Francesc Xavier Aymerich1,2, Cristina Auger3, Julio Alonso3, Andrea Barros3, Margareta A Clarke3, Juan Mora3, Georgina Arrambide4, Juan Francisco Corral3, Ana Andrino3, Jaume Sastre-Garriga4, Alex Rovira3. 1. Section of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain. xavier.aymerich.idi@gencat.cat. 2. Department of Automatic Control (ESAII), Universitat Politècnica de Catalunya, Barcelona, Spain. xavier.aymerich.idi@gencat.cat. 3. Section of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain. 4. Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain.
Abstract
PURPOSE: To qualitatively and quantitatively compare synthetic and conventional MRI sequences acquired on a 1.5-T system for patients with multiple sclerosis (MS). METHODS: Prospective study that involved twenty-seven consecutive relapsing-remitting MS patients scanned on a 1.5-T MRI scanner. The MRI protocol included 2D transverse conventional spin-echo sequences: proton density-weighted (PD), T2-weighted, T2-FLAIR, and T1-weighted. Synthetic images were generated using 2D transverse QRAPMASTER and SyMRI software with the same voxel size, repetition, echo, and inversion times as the conventional sequences. Four raters performed a crosstab qualitative analysis that involved evaluating global image quality, contrast, flow artefacts, and confidence in lesion assessment introducing the concepts of predominance, agreement, and disagreement. A quantitative analysis was also performed and included evaluating the number of lesions (periventricular, juxtacortical, brainstem, and cerebellum) and the contrast-to-noise ratio between regions (CSF, white matter, grey matter, lesions). RESULTS: The global image quality assessment showed predominance for better scores for conventional sequences over synthetic sequences, whereas contrast, confidence in lesion assessment, and flow artefacts showed predominance for agreement between sequences. There was predominance for disagreement between all pairs of raters in most of the evaluated qualitative parameters. Synthetic PD and T2-FLAIR images showed higher contrast-to-noise ratios than the corresponding conventional images for most comparison between regions. There were no significant differences in the number of lesions detected for most of the study regions between conventional and synthetic images. CONCLUSION: Synthetic MRI can be potentially used as an alternative to conventional brain MRI sequences in the assessment of MS.
PURPOSE: To qualitatively and quantitatively compare synthetic and conventional MRI sequences acquired on a 1.5-T system for patients with multiple sclerosis (MS). METHODS: Prospective study that involved twenty-seven consecutive relapsing-remitting MS patients scanned on a 1.5-T MRI scanner. The MRI protocol included 2D transverse conventional spin-echo sequences: proton density-weighted (PD), T2-weighted, T2-FLAIR, and T1-weighted. Synthetic images were generated using 2D transverse QRAPMASTER and SyMRI software with the same voxel size, repetition, echo, and inversion times as the conventional sequences. Four raters performed a crosstab qualitative analysis that involved evaluating global image quality, contrast, flow artefacts, and confidence in lesion assessment introducing the concepts of predominance, agreement, and disagreement. A quantitative analysis was also performed and included evaluating the number of lesions (periventricular, juxtacortical, brainstem, and cerebellum) and the contrast-to-noise ratio between regions (CSF, white matter, grey matter, lesions). RESULTS: The global image quality assessment showed predominance for better scores for conventional sequences over synthetic sequences, whereas contrast, confidence in lesion assessment, and flow artefacts showed predominance for agreement between sequences. There was predominance for disagreement between all pairs of raters in most of the evaluated qualitative parameters. Synthetic PD and T2-FLAIR images showed higher contrast-to-noise ratios than the corresponding conventional images for most comparison between regions. There were no significant differences in the number of lesions detected for most of the study regions between conventional and synthetic images. CONCLUSION: Synthetic MRI can be potentially used as an alternative to conventional brain MRI sequences in the assessment of MS.
Authors: Àlex Rovira; Mike P Wattjes; Mar Tintoré; Carmen Tur; Tarek A Yousry; Maria P Sormani; Nicola De Stefano; Massimo Filippi; Cristina Auger; Maria A Rocca; Frederik Barkhof; Franz Fazekas; Ludwig Kappos; Chris Polman; David Miller; Xavier Montalban Journal: Nat Rev Neurol Date: 2015-07-07 Impact factor: 42.937
Authors: L N Tanenbaum; A J Tsiouris; A N Johnson; T P Naidich; M C DeLano; E R Melhem; P Quarterman; S X Parameswaran; A Shankaranarayanan; M Goyen; A S Field Journal: AJNR Am J Neuroradiol Date: 2017-04-27 Impact factor: 3.825
Authors: Alan J Thompson; Brenda L Banwell; Frederik Barkhof; William M Carroll; Timothy Coetzee; Giancarlo Comi; Jorge Correale; Franz Fazekas; Massimo Filippi; Mark S Freedman; Kazuo Fujihara; Steven L Galetta; Hans Peter Hartung; Ludwig Kappos; Fred D Lublin; Ruth Ann Marrie; Aaron E Miller; David H Miller; Xavier Montalban; Ellen M Mowry; Per Soelberg Sorensen; Mar Tintoré; Anthony L Traboulsee; Maria Trojano; Bernard M J Uitdehaag; Sandra Vukusic; Emmanuelle Waubant; Brian G Weinshenker; Stephen C Reingold; Jeffrey A Cohen Journal: Lancet Neurol Date: 2017-12-21 Impact factor: 44.182
Authors: A Hagiwara; M Hori; K Yokoyama; M Y Takemura; C Andica; T Tabata; K Kamagata; M Suzuki; K K Kumamaru; M Nakazawa; N Takano; H Kawasaki; N Hamasaki; A Kunimatsu; S Aoki Journal: AJNR Am J Neuroradiol Date: 2016-12-08 Impact factor: 3.825
Authors: T Granberg; M Uppman; F Hashim; C Cananau; L E Nordin; S Shams; J Berglund; Y Forslin; P Aspelin; S Fredrikson; M Kristoffersen-Wiberg Journal: AJNR Am J Neuroradiol Date: 2016-01-21 Impact factor: 3.825
Authors: Jaume Sastre-Garriga; Deborah Pareto; Marco Battaglini; Maria A Rocca; Olga Ciccarelli; Christian Enzinger; Jens Wuerfel; Maria P Sormani; Frederik Barkhof; Tarek A Yousry; Nicola De Stefano; Mar Tintoré; Massimo Filippi; Claudio Gasperini; Ludwig Kappos; Jordi Río; Jette Frederiksen; Jackie Palace; Hugo Vrenken; Xavier Montalban; Àlex Rovira Journal: Nat Rev Neurol Date: 2020-02-24 Impact factor: 42.937