Biomedical subjects

Carl N Stephan

Publications and source records attributed to Carl N Stephan.

10 recordsLinked to original sources

PubMed2006

Facial soft tissue thicknesses in Australian adult cadavers.

Craniofacial identification methods heavily rely on the knowledge of average soft tissue depths. This study measured soft tissue thicknesses of an Australian cadaver sample (N = 33) using published needle puncture techniques at 13 anatomical locations. Data were compared and contrasted with other studies that used essentially identical samples and methods. Full descriptive statistics were calculated for measurements made in this study and means, medians, and modes were reported. Differences between mean values for males and females were found to be minimal (2.2 mm or less) and considerable overlap was found between the groups. There were no statistically significant differences between the soft tissue depths of the sexes (P>0.05). These findings indicate that differences between male and female soft tissue depths are of little practical significance for craniofacial identification and, therefore, data (means, standard deviations, and sample sizes) reported for Australians were pooled across the sexes and the studies. Although these new pooled means have increased statistical power, data distributions at some landmarks were skewed and thus emphasis is placed on median and modes reported for this study rather than upon the collapsed data means.

Aged↗

PubMed2006

Beyond the sphere of the English facial approximation literature: ramifications of German papers on western method concepts.

In the English literature, facial approximation methods have been commonly classified into three types: "Russian,""American," or "Combination." These categorizations are based on the protocols used, for example, whether methods use average soft-tissue depths (American methods) or require face muscle construction (Russian methods). However, literature searches outside the usual realm of English publications reveal key papers that demonstrate that the Russian category above has been founded on distorted views. In reality, Russian methods are based on limited face muscle construction, with heavy reliance on modified average soft-tissue depths. A closer inspection of the American method also reveals inconsistencies with the recognized classification scheme. This investigation thus demonstrates that all major methods of facial approximation depend on both face anatomy and average soft-tissue depths, rendering common method classification schemes redundant. The best way forward appears to be for practitioners to describe the methods they use (including the weight each one gives to average soft-tissue depths and deep face tissue construction) without placing them in any categorical classificatory group or giving them an ambiguous name. The state of this situation may need to be reviewed in the future in light of new research results and paradigms.

Face↗

PubMed2005

Does sexual dimorphism in facial soft tissue depths justify sex distinction in craniofacial identification?

Separation of male and female soft tissue depths into discrete groups for craniofacial identification implies that males and females differ enough from each other, with respect to this application, for this distinction to be useful. In this study, previously published soft tissue depth data were analyzed for sex separation. It was found that the variation within each sex was large while the variation between the sexes was small. Often the value of two standard deviations of the measurement for either sex was larger than the difference displayed between the means of each sex. Furthermore, opposite sex overlap in regions defined to be close to the male or female mean were found to be large and the amount of variance explained by sex was small (less than 6% on average). These results indicate that while male and female means at single craniofacial landmarks may differ slightly, and even at statistically significant levels, individual male and female soft tissue depths are often the same or very similar. On average, soft tissue depths of the face do display some sexual dimorphism but it is not marked and of little practical meaning for craniofacial identification where a single individual must be independently considered. Thus, there is little use in separate reporting of data for males and females and data should be combined to increase sample sizes.

Adolescent↗

PubMed2005

Estimating eyeball protrusion from body height, interpupillary distance, and inter-orbital distance in adults.

Eyeball protrusion is one characteristic that must be assessed/predicted in craniofacial identification methods of skull-face superimposition and facial approximation. Previously it has been suggested that average exophthalmometry values, as measured on living individuals, should be used. However, it is unknown if proptosis prediction can be improved beyond the accuracy obtained when using mean values. Some authors have suggested that relationships between exophthalmos, height, interpupillary distance, and interorbital distance exist and it has been reported that these latter variables can be used to estimate eyeball projection. However, crucial tests are yet to be conducted. This study measures these variables and tests the accuracy of exophthalmometry means, a previously proposed prediction equation, and newly derived regression equations to determine which methods provide the best results. Data indicate that variation in exophthalmos is fairly small and as such prediction from other variables, like body height, are weak; thus, exophthalmometry means currently offer the best practical method of prediction. It should be noted that up to 2 mm error from either side of the mean is expected for 68% of cases.

Adult↗

PubMed2004

A new rig for standardized craniofacial photography put to the test.

This article describes and tests a photography rig that has been built at the University of Melbourne, Australia, specifically for the purpose of taking rapid and highly standardized craniofacial photographs, in simultaneous views of front and profile. The rig uses a novel projected light range-finding system that has been designed for easy and accurate positioning of subjects, in the natural head position, at precise distances from the frontal camera. Results of experiments examining the intraobserver error of multiple photographs taken on the rig indicate that high-quality, repeatable photographs can be taken after a reasonably large amount of time has lapsed between photography sessions (e.g., 30 days). This study also indicates that some variability remains between photographs even when highly standardized protocols are followed. Consequently, it is expected that the variation between photographs with limited standardization is much larger and more likely to cause significant errors in any comparisons.

Equipment Design↗

PubMed2003

Facial approximation: an evaluation of mouth-width determination.

Facial approximation techniques rely on the prediction of soft tissues from the skull, yet few prediction methods have been scientifically evaluated, despite being frequently used in the past. This study tests several published and commonly used methods for determining mouth width from the skull. The methods tested are: 1) that mouth width is equal to the distance between the pupils; 2) that mouth width is equal to the distance between the medial borders of the iris; and 3) that mouth width is equal to the distance between the most lateral junctions of the canines and the first premolars. The study primarily examines living Australian European and Central/South East Asian participants (of both sexes) using photogrammetric methods. The results of this study indicate that methods 1 and 3 are highly inaccurate. Method 1 overestimated mouth width, on average, by approximately 11 mm (SD, 4 mm), while method 3 underestimated mouth width by approximately 13 mm (SD, 3 mm). Method 2 was the most accurate of the methods evaluated, but on average underrepresented mouth width by approximately 2 mm (SD, 4 mm). All three methods produced mouth-width predictions that, in general, were statistically different from actual mouth widths (P < 0.05). A new guideline, describing mouth width as canine width plus 57% of the cumulative distance between the lateral canine borders and the pupil centers on each side was found not to differ at statistically significant levels from actual mouth widths (P > 0.05). On average, this guideline did not under/overestimate actual mouth width, with the difference between them being 0 mm (SD, 3 mm). The increased accuracy of this new guideline in comparison to others suggests that it is the most appropriate for facial approximation. However, it should be further tested using independent samples. The finding that commonly used mouth-width prediction guidelines are not accurate suggests that many facial approximations previously made have incorrect mouth widths. This could reduce the recognition of these facial approximations and may, especially if other guidelines are inaccurate, render the facial approximations unrecognizable as their respective target individual (individual to whom the skull belongs).

Adult↗

PubMed2003

Predicting nose projection and pronasale position in facial approximation: a test of published methods and proposal of new guidelines.

Many prediction guidelines exist in facial approximation for determining the soft-tissue features of the face, and the reliability of each is generally unknown. This study examines four published and commonly used soft-tissue prediction guidelines for estimating nose projection, two of which also estimate the position of the pronasale. The methods tested are those described by: 1) Gerasimov ([1971] The Face Finder; London: Hutchinson & Co.), using the distal third of the nasal bones and the nasal spine; 2) Krogman ([1962] The Human Skeleton in Forensic Medicine; Springfield: Charles C. Thomas), using the average soft-tissue depth at midphiltrum, plus three times the length of the nasal spine (and a variation of this technique: plus three times the distance of the tip of the nasal spine from the nasal aperture); 3) Prokopec and Ubelaker ([2002] Forensic Sci Commun 4:1-4), using the reflected profile line of the nasal aperture; and 4) George ([1987] J Forensic Sci 32:1305-1330), using a variation of the Goode method. Four identical hard-tissue tracings were made of 59 adult lateral head cephlograms (29 males, mean age 24, SD 10 years; 30 females, mean age 23, SD 5 years) on separate sheets of tracing paper. One soft-tissue tracing was also made for each radiograph. All tracings were marked with three identical reference points. Soft-tissue tracings were isolated from one of us (C.N.S.), who attempted under blind conditions to predict pronasale position and nose projection on the hard-tissue tracings, using the soft-tissue prediction guides above. Actual soft-tissue tracings were then compared to each of the predicted tracings, and differences in projection/pronasale position were measured. Results indicate that for nose projection, methods 3 and 4 performed well, while methods 1 and 2 performed poorly. Features which are most related to nose projection/pronasale are described in this paper, as are regression equations generated from these variables that predict pronasale/nose projection better than the traditional methods mentioned above. The results of this study are significant because they: 1) indicate that the popular facial approximation methods used to build the nose are inaccurate and produce incorrect nose anatomy; and 2) indicate that the new pronasale prediction methods developed here appear to have less error than traditional methods.

Adult↗

PubMed2003

Predicting mouth width from inter-canine width--a 75% rule.

It has been suggested that inter-canine width plus 57% of the cumulative distance between the lateral aspect of the canines and the pupil centers can be used to estimate mouth width. Evidence also suggests that the distance between the medial irises approximates actual mouth width fairly well. However, these soft tissue prediction guidelines are limited because they rely on accurate medio-lateral positioning of the pupils within the orbits, for which no systematic empirical evidence appears to exist at this stage. It would, therefore, be more appropriate to use only known hard tissue landmarks in mouth width prediction. This study reports the results of using inter-canine width as a percentage of mouth width for its prediction. This method seems favorable in comparison to the other guidelines because it is as accurate, uses known hard tissue landmarks, and does not rely on assumptions concerning pupil location. Estimating mouth width by using the canines alone, therefore, seems the best guideline to use in facial approximation techniques, at least given knowledge existing at this stage.

Anthropometry↗

PubMed2002

Do resemblance ratings measure the accuracy of facial approximations?

Since forensic facial approximations are used to promote recognition of a deceased person, an accurate forensic facial approximation (FFA) should be easily recognized as the person to whom the skull belonged (target individual). However, the accuracy of FFAs has been previously assessed by the direct comparison of an FFA to the corresponding target individual for similarity (i.e., a resemblance rating). Resemblance ratings may not indicate a facial approximation's accuracy since the resemblance of non-target individuals is not accounted for. This experiment tests the validity of using resemblance ratings to assess the accuracy of FFAs. The study indicates that there is no statistically significant difference between: (a) resemblance ratings of FFAs to target individuals and (b) resemblance ratings of FFAs to individuals incorrectly identified as the target individual. It is concluded that it is not possible from resemblance ratings to determine the accuracy and/or quality of a facial approximation since a non-target individual may receive a resemblance rating equal to, or higher than, the target individual.

Cephalometry↗

PubMed2002

Facial approximation: globe projection guideline falsified by exophthalmometry literature.

The projection of the cornea from the bony orbit has been determined, in facial approximation, by centrally locating the eyeball in the orbit and positioning the cornea so that its most anterior point falls in line with a tangent dropped from the mid-superior to the mid-inferior orbital rim. However, there appears to be no scientific evidence to justify this guideline; yet, there have been numerous studies that measure globe projection in living subjects, from the lateral orbit using an exophthalmometer. The aim of this study was to determine if the traditional facial approximation guideline is consistent with the exophthalmometry literature. MRI research shows that corneal projection is underestimated using the traditional facial approximation guideline. An underestimation is also strongly supported by statistical comparisons of globe projection measures taken using more traditional instruments (e.g., Hertel's exophthalmometer) to skull morphology (p < 0.006). It is suggested that the traditional facial approximation guideline not be used in future facial approximations since it appears to under-predict anterior globe projection by 4 mm on average. It is also suggested that average exophthalmometer values be used until more accurate and precise ways of determining globe projection have been determined.

Anthropometry↗