An optimized framework for quantitative magnetization transfer imaging of the cervical spinal cord in vivo

What contributes to disability in progressive MS? A brain and cervical cord-matched quantitative MRI study

BACKGROUND

We assessed the ability of a brain-and-cord-matched quantitative magnetic resonance imaging (qMRI) protocol to differentiate patients with progressive multiple sclerosis (PMS) from controls, in terms of normal-appearing (NA) tissue abnormalities, and explain disability.

METHODS

A total of 27 patients and 16 controls were assessed on the Expanded Disability Status Scale (EDSS), 25-foot timed walk (TWT), 9-hole peg (9HPT) and symbol digit modalities (SDMT) tests. All underwent 3T brain and (C2-C3) cord structural imaging and qMRI (relaxometry, quantitative magnetisation transfer, multi-shell diffusion-weighted imaging), using a fast brain-and-cord-matched protocol with brain-and-cord-unified imaging readouts. Lesion and NA-tissue volumes and qMRI metrics reflecting demyelination and axonal loss were obtained. Random forest analyses identified the most relevant volumetric/qMRI measures to clinical outcomes. Confounder-adjusted linear regression estimated the actual MRI-clinical associations.

RESULTS

Several qMRI/volumetric differences between patients and controls were observed (p < 0.01). Higher NA-deep grey matter quantitative-T1 (EDSS: beta = 7.96, p = 0.006; 9HPT: beta = -0.09, p = 0.004), higher NA-white matter orientation dispersion index (TWT: beta = -3.21, p = 0.005; SDMT: beta = -847.10, p < 0.001), lower whole-cord bound pool fraction (9HPT: beta = 0.79, p = 0.001) and higher NA-cortical grey matter quantitative-T1 (SDMT = -94.31, p < 0.001) emerged as particularly relevant predictors of greater disability.

CONCLUSION

Fast brain-and-cord-matched qMRI protocols are feasible and identify demyelination - combined with other mechanisms - as key for disability accumulation in PMS.

Feasibility of in vivo multi-parametric quantitative magnetic resonance imaging of the healthy sciatic nerve with a unified signal readout protocol

Magnetic resonance neurography (MRN) has been used successfully over the years to investigate the peripheral nervous system (PNS) because it allows early detection and precise localisation of neural tissue damage. However, studies demonstrating the feasibility of combining MRN with multi-parametric quantitative magnetic resonance imaging (qMRI) methods, which provide more specific information related to nerve tissue composition and microstructural organisation, can be invaluable. The translation of emerging qMRI methods previously validated in the central nervous system to the PNS offers real potential to characterise in patients in vivo the underlying pathophysiological mechanisms involved in a plethora of conditions of the PNS. The aim of this study was to assess the feasibility of combining MRN with qMRI to measure diffusion, magnetisation transfer and relaxation properties of the healthy sciatic nerve in vivo using a unified signal readout protocol. The reproducibility of the multi-parametric qMRI protocol as well as normative qMRI measures in the healthy sciatic nerve are reported. The findings presented herein pave the way to the practical implementation of joint MRN-qMRI in future studies of pathological conditions affecting the PNS.

Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions

Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.

Diffusion Kurtosis Imaging of Neonatal Spinal Cord in Clinical Routine

Diffusion kurtosis imaging (DKI) has undisputed advantages over the more classical diffusion magnetic resonance imaging (dMRI) as witnessed by the fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized, in particular in spinal cord (SC) imaging, because of its inherently demanding technological requirements. Due to its extreme sensitivity to non-Gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, which are not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between the SC region and the brain above, managing to apply such a method to the neonatal cohort becomes of utmost importance. This study will (i) mention current methodological challenges associated with the application of advanced dMRI methods, like DKI, in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox for handling the DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present results of its application in a pilot clinical case study. With the proposed pipeline, we preliminarily show that DKI is more sensitive than DTI-related measures to alterations caused by brain white matter injuries in the underlying cervical SC.

Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications

Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.

Sample size estimation: Current practice and considerations for original investigations in MRI technical development studies

PURPOSE

To investigate and to provide guidance for sample size selection based on the current practice in MR technical development studies in which healthy volunteers are examined.

METHODS

All original articles published in Magnetic Resonance in Medicine between 2017 and 2019 were investigated and categorized according to technique, anatomical region, and magnetic field strength. The number of examined healthy volunteers (ie, the sample size) was collected and evaluated, whereas the number of patients was not considered. Papers solely measuring patients, animals, phantoms, specimens, or studies using existing data, for example, from an open databank, or consisting only of theoretical work or simulations were excluded.

RESULTS

The median sample size of the 882 included studies was 6. There were some peaks in the sample size distribution (eg, 1, 5, and 10). In 49.9%, 82.1%, and 95.6% of the studies, the sample size was smaller or equal to 5, 10, and 20, respectively.

CONCLUSION

We observed a large variance in sample sizes reflecting the variety of studies published in Magnetic Resonance in Medicine. Therefore, it can be concluded that it is current practice to balance the need for statistical power with the demand to minimize experiments involving healthy humans, often by choosing small sample sizes between 1 and 10. Naturally, this observation does not release an investigator from ensuring that sufficient data are acquired to reach statistical conclusions.

Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising

Multi-parametric quantitative MRI (qMRI) of the spinal cord is a promising non-invasive tool to probe early microstructural damage in neurological disorders. It is usually performed in vivo by combining acquisitions with multiple signal readouts, which exhibit different thermal noise levels, geometrical distortions and susceptibility to physiological noise. This ultimately hinders joint multi-contrast modelling and makes the geometric correspondence of parametric maps challenging. We propose an approach to overcome these limitations, by implementing state-of-the-art microstructural MRI of the spinal cord with a unified signal readout in vivo (i.e. with matched spatial encoding parameters across a range of imaging contrasts). We base our acquisition on single-shot echo planar imaging with reduced field-of-view, and obtain data from two different vendors (vendor 1: Philips Achieva; vendor 2: Siemens Prisma). Importantly, the unified acquisition allows us to compare signal and noise across contrasts, thus enabling overall quality enhancement via multi-contrast image denoising methods. As a proof-of-concept, here we provide a demonstration with one such method, known as Marchenko-Pastur (MP) Principal Component Analysis (PCA) denoising. MP-PCA is a singular value (SV) decomposition truncation approach that relies on redundant acquisitions, i.e. such that the number of measurements is large compared to the number of components that are maintained in the truncated SV decomposition. Here we used in vivo and synthetic data to test whether a unified readout enables more efficient MP-PCA denoising of less redundant acquisitions, since these can be denoised jointly with more redundant ones. We demonstrate that a unified readout provides robust multi-parametric maps, including diffusion and kurtosis tensors from diffusion MRI, myelin metrics from two-pool magnetisation transfer, and T1 and T2 from relaxometry. Moreover, we show that MP-PCA improves the quality of our multi-contrast acquisitions, since it reduces the coefficient of variation (i.e. variability) by up to 17% for mean kurtosis, 8% for bound pool fraction (myelin-sensitive), and 13% for T1, while enabling more efficient denoising of modalities limited in redundancy (e.g. relaxometry). In conclusion, multi-parametric spinal cord qMRI with unified readout is feasible and provides robust microstructural metrics with matched resolution and distortions, whose quality benefits from multi-contrast denoising methods such as MP-PCA.

Fast bound pool fraction mapping via steady-state magnetization transfer saturation using single-shot EPI

PURPOSE

To enable clinical applications of quantitative magnetization transfer (qMT) imaging by developing a fast method to map one of its fundamental model parameters, the bound pool fraction (BPF), in the human brain.

THEORY AND METHODS

The theory of steady-state MT in the fast-exchange approximation is used to provide measurements of BPF, and bound pool transverse relaxation time ( T 2 B ). A sequence that allows sampling of the signal during steady-state MT saturation is used to perform BPF mapping with a 10-min-long fully echo planar imaging-based MRI protocol, including inversion recovery T₁ mapping and B₁ error mapping. The approach is applied in 6 healthy subjects and 1 multiple sclerosis patient, and validated against a single-slice full qMT reference acquisition.

RESULTS

BPF measurements are in agreement with literature values using off-resonance MT, with average BPF of 0.114(0.100-0.128) in white matter and 0.068(0.054-0.085) in gray matter. Median voxel-wise percentage error compared with standard single slice qMT is 4.6%. Slope and intercept of linear regression between new and reference BPF are 0.83(0.81-0.85) and 0.013(0.11-0.16). Bland-Altman plot mean bias is 0.005. In the multiple sclerosis case, the BPF is sensitive to pathological changes in lesions.

CONCLUSION

The method developed provides accurate BPF estimates and enables shorter scan time compared with currently available approaches, demonstrating the potential of bringing myelin sensitive measurement closer to the clinic.

Sensitivity regularization of the Cramér-Rao lower bound to minimize B1 nonuniformity effects in quantitative magnetization transfer imaging

PURPOSE

To develop and validate a regularization approach of optimizing B₁ insensitivity of the quantitative magnetization transfer (qMT) pool-size ratio (F).

METHODS

An expression describing the impact of B₁ inaccuracies on qMT fitting parameters was derived using a sensitivity analysis. To simultaneously optimize for robustness against noise and B₁ inaccuracies, the optimization condition was defined as the Cramér-Rao lower bound (CRLB) regularized by the B₁ -sensitivity expression for the parameter of interest (F). The qMT protocols were iteratively optimized from an initial search space, with and without B₁ regularization. Three 10-point qMT protocols (Uniform, CRLB, CRLB+B₁ regularization) were compared using Monte Carlo simulations for a wide range of conditions (e.g., SNR, B₁ inaccuracies, tissues).

RESULTS

The B₁ -regularized CRLB optimization protocol resulted in the best robustness of F against B₁ errors, for a wide range of SNR and for both white matter and gray matter tissues. For SNR = 100, this protocol resulted in errors of less than 1% in mean F values for B₁ errors ranging between -10 and 20%, the range of B₁ values typically observed in vivo in the human head at field strengths of 3 T and less. Both CRLB-optimized protocols resulted in the lowest σ_F values for all SNRs and did not increase in the presence of B₁ inaccuracies.

CONCLUSION

This work demonstrates a regularized optimization approach for improving the robustness of auxiliary measurements (e.g., B₁ ) sensitivity of qMT parameters, particularly the pool-size ratio (F). Predicting substantially less B₁ sensitivity using protocols optimized with this method, B₁ mapping could even be omitted for qMT studies primarily interested in F.