RESUMEN: A flexible class of multi-parameter qMRI protocols

Normative values of the topological metrics of the structural connectome: A multi-site reproducibility study across the Italian Neuroscience network

PURPOSE

The use of topological metrics to derive quantitative descriptors from structural connectomes is receiving increasing attention but deserves specific studies to investigate their reproducibility and variability in the clinical context. This work exploits the harmonization of diffusion-weighted acquisition for neuroimaging data performed by the Italian Neuroscience and Neurorehabilitation Network initiative to obtain normative values of topological metrics and to investigate their reproducibility and variability across centers.

METHODS

Different topological metrics, at global and local level, were calculated on multishell diffusion-weighted data acquired at high-field (e.g. 3 T) Magnetic Resonance Imaging scanners in 13 different centers, following the harmonization of the acquisition protocol, on young and healthy adults. A "traveling brains" dataset acquired on a subgroup of subjects at 3 different centers was also analyzed as reference data. All data were processed following a common processing pipeline that includes data pre-processing, tractography, generation of structural connectomes and calculation of graph-based metrics. The results were evaluated both with statistical analysis of variability and consistency among sites with the traveling brains range. In addition, inter-site reproducibility was assessed in terms of intra-class correlation variability.

RESULTS

The results show an inter-center and inter-subject variability of <10%, except for "clustering coefficient" (variability of 30%). Statistical analysis identifies significant differences among sites, as expected given the wide range of scanners' hardware.

CONCLUSIONS

The results show low variability of connectivity topological metrics across sites running a harmonised protocol.

Technical note: MAMBA-Multi-pAradigM voxel-Based Analysis: A computational cookbot

BACKGROUND

Voxel-Based (VB) analysis embraces a multifaceted ensemble of sophisticated techniques, lying at the boundary between image processing and statistical modeling, that allow for a frequentist inference of pathophysiological properties anchored to an anatomical reference. VB methods has been widely adopted in neuroimaging studies and, more recently, they are gaining momentum in radiation oncology research. However, the price for the power of VB analysis is the complexity of the underlying mathematics and algorithms.

PURPOSE

In this paper, we present the Multi-pAradigM voxel-Based Analysis (MAMBA) toolbox, which is intended for a flexible application of VB analysis in a wide variety of scenarios in medical imaging and radiation oncology.

METHODS

The MAMBA toolbox is implemented in Matlab. It provides open-source functions to compute VB statistical models of the input data, according to a great variety of regression schemes, and to derive VB maps of the observed significance level, performing a non-parametric permutation inference. The toolbox allows for including VB and global outcomes, as well as an arbitrary amount of VB and global Explanatory Variables (EVs). In addition, the Matlab Parallel Computing Toolbox is exploited to take advantage of the perfect parallelizability of most workloads.

RESULTS

The use of MAMBA was demonstrated by means of several realistic examples on a synthetic dataset mimicking a radiation oncology scenario.

CONCLUSION

MAMBA is an open-source toolbox, freely available for academic and non-commercial purposes. It is designed to make state-of-the-art VB analysis accessible to research scientists without the programming resources needed to build from scratch their own software solutions. At the same time, the source code is handed out for more experienced users to complement their own tools, also customizing user-defined models. MAMBA guarantees high generality and flexibility in the design of the statistical models, significantly expanding on the features of available free tools for VB analysis. The presented toolbox aims at increasing the reach of VB studies as well as the sharing of research results.

Clinical correlates of R1 relaxometry and magnetic susceptibility changes in multiple sclerosis: a multi-parameter quantitative MRI study of brain iron and myelin

OBJECTIVES

The clinical impact of brain microstructural abnormalities in multiple sclerosis (MS) remains elusive. We aimed to characterize the topography of longitudinal relaxation rate (R1) and quantitative susceptibility (χ) changes, as indices of iron and myelin, together with brain atrophy, and to clarify their contribution to cognitive and motor disability in MS.

METHODS

In this cross-sectional study, voxel-based morphometry, and voxel-based quantification analyses of R1 and χ maps were conducted in gray matter (GM) and white matter (WM) of 117 MS patients and 53 healthy controls. Voxel-wise between-group differences were assessed with nonparametric permutation tests, while correlations between MRI metrics and clinical variables (global disability, cognitive and motor performance) were assessed both globally and voxel-wise within clusters emerging from the between-group comparisons.

RESULTS

MS patients showed widespread R1 decrease associated with more limited modifications of χ, with atrophy mainly involving deep GM, posterior and infratentorial regions (p < 0.02). While R1 and χ showed a parallel reduction in several WM tracts (p < 0.001), reduced GM R1 values (p < 0.001) were associated with decreased thalamic χ (p < 0.001) and small clusters of increased χ in the caudate nucleus and prefrontal cortex (p < 0.02). In addition to the atrophy, χ values in the cingulum and corona radiata correlated with global disability and motor performance, while focal demyelination correlated with cognitive performance (p < 0.04).

CONCLUSIONS

We confirmed the presence of widespread R1 changes, involving both GM and WM, and atrophy in MS, with less extensive modifications of tissue χ. While atrophy and χ changes are related to global and motor disability, R1 changes are meaningful correlates of cognition.

KEY POINTS

• Compared to healthy controls, multiple sclerosis patients showed R1 and χ changes suggestive of iron increase within the basal ganglia and reduced iron and myelin content within (subnuclei of) the thalamus. • Thalamic volume and χ changes significantly predicted clinical disability, as well as pulvinar R1 and χ changes, independently from atrophy. • Atrophy-independent R1 and χ changes, suggestive of thalamic iron and myelin depletion, may represent a sensitive marker of subclinical inflammation.

Quantitative MRI in Multiple Sclerosis: From Theory to Application

Quantitative MR imaging techniques allow evaluating different aspects of brain microstructure, providing meaningful information about the pathophysiology of damage in CNS disorders. In the study of patients with MS, quantitative MR imaging techniques represent an invaluable tool for studying changes in myelin and iron content occurring in the context of inflammatory and neurodegenerative processes. In the first section of this review, we summarize the physics behind quantitative MR imaging, here defined as relaxometry and quantitative susceptibility mapping, and describe the neurobiological correlates of quantitative MR imaging findings. In the second section, we focus on quantitative MR imaging application in MS, reporting the main findings in both the gray and white matter compartments, separately addressing macroscopically damaged and normal-appearing parenchyma.

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).

Precision Medicine in Radiomics and Radiogenomics

Precision medicine is an innovative and emerging approach to treatment that accounts for individual variability in genetic and environmental factors to identify and utilize the specific biomedical profile of a patient's disease [...].

New developments in MRI: System characterization, technical advances and radiotherapy applications

A Special Issue of Physica Medica - European Journal of Medical Physics, focused on some important points of contact between the world of magnetic resonance and that of medical physics, was published during 2021. This Editorial describes and comments on the content of this Focus Issue, which contains articles from leading groups invited by the Guest Editors.