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. 2023 Sep 20:19:101714.
doi: 10.1016/j.bonr.2023.101714. eCollection 2023 Dec.

Three-dimensional morphometric analysis of cranial sutures - A novel approach to quantitative analysis

Affiliations

Three-dimensional morphometric analysis of cranial sutures - A novel approach to quantitative analysis

Ross Remesz et al. Bone Rep. .

Abstract

Objective: Differences in complexity of cranial suture forms on the endocranial (i.e., deep) and ectocranial (i.e., superficial) skull surfaces have been noted in the literature, indicating through thickness three-dimensional (3D) suture variability depending on the chosen section and necessity for considering the complete 3D structure in many cases. This study aims to evaluate the variability of suture morphology through the skull thickness using a rat model, and to provide more robust metrics and methodologies to analyze suture morphology.

Design: X-ray micro-computed tomographic (μCT) imaging methods were utilized in order to provide internal structure information. Methods were developed to isolate and analyze sutures widths and linear interdigitation index (LII) values on each adjacent offset transverse plane of the μCT datasets. LII was defined as the curved path length of the suture divided by the linear length between the ends of the region of interest. Scans were obtained on 15 female rats at ages of 16, 20, and 24 weeks (n = 5/age). Samples were imaged at 18 μm resolutions with 90 kV source voltage, 278 μA source amperage, and 0.7° increments. Suture widths and LII values were compared using a Kruskal-Wallis test.

Results: 3D variability in local suture widths within individuals, as well as through thickness variabilities in planar widths and LII was observed. Kruskal-Wallis tests for bulk through thickness averaged suture widths and LII were found to be statistically insignificant, despite clear geometric differences through suture thicknesses.

Conclusion: Although the bulk morphometric variability between age groups was found to be statistically insignificant, the 3D variability within individuals point to the importance of analyzing suture form using 3D metrics when studying suture development, response to functional activity, or morphometry in general.

Keywords: Computed tomography; Cranial suture; Image analysis; Linear interdigitation index; Morphology.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
A representative schematic showing sutures of interest, including the coronal (green), sagittal (blue), anterior lambdoid (red), and posterior lambdoid (orange). The approximate regions of interest are labeled as follows: 1, right-hand side coronal (C RHS); 2, left-hand side coronal (C LHS); 3, sagittal (S); 4, left-hand side anterior lambdoid (A RHS); 5, right-hand side anterior lambdoid (A LHS); and 6, posterior lambdoid (PL). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 2
Fig. 2
A sample of the DataViewer interface used for reorienting datasets. A single plane of the output dataset for the posterior lambdoid suture is shown in the transaxial plane. The location of the transaxial image in this instance can be seen in the sagittal and coronal planes.
Fig. 3
Fig. 3
Image processing of the posterior lambdoid suture from a 24-week-old female SD rat. (a) Cropped image of reoriented scan; (b) Histogram equalized; (c) Adjusted; (d) Binarized; (e) Filled; (f) Morphologically opened; (g) Segmentation, black to white; (h) Segmentation, white to black, final binary image; (i) Isolated suture area (65 % transparency) shown in (h) overlay on cropped image shown in (a).
Fig. 4
Fig. 4
Analysis of processed binary image of the posterior lambdoid suture from a 24-week-old female SD rat. (a) Analysis code in progress (early); (b) Analysis code in progress (middle); (c) Completed analysis; (d) Overlay of quantitative analysis on cropped image, suture length and linear length marked.
Fig. 5
Fig. 5
Representative local planar widths along planar suture outline of the posterior lambdoid suture from a 24-week-old female SD rat.
Fig. 6
Fig. 6
Representative 3D centerlines of suture regions of interest from a single sample, scale is in μm. LHS = left-hand side, RHS = right-hand side.
Fig. 7
Fig. 7
16-week-old rats: Planar linear interdigitation index (LII). LHS = left-hand side, RHS = right-hand side.
Fig. 8
Fig. 8
20-week-old rats: Planar linear interdigitation index (LII). LHS = left-hand side, RHS = right-hand side.
Fig. 9
Fig. 9
24-week-old rats: Planar linear interdigitation index (LII). LHS = left-hand side, RHS = right-hand side.
Fig. 10
Fig. 10
16-Week-old rats: Mean planar widths. LHS = left-hand side, RHS = right-hand side.
Fig. 11
Fig. 11
20-Week-old rats: Mean planar widths. LHS = left-hand side, RHS = right-hand side.
Fig. 12
Fig. 12
24-Week-old rats: Mean planar widths. LHS = left-hand side, RHS = right-hand side.
Fig. 13
Fig. 13
Mean suture linear interdigitation index (LII) boxplots for suture regions of interest, grouped by age (16, 20, 24 week-of-age). LHS = left-hand side, RHS = right-hand side.
Fig. 14
Fig. 14
Mean suture width boxplots for suture regions of interest, grouped by age (16, 20, 24 week-of-age). LHS = left-hand side, RHS = right-hand side.

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