Comparability of skeletal fibulae surfaces generated by different source scanning (dual‐energy CT scan vs. high resolution laser scanning) and 3D geometric morphometric validation

Abstract

This work aims to test accuracy and comparability of 3D models of human skeletal fibulae generated by clinical CT and laser scanner virtual acquisitions. Mesh topology, segmentation and smoothing protocols were tested to assess variation among meshes generated with different scanning methods and procedures, and to evaluate meshes‐interchangeability in 3D geometric morphometric analysis. A sample of 13 left human fibulae were scanned separately with Revolution Discovery CT dual energy (0.625 mm resolution) and ARTEC Space Spider 3D structured light laser scanner (0.1 mm resolution). Different segmentation methods, including half‐maximum height (HMH) and MIA‐clustering protocols, were compared to their high‐resolution standard generated with laser‐scanner by calculating topological surface deviations. Different smoothing algorithms were also evaluated, such as Laplacian and Taubin smoothing. A total of 142 semilandmarks were used to capture the shape of both proximal and distal fibular epiphyses. After Generalized Procrustes superimposition, the Procrustes coordinates of the proximal and distal fibular epiphyses were used separately to assess variation due to scanning methods and the operator error. Smoothing algorithms at low iteration do not provide significant variation among reconstructions, but segmentation protocol may influence final mesh quality (0.09–0.24 mm). Mean deviation among CT‐generated meshes that were segmented with MIA‐clustering protocol, and laser scanner‐generated ones, is optimal (0.42 mm, ranging 0.35–0.56 mm). Principal component analysis reveals that homologous samples scanned with the two methods cluster together for both the proximal and distal fibular epiphyses. Similarly, Procrustes ANOVA reveals no shape differences between scanning methods and replicates, and only 1.38–1.43% of shape variation is due to scanning device. Topological similarities support the comparability of CT‐ and laser scanner‐generated meshes and validate its simultaneous use in shape analysis with potential clinical relevance. We precautionarily suggest that dedicated trials should be performed in each study when merging different data sources prior to analyses.

Sexual Dimorphism in the Fibular Extremities of Italians and South Africans of Identified Modern Human Skeletal Collections: A Geometric Morphometric Approach

“…The specimens were either digitized through computed tomography (CT) or laser scanning, as previous studies have shown that digital models of long bones from these two acquisition methods are comparable [ 37 , 38 , 39 ]. The acquisition of the 3D models of fibulae belonging to the Raymond A.…”

“… Landmarks (black), curve (light blue), and surface (semi)landmarks (orange) digitized on a left fibula ( A ), proximal fibula, medial view; ( B ), proximal fibula, lateral view; ( C ), proximal fibula, posteromedial view; ( D ), distal fibula, medial view; ( E ), distal fibula, lateral view; ( F ), distal fibula, posterior view. See Table 2 for a detailed description of the anatomical landmarks [ 37 ] (license: CC BY 4.0). …”

“…Data from CT scans were processed in Avizo 9.2 (Thermo Fisher Scientific, Waltham, MA, USA) for image segmentation, utilizing the threshold-based segmentation protocol of half-maximum height (HMH) outlined by Spoor, Zonneveld, and Macho (1993) [40]. We applied the protocol following the modified version detailed by Coleman and Colbert (2007) [41], already used in several applications in anthropology (e.g., [37,42,43]). Then, a surface model was generated (isosurface reconstructions), saved in STL format, and loaded into Viewbox 4 v. 4.0 (dHAL Software, Kifissia, Greece) for landmarking.…”

“…Following that, (semi)landmarks can be considered geometrically homologous among specimens [45,46]. The template repeatability (i.e., high intra-observer agreement) and reproducibility with different scanning devices were tested [37]. This work revealed that for this template (1) the intra-observer error is negligible, (2) and that the 3D-GM comparisons of specimens scanned with different scanning devices are not influenced by repeating the template on the same individual (intra-observer error).…”

“…This permutation design allows one to avoid Type I error and normality violations. 2 for a detailed description of the anatomical landmarks [37] (license: CC BY 4.0).…”