Introduction
Bone regeneration around teeth is a consequence of complex bone remodeling which involves a balance of resorption of mineralized bone and formation of new bone matrix [
1‐
3]. Evaluation and quantification of bone micromorphometry around teeth can be of interest in the orthodontic field, but also to assess bone regeneration at periodontally compromised teeth [
4]. For this purpose, histological examinations were frequently employed [
5‐
9]. Major drawbacks of histological approaches, however, are the limitation to two dimensions and information loss during undecalcified sectioning. In addition, bone microstructure may largely vary with respect to the cutting position. Eventually, most histological analyses are limited to end-point analyses [
10‐
12].
In contrast, microcomputed tomography (micro-CT) is a nondestructive alternative overcoming the above-mentioned limitations. It provides high-resolution volumetric images and enables three-dimensional (3D) analyses of bone microstructural properties [
13‐
15]. For small animals, the dynamics of bone remodeling can be studied even longitudinally by means of in vivo micro-CT. If only end-point analyses are possible, corresponding contralateral sites can be compared instead [
16,
17].
To perform 3D quantitative and qualitative analyses of hard tissue around teeth, segmentation of the alveolar bone and definition of standardized volumes of interest (VOIs) is mandatory. This step can be challenging when histograms from bone, cement and dentin overlap [
18]. Therefore, the majority of previous micro-CT studies performed linear measurements in two-dimensional (2D) slices around teeth or defined a rectangular VOIs between tooth roots to analyze the alveolar bone microstructural properties [
19,
20]. To the best knowledge of the authors, no methods have been reported for standardized automated analyses of the alveolar bone around teeth/periodontal ligament space.
The marker-based Watershed algorithm (WS) has been described in the literature as a tool to segment tissues with overlapping histograms in volumetric radiographic images [
21,
22]. After placement of different markers at each anatomical structure, they will be enlarged until reaching the closest edge. Eventually, a labeled image is created that can be used for standardized definitions of VOIs and microstructural analyses.
Therefore, the present study aimed at presenting and validating a novel WS-based method for automated and standardized assessment of bone micromorphometry around tooth roots following orthodontic tooth movement in split-mouth preclinical animal studies.
Discussion
Microstructural analyses of bone in conventional histology are limited to two dimensions and crucially depend on the selected cutting position. Whereas histology provides valuable information on the cell level, micro-CT has been reported to be an accurate and complementary technique to assess bone remodeling in all three dimensions [
11,
13]. In case of overlapping histograms from bone and teeth, bone segmentation can be challenging and may require advanced methodologies. To allow quantitative comparisons, standardized definition of a volume of interest (VOI) is required. In previous studies, linear 2D measurements and cubic VOIs have been frequently applied. However, no automated and standardized approaches have been reported for reliable segmentation and definition of standardized VOIs around tooth roots. Therefore, the present study aimed at presenting and validating a method for automated and standardized assessment of bone micromorphometry around tooth roots, and to apply the novel method to micro-CT scans from a preclinical animal study performing orthodontic tooth protraction in mice. The respective 2D measurements have been published previously [
20].
The intraclass correlation coefficient amounted to 0.99 and confirmed the high reliability of the novel approach.
When comparing BV/TV values between contralateral sites in the untreated animals (Method part), Bland–Altman analyses revealed negligible differences of 1.72% in the upper, and of 2.15% in the lower jaw. Nevertheless, it has to be noted that BV/TV values were slightly more heterogeneous in the lower jaw. The differences between animals were greater than differences between contralateral sites and amounted to 3.17% ± 1.23% in the upper jaw and 2.00% ± 0.71% in the lower jaw.
Application of the novel method (Application part) revealed significantly lower BV/TV values at protracted molars compared to the contralateral control sites, probably resulting from bone resorption in the pressure zones, and less mineralized newly formed bone at the tension zones.
Undecalcified regions were mostly found in proximity to the tooth root and decreased towards the borders of the 100 µm VOI, suggesting that bone resorption was highest in close proximity to the roots but still present in the selected region. In addition, bone resorption was highest at the mesial roots which is in line with a recent 3D analysis showing that intrusion and mesial–palatal tipping was the most common movement of the protracted teeth [
26].
Nonetheless, definition of a reliable VOI is challenging. It has to be large enough to be representative, whereas on the other hand, it must not exceed the jawbone. Furthermore, it should be limited to the areas in which bone remodeling occurs. In the present study, a diameter of 100 μm was found to be optimal, as this was the maximum possible size giving the boundaries of the jawbone. The Application part confirmed that bone remodeling occurred in the VOIs, which demonstrated that the analyzed regions were not too small.
When comparing the present findings with the previously published data, it has to be noted that no significant differences in vertical bone loss could be found in the previously published 2D measurements [
20]. In contrast, the present analysis revealed a significant decrease of BV/TV at the test site. In addition, it revealed that bone loss was most pronounced at the mesial root and decreased towards periphery. Hence, we believe that this novel approach is a valuable tool to better understand volumetric changes in bone micromorphology following orthodontic tooth movements.
Limitations of the present investigation include the lack of longitudinal data; thus, different animals were used for method validation, and the comparison of the test and control sites after 11 days of molar protraction. Furthermore, the study design did not allow differentiation of whether the minor BV/TV differences between animals from the Method part resulted from differences in genetic background, age, or were related to the orthodontic appliance which might have impaired food intake. In addition, analyses were limited to assessment of BV/TV values. Additional parameters such as trabecular thickness, bone mineral density, bone surface area or trabecular spacing may be calculated in future studies utilizing the presented approach to understand the impact of genetic disorders, metabolic diseases or drug intake on bone remodeling during orthodontic treatments.
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