Objectives: Conventional two-dimensional (2D) cephalometric radiography is an integral part of orthodontic patient diagnosis and treatment planning. One must be mindful of its limitations as it indeed is a 2D representation of a vaster three-dimensional (3D) object. Issues with projection errors, landmark identification, and measurement inaccuracies impose significant limitations, which may now be overcome with the advent of cone-beam computed tomography (CBCT). A systematic review of the reliability of different 3D cephalometric landmarks in CBCT imaging was conducted. Materials and Methods: Electronic database searches were administered until October 2017 using PubMed, MEDLINE via OvidSP, EBMR and EMBASE via OvidSP, Scopus, and Web of Science. Google Scholar was used as an adjunctive search tool. Results: Thirteen articles considering CBCT scans of human subjects from preexisting data sets were selected and reviewed. Most of the studies had methodological limitations and were of moderate quality. Because of their heterogeneity, key data from each could not be combined and were reported qualitatively. Overall, in 3D, midsagittal plane landmarks demonstrated greater reliability compared with bilateral landmarks. A minimum number of dental landmarks were reported, although most were recommended for use. Conclusions: Further research is required to evaluate the reliability of 3D cephalometric landmarks when evaluating 3D craniofacial complexes.

Objective: The purpose of this study was to determine a conversion coefficient for Hounsfield Units (HU) to material density (g cm−3) obtained from cone-beam computed tomography (CBCT-NewTom QR-DVT 9000) data. Methods: Six cylindrical models of materials with different densities were made and scanned using the NewTom QR-DVT 9000 Volume Scanner. The raw data were converted into DICOM format and analysed using Merge eFilm and AMIRA to determine the HU of different areas of the models. Results: There was no significant difference (P=0.846) between the HU given by each piece of software. A linear regression was performed using the density, ρ (g cm−3), as the dependent variable in terms of the HU (H). The regression equation obtained was ρ=0.002H−0.381 with an R2 value of 0.986. The standard error of the estimation is 27.104 HU in the case of the Hounsfield Units and 0.064 g cm−3 in the case of density. Conclusion: CBCT provides an effective option for determination of material density expressed as Hounsfield ...

The purpose of this study was to determine the effect of an object's location in a cone beam CT imaging chamber (CBCT-NewTom 3G) on its apparent density and to develop a linear conversion coefficient for Hounsfield units (HU) to material density (g cm(-3)) for the NewTom 3G Scanner. Three cylindrical models of materials with different densities were constructed and scanned at five different locations in a NewTom 3G Volume Scanner. The average HU value for each model at each location was obtained using two different types of software. Next, five cylinders of different known densities were scanned at the exact centre of a NewTom 3G Scanner. The collected data were analysed using the same two types of software to determine a standard linear relationship between density and HU for each type of software. There is no statistical significance of location of an object within the CBCT scanner on determination of its density. A linear relationship between the density of an object and the HU of a scan was rho = 0.001(HU)+1.19 with an R2 value of 0.893 (where density, rho, is measured in g cm(-3)). This equation is to be used on a range between 1.42 g cm(-3) and 0.4456 g cm(-3). A linear relationship can be used to determine the density of materials (in the density range of bone) from the HU values of a CBCT scan. This relationship is not affected by the object's location within the scanner itself.

The accuracy of 3D reconstructions of the craniomaxillofacial region using cone beam computed tomography (CBCT) is important for the morphological evaluation of specific anatomical structures. Moreover, an accurate segmentation process is fundamental for the physical reconstruction of the anatomy (3D printing) when a preliminary simulation of the therapy is required. In this regard, the objective of this study is to evaluate the accuracy of four different types of software for the semiautomatic segmentation of the mandibular jaw compared to manual segmentation, used as a gold standard. Twenty cone beam computed tomography (CBCT) with a manual approach (Mimics) and a semi-automatic approach (Invesalius, ITK-Snap, Dolphin 3D, Slicer 3D) were selected for the segmentation of the mandible in the present study. The accuracy of semi-automatic segmentation was evaluated: (1) by comparing the mandibular volumes obtained with semi-automatic 3D rendering and manual segmentation and (2) by deviation analysis between the two mandibular models. An analysis of variance (ANOVA) was used to evaluate differences in mandibular volumetric recordings and for a deviation analysis among the different software types used. Linear regression was also performed between manual and semi-automatic methods. No significant differences were found in the total volumes among the obtained 3D mandibular models (Mimics = 40.85 cm³, ITK-Snap = 40.81 cm³, Invesalius = 40.04 cm³, Dolphin 3D = 42.03 cm³, Slicer 3D = 40.58 cm³). High correlations were found between the semi-automatic segmentation and manual segmentation approach, with R coefficients ranging from 0,960 to 0,992. According to the deviation analysis, the mandibular models obtained with ITK-Snap showed the highest matching percentage (Tolerance A = 88.44%, Tolerance B = 97.30%), while those obtained with Dolphin 3D showed the lowest matching percentage (Tolerance A = 60.01%, Tolerance B = 87.76%) (p < 0.05). Colour-coded maps showed that the area of greatest mismatch between semi-automatic and manual segmentation was the condylar region and the region proximate to the dental roots. Despite the fact that the semi-automatic segmentation of the mandible showed, in general, high reliability and high correlation with the manual segmentation, caution should be taken when evaluating the morphological and dimensional characteristics of the condyles either on CBCT-derived digital models or physical models (3D printing).

Objective: To identify anatomic structures in three dimensions and examine their reliability to be used as landmarks in a three-dimensional coordinate cephalometric analysis, using cone-beam computerized tomography (CBCT). Materials and Methods: Thirty CBCT images were randomly selected for landmark location. Forty-two anatomic landmarks, which are not included in the traditional cephalometric landmarks, were chosen based on radiographic characteristics that make them pragmatic to mark in the CBCT image slices. The principal investigator marked the full set of landmarks on the software by navigating in the X, Y, and Z axes for every image three times, with each measurement trial being at least 1 week apart. One other investigator also located the landmarks once for each image for reliability purposes. Intraclass correlation coefficients (ICCs) were used to analyze the mean differences in landmark location in all axes. Results: Intra- and interexaminer reliability for x, y, and z coordinates for all landmarks had ICC greater than 0.95 with confidence interval of 0.88–0.99. Mean measurement differences found were <1.4 mm for all landmarks in all three coordinates. Mean measurement error differences obtained in the principal investigator's trials were primarily <0.5 mm. Conclusion: The most reliable and reproducible landmarks tested for use in CBCT are mental foramina, infraorbital foramina, inferior hamulus, dens axis, foramina transversarium of atlas, medial and lateral condyles of the mandible, superior clinoid processes, and mid-clinoid.