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Pierre Payoux

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

9 papers
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9

YNICL Journal 2025 Journal Article

Amyloid PET predicts atrophy in older adults without dementia: Results from the AMYPAD Prognostic & Natural History study

  • Leonard Pieperhoff
  • Luigi Lorenzini
  • Sophie Mastenbroek
  • Mario Tranfa
  • Mahnaz Shekari
  • Alle Meije Wink
  • Robin Wolz
  • Sylke Grootoonk

Highlights • Aβ-PET predicts atrophy in key brain regions in older adults without dementia.• Fusiform volumetric loss is linked to Aβ independent of CSF tau levels.• Temporal atrophy is stronger in women with higher Aβ burden.• APOE-ε4 carriers show larger Aβ-driven frontal & hippocampal atrophy.

YNIMG Journal 2025 Journal Article

The evolution of spatial patterns of brain activity during development and their role in the functional specialization of brain networks

  • Kuzma Strelnikov
  • Malik Berdier
  • Pierre Payoux
  • Pascal Barone
  • Chloe Farrer

The development of functionally specialized brain networks allows the emergence and improvement of cognitive abilities. This specialization emerges in part from the interactions between brain regions through changes in the temporal organization of their brain activity. In addition, it is now well assumed that the functioning of mature brain networks also depends on the spatial organization of their brain activity. However, how this spatial organization is formed during development remains unknown, nor do we know whether it contributes to the functional specialization of brain networks. This study attempts to answer these questions by examining the developmental changes in the spatial patterns of brain activity of the functional brain network involved in the theory of mind (capacity to understand others' mental states). Using fMRI dataset from the cross-sectional study of Richardson et al. (2018), our findings show for the first time that the brain regions of this network show increasingly similar spatial patterns of activity. Furthermore, this increasing spatial similarity is associated with improved children's performance in a theory-of-mind task. We propose that the increasing similarity between spatial brain activity patterns during development has important implications for understanding the functional specialization of brain networks.

YNICL Journal 2024 Journal Article

Translocator protein (TSPO) genotype does not change cerebrospinal fluid levels of glial activation, axonal and synaptic damage markers in early Alzheimer’s disease

  • Dominique Gouilly
  • Agathe Vrillon
  • Elsa Bertrand
  • Marie Goubeaud
  • Hélène Catala
  • Johanne Germain
  • Nadéra Ainaoui
  • Marie Rafiq

BACKGROUND: PET imaging of the translocator protein (TSPO) is used to assess in vivo brain inflammation. One of the main methodological issues with this method is the allelic dependence of the radiotracer affinity. In Alzheimer's disease (AD), previous studies have shown similar clinical and patho-biological profiles between TSPO genetic subgroups. However, there is no evidence regarding the effect of the TSPO genotype on cerebrospinal-fluid biomarkers of glial activation, and synaptic and axonal damage. METHOD: We performed a trans-sectional study in early AD to compare cerebrospinal-fluid levels of GFAP, YKL-40, sTREM2, IL-6, IL-10, NfL and neurogranin between TSPO genetic subgroups. RESULTS: We recruited 33 patients with early AD including 16 (48%) high affinity binders, 13 (39%) mixed affinity binders, and 4/33 (12%) low affinity binders. No difference was observed in terms of demographics, and cerebrospinal fluid levels of each biomarker for the different subgroups. CONCLUSION: TSPO genotype is not associated with a change in glial activation, synaptic and axonal damage in early AD. Further studies with larger numbers of participants will be needed to confirm that the inclusion of specific TSPO genetic subgroups does not introduce selection bias in studies and trials of AD that combine TSPO imaging with cerebrospinal fluid biomarkers.

YNICL Journal 2022 Journal Article

The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow

  • Luigi Lorenzini
  • Silvia Ingala
  • Alle Meije Wink
  • Joost P.A. Kuijer
  • Viktor Wottschel
  • Mathijs Dijsselhof
  • Carole H. Sudre
  • Sven Haller

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features - i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features - Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) - were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.

YNIMG Journal 2020 Journal Article

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors

  • Giulia Quattrini
  • Michela Pievani
  • Jorge Jovicich
  • Marco Aiello
  • Núria Bargalló
  • Frederik Barkhof
  • David Bartres-Faz
  • Alberto Beltramello

BACKGROUND: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. METHODS: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. RESULTS: (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε ​ ​0.80). CONCLUSION: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.

YNIMG Journal 2020 Journal Article

Modular slowing of resting-state dynamic functional connectivity as a marker of cognitive dysfunction induced by sleep deprivation

  • Diego Lombardo
  • Catherine Cassé-Perrot
  • Jean-Philippe Ranjeva
  • Arnaud Le Troter
  • Maxime Guye
  • Jonathan Wirsich
  • Pierre Payoux
  • David Bartrés-Faz

Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks –including Rapid Visual Processing (RVP, assessing sustained visual attention)– and dFC speed quantified at the level of functional sub-networks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module.

YNIMG Journal 2016 Journal Article

Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study

  • Jorge Jovicich
  • Ludovico Minati
  • Moira Marizzoni
  • Rocco Marchitelli
  • Roser Sala-Llonch
  • David Bartrés-Faz
  • Jennifer Arnold
  • Jens Benninghoff

To date, limited data are available regarding the inter-site consistency of test–retest reproducibility of functional connectivity measurements, in particular with regard to integrity of the Default Mode Network (DMN) in elderly participants. We implemented a harmonized resting-state fMRI protocol on 13 clinical scanners at 3. 0T using vendor-provided sequences. Each site scanned a group of 5 healthy elderly participants twice, at least a week apart. We evaluated inter-site differences and test–retest reproducibility of both temporal signal-to-noise ratio (tSNR) and functional connectivity measurements derived from: i) seed-based analysis (SBA) with seed in the posterior cingulate cortex (PCC), ii) group independent component analysis (ICA) separately for each site (site ICA), and iii) consortium ICA, with group ICA across the whole consortium. Despite protocol harmonization, significant and quantitatively important inter-site differences remained in the tSNR of resting-state fMRI data; these were plausibly driven by hardware and pulse sequence differences across scanners which could not be harmonized. Nevertheless, the tSNR test–retest reproducibility in the consortium was high (ICC=0. 81). The DMN was consistently extracted across all sites and analysis methods. While significant inter-site differences in connectivity scores were found, there were no differences in the associated test–retest error. Overall, ICA measurements were more reliable than PCC-SBA, with site ICA showing higher reproducibility than consortium ICA. Across the DMN nodes, the PCC yielded the most reliable measurements (≈4% test–retest error, ICC=0. 85), the medial frontal cortex the least reliable (≈12%, ICC=0. 82) and the lateral parietal cortices were in between (site ICA). Altogether these findings support usage of harmonized multisite studies of resting-state functional connectivity to characterize longitudinal effects in studies that assess disease progression and treatment response.

YNIMG Journal 2014 Journal Article

Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects

  • Jorge Jovicich
  • Moira Marizzoni
  • Beatriz Bosch
  • David Bartrés-Faz
  • Jennifer Arnold
  • Jens Benninghoff
  • Jens Wiltfang
  • Luca Roccatagliata

Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2×2×2mm3, b=700s/mm2, 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test–retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test–retest reproducibility. White matter b0 SNR reproducibility was on average 7±1% with no significant MRI site effects. Whole brain analysis resulted in no significant test–retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2–4% range for FA and AD and 2–6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.

YNIMG Journal 2013 Journal Article

Brain morphometry reproducibility in multi-center 3T MRI studies: A comparison of cross-sectional and longitudinal segmentations

  • Jorge Jovicich
  • Moira Marizzoni
  • Roser Sala-Llonch
  • Beatriz Bosch
  • David Bartrés-Faz
  • Jennifer Arnold
  • Jens Benninghoff
  • Jens Wiltfang

Large-scale longitudinal multi-site MRI brain morphometry studies are becoming increasingly crucial to characterize both normal and clinical population groups using fully automated segmentation tools. The test–retest reproducibility of morphometry data acquired across multiple scanning sessions, and for different MR vendors, is an important reliability indicator since it defines the sensitivity of a protocol to detect longitudinal effects in a consortium. There is very limited knowledge about how across-session reliability of morphometry estimates might be affected by different 3T MRI systems. Moreover, there is a need for optimal acquisition and analysis protocols in order to reduce sample sizes. A recent study has shown that the longitudinal FreeSurfer segmentation offers improved within session test–retest reproducibility relative to the cross-sectional segmentation at one 3T site using a nonstandard multi-echo MPRAGE sequence. In this study we implement a multi-site 3T MRI morphometry protocol based on vendor provided T1 structural sequences from different vendors (3D MPRAGE on Siemens and Philips, 3D IR-SPGR on GE) implemented in 8 sites located in 4 European countries. The protocols used mild acceleration factors (1. 5–2) when possible. We acquired across-session test–retest structural data of a group of healthy elderly subjects (5 subjects per site) and compared the across-session reproducibility of two full-brain automated segmentation methods based on either longitudinal or cross-sectional FreeSurfer processing. The segmentations include cortical thickness, intracranial, ventricle and subcortical volumes. Reproducibility is evaluated as absolute changes relative to the mean (%), Dice coefficient for volume overlap and intraclass correlation coefficients across two sessions. We found that this acquisition and analysis protocol gives comparable reproducibility results to previous studies that used longer acquisitions without acceleration. We also show that the longitudinal processing is systematically more reliable across sites regardless of MRI system differences. The reproducibility errors of the longitudinal segmentations are on average approximately half of those obtained with the cross sectional analysis for all volume segmentations and for entorhinal cortical thickness. No significant differences in reliability are found between the segmentation methods for the other cortical thickness estimates. The average of two MPRAGE volumes acquired within each test–retest session did not systematically improve the across-session reproducibility of morphometry estimates. Our results extend those from previous studies that showed improved reliability of the longitudinal analysis at single sites and/or with non-standard acquisition methods. The multi-site acquisition and analysis protocol presented here is promising for clinical applications since it allows for smaller sample sizes per MRI site or shorter trials in studies evaluating the role of potential biomarkers to predict disease progression or treatment effects.

v2026.09.13