Published: September 8th, 2023
Presented here is a detailed protocol for the conduction of three-dimensional cephalometric analysis with the use of human cone beam computed tomography scans.
Craniofacial cephalometric analysis is a diagnostic tool used for the assessment of the relationship of various bones and soft tissues in the head and face. Cephalometric analysis has been traditionally conducted with the use of 2D radiographs and landmark sets and restricted to size, linear and angular measurements, and 2D relationships. The increasing use of 3D cone beam computed tomography (CBCT) scans in the dental field dictates the need for the evolution to 3D cephalometric analysis, which incorporates shape and a more realistic analysis of longitudinal development in all three planes. This study is a demonstration of 3D cephalometric analysis with the use of a validated set of skeletal tissue landmarks on human CBCT scans. Detailed instructions for the annotation of each landmark on a 3D volume are provided as part of a step-by-step protocol. The generated measurements and 3D coordinates of the landmarks can be exported and used both for clinical and research purposes. The introduction of 3D cephalometric analysis in basic and clinical craniofacial studies will lead to future advancements in the field of craniofacial growth and development.
Cephalometric analysis, which examines the dental and skeletal relationships of the human skull, is the clinical application of cephalometry. In addition to anthropologists, developmental biologists, forensic experts, and craniofacial researchers who study human evolution and craniofacial development, it is utilized by oral health professionals, including dentists, orthodontists, and oral and maxillofacial surgeons, as a treatment planning tool. The earliest institutions that used cephalometric analysis in orthodontics were Hofrath in Germany and Broadbent in the USA in 19311,2,3. The primary objective of the analysis was to provide a theoretical and practical resource to evaluate the craniofacial proportions of an individual and to define the anatomical source of malocclusion1. This allowed for the growth pattern of the maxilla and mandible to be tracked, their relational positions in space to be monitored, and changes in soft tissue and teeth displacement to be observed. As a result, changes brought about by orthodontic treatment could be monitored, and skeletal and dental relationships could be characterized for a diagnosis to be made for treatment planning. Evaluation of the dentofacial complex was done by comparing a patient's cephalometric tracing with reference values that were representative of a normal population of similar age, race, and ethnicity1.
The traditional method of analysis consisted of a two-dimensional (2D) depiction of three-dimensional (3D) structures4,5. A major setback of this technique is the distortion and magnification of anatomical structures via conventional x-ray imaging on plain film or digital formats, which can lead to inaccurate cephalometric tracings and interpretations6,7. The initial introduction of 3D imaging in the form of axial computed tomography (CT) and spiral CT did not include dental or non-medical applications due to high cost and high radiation doses. However, the emergence of cone beam computed tomography (CBCT) scans mitigated these concerns, as expenses and radiation doses were significantly lower than CT1. The shift in this imaging narrative galvanized the widespread use of CBCT in orthodontics for improvement in diagnosis and treatment planning. The main advantage of 3D imaging over the conventional 2D image technique is that 3D allows the examiner to view anatomical structures without superimpositions and spatial distortions (i.e., head position of the individual). Therefore, a much more accurate positioning of the anatomical landmarks used for the conduction of cephalometric analysis is possible, especially in cases of facial asymmetry. Moreover, a much larger anatomical area can be analyzed.
One of the most recent advances in the field of cephalometry is the implementation of deep learning (DL) for automated landmark detection8,9,10,11. Although the results of these studies are promising, the levels of accuracy in the placement of the landmarks are not yet satisfactory. Moreover, most of these studies use relatively small landmark sets that are derived from previous 2D cephalometric analyses, providing insufficient coverage of the cranial base, which is an important structure for the study of craniofacial growth and development. This demonstration video showcases in detail a methodology for the conduction of manual, high-accuracy 3D cephalometric analysis with the use of a validated set of 3D skeletal tissue landmarks covering the areas of the face, cranial base, mandible, and teeth for use in clinical and research studies involving CBCT imaging4. An example of a completed 3D analysis can be seen in Figure 1.
This protocol follows the guidelines of the human research ethics committees of the Institutional Review Boards of the National Institutes of Health (NIDCR IRB #16-D-0040) and Roseman University of Health Sciences. See the Table of Materials for details related to the software used in this protocol. The same protocol can be followed with the use of different software, after adjustments based on their specific settings and technical details. The CBCT scans used for creation of the figure included in this paper, as well as the video demonstration, have been anonymized prior to their use, and informed consent has been acquired from the subjects, allowing the use of their scans in research related publications. Both subjects were seen at the NIH Dental Clinic, where the scans were acquired (Planmeca ProMax 3D system; low dose mode, 400 µm resolution) and had been consented onto an NIH IRB-approved protocol (NCT02639312).
1. Uploading the CBCT scan and view in the 3DAnalysis module
2. Uploading a landmark configuration file
3. Coordinate system setup
4. CBCT scan image adjustments
5. Addition of new landmarks
6. Annotation of 3D anatomical landmarks
7. Definition and specific annotation instructions for each 3D landmark
8. Saving of the CBCT scan with annotated landmarks
9. Export measurements and/or landmark 3D coordinates
The annotation of a validated 3D landmark configuration is described in detail with the use of a step-by-step protocol and video demonstration. Specific instructions are provided for the annotation of each landmark on the 3D volume, as well as the refinement of their initial positions with the help of the 2D section views that correspond to each plane of space. By following the detailed methodology provided in the protocol in combination with the video instructions, the user can learn how to conduct cephalometric analysis with the use of human CBCT scans.
Figure 1 represents frontal and three-quarter views of a full head CBCT scan of a human skull with the annotated 3D landmarks included in the current configuration. All the described landmarks are Type 1 and Type 2. Type 1 landmarks represent clearly recognizable points usually observed at the intersection of distinct anatomical structures. Type 2 landmarks represent points of maximal curvature on the contour of recognizable anatomical structures12. No Type 3 or semi-landmarks were included in this analysis.
After the completion of the annotation of the landmarks, there are two types of data that can be exported and further analyzed by the user: cephalometric measurement and 3D coordinate values. The values of key cephalometric measurements required for the diagnosis and assessment of dentoskeletal malocclusion are provided. These measurements provide a detailed assessment of the skeletal and dental relationships in all three planes of space: sagittal, vertical, and transverse. The 3D coordinate values (x, y, z) of each landmark can be exported and used for the calculation of angles and linear distances. The values of the same coordinates can be used for the conduction of multivariate geometric morphometric analysis (GMA). GMA is a method for studying shape that can capture morphologically different shape variables utilizing Cartesian landmark and/or semi-landmark coordinates. Several statistical techniques can be used to examine shape, without taking into account the size, location, or orientation of the examined structures. Geometric morphometrics is currently the most established body of morphometric theory for handling landmark-based data.
Figure 1: Frontal and three-quarter views of a full head CBCT scan of a human skull with the annotated 3D landmarks included in the current configuration. Please click here to view a larger version of this figure.
Supplementary File 1: Configuration file including the landmarks used in this protocolwhich can be directly uploaded to the software for analysis. Please click here to download this File.
Medicine and dentistry have already entered the 3D imaging era. In the disciplines of craniofacial and dental imaging, CBCT scans are increasingly being used, due to the low radiation and decreased cost of the updated systems in comparison to traditional CT machines, easy personnel usage calibration, relatively quick and easy acquisition with minimal patient cooperation, as well as the ability to generate multiple other diagnostic images and analyses from one single scan. Therefore, it is essential for clinicians and researchers to know how to read, diagnose, and analyze these 3D images, as well as learn how to study craniofacial growth and development in 3D.
To assist clinicians and researchers in this field, we present a step-by-step protocol and video demonstration for the conduction of 3D cephalometric analysis with the use of human CBCT scans. These landmarks have been previously defined and validated in a previous publication, where their accuracy and repeatability were confirmed4. The detailed refinement instructions for each landmark also assist users in the correct annotation of each landmark. The landmark annotation process is further simplified with the use of preset views of the scan that correspond to the area that each landmark should be positioned. This function saves significant time and effort for the user. Nevertheless, there is a learning curve involved, and practice is required by users to achieve accurate landmark annotation.
The validated 3D landmark configuration used in this protocol provides sufficient coverage of the skeletal tissue of the face, maxilla, mandible, and cranial base. In this way, the true morphology of the craniofacial structures is more accurately represented for evaluation of the dimensions, configuration, and orientation of the craniofacial complex and its component structures. Soft tissue landmarks are not included in this protocol, but users can add landmarks of choice to the provided configuration, as described in the protocol. In addition, for practical reasons, this protocol could not include specific instructions for other 3D analysis software, but can be adapted accordingly by each user.
Apart from the diagnostic value of the generated standard cephalometric measurements, mainly for clinicians, the freedom offered with the use of this analysis to compute angles and linear distances between any 3D landmarks will allow the establishment of new cephalometric analyses that will provide more detailed and complete assessments. Nevertheless, our future direction includes establishing new respective normative values, in the same way that 2D normative values were created in the past.
Moreover, the applications of landmarked based GMA in the craniofacial clinical and research field are developing at a fast pace. Researchers in evolutionary and developmental biology and anthropology for have been using this analysis for more than a decade, but new clinical applications have also been recently presented in the fields of orthodontics, dentofacial orthopedics, and craniofacial surgery. GMA can be also used as part of a quantitative phenotyping in the case of congenital diseases with craniofacial manifestations, as well as for the detection of subtle morphological differences attributed to gene mutations13,14,15,16. In addition, the integration of different quantitative approaches by linking morphometric data with functional analysis as well as genetic data can provide new knowledge regarding craniofacial development in healthy, as well as disease, groups.
Because of recent advances in computation and visualization, the conduction of this type of analysis is now feasible on personal computers, with several software packages already available, including Checkpoint, Geomorph (a package of R statistical software), Amira-Avizo, and SlicerMorph. These programs can assist researchers in the medical fields that may be unfamiliar with multivariate statistical analyses to conduct GMA with the availability of built-in automated functions.
The authors declare no conflicts of interest.
This research was supported by the Intramural Research Program of the National Institute of Dental and Craniofacial Research (NIDCR) of the National Institutes of Health (NIH), and the Advanced Education in Orthodontics and Dentofacial Orthopedics program of Roseman University College of Dental Medicine.
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