Literature DB >> 18783476

Facial soft tissue depths in craniofacial identification (part I): An analytical review of the published adult data.

Carl N Stephan1, Ellie K Simpson.   

Abstract

With the ever increasing production of average soft tissue depth studies, data are becoming increasingly complex, less standardized, and more unwieldy. So far, no overarching review has been attempted to determine: the validity of continued data collection; the usefulness of the existing data subcategorizations; or if a synthesis is possible to produce a manageable soft tissue depth library. While a principal components analysis would provide the best foundation for such an assessment, this type of investigation is not currently possible because of a lack of easily accessible raw data (first, many studies are narrow; second, raw data are infrequently published and/or stored and are not always shared by some authors). This paper provides an alternate means of investigation using an hierarchical approach to review and compare the effects of single variables on published mean values for adults whilst acknowledging measurement errors and within-group variation. The results revealed: (i) no clear secular trends at frequently investigated landmarks; (ii) wide variation in soft tissue depth measures between different measurement techniques irrespective of whether living persons or cadavers were considered; (iii) no clear clustering of non-Caucasoid data far from the Caucasoid means; and (iv) minor differences between males and females. Consequently, the data were pooled across studies using weighted means and standard deviations to cancel out random and opposing study-specific errors, and to produce a single soft tissue depth table with increased sample sizes (e.g., 6786 individuals at pogonion).

Entities:  

Mesh:

Year:  2008        PMID: 18783476     DOI: 10.1111/j.1556-4029.2008.00852.x

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  15 in total

1.  A standardized nomenclature for craniofacial and facial anthropometry.

Authors:  Jodi Caple; Carl N Stephan
Journal:  Int J Legal Med       Date:  2015-12-11       Impact factor: 2.686

2.  The influence of sex, age and body mass index on facial soft tissue depths.

Authors:  S De Greef; D Vandermeulen; P Claes; P Suetens; G Willems
Journal:  Forensic Sci Med Pathol       Date:  2009-05-13       Impact factor: 2.007

3.  Accuracies of facial soft tissue depth means for estimating ground truth skin surfaces in forensic craniofacial identification.

Authors:  Carl N Stephan
Journal:  Int J Legal Med       Date:  2014-11-14       Impact factor: 2.686

4.  Lip morphology estimation models based on three-dimensional images in a modern adult population from China.

Authors:  Jia-Min Zhao; Ling-Ling Ji; Meng-Qi Han; Qing-Nan Mou; Guang Chu; Teng Chen; Shao-Yi Du; Yu-Xia Hou; Yu-Cheng Guo
Journal:  Int J Legal Med       Date:  2021-03-24       Impact factor: 2.686

5.  Using Computed Tomography (CT) Data to Build 3D Resources for Forensic Craniofacial Identification.

Authors:  Terrie Simmons-Ehrhardt; Catyana R S Falsetti; Anthony B Falsetti
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

6.  In vivo facial soft tissue depths of a modern adult population from Germany.

Authors:  Nicolle Thiemann; Volker Keil; Uwe Roy
Journal:  Int J Legal Med       Date:  2017-04-17       Impact factor: 2.686

7.  "Bochdalek's" skull: morphology report and reconstruction of face.

Authors:  Ivo Klepáček; Pavla Zedníková Malá
Journal:  Forensic Sci Med Pathol       Date:  2012-08-24       Impact factor: 2.007

Review 8.  An overview of the latest developments in facial imaging.

Authors:  Carl N Stephan; Jodi M Caple; Pierre Guyomarc'h; Peter Claes
Journal:  Forensic Sci Res       Date:  2018-10-29

9.  Application of cone beam computed tomography in facial soft tissue thickness measurements for craniofacial reconstruction.

Authors:  Manasa Anand Meundi; Chaya Manoranjini David
Journal:  J Oral Maxillofac Pathol       Date:  2019 Jan-Apr

10.  A method for automatic forensic facial reconstruction based on dense statistics of soft tissue thickness.

Authors:  Thomas Gietzen; Robert Brylka; Jascha Achenbach; Katja Zum Hebel; Elmar Schömer; Mario Botsch; Ulrich Schwanecke; Ralf Schulze
Journal:  PLoS One       Date:  2019-01-23       Impact factor: 3.240

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