PhD Scientific Days 2021

Budapest, 7-8 July 2021

TT_III_L: Theoretical and Translational Medicine III. Lectures

The role of palatal geometry in gender discrimination and human identification

Text of the abstract

IntroductionThe features of the 3D palate could be classified into two categories; the geometry feature such as curvature, width, depth, and height, and the surface morphology such as the palatal rugae. The three-dimensional digitalized palate makes it possible to accomplish precise geometrical measurements and develop automatic pattern recognition methods by artificial intelligence
aims to investigate the role of the ruga pattern and the geometry of the palatine vault separately in shaping individual characteristics. We wanted to use the palatal vault geometry parameters (height, width, depth) to construct a linear discriminative equation to separate individual, sibling relatedness, and gender
MethodThree replicates of 61 MZ twin pairs and 26 DZ twin pairs of three scions, totaling 522 scions, were used in the measurement. We improvised the scans one by one into the GOM software and digitally measured the height, width, and depth of the palatal vault after assigning landmarks and planes. Absolute differences in the measured parameters were calculated between two siblings, between all individuals, and between 3 scan replicates per individual, forming about 15000 pairs. Based on the three-parameter differences, we performed a linear discriminant analysis and calculated the probabilities of separation
ResultsThe linear discriminant analysis for gender classification produced a function with significant Wilks'Lambda (0.66, p<0.001). The unstandardized function parameters were as follows, gender=0.54 × height + 0.06 × depth + 0.21 × width - 17.3. In the structure correlation matrix the height had highest value (r=0.83), followed by the width (r=0.37) and depth (r=0.24). The group centroid was -0.40 for females and 1.28 for males. 74 females from the 90 (82.2%) were classified correctly as female, and 25 males from the 28 (89.3%) classified correctly as male.
ConclusionThe height might be the best predictor for gender, identity and zygosity. As height factor is primarly determined by shared environment, it indicates that higher the shared environment effect, higher the discriminant potential. Due to its high genetic influence, it might be good for ethnic/race determination
Funding Supported by the ÚNKP-20-3-SE-23 New National Excellence Program Of The Ministry For Innovation And Technology from the source of the National Research, Development and Innovation Fund

University and Doctoral School

Semmelweis University, Károly Rácz Doctoral School of Clinical Medicine