Abstract

Magnetic Resonance Imaging (MRI) has become part of the clinical routine for diagnosing neurodegenerative disorders. Since acquisitions are performed at multiple centers using multiple imaging systems, detailed analysis of brain volumetry differences between MRI systems and scan-rescan acquisitions can provide valuable information to correct for different MRI scanner effects in multi-center longitudinal studies. To this end, five healthy controls and five patients belonging to various stages of the AD continuum underwent brain MRI acquisitions on three different MRI systems (Philips Achieva dStream 1.5T, Philips Ingenia 3T, and GE Discovery MR750w 3T) with harmonized scan parameters. Each participant underwent two subsequent MRI scans per imaging system, repeated on three different MRI systems within 2 h. Brain volumes computed by icobrain dm (v5.0) were analyzed using absolute and percentual volume differences, Dice similarity (DSC) and intraclass correlation coefficients, and coefficients of variation (CV). Harmonized scans obtained with different scanners of the same manufacturer had a measurement error closer to the intra-scanner performance. The gap between intra- and inter-scanner comparisons grew when comparing scans from different manufacturers. This was observed at image level (image contrast, similarity, and geometry) and translated into a higher variability of automated brain volumetry. Mixed effects modeling revealed a significant effect of scanner type on some brain volumes, and of the scanner combination on DSC. The study concluded a good intra- and inter-scanner reproducibility, as illustrated by an average intra-scanner (inter-scanner) CV below 2% (5%) and an excellent overlap of brain structure segmentation (mean DSC > 0.88).

Highlights

  • MATERIALS AND METHODSThe elderly population is drastically increasing and so does the prevalence of dementia

  • There is a very high similarity between different scan-rescan T1w acquired in each scanner, as demonstrated by a reliable affine similarity index, low white matter (WM)/gray matter (GM) contrast difference, and a maximum scaling factor of 1 for all comparisons between images of the same scanner

  • As the potential added diagnostic value of artificial intelligence (AI)-based automated volumetry on brain Magnetic Resonance Imaging (MRI) scans might at least in part be neutralized by intra- and inter-scanner variability, a thorough evaluation of the measurement error and variability in clinical routine circumstances is crucial

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Summary

Introduction

MATERIALS AND METHODSThe elderly population is drastically increasing and so does the prevalence of dementia. Magnetic resonance imaging (MRI) has become an important tool in the diagnostic work-up for patients with Alzheimer’s disease (AD), where MRI scans are essential for detecting brain atrophy and atrophy patterns for differential diagnosis of dementia subtypes (Frisoni et al, 2010) In this context, the introduction of visual rating scales to assess hyperintensities, global cortical atrophy, posterior cortical atrophy, and medial temporal lobe atrophy on brain MRI scans has helped standardizing radiological reading in AD and the differential diagnosis in dementia (Albert et al, 2011; Jack et al, 2011; Dubois et al, 2014; Niemantsverdriet et al, 2018; Struyfs et al, 2020). The purpose of this study is to determine the extent of intra and inter-scanner variability with harmonized acquisition parameters and its implication in routine clinical practice

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