Original article| Volume 41, ISSUE 10, P870-877, November 2019

Download started.


Automatic calculation of Mercuri grades from CT and MR muscle images



      Mercuri grading of muscle images is a useful method to evaluate the progression of muscular dystrophies. However, because Mercuri grading is skill-based, few competent experts are available. We therefore developed an automated method for Mercuri grade calculations.


      We used computed tomography (CT) and magnetic resonance (MR) images of the thigh and lower leg muscles taken from a Japanese limb-girdle muscular dystrophy patient database. We calculated muscle impairment ratios based on the CT images, and then converted the ratios to revised Mercuri grades. This method was also applied to T1-weighted MR images. Additionally, radiation absorption doses in muscle and chest CT images from a separate patient group were also analyzed.


      We observed a close correlation between our automatically calculated Mercuri grades and skill-based visually determined Mercuri grades in both CT and MR images. The radiation absorption, measured by total dose length product, was lower in muscle CT (121.8 mGy-cm) than in chest CT (524.1 mGy-cm).


      We developed a new automatic Mercuri grading method using values obtained from CT images. This method was also applied to calculate the Mercuri grade of T1-weighted MR images. In addition, the radiation doses from muscle CT were observed to be lower than those from chest CT.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Brain and Development
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Mercuri E.
        • Cini C.
        • Counsell S.
        • Allsop J.
        • Zolkipli Z.
        • Jungbluth H.
        • et al.
        Muscle MRI findings in a three-generation family affected by Bethlem myopathy.
        Eur J Paediatr Neurol. 2002; 6: 309-314
        • Straub V.
        • Carlier P.G.
        • Mercuri E.
        TREAT-NMD workshop: pattern recognition in genetic muscle diseases using muscle MRI: 25–26 February 2011, Rome, Italy.
        Neuromuscul Disord. 2012; 22: S42-S53
        • Díaz-Manera J.
        • Llauger J.
        • Gallardo E.
        Muscle MRI in muscular dystrophies.
        Acta Myol. 2015; 34: 95-108
        • Finlayson S.
        • Morrow J.M.
        • Rodriguez Cruz P.M.
        • Sinclair C.D.
        • Fischmann A.
        • Thornton J.S.
        • et al.
        Muscle magnetic resonance imaging in congenital myasthenic syndromes.
        Muscle Nerve. 2016; 54: 211-219
        • Dixon W.T.
        Simple proton spectroscopic imaging.
        Radiology. 1984; 153: 189-194
        • Willis T.A.
        • Hollingsworth K.G.
        • Coombs A.
        • Sveen M.L.
        • Andersen S.
        • Stojkovic T.
        • et al.
        Quantitative muscle MRI as an assessment tool for monitoring disease progression in LGMD2I: a multicentre longitudinal study.
        PLoS One. 2013; 8e70993
        • Kim H.K.
        • Laor T.
        • Horn P.S.
        • Wong B.
        Quantitative assessment of the T2 relaxation time of the gluteus muscles in children with Duchenne muscular dystrophy: a comparative study before and after steroid treatment.
        Korean J Radiol. 2010; 11: 304-311
        • Bonati U.
        • Schmid M.
        • Hafner P.
        • Haas T.
        • Bieri O.
        • Gloor M.
        • et al.
        Longitudinal 2-point dixon muscle magnetic resonance imaging in Becker muscular dystrophy.
        Muscle Nerve. 2015; 51: 918-921
        • Alizai H.
        • Nardo L.
        • Karampinos D.C.
        • Joseph G.B.
        • Yap S.P.
        • Baum T.
        • et al.
        Comparison of clinical semi-quantitative assessment of muscle fat infiltration with quantitative assessment using chemical shift-based water/fat separation in MR studies of the calf of post-menopausal women.
        Eur Radiol. 2012; 22: 1592-1600
        • Goutallier D.
        • Postel J.M.
        • Bernageau J.
        • Lavau L.
        • Voisin M.C.
        Fatty muscle degeneration in cuff ruptures. Pre- and postoperative evaluation by CT scan.
        Clin Orthop Relat Res. 1994; 304: 78-83
        • Polavarapu K.
        • Manjunath M.
        • Preethish-Kumar V.
        • Sekar D.
        • Vengalil S.
        • Thomas P.
        • et al.
        Muscle MRI in Duchenne muscular dystrophy: Evidence of a distinctive pattern.
        Neuromusc Disord. 2016; 26: 768-774
        • Nakayama T.
        • Ishiyama A.
        • Kuru S.
        IBIC-LG: Database of muscle images of patients with limb-girdle muscular dystrophy in Japan.
        Neuromuscul Disord. 2016; 26: S98-S99
        • Nakayama T.
        • Kuru S.
        • Okura M.
        • Motoyoshi Y.
        • Kawai M.
        Estimation of net muscle volume in patients with muscular dystrophy using muscle CT for prospective muscle volume analysis: an observational study.
        BMJ Open. 2013; 3e003603
        • Kuru S.
        • Sakai M.
        • Tanaka N.
        • Konagaya M.
        • Nakayam T.
        • Kawai M.
        Natural course of muscular involvement assessed by a new computed tomography method in Duchenne muscular dystrophy.
        Neurology Clin Neurosci. 2013; 1: 63-68
        • Chien H.
        • Smith P.J.
        On the estimation of the kinematic parameters in the atmosphere from radiosonde wind data.
        Mon Weather Rev. 1973; 101: 252
        • Kawai M.
        • Kunimoto M.
        • Motoyoshi Y.
        • Kuwata T.
        • Nakano I.
        Computed tomography in Duchenne type muscular dystrophy – Morphological stages based on the computed tomographical findings.
        Rinsho Shinkeigaku. 1985; 25: 578-590
        • Godi C.
        • Ambrosi A.
        • Nicastro F.
        • Previtali S.C.
        • Santarosa C.
        • Napolitano S.
        • et al.
        Longitudinal MRI quantification of muscle degeneration in Duchenne muscular dystrophy.
        Ann Clin Transl Neurol. 2016; 3: 607-622
      1. Japan Network for Research and Information on Medical Exposures: J-RIME. Disease Diagnostic Level in Japan,; 2015 [accessed 11.08.15].