Cranial morphology in metopism: A comparative geometric morphometric study

BACKGROUND

Cranial sutures are active bone growth sites and any alteration in their normal formation, patency and closure influences the overall cranial morphology. This comparative study aims to establish whether the cranial shape and size are significantly modified when metopic suture persists into adulthood using geometric morphometric analyses.

METHODS

The sample consisted of 63 metopic and 184 non-metopic dry adult male crania. Three-dimensional polygonal models of the crania were generated using a hand-held laser scanner Creaform VIUscan. A total of 50 landmarks were digitized on the three-dimensional models and eight landmark configurations delineating the cranium and its compartments were constructed and analyzed. Geometric morphometric analyses were applied to investigate separately the size and shape differences between the metopic and non-metopic series in each of the landmark configurations.

RESULTS

Significant size differences were established solely in the neurocranium, but not in its total size, rather in its parts. The size modification was expressed by an enlargement of the anterior part of the neurocranium at the expense of the middle and posterior ones. All investigated landmark sets differed significantly between the series regarding the shape. In metopic series, the shape alteration was mainly in a mediolateral widening and an anteroposterior shortening contributing to a more rounded overall shape of the cranium.

CONCLUSIONS

The slight modification of the cranial morphology in metopism suggests that the metopic suture persistence is not an isolated variation limited to the frontal bone. It is rather a complex condition associated with a combination of specific phenotypic characteristics.

How does scanner choice and 3D model resolution affect data accuracy?

Researchers using digital methods often collect data from 3D models at different resolutions, obtained using different scanning techniques. Although previous research has sought to understand whether scanning method and model resolution affect data accuracy, no study has systematically evaluated the sources of error associated with scanning method, data acquisition method and model resolution with the aim of providing practical recommendations about the model resolution required to yield sufficiently accurate data for specimens of given sizes. In this study, using data taken from primate specimens of three broad size categories, we test whether 3D models obtained using five different scanners (Breuckmann SmartSCAN, DAVID/HP 3D Pro S3, NextEngine 2020i, Creaform Go!Scan 20 and microCT/clinicalCT) yield accurate measurements. We assess whether caliper measurements can be used alongside measurements collected from 3D surface models, whether scanning resolution affects measurement accuracy, and how scan resolution, estimated using each scanner's proprietary software, compares to model resolution measured in a standardized way. Each scanner produces 3D models that yield accurate measurements for each size category, however, combining caliper data with those taken from digital models can be problematic. Our results indicate that the accuracy of measurements taken from 3D models depends on both object size and model resolution. Based on our findings, we recommend that small specimens should be scanned at <0.3 mm, medium specimens at 0.3-0.7 mm, and large specimens at 0.3-0.5 mm resolutions if data taken from 3D surface models are to be combined with caliper datasets. We further show, for the first time, that discrepancies in estimated final model resolution are frequently observed across software packages. We therefore recommend that researchers ensure that final model resolutions are adequate based on specimen size and are independently verified using a software package other than the scanner's proprietary software. Finally, we consider the implications of the findings that measurements obtained from surface models are variably consistent with those obtained using calipers.

Data mining for sex estimation based on cranial measurements

The aim of the present study is to develop effective and understandable classification models for sex estimation and to identify the most dimorphic linear measurements in adult crania by means of data mining techniques. Furthermore, machine learning models and models developed through logistic regression analysis are compared in terms of performance. Computed tomography scans of 393 adult individuals were used in the study. A landmark-based approach was applied to collect the metric data. The three-dimensional coordinates of 47 landmarks were acquired and used for calculation of linear measurements. Two datasets of cranial measurements were assembled, including 37standard measurements and 1081 interlandmark distances, respectively. Three data mining algorithms were applied: the rule induction algorithms JRIP and Ridor, and the decision tree algorithm J48. Two advanced attribute selection methods (Weka BestFirst and Weka GeneticSearch) were also used. The best accuracy result (91.9 %) was achieved by a set of rules learnt by the JRIP algorithm from the dataset constructed by application of the GeneticSearch selection algorithm to the dataset of standard cranial measurements. The set consisted of five rules including seven cranial measurements. Its accuracy was even better than the classification rates achieved by the logistic regression models. Concerning the second dataset of nonstandard measurements, the best accuracy (88.3 %) was obtained by using classification models learnt by two algorithms - JRIP with a dataset preprocessed by the BestFirst selection algorithm and Ridor with preprocessing by the GeneticSearch selection algorithm. Our experiments show that for the two datasets mentioned above the rule-based models contain smaller sets of rules with shorter lists of measurements and achieve better classification accuracy results in comparison with decision tree-based models.