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Assessment of 2D conventional and synthetic MRI in multiple sclerosis

  • Diagnostic Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript



To qualitatively and quantitatively compare synthetic and conventional MRI sequences acquired on a 1.5-T system for patients with multiple sclerosis (MS).


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).


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.


Synthetic MRI can be potentially used as an alternative to conventional brain MRI sequences in the assessment of MS.

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Fig. 1

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A cq :


A cs :

Agreement between conventional and synthetic images

A r k r l :

Agreement between raters


Contrast of lesions to white matter


Contrast-to-noise ratio


Cerebrospinal fluid

DAr k r l :

Disagreement between raters


Distance factor


Kurtzke expanded disability status scale


Flip angle


Flow artefacts in the posterior fossa


Field of view


Fluid attenuated inversion recovery


Global image contrast


Global image quality


Grey matter


Integrated parallel acceleration techniques


Whole lesion

LCLA infra:

Level of confidence in the assessment of lesions in the infratentorial location

LCLA supra:

Level of confidence in the assessment of lesions in the supratentorial location


Inner lesion


Magnetic resonance imaging


Multiple sclerosis

Pc :

Predominance on conventional images


Proton density

P rl :

Predominance of rate l

P rk :

Predominance of rater k

P s :

Predominance on synthetic images


Region of interest


Relapsing-remitting multiple sclerosisSS


Standard deviation


Acquisition time


Echo time


Inversion time


Repetition time


White matter


  1. Simon JH (2014) MRI outcomes in the diagnosis and disease course of multiple sclerosis. In: Handb Clin Neurol

  2. Sinnecker T, Kuchling J, Dusek P et al (2015) Ultrahigh field MRI in clinical neuroimmunology: a potential contribution to improved diagnostics and personalised disease management. EPMA J. 6

  3. Rovira A, Wattjes MP, Tintoré M et al (2015) Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis - clinical implementation in the diagnostic process. Nat Rev Neurol 11:471–482.

    Article  PubMed  Google Scholar 

  4. Sastre-Garriga J, Pareto D, Battaglini M et al (2020) MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice. Nat Rev Neurol 16:171–182.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Warntjes JBM, DahlqvistLeinhard O, West J, Lundberg P (2008) Rapid magnetic resonance quantification on the brain: optimization for clinical usage. Magn Reson Med 60:320–329.

    Article  CAS  PubMed  Google Scholar 

  6. Granberg T, Uppman M, Hashim F et al (2016) Clinical feasibility of synthetic MRI in multiple sclerosis: a diagnostic and volumetric validation study. Am J Neuroradiol 37:1023–1029.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Hagiwara A, Hori M, Yokoyama K et al (2017) Synthetic MRI in the detection of multiple sclerosis plaques. Am J Neuroradiol 38:257–263.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Blystad I, Håkansson I, Tisell A, et al (2016) Quantitative MRI for analysis of active multiple sclerosis lesions without gadolinium-based contrast agent. Am J Neuroradiol 37:

  9. Krauss W, Gunnarsson M, Nilsson M, Thunberg P (2018) Conventional and synthetic MRI in multiple sclerosis: a comparative study. Eur Radiol 28:1692–1700.

    Article  PubMed  Google Scholar 

  10. Wattjes MP, Ciccarelli O, Reich DS et al (2021) MAGNIMS–CMSC–NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 4422:1–18.

    Article  Google Scholar 

  11. Thompson AJ, Banwell BL, Barkhof F et al (2018) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17:162–173.

    Article  PubMed  Google Scholar 

  12. Hinkle, Wiersma, Jurs (2003) Rule of thumb for interpreting the size of a correlation coefficient matrix showing correlation coefficients appropriate for scales of measurement for variable X and variable Y. Appl Stat Behav Sci 1

  13. Ryu KH, Baek HJ, Moon J Il, et al (2020) Initial clinical experience of synthetic MRI as a routine neuroimaging protocol in daily practice: a single-center study. J Neuroradiol 47:

  14. Tanenbaum LN, Tsiouris AJ, Johnson AN et al (2017) Synthetic MRI for clinical neuroimaging: results of the magnetic resonance image compilation (MAGiC) prospective, multicenter, multireader trial. Am J Neuroradiol 38:1103–1110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Di Giuliano F, Minosse S, Picchi E et al (2020) Comparison between synthetic and conventional magnetic resonance imaging in patients with multiple sclerosis and controls. Magn Reson Mater Physics Biol Med 33:549–557.

    Article  Google Scholar 

  16. Betts AM, Leach JL, Jones BV et al (2016) Brain imaging with synthetic MR in children: clinical quality assessment. Neuroradiology 58:1017–1026.

    Article  PubMed  Google Scholar 

  17. Blystad I, Warntjes JBM, Smedby O et al (2012) Synthetic MRI of the brain in a clinical setting. Acta radiol 53:1158–1163.

    Article  CAS  PubMed  Google Scholar 

  18. Hagens MHJ, Burggraaff J, Kilsdonk ID, et al (2019) Impact of 3 Tesla MRI on interobserver agreement in clinically isolated syndrome: a MAGNIMS multicentre study. Mult Scler J 25:

  19. Hagens MHJ, Burggraaff J, Kilsdonk ID, et al (2018) Three-Tesla MRI does not improve the diagnosis of multiple sclerosis: a multicenter study. Neurology 91:

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We thank Martin Uppman, MSc, Tobias Granberg, MD PhD (Karolinska University Hospital, Stockholm, Sweden), and Frederik Testud, PhD (Siemens Healthcare AB, Sweden) for their work on the MDME (formerly known as QRAPMASTER) sequence.


No funding was received for this study.

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Correspondence to Francesc Xavier Aymerich.

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Ethical approval

All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Conflicts of interest

J. Sastre-Garriga declares grants and personal fees from Genzyme; personal fees from Almirall, Biogen, Celgene, Merck, Novartis, Roche and Teva; and is a member of the Editorial Committee of Multiple Sclerosis Journal and Director of the Scientific Committee of Revista de Neurologia. M.A. Clarke declares personal fees from Novartis and received 2018 ECTRIMS-MAGNIMS fellowship. G. Arrambide has received compensation for consulting services or participation in advisory boards from Sanofi and Merck; research support from Novartis; travel expenses for scientific meetings from Novartis and Roche; and speaking honoraria from Stendhal, Sanofi, and Merck. A. Rovira serves on scientific advisory boards for Novartis, Sanofi-Genzyme, Synthetic MR, Roche, Biogen, and OLEA Medical, and has received speaker honoraria from Sanofi-Genzyme, Bracco, Merck-Serono, Teva Pharmaceutical Industries Ltd, Novartis, Roche, and Biogen. F.X. Aymerich, C. Auger, J. Alonso, A. Barros, J. Mora, A. Andrino, and J.F. Corral have nothing to disclose.

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Aymerich, F.X., Auger, C., Alonso, J. et al. Assessment of 2D conventional and synthetic MRI in multiple sclerosis. Neuroradiology 64, 2315–2322 (2022).

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