Êtes-vous un étudiant de l'EPFL à la recherche d'un projet de semestre?
Travaillez avec nous sur des projets en science des données et en visualisation, et déployez votre projet sous forme d'application sur Graph Search.
Background and purpose. - Automated synthetic magnetic resonance imaging (MRI) provides qualitative, weighted image contrasts as well as quantitative information from one scan and is well-suited for various applications such as analysis of white matter disorders. However, the synthesized contrasts have been poorly evaluated in pediatric applications. The purpose of this study was to compare the image quality of synthetic T2 to conventional turbo spin-echo (TSE) T2 in pediatric brain MRI. Materials and methods. - This was a mono-center prospective study. Synthetic and conventional MRI acquisitions at 1.5 Tesla were performed for each patient during the same session using a prototype accelerated T2 mapping sequence package (TA(synthetic) = 3:07 min, TA(conventional) = 2:33 min). Image sets were blindly and randomly analyzed by pediatric neuroradiologists. Global image quality, morphologic legibility of standard structures and artifacts were assessed using a 4-point Likert scale. Inter-observer kappa agreements were calculated. The capability of the synthesized contrasts and conventional TSE T2 to discern normal and pathologic cases was evaluated. Results. - Sixty patients were included. The overall diagnostic quality of the synthesized contrasts was non-inferior to conventional imaging scale (P = 0.06). There was no significant difference in the legibility of normal and pathological anatomic structures of synthetized and conventional TSE T2 (all P> 0.05) as well as for artifacts except for phase encoding (P = 0.008). Inter-observer agreement was good to almost perfect (kappa between 0.66 and 1). Conclusions. - T2 synthesized contrasts, which also provides quantitative T2 information that could be useful, could be suggested as an equivalent technique in pediatric neuro-imaging, compared to conventional TSE T2. (C) 2018 Elsevier Masson SAS. All rights reserved.
Edoardo Charbon, Claudio Bruschini, Paul Mos, Arin Can Ülkü