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  • 1.
    Downham, David
    et al.
    Department of Statistics & Computational Mathematics, University of Liverpool.
    Taylor, B.C.
    Department of Statistics & Computational Mathematics, University of Liverpool.
    Lexell, Jan
    Sjöström, Michael
    Department of Neurology, Umeå university.
    Distribution of different fibre types in human skeletal muscles: a method for the detection of neurogenic disorders1987In: IMA journal of mathematics applied in medicine and biology, ISSN 0265-0746, E-ISSN 1471-6879, Vol. 4, no 1, p. 81-91Article in journal (Refereed)
    Abstract [en]

    Human skeletal muscles are composed of two distinguishable types of fibres, which in healthy muscles appear to be randomly arranged. Large groups of one fibre type are commonly regarded as evidence of a neuropathological process affecting the peripheral nerves or the nerve cells in the spinal cord. An objective method that detects non-random arrangements as a sign of a neurogenic disorder, particularly in its early stages, could improve diagnosis. The randomness, or otherwise, of the fibre type arrangement is here considered in terms of the numbers of fibres surrounded entirely by others of the same type (enclosed fibres). The distribution of the number of enclosed fibres is studied for a free-sampling model using Monte Carlo methods. The negative binomial distribution is shown to fit closely, where the parameters can be expressed in terms of the number of fibres and the fibre type proportion in a sample area. This result permits the calculation of significance levels for a sample area and the combination of information in several sample areas. Finally, the method is applied to whole cross-sections of 24 male human autopsied muscles.

  • 2.
    Wilson, B.C.
    et al.
    Department of Statistics & Computational Mathematics, University of Liverpool.
    Downham, David
    Department of Statistics & Computational Mathematics, University of Liverpool.
    Lexell, Jan
    Sjöström, Michael
    Department of Neurology, Umeå university.
    Some probability models for diagnosing neurogenic disorders1988In: IMA journal of mathematics applied in medicine and biology, ISSN 0265-0746, E-ISSN 1471-6879, Vol. 5, no 3, p. 167-79Article in journal (Refereed)
    Abstract [en]

    Healthy human skeletal muscles are composed of two distinguishable types of fibre, apparently randomly arranged within fascicles (bundles of fibres surrounded by connective tissue). Large groups of fibres of the same type indicate a neurogenic muscle disorder. An objective method for detecting nonrandom arrangements of fibres could improve the diagnosis of such disorders, particularly at an early stage. The number of enclosed fibres (NEF)--fibres surrounded by others of the same type--is considered here as a measure of nonrandomness. The distribution of NEF is shown to be approximately negative binomial for a non-free-sampling model, which is then compared with a free-sampling model studied previously. A modification for a known boundary effect is also investigated. The models are applied to data from m. vastus lateralis obtained post mortem from 24 previously healthy men. Finally, the relationship between size of biopsy and the accuracy of predictions is discussed.

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