title: Some probability models for diagnosing neurogenic disorders.
abstract: 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.
authors.affiliation: Department of Statistics and Computational Mathematics, University of Liverpool, UK.
authors.forename: B C
authors.initials: BC
authors.lastname: Wilson
authors.forename: D Y
authors.initials: DY
authors.lastname: Downham
authors.forename: J
authors.initials: J
authors.lastname: Lexell
authors.forename: M
authors.initials: M
authors.lastname: Sjöström
mesh_terms: D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D009132:Muscles / Q000473:pathology*; D009468:Neuromuscular Diseases / Q000175:diagnosis* / Q000473:pathology; D011336:Probability