64.54 ± 8.2 ms, and PSD was 340.93 ± 78.8. ICCs ranged between 0.81 (MTR) and 0.94 (PSD) for interreader reliability and between 0.75 (MTR) and 0.94 (PSD) for test-retest reliability. SEM for interreader reliability was 1.7% for MTR, 2.67 ms for T2, and 21.3 for PSD. SEM for test-retest reliability was 1.7% for MTR, 2.66 ms for T2, and 20.1 for PSD.

Conclusions

MTI and T2 relaxometry of the sciatic nerve are reliable and reproducible. The values of measurement imprecision reported here may serve as a guide for correct interpretation of quantitative MRN biomarkers in future studies.

Key Points

• Magnetization transfer imaging (MTI) and T2 relaxometry of the sciatic nerve are reliable and reproducible.

• The imprecision that is unavoidably associated with different scans or different readers can be estimated by the here presented SEM values for the biomarkers T2, PSD, and MTR.

• These values may serve as a guide for correct interpretation of quantitative MRN biomarkers in future studies and possible clinical applications.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-08072-9.

One-minute whole-brain magnetization transfer ratio imaging with intrinsic B1 -correction

PURPOSE

Magnetization transfer ratio (MTR) histograms are used widely for the assessment of diffuse pathological changes in the brain. For broad clinical application, MTR scans should not only be fast, but confounding factors should also be minimized for high reproducibility. To this end, a 1-minute whole-brain spiral MTR method with intrinsic B₁ -field correction is introduced.

METHODS

A spiral multislice spoiled gradient-echo sequence with adaptable magnetization-transfer saturation pulses (angle β) is proposed. After a low-resolution single-shot spiral readout and a dummy preparation period, high-resolution images are acquired using an interleaved spiral readout. For whole-brain MTR imaging, 50 interleaved slices with three different magnetization-transfer contrasts (β = 0°, 350°, and 550°) together with an intrinsic B₁ -field map are recorded in 58.5 seconds on a clinical 3T system. From the three contrasts, two sets of MTR images are derived and used for subsequent B₁ correction, assuming a linear dependency on β. For validation, a binary spin bath model is used.

RESULTS

For the proposed B₁ -correction scheme, numerical simulations indicate for brain tissue a decrease of about a factor of 10 for the B₁ -related bias on MTR. As a result, following B₁ correction, MTR differences in gray and white matter become markedly accentuated, and the reproducibility of MTR histograms from scan-rescan experiments is improved. Furthermore, B₁ -corrected MTR histograms show a lower variability for age-matched normal-appearing brain tissue.

CONCLUSION

From its speed and offering intrinsic B₁ correction, the proposed method shows excellent prospects for clinical studies that explore magnetization-transfer effects based on MTR histogram analysis.

Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence

Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be difficult to detect with human eyes, complement or replace biopsy, and provide clear differentiation of disease stage. Further, objective assessment by quantification is a prerequisite of personalized/precision medicine. This review article aims to summarize and discuss how the variability of quantitative values derived from radiological images are induced by a number of factors and how these variabilities are mitigated and standardization of the quantitative values are achieved. We discuss the variabilities of specific biomarkers derived from magnetic resonance imaging and computed tomography, and focus on diffusion-weighted imaging, relaxometry, lung density evaluation, and computer-aided computed tomography volumetry. We also review the sources of variability and current efforts of standardization of the rapidly evolving techniques, which include radiomics and artificial intelligence.

Assessing White Matter Microstructure in Brain Regions with Different Myelin Architecture Using MRI

OBJECTIVE

We investigate how known differences in myelin architecture between regions along the cortico-spinal tract and frontal white matter (WM) in 19 healthy adolescents are reflected in several quantitative MRI parameters that have been proposed to non-invasively probe WM microstructure. In a clinically feasible scan time, both conventional imaging sequences as well as microstructural MRI parameters were assessed in order to quantitatively characterise WM regions that are known to differ in the thickness of their myelin sheaths, and in the presence of crossing or parallel fibre organisation.

RESULTS

We found that diffusion imaging, MR spectroscopy (MRS), myelin water fraction (MWF), Magnetization Transfer Imaging, and Quantitative Susceptibility Mapping were myelin-sensitive in different ways, giving complementary information for characterising WM microstructure with different underlying fibre architecture. From the diffusion parameters, neurite density (NODDI) was found to be more sensitive than fractional anisotropy (FA), underlining the limitation of FA in WM crossing fibre regions. In terms of sensitivity to different myelin content, we found that MWF, the mean diffusivity and chemical-shift imaging based MRS yielded the best discrimination between areas.

CONCLUSION

Multimodal assessment of WM microstructure was possible within clinically feasible scan times using a broad combination of quantitative microstructural MRI sequences. By assessing new microstructural WM parameters we were able to provide normative data and discuss their interpretation in regions with different myelin architecture, as well as their possible application as biomarker for WM disorders.

Quantitative Magnetization Transfer Imaging as a Biomarker for Effects of Systemic Inflammation on the Brain

BACKGROUND

Systemic inflammation impairs brain function and is increasingly implicated in the etiology of common mental illnesses, particularly depression and Alzheimer's disease. Immunotherapies selectively targeting proinflammatory cytokines demonstrate efficacy in a subset of patients with depression. However, efforts to identify patients most vulnerable to the central effects of inflammation are hindered by insensitivity of conventional structural magnetic resonance imaging.

METHODS

We used quantitative magnetization transfer (qMT) imaging, a magnetic resonance imaging technique that enables quantification of changes in brain macromolecular density, together with experimentally induced inflammation to investigate effects of systemic inflammatory challenge on human brain microstructure. Imaging with qMT was performed in 20 healthy participants after typhoid vaccination and saline control injection. An additional 20 participants underwent fluorodeoxyglucose positron emission tomography following the same inflammatory challenge.

RESULTS

The qMT data demonstrated that inflammation induced a rapid change in brain microstructure, reflected in increased magnetization exchange from free (water) to macromolecular-bound protons, within a discrete region of insular cortex implicated in representing internal physiologic states including inflammation. The functional significance of this change in insular microstructure was demonstrated by correlation with inflammation-induced fatigue and fluorodeoxyglucose positron emission tomography imaging, which revealed increased resting glucose metabolism within this region following the same inflammatory challenge.

CONCLUSIONS

Together these observations highlight a novel structural biomarker of the central physiologic and behavioral effects of mild systemic inflammation. The widespread clinical availability of magnetic resonance imaging supports the viability of qMT imaging as a clinical biomarker in trials of immunotherapeutics, both to identify patients vulnerable to the effects of systemic inflammation and to monitor neurobiological responses.

Quantitative magnetization transfer imaging of rodent glioma using selective inversion recovery

Magnetization transfer (MT) provides an indirect means to detect noninvasively variations in macromolecular contents in biological tissues, but, so far, there have been only a few quantitative MT (qMT) studies reported in cancer, all of which used off-resonance pulsed saturation methods. This article describes the first implementation of a different qMT approach, selective inversion recovery (SIR), for the characterization of tumor in vivo using a rodent glioma model. The SIR method is an on-resonance method capable of fitting qMT parameters and T1 relaxation time simultaneously without mapping B0 and B1 , which is very suitable for high-field qMT measurements because of the lower saturation absorption rate. The results show that the average pool size ratio (PSR, the macromolecular pool versus the free water pool) in rat 9 L glioma (5.7%) is significantly lower than that in normal rat gray matter (9.2%) and white matter (17.4%), which suggests that PSR is potentially a sensitive imaging biomarker for the assessment of brain tumor. Despite being less robust, the estimated MT exchange rates also show clear differences from normal tissues (19.7 Hz for tumors versus 14.8 and 10.2 Hz for gray and white mater, respectively). In addition, the influence of confounding effects, e.g. B1 inhomogeneity, on qMT parameter estimates is investigated with numerical simulations. These findings not only help to better understand the changes in the macromolecular contents of tumors, but are also important for the interpretation of other imaging contrasts, such as chemical exchange saturation transfer of tumors.

On the accuracy of T1 mapping: searching for common ground

PURPOSE

There are many T1 mapping methods available, each of them validated in phantoms and reporting excellent agreement with literature. However, values in literature vary greatly, with T1 in white matter ranging from 690 to 1100 ms at 3 Tesla. This brings into question the accuracy of one of the most fundamental measurements in quantitative MRI. Our goal was to explain these variations and look into ways of mitigating them.

THEORY AND METHODS

We evaluated the three most common T1 mapping methods (inversion recovery, Look-Locker, and variable flip angle) through Bloch simulations, a white matter phantom and the brains of 10 healthy subjects (single-slice). We pooled the T1 histograms of the subjects to determine whether there is a sequence-dependent bias and whether it is reproducible across subjects.

RESULTS

We found good agreement between the three methods in phantoms, but poor agreement in vivo, with the white matter T1 histogram peak in healthy subjects varying by more than 30% depending on the method used. We also found that the pooled brain histograms displayed three distinct white matter peaks, with Look-Locker consistently underestimating, and variable flip angle overestimating the inversion recovery T1 values. The Bloch simulations indicated that incomplete spoiling and inaccurate B1 mapping could account for the observed differences.

CONCLUSION

We conclude that the three most common T1 mapping protocols produce stable T1 values in phantoms, but not in vivo. To improve the accuracy of T1 mapping, we recommend that sites perform in vivo validation of their T1 mapping method against the inversion recovery reference method, as the first step toward developing a robust calibration scheme.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Clinically feasible MTR is sensitive to cortical demyelination in MS

OBJECTIVE

Presently there is no clinically feasible imaging modality that can effectively detect cortical demyelination in patients with multiple sclerosis (MS). The objective of this study is to determine if clinically feasible magnetization transfer ratio (MTR) imaging is sensitive to cortical demyelination in MS.

METHODS

MRI were acquired in situ on 7 recently deceased patients with MS using clinically feasible sequences at 3 T, including relatively high-resolution T1-weighted and proton density-weighted images with/without a magnetization transfer pulse for calculation of MTR. The brains were rapidly removed and placed in fixative. Multiple cortical regions from each brain were immunostained for myelin proteolipid protein and classified as mostly myelinated (MM(ctx)), mostly demyelinated (MD(ctx)), or intermediately demyelinated (ID(ctx)). MRIs were registered with the cortical sections so that the cortex corresponding to each cortical section could be identified, along with adjacent subcortical white matter (WM). Mean cortical MTR normalized to mean WM MTR was calculated for each cortical region. Linear mixed-effects models were used to test if mean normalized cortical MTR was significantly lower in demyelinated cortex.

RESULTS

We found that mean normalized cortical MTR was significantly lower in cortical tissue with any demyelination (ID(ctx) or MD(ctx)) compared to MM(ctx) (demyelinated cortex: least-squares mean [LSM] = 0.797, SE = 0.007; MM(ctx): LSM = 0.837, SE = 0.006; p = 0.01, n = 89).

CONCLUSIONS

This result demonstrates that clinically feasible MTR imaging is sensitive to cortical demyelination and suggests that MTR will be a useful tool to help detect MS cortical lesions in living patients with MS.

Multicentre imaging measurements for oncology and in the brain

Multicentre imaging studies of brain tumours (and other tumour and brain studies) can enable a large group of patients to be studied, yet they present challenging technical problems. Differences between centres can be characterised, understood and minimised by use of phantoms (test objects) and normal control subjects. Normal white matter forms an excellent standard for some MRI parameters (e.g. diffusion or magnetisation transfer) because the normal biological range is low (<2-3%) and the measurements will reflect this, provided the acquisition sequence is controlled. MR phantoms have benefits and they are necessary for some parameters (e.g. tumour volume). Techniques for temperature monitoring and control are given. In a multicentre study or treatment trial, between-centre variation should be minimised. In a cross-sectional study, all groups should be represented at each centre and the effect of centre added as a covariate in the statistical analysis. In a serial study of disease progression or treatment effect, individual patients should receive all of their scans at the same centre; the power is then limited by the within-subject reproducibility. Sources of variation that are generic to any imaging method and analysis parameters include MR sequence mismatch, B(1) errors, CT effective tube potential, region of interest generation and segmentation procedure. Specific tissue parameters are analysed in detail to identify the major sources of variation and the most appropriate phantoms or normal studies. These include dynamic contrast-enhanced and dynamic susceptibility contrast gadolinium imaging, T(1), diffusion, magnetisation transfer, spectroscopy, tumour volume, arterial spin labelling and CT perfusion.

Methodology of diffusion-weighted, diffusion tensor and magnetisation transfer imaging

MRI offers a number of opportunities to examine characteristics of tissue well below the spatial resolution of the imaging technique. The best known of these is diffusion imaging, which allows the production of images whose contrast reflects the ability of water molecules to move through the extravascular extracellular space. Less well-known, but increasingly important, is magnetisation transfer imaging, which produces contrast based on the ability of protons to move between the free water pool and local macromolecules. Both of these techniques offer unique information about the microscopic and molecular structure of tumour tissue. This article will briefly review the underlying theory and technical aspects associated with these imaging techniques.

Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging

Many therapeutic approaches to cancer affect the tumour vasculature, either indirectly or as a direct target. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important means of investigating this action, both pre-clinically and in early stage clinical trials. For such trials, it is essential that the measurement process (i.e. image acquisition and analysis) can be performed effectively and with consistency among contributing centres. As the technique continues to develop in order to provide potential improvements in sensitivity and physiological relevance, there is considerable scope for between-centre variation in techniques. A workshop was convened by the Imaging Committee of the Experimental Cancer Medicine Centres (ECMC) to review the current status of DCE-MRI and to provide recommendations on how the technique can best be used for early stage trials. This review and the consequent recommendations are summarised here. Key Points • Tumour vascular function is key to tumour development and treatment • Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumour vascular function • Thus DCE-MRI with pharmacokinetic models can assess novel treatments • Many recent developments are advancing the accuracy of and information from DCE-MRI • Establishing common methodology across multiple centres is challenging and requires accepted guidelines.

Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains

The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains.

Comprehensive brain analysis with automated high-resolution magnetization transfer measurements

PURPOSE

To enhance the reliability and spatial resolution of magnetization transfer ratio (MTR) measurements for interrogation of subcortical brain regions with an automated volume of interest (VOI) approach.

MATERIALS AND METHODS

A 3D magnetization transfer (MT) sequence was acquired using a scan-rescan imaging protocol in nine healthy volunteers. VOI definition masks for the MTR measurements were generated using FreeSurfer and compared to a manual region of interest (ROI) approach. (The longitudinal stability of MTR was monitored using agar gel phantom over a 5-month period.) Intraclass correlation coefficients (ICCs), coefficients of variation (CVs), and instrumental standard deviation (ISD) were determined.

RESULTS

CVs ranged from 1.29%-2.64% (automated) vs. 1.30%-3.40% (manual). ISDs ranged from 0.62-1.10 pu (automated) vs. 0.68-1.67 pu (manual). The SD of the running difference was 1.70% for the phantom scans. The Bland-Altman method indicated interchangeability of the automated VOI and manual ROI measurements.

CONCLUSION

The automated VOI approach for MTR measurement yielded higher ICCs, lower CVs, and lower ISDs compared to the manual method, supporting the utility of this strategy. These results demonstrate the feasibility of obtaining reliable MTR measurements in hippocampus and other critical subcortical regions.

Quantitative magnetization transfer provides information complementary to grey matter atrophy in Alzheimer's disease brains

Preliminary studies, based on a region-of-interest approach, suggest that quantitative magnetization transfer (qMT), an extension of magnetization transfer imaging, provides complementary information to conventional magnetic resonance imaging (MRI) in the characterisation of Alzheimer's disease (AD). The aim of this study was to extend these findings to the whole brain, using a voxel-wise approach. We recruited 19AD patients and 11 healthy subjects (HS). All subjects had an MRI acquisition at 3.0T including a T(1)-weighted volume, 12 MT-weighted volumes for qMT, and data for computing T(1) and B(1) maps. The T(1)-weighted volumes were processed to yield grey matter (GM) volumetric maps, while the other sequences were used to compute qMT parametric maps of the whole brain. qMT maps were warped to standard space and smoothed, and subsequently compared between groups. Of all the qMT parameters considered, only the forward exchange rate, RM(0)(B), showed significant group differences. These images were therefore retained for the multimodal statistical analysis, designed to locate brain regions of RM(0)(B) differences between AD and HS groups, adjusting for local GM atrophy. Widespread areas of reduced RM(0)(B) were found in AD patients, mainly located in the hippocampus, in the temporal lobe, in the posterior cingulate and in the parietal cortex. These results indicate that, among qMT parameters, RM(0)(B) is the most sensitive to AD pathology. This quantity is altered in the hippocampus of patients with AD (as found by previous works) but also in other brain areas, that PET studies have highlighted as involved with both, reduced glucose metabolism and amyloid β deposition. RM(0)(B) might reflect, through the measurement of the efficiency of MT exchange, some information with a specific pathological counterpart. Given previous evidence of a strict relationship between RM(0)(B) and intracellular pH, an intriguing speculation is that our findings might reflect metabolic changes related to mitochondrial dysfunction, which has been proposed as a contributor to neurodegeneration in AD.

A robust methodology for in vivo T1 mapping

In this article, a robust methodology for in vivo T(1) mapping is presented. The approach combines a gold standard scanning procedure with a novel fitting procedure. Fitting complex data to a five-parameter model ensures accuracy and precision of the T(1) estimation. A reduced-dimension nonlinear least squares method is proposed. This method turns the complicated multi-parameter minimization into a straightforward one-dimensional search. As the range of possible T(1) values is known, a global grid search can be used, ensuring that a global optimal solution is found. When only magnitude data are available, the algorithm is adapted to concurrently restore polarity. The performance of the new algorithm is demonstrated in simulations and phantom experiments. The new algorithm is as accurate and precise as the conventionally used Levenberg-Marquardt algorithm but much faster. This gain in speed makes the use of the five-parameter model viable. In addition, the new algorithm does not require initialization of the search parameters. Finally, the methodology is applied in vivo to conventional brain imaging and to skin imaging. T(1) values are estimated for white matter and gray matter at 1.5 T and for dermis, hypodermis, and muscle at 1.5 T, 3 T, and 7 T.

Reproducibility of quantitative magnetization-transfer imaging parameters from repeated measurements

Quantitative magnetization-transfer imaging methods provide in vivo estimates of parameters of the two-pool model for magnetization-transfer in tissue. The goal of this study was to evaluate the reproducibility of quantitative magnetization-transfer imaging parameter estimates in healthy subjects. Magnetization-transfer-weighted and T(1) relaxometry data were acquired in five healthy subjects at multiple time points, and the variability of the resulting fitted magnetization-transfer parameters was evaluated. The impact of subsampling the magnetization-transfer data and correcting field inhomogeneities was also evaluated. The key parameters measured in this study had an average variability, across time points, of 4.7% for the relative size of the restricted pool (F), 7.3% for the forward exchange constant (k(f)), 1.9% for the free pool spin-lattice relaxation constant (R(1f)), 4.5% for the T(2) of the free pool (T(2f)), and 2.3% for the T(2) of the restricted pool (T(2r)). Our findings show that serial quantitative magnetization-transfer imaging experiments can be performed reliably, with good reproducibility of the model parameter estimates, and demonstrate the reproducibility of acquisition schemes with fewer magnetization-transfer contrasts. This establishes the feasibility of this technique for monitoring patients affected by degenerative white matter diseases while providing critical data to estimate the statistical power of such studies.

Lesional magnetization transfer ratio: a feasible outcome for remyelinating treatment trials in multiple sclerosis

Magnetization transfer ratio (MTR) is a sensitive parameter to quantify the integrity of myelinated white matter in patients with multiple sclerosis. Lesional MTR decreases in the acute phase due to demyelination, and subsequently shows recovery depending on the degree of remyelination in the absence of axonal loss. Recovery of average lesion MTR therefore might prove a viable outcome measure to assess the effect of remyelinating agents. Our objective was to determine the required sample size for phase II multicentre clinical trials using the recovery of average lesion MTR as primary outcome measure. With 7-monthly MRI scans, the MTR evolution of 349 new enhancing lesions before and after enhancement was assessed in 32 MS patients from 5 centres. Multilevel models were fitted to the data yielding estimates for the variance components, which were applied in power calculations. Sample sizes were determined for placebo-controlled, multicentre trials using lesional MTR recovery post-enhancement as primary outcome measure. Average lesion MTR decreased slightly in the build-up to enhancement, decreased dramatically during enhancement and showed recovery in the period after cessation. The power calculations showed that for a power of 80%, approximately 136 patients per trial (mean number of 6 lesions per patient) are required to detect a 30% increase in lesional MTR post-enhancement compared with placebo, whereas 48 subjects are required to detect a 50% increase in lesional MTR compared with placebo. Recovery of lesion MTR is a feasible outcome measure for future multicentre clinical trials measuring the effect of remyelinating agents.

Statistical evaluations of the reproducibility and reliability of 3-tesla high resolution magnetization transfer brain images: a pilot study on healthy subjects

Magnetization transfer imaging (MT) may have considerable promise for early detection and monitoring of subtle brain changes before they are apparent on conventional magnetic resonance images. At 3 Tesla (T), MT affords higher resolution and increased tissue contrast associated with macromolecules. The reliability and reproducibility of a new high-resolution MT strategy were assessed in brain images acquired from 9 healthy subjects. Repeated measures were taken for 12 brain regions of interest (ROIs): genu, splenium, and the left and right hemispheres of the hippocampus, caudate, putamen, thalamus, and cerebral white matter. Spearman's correlation coefficient, coefficient of variation, and intraclass correlation coefficient (ICC) were computed. Multivariate mixed-effects regression models were used to fit the mean ROI values and to test the significance of the effects due to region, subject, observer, time, and manual repetition. A sensitivity analysis of various model specifications and the corresponding ICCs was conducted. Our statistical methods may be generalized to many similar evaluative studies of the reliability and reproducibility of various imaging modalities.

Investigation of quantitative magnetisation transfer parameters of lesions and normal appearing white matter in multiple sclerosis

The aim of this study was to use quantitative magnetisation transfer (MT) imaging to assess the different pathological substrates of tissue damage in multiple sclerosis (MS) and examine whether the MT parameters may be used to explain the disability in relapsing remitting (RR) MS. Thirteen patients with RRMS and 14 healthy controls were prescribed conventional MRI and quantitative MT imaging at 3.0 T. A two-pool model of MT (where A refers to the free pool and B to the macromolecular pool) was fitted to the data yielding a longitudinal relaxation rate R(A), a relative size F of macromolecular pool, transverse relaxation times T(2) (A) and T(2) (B) for the two pools and a forward exchange rate RM(0) (B). The MT ratio (MTR) was also computed. The mean MT parameters of the normal appearing white matter (NAWM) and of lesions in patients, and of white matter in controls were estimated. MT parameters were significantly different between lesions and NAWM in patients, and between the NAWM and the white matter of controls (with the exception of T(2) (B) and the MTR). Two models were investigated using ordered logistic regression, with the expanded disability status scale (EDSS) as the dependent variable. In the first one, mean NAWM MT parameters and lesion load were entered as explanatory variables; in the second one, mean MT variables within lesions and lesion load were entered as explanatory variables. Unexpectedly, T(2) (B) was the parameter most significantly associated with EDSS in NAWM. This parameter might represent a weighted average of the relaxation times of spins with different molecular environments, and therefore its variation could indicate a change in the balance between subpopulations of macromolecular spins. Conversely, in lesions, RM(0) (B), T(2) (B), F, R(A), and lesion load significantly predicted disability only when combined together. This might reflect the complex interaction between demyelination, remyelination, gliosis, inflammation and axonal loss taking place within lesions.

Characterization of white matter damage in animal models of multiple sclerosis by magnetization transfer ratio and quantitative mapping of the apparent bound proton fraction f*

Quantitative magnetization transfer magnetic resonance imaging (qMT-MRI) can be used to improve detection of white matter tissue damage in multiple sclerosis (MS) and animal models thereof. To study the correlation between MT parameters and tissue damage, the magnetization transfer ratio (MTR), the parameter f* (closely related to the bound proton fraction) and the bound proton transverse relaxation time T2B of lesions in a model of focal experimental autoimmune encephalomyelitis (EAE) were measured on a 7T animal scanner and data were compared with histological markers indicative for demyelination, axonal density, and tissue damage. A clear spatial correspondence was observed between reduced values of MTR and demyelination in this animal model. We observed two different levels of MTR and f* reduction for these lesions. One was characterized by a pronounced demyelination and the other corresponded to a more severe loss of the cellular matrix. Changes in f* were generally more pronounced than those of MTR in areas of demyelination. Moreover, a reduction of f* was already observed for tissue where MTR was virtually normal. No changes in T2B were observed for the lesions. We conclude that MTR and qMT mapping are efficient and reliable readouts for studying demyelination in animal models of MS, and that the analysis of regional f* might be even superior to the analysis of MTR values. Therefore, quantitative mapping of f* from human brains might also improve the detection of white matter damage in MS.

Quantifying subclinical central nervous lesions in primary antiphospholipid syndrome: the role of magnetization transfer imaging

PURPOSE

To define the role of magnetization transfer imaging (MTI) in detecting subclinical central nervous system (CNS) lesions in primary antiphospholipid syndrome (PAPS).

MATERIALS AND METHODS

Ten non-CNS PAPS patients were compared to 10 CNS PAPS patients and 10 age- and sex-matched controls. All PAPS patients met Sapporo criteria. All subjects underwent conventional MRI and complementary MTI analysis to compose histograms. CNS viability was determined according to the magnetization transfer ratio (MTR) by mean pixel intensity (MPI) and the mean peak height (MPH). Volumetric cerebral measurements were assessed by brain parenchyma factor (BPF) and total/cerebral volume.

RESULTS

MTR histograms analysis revealed that MPI was significantly different among groups (P < 0.0001). Non-CNS PAPS had a higher MPI than CNS PAPS (30.5 +/- 1.01 vs. 25.1 +/- 3.17 percent unit (pu); P < 0.05) although lower than controls (30.5 +/- 1.01 vs. 31.20 +/- 0.50 pu; P < 0.05). MPH in non-CNS PAPS (5.57 +/- 0.20% (1/pu)) was similar to controls (5.63 +/- 0.20% (1/pu), P > 0.05) and higher than CNS PAPS (4.71 +/- 0.30% (1/pu), P < 0.05). A higher peak location (PL) was also observed in the CNS PAPS group in comparison with the other groups (P < 0.0001). In addition, a lower BPF was found in non-CNS PAPS compared to controls (0.80 +/- 0.03 vs. 0.84 +/- 0.02 units; P < 0.05) but similar to CNS PAPS (0.80 +/- 0.03 vs. 0.79 +/- 0.05 units; P > 0.05).

CONCLUSION

Our findings suggest that non-CNS PAPS patients have subclinical cerebral damage. The long-termclinical relevance of MTI analysis in these patients needs to be defined by prospective studies.

Quantitative magnetic resonance of postmortem multiple sclerosis brain before and after fixation

Unfixed and fixed postmortem multiple sclerosis (MS) brain is being used to probe pathology underlying quantitative MR (qMR) changes. Effects of fixation on qMR indices in MS brain are unknown. In 15 postmortem MS brain slices T(1), T(2), MT ratio (MTR), macromolecular proton fraction (f(B)), fractional anisotropy (FA), and mean, axial, and radial diffusivity (MD, D(ax), and D(rad)) were assessed in white matter (WM) lesions (WML) and normal appearing WM (NAWM) before and after fixation in formalin. Myelin content, axonal count, and gliosis were quantified histologically. Student's t-test and regression were used for analysis. T(1), T(2), MTR, and f(B) obtained in unfixed MS brain were similar to published values obtained in patients with MS in vivo. Following fixation T(1), T(2) (NAWM, WML) and MTR (NAWM) dropped, whereas f(B) (NAWM, WML) increased. Compared to published in vivo data all diffusivity measures were lower in unfixed MS brain, and dropped further following fixation (except for FA). MTR was the best predictor of T(myelin) (inversely related to myelin) in unfixed MS brain (r = -0.83; P < 0.01) whereas postfixation T(2) (r = 0.92; P < 0.01), T(1) (r = 0.89; P < 0.01), and f(B) (r = -0.86; P < 0.01) were superior. All diffusivity measures (except for D(ax) in unfixed tissue) were predictors of myelin content.

Standardized structural magnetic resonance imaging in multicentre studies using quantitative T1 and T2 imaging at 1.5 T

The ability to acquire MRI data with consistent tissue contrast at multiple time points, and/or across different imaging centres has become increasingly important as the number of large longitudinal and multicentre studies has grown. Here, the use of quantitative magnetic resonance relaxation times measurement, or, voxel-wise determination of the intrinsic longitudinal and transverse relaxation times, T1 and T2 respectively, for standardizing the structural imaging component of such studies is reported. To demonstrate the ability to standardize across multiple time-points and imaging centres, T1 and T2 maps of seven healthy volunteers were acquired using the rapid DESPOT1 and DESPOT2 (driven equilibrium single pulse observation of T1 and T2) mapping techniques at three centres across the United Kingdom (each centre utilizing scanners from competing manufacturers and/or with varying gradient performance). An average coefficient of variation of the estimates of T1 and T2 was found to be approximately 6.5% and 8%, respectively, across the three centres and comparable to that achieved between repeated imaging sessions performed at the same centre. With a total combined imaging time of less than 12 min for whole-brain approximately 1.2 mm isotropic voxel T1 and T2 maps, quantitative voxel-wise T1 and T2 mapping represents an attractive and easy-to-implement approach for signal intensity standardization and normalization. Further, as T1 and T2 are related to tissue microstructure and biochemistry, quantitative images provide additional diagnostic information that can be compared between patient and control populations, for example through voxel-based analysis techniques.