Signal quality as Achilles\u2019 heel of graph theory in functional magnetic resonance imaging in multiple sclerosis

Johan Baijot,Stijn Denissen,Guy Nagels,Jeroen Van Schependom,Jeroen Gielen,Lars Costers,Miguel D’Haeseleer,Melissa Cambron,Marie B D’Hooghe,Anne-Marie Vanbinst,Johan De Mey

doi:10.1038/s41598-021-86792-0

Abstract

Graph-theoretical analysis is a novel tool to understand the organisation of the brain.We assessed whether altered graph theoretical parameters, as observed in multiple sclerosis (MS), reflect pathology-induced restructuring of the brain's functioning or result from a reduced signal quality in functional MRI (fMRI). In a cohort of 49 people with MS and a matched group of 25 healthy subjects (HS), we performed a cognitive evaluation and acquired fMRI. From the fMRI measurement, Pearson correlation-based networks were calculated and graph theoretical parameters reflecting global and local brain organisation were obtained. Additionally, we assessed metrics of scanning quality (signal to noise ratio (SNR)) and fMRI signal quality (temporal SNR and contrast to noise ratio (CNR)). In accordance with the literature, we found that the network parameters were altered in MS compared to HS. However, no significant link was found with cognition. Scanning quality (SNR) did not differ between both cohorts. In contrast, measures of fMRI signal quality were significantly different and explained the observed differences in GTA parameters. Our results suggest that differences in network parameters between MS and HS in fMRI do not reflect a functional reorganisation of the brain, but rather occur due to reduced fMRI signal quality.

Highlights

Graph-theoretical analysis is a novel tool to understand the organisation of the brain
Since multiple sclerosis (MS) causes damage to the central nervous system by inflammation, demyelination and neurodegeneration[4], it is hypothesized that damage and response to damage are reflected in the graphs that are derived from brain imaging
Since functional MRI (fMRI) relies on the blood oxygen level dependent (BOLD) signal to indirectly measure the brain activity, and because of the vulnerability of this method to pathology-induced pitfalls[8], this study aims to reconsider network alterations in MS in the light of fMRI quality issues

Summary

Introduction

Graph-theoretical analysis is a novel tool to understand the organisation of the brain. We assessed whether altered graph theoretical parameters, as observed in multiple sclerosis (MS), reflect pathology-induced restructuring of the brain’s functioning or result from a reduced signal quality in functional MRI (fMRI). Our results suggest that differences in network parameters between MS and HS in fMRI do not reflect a functional reorganisation of the brain, but rather occur due to reduced fMRI signal quality. Several studies[5,6,7] demonstrated a disruption of different network parameters derived from functional Magnetic Resonance Imaging (fMRI) in people with MS (PwMS) compared to healthy subject (HS). Network parameters were deviant when comparing cognitively impaired (CI) patients to cognitively preserved (CP) patients, and allowed to categorize MS patients in these g roups[3,5] These findings seemed to indicate a reduced global, but relatively spared local connectivity in MS. Since fMRI relies on the blood oxygen level dependent (BOLD) signal to indirectly measure the brain activity, and because of the vulnerability of this method to pathology-induced pitfalls[8], this study aims to reconsider network alterations in MS in the light of fMRI quality issues

Objectives

Methods

Conclusion