Facial soft tissue thicknesses in craniofacial identification: Data collection protocols and associated measurement errors. (November 2019)

• Record Type: Journal Article
• Authors: Stephan, C.N.; Meikle, B.; Freudenstein, N.; Taylor, R.; Claes, P.
• Is Part Of: Forensic science international. Volume 304(2019)
• Publication Date: 2019-11
• Subjects: Craniofacial identification -- Facial approximation -- Facial reconstruction -- Craniofacial superimposition -- Facial soft tissue depth -- Skull -- Measurement error; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2019.109965
• Languages: English
• ISSNs: 0379-0738

Abstract

Highlights: Facial soft tissue thickness are a cornerstone of craniofacial identification. Many methods have been used to measure facial soft tissue thicknesses. Measurement errors appear to be large and have not been sufficiently documented. We review pre-existing data and recommend new future standards. Abstract: Facial soft tissue thicknesses (FSTT) form a key component of craniofacial identification methods, but as for any data, embedded measurement errors are highly pertinent. These in part dictate the effective resolution of the measurements. As herein reviewed, measurement methods are highly varied in FSTT studies and associated measurement errors have generally not been paid much attention. Less than half (44%) of 95 FSTT studies comment on measurement error and not all of these provide specific quantification. Where informative error measurement protocols are employed (5% of studies), the mean error magnitudes range from 3% to 45% rTEM and are typically in the order of 10–20%. These values demonstrate that FSTT measurement errors are similar in size to (and likely larger than) the magnitudes of many biological effects being chased. As a result, the attribution of small millimeter or submillimeter differences in FSTT to biological variables must be undertaken with caution, especially where they have not been repeated across different studies/samples. To improve the integrity of FSTT studies and the reporting of FSTT measurement errors, we propose the following standard: (1) calculate the technical error of measurement (TEM or rTEM) in any FSTT research work; (2) assess the error embedded in the full data collection procedure; and (3) conduct validation testing of FSTT means proposed for point estimation prior to publication to ensure newly calculated FSTT means provide improvements. In order to facilitate the latter, a freely available R tool TDValidator that uses the C-Table data for validation testing is provided.