Comparison of 2 root surface area measurement methods: 3-dimensional laser scanning and cone-beam computed tomography

Automatic tooth periodontal ligament segmentation of cone beam computed tomography based on instance segmentation network

Objective

The three-dimensional morphological structures of periodontal ligaments (PDLs) are important data for periodontal, orthodontic, prosthodontic, and implant interventions. This study aimed to employ a deep learning (DL) algorithm to segment the PDL automatically in cone-beam computed tomography (CBCT).

Method

This was a retrospective study. We randomly selected 389 patients and 1734 axial CBCT images from the CBCT database, and designed a fully automatic PDL segmentation computer-aided model based on instance segmentation Mask R-CNN network. The labels of the model training were 'teeth' and 'alveolar bone', and the 'PDL' is defined as the region where the 'teeth' and 'alveolar bone' overlap. The model's segmentation performance was evaluated using CBCT data from eight patients outside the database.

Results

Qualitative evaluation indicates that the PDL segmentation accuracy of incisors, canines, premolars, wisdom teeth, and implants reached 100%. The segmentation accuracy of molars was 96.4%. Quantitative evaluation indicates that the mIoU and mDSC of PDL segmentation were 0.667 ± 0.015 (>0.6) and 0.799 ± 0.015 (>0.7) respectively.

Conclusion

This study analysed a unique approach to AI-driven automatic segmentation of PDLs on CBCT imaging, possibly enabling chair-side measurements of PDLs to facilitate periodontists, orthodontists, prosthodontists, and implantologists in more efficient and accurate diagnosis and treatment planning.

Effects of the cone-beam computed tomography protocol on the accuracy and image quality of root surface area measurements: An in vitro study

Purpose

The objective of this study was to evaluate and compare the accuracy and image quality of root surface area (RSA) measurements obtained with various cone-beam computed tomography (CBCT) protocols, relative to the gold standard of micro-computed tomography (CT), in an in vitro setting.

Materials and Methods

Four dry human skulls were scanned using 8 different protocols, with voxel sizes of 0.15 mm, 0.3 mm, and 0.4 mm. Three-dimensional models of the selected teeth were constructed using CBCT and micro-CT protocols, and the RSA was automatically measured by the image-processing software. The absolute difference in the percentage of the RSA (%ΔRSA) was calculated and compared across the 8 CBCT protocols using repeated-measures analysis of variance. Finally, image quality scores of the RSA measurements were computed and reported in terms of percent distribution.

Results

No significant differences were observed in the %ΔRSA across the 8 protocols (P>0.05). The deviation in %ΔRSA ranged from 1.51% to 4.30%, with an increase corresponding to voxel size. As the voxel size increased, the image quality deteriorated. This decline in quality was particularly noticeable at the apical level of the root, where the distribution of poorer scores was most concentrated.

Conclusion

Relative to CBCT protocols with voxel sizes of 0.15 mm and 0.3 mm, the protocols with a voxel size of 0.4 mm demonstrated inferior image quality at the apical levels. In spite of this, no significant discrepancies were observed in RSA measurements across the different CBCT protocols.

Evaluation of the accuracy of cone-beam computed tomography image segmentation of isolated tooth roots based on the dynamic threshold method

OBJECTIVE

Accurate quantification of the root surface area (RSA) plays a decisive role in the advancement of periodontal, orthodontic, and restorative treatment modalities. In this study, we aimed to develop a dynamic threshold-based computer-aided system for segmentation and calculation of the RSA of isolated teeth on cone-beam computed tomography (CBCT) and to assess the accuracy of the measured data.

METHOD

We selected 24 teeth to be extracted, including single-rooted and multi-rooted teeth, from 22 patients who required tooth extraction. In the experimental group, we scanned 24 isolated teeth using CBCT with a voxel size of 0.3 mm. We designed a computer-aided system based on a personalized dynamic threshold algorithm to automatically segment the roots of 24 isolated teeth in CBCT images and calculate the RSA. In the control group, we employed digital intraoral scanner devices to perform optical scanning on 24 isolated teeth and subsequently manually segmented the roots using 3-matic software to calculate the RSA. We used the paired t-test (P < 0.05) and Bland-Altman plots to analyze the consistency of the two measurement methods.

RESULTS

The results of the paired t-test showed that there was no significant difference in the RSAs obtained using the dynamic threshold method and the optical scanning image reconstruction (t = 1.005, P = 0.325 > 0.05). As per the Bland-Altman plot, the results were evenly distributed within the region of ± 1.96 standard deviations of the mean, with no increasing or decreasing trends and good consistency.

CONCLUSION

In this study, we designed a computer-aided root segmentation system based on a personalized dynamic threshold algorithm to automatically segment the roots of isolated teeth in CBCT images with a voxel size of 0.3 mm. We found that the RSA calculated using this approach was highly accurate, and a voxel of 0.3 mm in size could accurately display the surface area data in CBCT images. Overall, our findings in this study provide a foundation for future work on accurate automatic segmentation of tooth roots in full-mouth CBCT images and the computation of RSA.

Root surface areas of maxillary permanent teeth in anterior normal overbite and anterior open bite assessed using cone-beam computed tomography

Purpose

The aim of this study was to compare the root surface areas of the maxillary permanent teeth in Thai patients exhibiting anterior normal overbite and in those exhibiting anterior open bite, using cone-beam computed tomography (CBCT).

Materials and Methods

CBCT images of maxillary permanent teeth from 15 patients with anterior normal overbite and 18 patients with anterior open bite were selected. Three-dimensional tooth models were constructed using Mimics Research version 17.0. The cementoenamel junction was marked manually. The root surface area was calculated automatically by 3-Matic Research version 9.0. The root surface areas of each tooth type from both types of bite were compared using the independent t-test (P<.05). The intraclass correlation coefficient was used to assess intraobserver reliability.

Results

The mean root surface areas of the maxillary central and lateral incisors in individuals with anterior open bite were significantly less than those in those with normal bite. The mean root surface area of the maxillary second premolar in individuals with anterior open bite was significantly greater than in those with normal bite.

Conclusion

Anterior open-bite malocclusion might affect the root surface area, so orthodontic force magnitudes should be carefully determined.