Quantifying skeletal muscle volume and shape in humans using MRI: A systematic review of validity and reliability

Christelle Pons, Bhushan Borotikar, Marc Garetier, Valérie Burdin, Douraied Ben Salem, Mathieu Lempereur, Sylvain Brochard, Christelle Pons, Bhushan Borotikar, Marc Garetier, Valérie Burdin, Douraied Ben Salem, Mathieu Lempereur, Sylvain Brochard

Abstract

Aims: The aim of this study was to report the metrological qualities of techniques currently used to quantify skeletal muscle volume and 3D shape in healthy and pathological muscles.

Methods: A systematic review was conducted (Prospero CRD42018082708). PubMed, Web of Science, Cochrane and Scopus databases were searched using relevant keywords and inclusion/exclusion criteria. The quality of the articles was evaluated using a customized scale.

Results: Thirty articles were included, 6 of which included pathological muscles. Most evaluated lower limb muscles. Partially or completely automatic and manual techniques were assessed in 10 and 24 articles, respectively. Manual slice-by-slice segmentation reliability was good-to-excellent (n = 8 articles) and validity against dissection was moderate to good(n = 1). Manual slice-by-slice segmentation was used as a gold-standard method in the other articles. Reduction of the number of manually segmented slices (n = 6) provided good to excellent validity if a sufficient number of appropriate slices was chosen. Segmentation on one slice (n = 11) increased volume errors. The Deformation of a Parametric Specific Object (DPSO) method (n = 5) decreased the number of manually-segmented slices required for any chosen level of error. Other automatic techniques combined with different statistical shape or atlas/images-based methods (n = 4) had good validity. Some particularities were highlighted for specific muscles. Except for manual slice by slice segmentation, reliability has rarely been reported.

Conclusions: The results of this systematic review help the choice of appropriate segmentation techniques, according to the purpose of the measurement. In healthy populations, techniques that greatly simplified the process of manual segmentation yielded greater errors in volume and shape estimations. Reduction of the number of manually segmented slices was possible with appropriately chosen segmented slices or with DPSO. Other automatic techniques showed promise, but data were insufficient for their validation. More data on the metrological quality of techniques used in the cases of muscle pathology are required.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Flow chart.
Fig 1. Flow chart.

References

    1. Lieber RL, Fridén J. Functional and clinical significance of skeletal muscle architecture. Muscle Nerve. 2000. November 1;23(11):1647–66.
    1. Fukunaga T, Miyatani M, Tachi M, Kouzaki M, Kawakami Y, Kanehisa H. Muscle volume is a major determinant of joint torque in humans. Acta Physiol Scand. 2001. August;172(4):249–55.
    1. Holzbaur KRS, Delp SL, Gold GE, Murray WM. Moment-generating capacity of upper limb muscles in healthy adults. J Biomech. 2007;40(11):2442–9.
    1. Trappe SW, Trappe TA, Lee GA, Costill DL. Calf muscle strength in humans. Int J Sports Med. 2001. April;22(3):186–91.
    1. Pons C, Sheehan FT, Im HS, Brochard S, Alter KE. Shoulder muscle atrophy and its relation to strength loss in obstetrical brachial plexus palsy. Clin Biomech Bristol Avon. 2017. October;48:80–7.
    1. Narici MV, Maganaris CN, Reeves ND, Capodaglio P. Effect of aging on human muscle architecture. J Appl Physiol Bethesda Md 1985. 2003. December;95(6):2229–34.
    1. Mathur S, Takai KP, Macintyre DL, Reid D. Estimation of thigh muscle mass with magnetic resonance imaging in older adults and people with chronic obstructive pulmonary disease. Phys Ther. 2008. February;88(2):219–30.
    1. Layec G, Venturelli M, Jeong E-K, Richardson RS. The validity of anthropometric leg muscle volume estimation across a wide spectrum: from able-bodied adults to individuals with a spinal cord injury. J Appl Physiol Bethesda Md 1985. 2014. May 1;116(9):1142–7.
    1. Marcon M, Ciritsis B, Laux C, Nanz D, Nguyen-Kim TDL, Fischer MA, et al. Cross-sectional area measurements versus volumetric assessment of the quadriceps femoris muscle in patients with anterior cruciate ligament reconstructions. Eur Radiol. 2015. February;25(2):290–8.
    1. Jenkins TM, Burness C, Connolly DJ, Rao DG, Hoggard N, Mawson S, et al. A prospective pilot study measuring muscle volumetric change in amyotrophic lateral sclerosis. Amyotroph Lateral Scler Front Degener. 2013. September;14(5–6):414–23.
    1. Godi C, Ambrosi A, Nicastro F, Previtali SC, Santarosa C, Napolitano S, et al. Longitudinal MRI quantification of muscle degeneration in Duchenne muscular dystrophy. Ann Clin Transl Neurol. 2016. August;3(8):607–22.
    1. Wu EX, Tang H, Tong C, Heymsfield SB, Vasselli JR. In vivo MRI quantification of individual muscle and organ volumes for assessment of anabolic steroid growth effects. Steroids. 2008. April;73(4):430–40.
    1. Popadic Gacesa JZ, Kozic DB, Dragnic NR, Jakovljevic DG, Brodie DA, Grujic NG. Changes of functional status and volume of triceps brachii measured by magnetic resonance imaging after maximal resistance training. J Magn Reson Imaging JMRI. 2009. March;29(3):671–6.
    1. Koltzenburg M, Yousry T. Magnetic resonance imaging of skeletal muscle. Curr Opin Neurol. 2007. October;20(5):595–9.
    1. Andersen H, Gjerstad MD, Jakobsen J. Atrophy of foot muscles: a measure of diabetic neuropathy. Diabetes Care. 2004. October;27(10):2382–5.
    1. Kaick O van, Hamarneh G, Ward AD, Schweitzer M, Zhang H. Learning Fourier descriptors for computer-aided diagnosis of the supraspinatus. Acad Radiol. 2010. August;17(8):1040–9.
    1. HajGhanbari B, Hamarneh G, Changizi N, Ward AD, Reid WD. MRI-based 3D shape analysis of thigh muscles patients with chronic obstructive pulmonary disease versus healthy adults. Acad Radiol. 2011. February;18(2):155–66.
    1. Blemker SS, Delp SL. Three-dimensional representation of complex muscle architectures and geometries. Ann Biomed Eng. 2005. May;33(5):661–73.
    1. de Boer MD, Maganaris CN, Seynnes OR, Rennie MJ, Narici MV. Time course of muscular, neural and tendinous adaptations to 23 day unilateral lower-limb suspension in young men. J Physiol-Lond. 2007. September 15;583(3):1079–91.
    1. Belavy DL, Ohshima H, Bareille M-P, Rittweger J, Felsenberg D. Limited effect of fly-wheel and spinal mobilization exercise countermeasures on lumbar spine deconditioning during 90 d bed-rest in the Toulouse LTBR study. Acta Astronaut. 2011. October;69(7–8):406–19.
    1. Engstrom CM, Walker DG, Kippers V, Mehnert AJH. Quadratus lumborum asymmetry and L4 pars injury in fast bowlers: a prospective MR study. Med Sci Sports Exerc. 2007. June;39(6):910–7.
    1. Inan M, Alkan A, Harma A, Ertem K. Evaluation of the gluteus medius muscle after a pelvic support osteotomy to treat congenital dislocation of the hip. J Bone Jt Surg-Am Vol. 2005. October;87A(10):2246–52.
    1. Tothill P, Stewart AD. Estimation of thigh muscle and adipose tissue volume using magnetic resonance imaging and anthropometry. J Sports Sci. 2002. July;20(7):563–76.
    1. Nakatani M, Takai Y, Akagi R, Wakahara T, Sugisaki N, Ohta M, et al. Validity of muscle thickness-based prediction equation for quadriceps femoris volume in middle-aged and older men and women. Eur J Appl Physiol. 2016. December;116(11–12):2125–33.
    1. Tingart MJ, Apreleva M, Lehtinen JT, Capell B, Palmer WE, Warner JJP. Magnetic resonance imaging in quantitative analysis of rotator cuff muscle volume. Clin Orthop. 2003. October;(415):104–10.
    1. Tracy BL, Ivey FM, Jeffrey Metter E, Fleg JL, Siegel EL, Hurley BF. A more efficient magnetic resonance imaging-based strategy for measuring quadriceps muscle volume. Med Sci Sports Exerc. 2003. March;35(3):425–33.
    1. Nordez A, Jolivet E, Südhoff I, Bonneau D, de Guise JA, Skalli W. Comparison of methods to assess quadriceps muscle volume using magnetic resonance imaging. J Magn Reson Imaging JMRI. 2009. November;30(5):1116–23.
    1. Yamauchi K, Yoshiko A, Suzuki S, Kato C, Akima H, Kato T, et al. Estimation of individual thigh muscle volumes from a single-slice muscle cross-sectional area and muscle thickness using magnetic resonance imaging in patients with knee osteoarthritis. J Orthop Surg Hong Kong. 2017. December;25(3):2309499017743101
    1. Kim S, Lee D, Park S, Oh K-S, Chung SW, Kim Y. Automatic segmentation of supraspinatus from MRI by internal shape fitting and autocorrection. Comput Methods Programs Biomed. 2017. March;140:165–74.
    1. de Vet HCW, Terwee CB, Knol DL, Bouter LM. When to use agreement versus reliability measures. J Clin Epidemiol. 2006. October;59(10):1033–9.
    1. Brink Y, Louw QA. Clinical instruments: reliability and validity critical appraisal. J Eval Clin Pract. 2012. December;18(6):1126–32.
    1. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol. 2010. July;63(7):737–45.
    1. Brunner G, Nambi V, Yang E, Kumar A, Virani SS, Kougias P, et al. Automatic quantification of muscle volumes in magnetic resonance imaging scans of the lower extremities. Magn Reson Imaging. 2011. October;29(8):1065–75.
    1. Mitsiopoulos N, Baumgartner RN, Heymsfield SB, Lyons W, Gallagher D, Ross R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J Appl Physiol Bethesda Md 1985. 1998. July;85(1):115–22.
    1. Esformes JI, Narici MV, Maganaris CN. Measurement of human muscle volume using ultrasonography. Eur J Appl Physiol. 2002. May;87(1):90–2.
    1. Borotikar B, Lempereur M, Lelievre M, Burdin V, Ben Salem D, Brochard S. Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders. PloS One. 2017;12(12):e0189587
    1. Pons C, Rémy-Néris O, Médée B, Brochard S. Validity and reliability of radiological methods to assess proximal hip geometry in children with cerebral palsy: a systematic review. Dev Med Child Neurol. 2013. December;55(12):1089–102.
    1. Whiting P, Rutjes AWS, Reitsma JB, Bossuyt PMM, Kleijnen J. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003. November 10;3:25
    1. Downs SH, Black N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Community Health. 1998. June;52(6):377–84.
    1. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg Lond Engl. 2014. December;12(12):1495–9.
    1. Lempereur M, Brochard S, Leboeuf F, Rémy-Néris O. Validity and reliability of 3D marker based scapular motion analysis: a systematic review. J Biomech. 2014. July 18;47(10):2219–30.
    1. Terwee CB, Mokkink LB, Knol DL, Ostelo RWJG, Bouter LM, de Vet HCW. Rating the methodological quality in systematic reviews of studies on measurement properties: a scoring system for the COSMIN checklist. Qual Life Res Int J Qual Life Asp Treat Care Rehabil. 2012. May;21(4):651–7.
    1. Mokkink LB, Terwee CB, Knol DL, Stratford PW, Alonso J, Patrick DL, et al. The COSMIN checklist for evaluating the methodological quality of studies on measurement properties: a clarification of its content. BMC Med Res Methodol. 2010. March 18;10:22
    1. Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med Auckl NZ. 1998. October;26(4):217–38.
    1. Valentin S, Yeates TD, Licka T, Elliott J. Inter-rater reliability of trunk muscle morphometric analysis. J Back Musculoskelet Rehabil. 2015;28(1):181–90.
    1. Barnouin Y, Butler-Browne G, Voit T, Reversat D, Azzabou N, Leroux G, et al. Manual segmentation of individual muscles of the quadriceps femoris using MRI: a reappraisal. J Magn Reson Imaging JMRI. 2014. July;40(1):239–47.
    1. Barnouin Y, Butler-Browne G, Moraux A, Reversat D, Leroux G, Behin A, et al. Comparison of Different Methods to Estimate the Volume of the Quadriceps Femoris Muscles Using MRI. J Med Imaging Health Inform. 2015. October;5(6):1201–7.
    1. Le Troter A, Fouré A, Guye M, Confort-Gouny S, Mattei J-P, Gondin J, et al. Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches. Magma N Y N. 2016. April;29(2):245–57.
    1. Lund H, Christensen L, Savnik A, Boesen J, Danneskiold-Samsøe B, Bliddal H. Volume estimation of extensor muscles of the lower leg based on MR imaging. Eur Radiol. 2002. December;12(12):2982–7.
    1. Popadic Gacesa J, Dragnic NR, Prvulovic NM, Barak OF, Grujic N. The validity of estimating triceps brachii volume from single MRI cross-sectional area before and after resistance training. J Sports Sci. 2011. March;29(6):635–41.
    1. Vanmechelen IM, Shortland AP, Noble JJ. Lower limb muscle volume estimation from maximum cross-sectional area and muscle length in cerebral palsy and typically developing individuals. Clin Biomech Bristol Avon. 2017. November 14;51:40–4.
    1. Albracht K, Arampatzis A, Baltzopoulos V. Assessment of muscle volume and physiological cross-sectional area of the human triceps surae muscle in vivo. J Biomech. 2008. July 19;41(10):2211–8.
    1. Amabile C, Moal B, Chtara OA, Pillet H, Raya JG, Iannessi A, et al. Estimation of spinopelvic muscles’ volumes in young asymptomatic subjects: a quantitative analysis. Surg Radiol Anat. 2017;39(4):393–403.
    1. Eng CM, Abrams GD, Smallwood LR, Lieber RL, Ward SR. Muscle geometry affects accuracy of forearm volume determination by magnetic resonance imaging (MRI). J Biomech. 2007;40(14):3261–6.
    1. Belavý DL, Miokovic T, Rittweger J, Felsenberg D. Estimation of changes in volume of individual lower-limb muscles using magnetic resonance imaging (during bed-rest). Physiol Meas. 2011. January;32(1):35–50.
    1. Lehtinen JT, Tingart MJ, Apreleva M, Zurakowski D, Palmer W, Warner JJP. Practical assessment of rotator cuff muscle volumes using shoulder MRI. Acta Orthop Scand. 2003. December;74(6):722–9.
    1. Mersmann F, Bohm S, Schroll A, Arampatzis A. Validation of a simplified method for muscle volume assessment. J Biomech. 2014. April 11;47(6):1348–52.
    1. Mersmann F, Bohm S, Schroll A, Boeth H, Duda G, Arampatzis A. Muscle shape consistency and muscle volume prediction of thigh muscles. Scand J Med Sci Sports. 2015. April;25(2):e208–213.
    1. Moal B, Raya JG, Jolivet E, Schwab F, Blondel B, Lafage V, et al. Validation of 3D spino-pelvic muscle reconstructions based on dedicated MRI sequences for fat-water quantification. Irbm. 2014. June;35(3):119–27.
    1. Morse CI, Degens H, Jones DA. The validity of estimating quadriceps volume from single MRI cross-sections in young men. Eur J Appl Physiol. 2007. June;100(3):267–74.
    1. Skorupska E, Keczmer P, Łochowski RM, Tomal P, Rychlik M, Samborski W. Reliability of MR-Based Volumetric 3-D Analysis of Pelvic Muscles among Subjects with Low Back with Leg Pain and Healthy Volunteers. PloS One. 2016;11(7):e0159587
    1. Smeulders MJC, van den Berg S, Oudeman J, Nederveen AJ, Kreulen M, Maas M. Reliability of in vivo determination of forearm muscle volume using 3.0 T magnetic resonance imaging. J Magn Reson Imaging JMRI. 2010. May;31(5):1252–5.
    1. Springer I, Müller M, Hamm B, Dewey M. Intra- and interobserver variability of magnetic resonance imaging for quantitative assessment of abductor and external rotator muscle changes after total hip arthroplasty. Eur J Radiol. 2012. May;81(5):928–33.
    1. Südhoff I, de Guise JA, Nordez A, Jolivet E, Bonneau D, Khoury V, et al. 3D-patient-specific geometry of the muscles involved in knee motion from selected MRI images. Med Biol Eng Comput. 2009. June;47(6):579–87.
    1. Andrews S, Hamarneh G. The Generalized Log-Ratio Transformation: Learning Shape and Adjacency Priors for Simultaneous Thigh Muscle Segmentation. IEEE Trans Med Imaging. 2015. September;34(9):1773–87.
    1. Elliott MA, Walter GA, Gulish H, Sadi AS, Lawson DD, Jaffe W, et al. Volumetric measurement of human calf muscle from magnetic resonance imaging. Magma N Y N. 1997. June;5(2):93–8.
    1. Engstrom CM, Fripp J, Jurcak V, Walker DG, Salvado O, Crozier S. Segmentation of the quadratus lumborum muscle using statistical shape modeling. J Magn Reson Imaging JMRI. 2011. June;33(6):1422–9.
    1. Jolivet E, Dion E, Rouch P, Dubois G, Charrier R, Payan C, et al. Skeletal muscle segmentation from MRI dataset using a model-based approach. Comput Methods Biomech Biomed Eng Imaging Vis. 2014. February 17;2.
    1. Jolivet E, Daguet E, Bousson V, Bergot C, Skalli W, Laredo JD. Variability of hip muscle volume determined by computed tomography. Biocybern Biomed Eng. 2009. February;30(1):14–9.
    1. Wang L, Chitiboi T, Meine H, Günther M, Hahn HK. Principles and methods for automatic and semi-automatic tissue segmentation in MRI data. Magma N Y N. 2016. April;29(2):95–110.
    1. Baudin PY, Azzabou N, Carlier PG, Paragios N. Prior knowledge, random walks and human skeletal muscle segmentation. Med Image Comput Comput-Assist Interv MICCAI Int Conf Med Image Comput Comput-Assist Interv. 2012;15(Pt 1):569–76.
    1. Baudin P-Y, Goodman D, Kumrnar P, Azzabou N, Carlier PG, Paragios N, et al. Discriminative parameter estimation for random walks segmentation. Med Image Comput Comput-Assist Interv MICCAI Int Conf Med Image Comput Comput-Assist Interv. 2013;16(Pt 3):219–26.
    1. Essafi S, Langs G, Paragios N. Hierarchical 3D diffusion wavelet shape priors. In: 2009 IEEE 12th International Conference on Computer Vision. 2009. p. 1717–24.
    1. Liu F, Zhou Z, Jang H, Samsonov A, Zhao G, Kijowski R. Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging. Magn Reson Med. 2017. July 21;
    1. Fallah F, Machann J, Martirosian P, Bamberg F, Schick F, Yang B. Comparison of T1-weighted 2D TSE, 3D SPGR, and two-point 3D Dixon MRI for automated segmentation of visceral adipose tissue at 3 Tesla. Magma N Y N. 2017. April;30(2):139–51.
    1. Fischmann A, Morrow JM, Sinclair CDJ, Reilly MM, Hanna MG, Yousry T, et al. Improved anatomical reproducibility in quantitative lower-limb muscle MRI. J Magn Reson Imaging JMRI. 2014. April;39(4):1033–8.
    1. Melke GS de F, Costa ALF, Lopes SLP de C, Fuziy A, Ferreira-Santos RI. Three-dimensional lateral pterygoid muscle volume: MRI analyses with insertion patterns correlation. Ann Anat Anat Anz Off Organ Anat Ges. 2016. November;208:9–18.
    1. Nakatani M, Takay Y, Wakahara T, Sugisaki N, Ohta M, Kawakami Y, Fukunaga T, Kanehisa H. Validity of muscle thickness-based prediction equation for quadriceps femoris volume in middle-aged and older men and women. Eur J Appl Physiol. 2016. December;116(11–12):2125–2133.
    1. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res. 2010. May;19(4):539–49.

Source: PubMed

3
订阅