Contributors: Neuroimagerie: méthodes et applications (Empenn); Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5); Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA); Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique); Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT); Département de Radiologie CHU de Rennes; Université de Rennes (UR); CHU Trousseau Tours; Centre Hospitalier Régional Universitaire de Tours (CHRU Tours); Département de Pédiatrie Rennes = Paediatrics Rennes; Centre Hospitalier Universitaire de Rennes CHU Rennes = Rennes University Hospital Ponchaillou; Results incorporated in this publication received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement n° 689260 (Digi-NewB project). This work was supported by the Société Française de Radiologie, Paris, France (2018 Research Grant), and the Agence Nationale de la Recherche, France (Project: ANR-15-CE23-0009, MAIA, Program: Appel à projets génériques 2015).; ANR-15-CE23-0009,MAIA,Analyse multiphysiques fondée sur l'imagerie pour la compréhension du développement cérébral des prématurés(2015); European Project: 689260,H2020,H2020-PHC-2015-single-stage,Digi-NewB(2016)
نبذة مختصرة : International audience ; Objectives The severity of neurocognitive impairment increases with prematurity. However, its mechanisms remain poorly understood. Our aim was firstly to identify multiparametric magnetic resonance imaging (MRI) markers that differ according to the degree of prematurity, and secondly to evaluate the impact of clinical complications on these markers. Materials and Methods We prospectively enrolled preterm infants who were divided into two groups according to their degree of prematurity: extremely preterm (>28 weeks’ gestational age) and very preterm (28–32 weeks’ gestational age). They underwent a multiparametric brain MRI scan at term-equivalent age including morphological, diffusion tensor and arterial spin labeling (ASL) perfusion sequences. We quantified overall and regional volumes, diffusion parameters, and cerebral blood flow (CBF). We then compared the parameters for the two groups. We also assessed the effects of clinical data and potential MRI morphological abnormalities on those parameters. Results Thirty-four preterm infants were included. Extremely preterm infants ( $n$ = 13) had significantly higher frontal relative volumes ( $p$ = 0.04), frontal GM relative volumes ( $p$ = 0.03), and regional CBF than very preterm infants, but they had lower brainstem and insular relative volumes (respectively $p$ = 0.008 and 0.04). Preterm infants with WM lesions on MRI had significantly lower overall GM CBF (13.3 ± 2 ml/100 g/min versus 17.7 ± 2.5, < ml/100 g/min $p$ = 0.03). Conclusion Magnetic resonance imaging brain scans performed at term-equivalent age in preterm infants provide quantitative imaging parameters that differ with respect to the degree of prematurity, related to brain maturation.
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