Reliability of cephalometric landmark identification on three-dimensional computed tomographic images

Long-term skeletal, cephalometric, and volumetric changes in two Helsinki bimaxillary face transplant patients

Analysis of skeletal, cephalometric, and volumetric changes and occlusion during long-term follow-up was performed for two patients who underwent bimaxillary facial transplantation (FT). The study material consisted of the follow-up data of two bimaxillary composite FT performed in Helsinki University Hospital, one in 2016 and the other in 2018. Serial three-dimensional computed tomography scans obtained during follow-up (6 years for patient 1, 4 years for patient 2) were analyzed. The position of the maxilla remained stable in both patients. At 4 and 6 years, the changes in the anterior maxilla were ≤1 mm, while the anterior mandible had moved 2.6-4 mm anteriorly and the mandibular midline 0.4-3.7 mm to the left side. Patient 1 underwent re-osteosynthesis 4 months after transplantation due to mandibular non-union. Patient 2 had a sagittal mandibular osteotomy at 15 months after FT due to lateral crossbite and tension created by temporomandibular joint rotation. Thereafter both patients had a stable occlusion. A continuous bone volume reduction in the mandible was noticed in both patients (6% and 9% reduction of the transplanted volume). The volume of the transplanted maxilla decreased during the early postoperative period but increased back to the original transplanted volume during the follow-up.

LOW CERTAINTY OF EVIDENCE SUPPORTS THE APPLICATION OF (AI) FOR THE AUTOMATIC DETECTION OF CEPHALOMETRIC LANDMARKS WITH PROSPECTS FOR IMPROVEMENTS

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION

Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis. J Digit Imaging. 2023 Jun;36(3):1158-1179. doi:10.1007/s10278-022-00766-w.

SOURCE OF FUNDING

The study was financed in part by the Coordenacao de Aperfeicoamentode Pessoal de Nivel Superior-Brazil (CAPES)-Finance Code 001.

TYPE OF STUDY/DESIGN

Systematic review and meta-analysis.

Shape variation and sex differences of the adult human mandible evaluated by geometric morphometrics

In cases of osseous defects, knowledge of the anatomy, and its age and sex-related variations, is essential for reconstruction of normal morphology. Here, we aimed at creating a 3D atlas of the human mandible in an adult sample using dense landmarking and geometric morphometrics. We segmented 50 male and 50 female mandibular surfaces from CBCT images (age range: 18.9-73.7 years). Nine fixed landmarks and 510 sliding semilandmarks were digitized on the mandibular surface, and then slid by minimizing bending energy against the average shape. Principal component analysis extracted the main patterns of shape variation. Sexes were compared with permutation tests and allometry was assessed by regressing on the log of the centroid size. Almost 49 percent of shape variation was described by the first three principal components. Shape variation was related to width, height and length proportions, variation of the angle between ramus and corpus, height of the coronoid process and inclination of the symphysis. Significant sex differences were detected, both in size and shape. Males were larger than females, had a higher ramus, more pronounced gonial angle, larger inter-gonial width, and more distinct antegonial notch. Accuracy of sexing based on the first two principal components in form space was 91 percent. The degree of edentulism was weakly related to mandibular shape. Age effects were not significant. The resulting atlas provides a dense description of mandibular form that can be used clinically as a guide for planning surgical reconstruction.

Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis

Using computer vision through artificial intelligence (AI) is one of the main technological advances in dentistry. However, the existing literature on the practical application of AI for detecting cephalometric landmarks of orthodontic interest in digital images is heterogeneous, and there is no consensus regarding accuracy and precision. Thus, this review evaluated the use of artificial intelligence for detecting cephalometric landmarks in digital imaging examinations and compared it to manual annotation of landmarks. An electronic search was performed in nine databases to find studies that analyzed the detection of cephalometric landmarks in digital imaging examinations with AI and manual landmarking. Two reviewers selected the studies, extracted the data, and assessed the risk of bias using QUADAS-2. Random-effects meta-analyses determined the agreement and precision of AI compared to manual detection at a 95% confidence interval. The electronic search located 7410 studies, of which 40 were included. Only three studies presented a low risk of bias for all domains evaluated. The meta-analysis showed AI agreement rates of 79% (95% CI: 76-82%, I2 = 99%) and 90% (95% CI: 87-92%, I2 = 99%) for the thresholds of 2 and 3 mm, respectively, with a mean divergence of 2.05 (95% CI: 1.41-2.69, I2 = 10%) compared to manual landmarking. The menton cephalometric landmark showed the lowest divergence between both methods (SMD, 1.17; 95% CI, 0.82; 1.53; I2 = 0%). Based on very low certainty of evidence, the application of AI was promising for automatically detecting cephalometric landmarks, but further studies should focus on testing its strength and validity in different samples.

An automated landmark method to describe geometric changes in the human mandible during growth

OBJECTIVE

The principal aim of this study was to assess an automatic landmarking approach to human mandibles based on the atlas method. The secondary aim was to identify the areas of greatest variation in the mandibles of middle-aged to older adults.

DESIGN

Our sample consisted of 160 mandibles from computed tomography scans of 80 men and 80 women aged between 40 and 79 years. Eleven anatomical landmarks were placed manually on mandibles. The automated landmarking through point cloud alignment and correspondence (ALPACA) method implemented in 3D Slicer was used to automatically place landmarks to all meshes. Euclidean distances, normalized centroid size, and Procrustes ANOVA were calculated for both methods. A pseudo-landmarks approach was followed using ALPACA to identify areas of changes among our sample.

RESULTS

The ALPACA method showed significant differences in Euclidean distances for all landmarks compared to the manual method. A mean Euclidean distance of 1.7 mm was found for the ALPACA method and 0.99 mm for the manual method. Both methods found that sex, age, and size had a significant effect on mandibular shape. The greatest variations were observed in the condyle, ramus, and symphysis regions.

CONCLUSION

The results obtained using the ALPACA method are acceptable and promising. This approach can automatically place landmarks with an average accuracy of less than 2 mm, which may be sufficient in most anthropometric analyses. In the light of our results, however, odontological application such as occlusal analysis is not recommended.

Accuracy of a surface-based fusion method when integrating digital models and the cone beam computed tomography scans with metal artifacts

The aim of this study was to evaluate the intra- and inter-observer reliability of maxillary digital dental model integration into cone-beam computed tomography (CBCT) scans to reconstruct three-dimensional (3D) skeletodental models for orthognathic patients. This retrospective study consisted of CBCT and digital maxillary dentition images of 20 Class III orthognathic patients. After two repeated fusions of digital cast images with reconstructed CBCT images by a digital engineer and an orthodontist respectively, the 3D coordinate values of the canines, first molars, and central incisors were evaluated. The intra- and inter-observer reliability of 3D positions of maxillary teeth were compared using intraclass correlation coefficients (ICCs). Intra-observer reliability of x-, y-, and z-coordinate values of maxillary teeth showed significant and excellent agreement in an engineer (0.946 ≤ ICC ≤ 1.000) and an orthodontist (0.876 ≤ ICC ≤ 1.000). The inter-observer reliability of the y- and z-coordinates of each tooth was significantly excellent or good, but that of the x-coordinates showed insignificantly poor to moderate agreement. This study showed that the integration of maxillary digital models into CBCT scans was clinically reliable. However, considering the low inter-observer reliability on the x-coordinates of dentition, clinical experience and repeated learning are needed for accurate application of digital skeletodental model in orthognathic patients.