title: Decision tree analysis as a supplementary tool to enhance histomorphological differentiation when distinguishing human from non-human cranial bone in both burnt and unburnt states: A feasibility study.
abstract: This feasibility study was undertaken to describe and record the histological characteristics of burnt and unburnt cranial bone fragments from human and non-human bones. Reference series of fully mineralized, transverse sections of cranial bone, from all variables and specimen states, were prepared by manual cutting and semi-automated grinding and polishing methods. A photomicrograph catalogue reflecting differences in burnt and unburnt bone from human and non-humans was recorded and qualitative analysis was performed using an established classification system based on primary bone characteristics. The histomorphology associated with human and non-human samples was, for the main part, preserved following burning at high temperature. Clearly, fibro-lamellar complex tissue subtypes, such as plexiform or laminar primary bone, were only present in non-human bones. A decision tree analysis based on histological features provided a definitive identification key for distinguishing human from non-human bone, with an accuracy of 100%. The decision tree for samples where burning was unknown was 96% accurate, and multi-step classification to taxon was possible with 100% accuracy. The results of this feasibility study strongly suggest that histology remains a viable alternative technique if fragments of cranial bone require forensic examination in both burnt and unburnt states. The decision tree analysis may provide an additional but vital tool to enhance data interpretation. Further studies are needed to assess variation in histomorphology taking into account other cranial bones, ontogeny, species and burning conditions.
authors.affiliation: Department of Forensic Science, Virginia Commonwealth University, Richmond, VA, USA tsimmons@vcu.edu.
authors.forename: T
authors.initials: T
authors.lastname: Simmons
authors.affiliation: School of Forensic and Investigative Sciences, University of Central Lancashire, Preston, UK.
authors.forename: B
authors.initials: B
authors.lastname: Goodburn
authors.affiliation: Oral & Dental Sciences Research Group, School of Medicine and Dentistry, University of Central Lancashire, Preston, UK.
authors.forename: S K
authors.initials: SK
authors.lastname: Singhrao
mesh_terms: D000328:Adult; D000368:Aged; D000818:Animals; D003663:Decision Trees; D004285:Dogs; D005240:Feasibility Studies; D005260:Female; D005390:Fires; D049429:Forensic Pathology; D006253:Haversian System / Q000473:pathology; D006801:Humans; D008297:Male; D045969:Mustelidae; D012756:Sheep; D012886:Skull / Q000473:pathology*; D013045:Species Specificity
keywords: Decision tree analysis; bone; burnt; histology; human; non-human; unburnt