Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Sequencing human ribs into anatomical order by quantitative multivariate methods|
|Citation:||Homo - journal of comparative human biology, 2012; 63(3):182-201|
|Publisher:||Urban & Fischer Verlag|
|John Cirillo, Maciej Henneberg|
|Abstract:||Little research has focussed on methods to anatomically sequence ribs. Correct anatomical sequencing of ribs assists in determining the location and distribution of regional trauma, age estimation, number of puncture wounds, number of individuals, and personal identification. The aim of the current study is to develop a method for placing fragmented and incomplete rib sets into correct anatomical position. Ribs 2-10 were used from eleven cadavers of an Australian population. Seven variables were measured from anatomical locations on the rib. General descriptive statistics were calculated for each variable along with an analysis of variance (ANOVA) and ANOVA with Bonferroni statistics. Considerable overlap was observed between ribs for univariate methods. Bivariate and multivariate methods were then applied. Results of the ANOVA with post hoc Bonferroni statistics show that ratios of various dimensions of a single rib could be used to sequence it within adjacent ribs. Using multiple regression formulae, the most accurate estimation of the anatomical rib number occurs when the entire rib is found in isolation. This however, is not always possible. Even when only the head and neck of the rib are preserved, a modified multivariate regression formula assigned 91.95% of ribs into correct anatomical position or as an adjacent rib. Using multivariate methods it is possible to sequence a single human rib with a high level of accuracy and they are superior to univariate methods. Left and right ribs were found to be highly symmetrical. Some rib dimensions were greater in males than in females, but overall the level of sexual dimorphism was low.|
|Keywords:||Ribs; Humans; Age Determination by Skeleton; Multivariate Analysis; Regression Analysis; Models, Anatomic; Aged; Aged, 80 and over; Middle Aged; Female; Male|
|Rights:||Copyright © 2012 Elsevier GmbH. All rights reserved.|
|Appears in Collections:||Anatomical Sciences publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.