Three-dimensional cephalometry

Evolution of 3D imaging: From 2D to 3D imaging

Craniofacial imaging is one of the essential tools for orthodontic diagnosis and treatment planning. Before the advent of cephalometry, craniometry and anthropometry were the only tools used to study the measurements of the human skull.

The craniometry method involves direct measurements of the dry skulls. This method has the advantage of precise and direct measurements of the skull (s) but cannot be used on living humans.

Anthropometry is the measurement of skeletal dimensions in living subjects. It involves using various soft tissue landmarks on the face and body to obtain measurements of the underlying skeleton, including facial bones and skull. Anthropometric measurements can be used to study the growth of an individual, but the significant disadvantage of imprecise measurements is introduced by variation in the soft tissue thickness.

Cephalometric radiography is a technique which provides the advantages of combined craniometry and anthropometry measurements. Orthodontists have routinely used landmark-based two-dimensional lateral cephalometric analyses for more than a half-century. Later, posteroanterior (PA) cephalometric was added to make measurements in the transverse plane. However, the 2D radiographic representation of three-dimensional (3D) craniofacial anatomical tissues has many inherent drawbacks.

Significant limitations of 2D cephalometry

  • 1.

    Non-linear magnification

  • 2.

    Distortion

  • 3.

    Overlapping of bilateral anatomical structures

  • 4.

    Difficulty in location and measurements of hidden anatomical structure

The development of computed tomography (CT) in the early 1970s satisfied the need for 3D anatomic imaging in medicine and dentistry. 3D imaging was first used in dentistry in 1980 for the analysis of craniofacial deformities, and the first simulation software was introduced in 1986. However, the use of this technology in dentistry, particularly in orthodontics, was limited due to its high radiation dose delivery and cost. Multi detector computed tomography (MDCT) has been used for diagnosing and planning craniofacial deformities.

The introduction of low radiation CBCT and advanced software functions has opened a new and exciting arena of craniofacial imaging.

3D volumetric imaging

The 3D spatial imaging of a patient is significantly valuable to understand the complex biological architecture, which is far superior to projected 2D X-ray images. 3D volumetric images of a body part can be obtained through radiation modalities, such as multi-slice computed tomography (MDCT) and cone beam computed tomography (CBCT), non-radiation imaging, which is magnetic resonance imaging (MRI), and 3D facial photos.

The software tools available for 3D evaluation are:

  • •

    Maxilim (Medicim NV, Sint-Nikaas, Belgium)

  • •

    Mimics (Materialise HQ Co., Technologielaan 15, 3001 Leuven Belgium)

  • •

    Dolphin (Dolphin Imaging & Management Solutions 9200 Oakdale Ave. Suite 700 Chatsworth, CA 91311, USA)

  • •

    Anatomage (Santa Clara, CA 95054, USA)

  • •

    Vitrea (Vital Images Inc., Plymouth, MN, USA)

  • •

    AMIRA (AMIRA, Mercury Computer System Inc., Berlin, Germany)

  • •

    Romexis 3D Cephalometry (Planmeca Oy, Helsinki, Finland)

  • •

    NemoFAB Ortho (Nemotec, Madris, Spain)

These software tools allow viewing, analysing and annotating volumetric images on 2D computer screens. Advanced software functions provide the facility to rotate the patient image 360 degrees to visualise the anatomy and internal structures from a distinct perspective. The measurements obtained through 3D volumetric images are comparable to those obtained directly on anatomical structures.

Though the radiation dose delivery of CBCT is lesser than conventional CT, it is well above the combined radiation dose of a lateral and a PA cephalogram, a panoramic X-ray and a set of intraoral radiographs.

2D cephalogram from 3D data

Derived cephalograms are digital images obtained from CBCT data and 3D volumetric information using multiple software functions. These images are 2D projections of a 3D anatomical structure, similar to traditional 2D cephalograms. The type of 2D image selected depends on its use and purpose. These are:

  • 1.

    Ray-sum

  • 2.

    Maximum intensity projection (MIP)

  • 3.

    Hemifacial projection

    • 1.

      The ray-sum image is a 2D image generated by overlapping all CBCT slices on one plane ( Fig. 38.1 ).

      Figure 38.1

      A lateral cephalogram generated as a Ray-Sum image.

    • 2.

      MIP image is created by overlapping only those CBCT slices with a significantly high intensity of anatomical structures ( Fig. 38.2 ).

      Figure 38.2

      A lateral cephalogram generated using the Maximum Intensity Projection (MIP) technique.

    • 3.

      Hemifacial projection overlapping of CBCT slices either from mid-sagittal to left-most sagittal or mid-sagittal to right-most sagittal on a 2D plane is called left-hemifacial projection and right hemifacial projection image, respectively. Hemifacial projection is most useful in the study of patients with asymmetrical faces ( Fig. 38.3 ).

      Figure 38.3

      Hemifacial projection.

      (A) Cephalogram derived from data of the left side of the face and (B) Right side of the face.

There are two projection methods to derive cephalograms from CBCT data.

  • 1.

    Orthogonal projection: The orthogonal projection uses a parallel (non-diverging) rays’ algorithm to create a cephalogram from CBCT data. The orthogonal projection provides cephalograms with proper overlapping of bilateral structures and 1:1 image ( Fig. 38.4 ).

    Figure 38.4

    Orthogonal projection.

  • 2.

    Perspective projection: The perspective projection simulates the geometry of the conventional cephalometric method by using the diverging ray’s algorithm. The perspective cephalograms from CBCT data could replicate the inherent magnification of conventional 2D cephalograms with high accuracy, and they could be used in comparison with 2D cephalograms ( Fig. 38.5 ).

    Figure 38.5

    Perspective projection.

CBCT-derived cephalograms versus conventional 2D cephalograms

Comparison of CBCT-derived cephalograms and conventional 2D cephalograms showed that angular and linear measurements were similar. The difference between the traditional and CBCT-derived orthogonal projection cephalograms can be compensated by correction of mid-sagittal magnification. Lamichane et al. showed that constructing a perspective lateral cephalogram from a CBCT scan could replicate the inherent magnification of a conventional 2D lateral cephalogram with high accuracy. The magnification of conventional cephalograms can be reproduced in perspective projection-derived cephalograms by setting source-to-object and object-to-film distances identically to the respective standard cephalometer distances.

Additional conventional cephalograms are not required once the CBCT data are available. The longitudinal data derived from conventional cephalograms could be the source of the norms for derived cephalograms from CBCT. The derived cephalograms can also be used for longitudinal research with conventional cephalogram data. ,

Indications of CBCT imaging

CBCT imaging has many advantages over conventional radiographs, but the radiation dose discourages its use as the first choice of imaging modality in routine orthodontics. CBCT imaging provides enhanced 3D information on impacted/unerupted teeth, root resorption, supernumerary teeth, temporomandibular joint (TMJ) and other craniofacial abnormalities. The CBCT imaging should be justified individually and recommended following a thorough clinical examination. It should be advised only when the CBCT imaging is likely to provide additional information that could change the course of treatment and improve treatment outcomes.

Indications of CBCT imaging in orthodontics are , :

  • 1.

    Small field of view (FoV)

    • a.

      Impacted teeth

    • b.

      Supernumerary teeth

    • c.

      Hypodontia

    • d.

      Root resorption

  • 2.

    Medium FoV

    • a.

      Cleft lip and palate

    • b.

      TMJ evaluation

  • 3.

    Large FoV

    • a.

      Orthognathic surgical planning

    • b.

      Other craniofacial deformities

Evolution of 3D cephalometric measurements

In 2006, Park et al. introduced the first 3D cephalometric analysis. This analysis was based on MDCT and assessed craniofacial morphology by measuring the zygoma, maxilla, mandibular region and facial convexity in 30 Korean patients. Authors proposed the use of 19 measurements that are similar to those used in 2D images. The measurements were compared with Korean normal averages, and no statistically significant differences were found. Landmark identification was reproducible.

The first comprehensive 3D cephalometric analysis was introduced by Swennen et al. Since 2006, several analyses have been proposed based on MDCT and CBCT data ( Table 38.1 ). ,

TABLE 38.1

Evolution of 3D cephalometric analysis

S. no. 3D analysis Year Objective Definitions and landmark features Imaging modality
1. Swennen GRJ et al. 2006 To propose cephalometric analysis on volumetric image based on 2D landmarks Landmark based on conventional cephalometry CT scans
2. Olszewski R et al. (3D Acro) 2006 Analysis that cannot be performed on 2D radiographs Landmarks not seen on 2D cephalograms CT scans
3. Farronato G 2010 To compare the 10-point cephalometry method using 3D images and the 2D Steiner cephalometry method taking lateral and posteroanterior cephalograms 10 landmarks Low dose CBCT
4. Bayome M 2013 Establishing relationships among skeletal and dentoalveolar parameters Landmark based on conventional cephalometry CBCT scans
5. Lee M 2015 Alternative measurement for differentiation of skeletal pattern class I and class II Novel landmarks and novel measurements CBCT scans
6. Gupta A 2016 Accuracy of 3D cephalometric measurements based on an automatic knowledge-based landmark detection algorithm Landmarks based on conventional cephalometry CBCT scans
7. Montúfar et al. 2018 Hybrid approach for cephalometric landmark detection Landmarks based on conventional cephalometry CBCT scans
8. Pinheiro et al. 2019 Protocol for the accurate quantification of the craniofacial symmetry and facial growth Landmarks based on conventional cephalometry Skull model
9. Kang et al. 2020 Automatic landmark identification Landmarks based on conventional cephalometry CT scans
10. Verhelst et al. 2021 Assessment of accuracy and reliability of shape quantification of the human mandible 3D landmarks on the mandible CBCT scans
11. Bermejo et al. 2021 Automatic landmark identification 3D surface landmarks 3D skull models
12. Li et al. 2021

  • Reliability of two- and three-dimensional cephalometric measurement

Landmarks based on conventional cephalometry CBCT scans
13. Kang et al. 2021 Automatic landmark identification Landmarks based on conventional cephalometry CT scans
14. Ghousi et al. 2022 Automatic landmark identification 3D landmarks CBCT scans

In 2015, researchers at All India Institute of Medical Sciences New Delhi and Central Scientific Instruments Organisation (CSIO), Chandigarh, demonstrated a comparison of 3D cephalometric measurements computed automatically and manually. These 3D measurements were obtained from various 2D cephalometric analyses used in routine clinical practices. Xia et al. proposed a cephalometric analysis method to assess the size, position, orientation, shape and symmetry. Progressively, several researchers have proposed their methods for landmark detection to conduct cephalometric analysis. Table 38.1 , shows the evolution of 3D cephalometric analysis.

3D facial photographs obtained through non-radiation imaging technology such as 3dMD can be superimposed on CBCT volumetric data, which provides a virtual face for evaluation and planning virtual treatment. 3D imaging at different ages adds the fourth dimension (4D), the ‘time’, enhancing our understanding of facial changes with growth and age.

This 4D analysis may involve ‘Dynamic imaging’ such as smiles and facial expressions or recording the growth or age-related changes over a period of time.

3D cephalometry is more complex than just adding a ‘third’ dimension to a conventional 2D cephalometric analysis. There are many complex issues in 3D analysis. These are related to reference systems, size, position, orientation and shape. Locating 3D landmarks and assessing the measurements are complex computational processes. Understanding these basic principles is essential for the correct use of 3D cephalometry.

Craniofacial anatomical structures visualisation and 3D landmarks

The CBCT images contain 3D information of scanned structures as stacked 2D base images in the axial direction, producing a 3D volumetric image. With the help of software, desired slices can be reconstructed from these base images to visualise anatomical structures of interest. The most used slices for visualising an anatomical structure are multi-planar reconstruction (MPR), which consists of three mutually orthogonally projected planes, namely axial, coronal and sagittal ( Fig. 38.6 ). Each slice is a 2D representation of a 3D structure from mutually orthogonal perspective views (X, Y and Z).

Figure 38.6

MPR slices and volume rendered image.

How landmarks on 3D volume rendered images differ from 2D cephalogram

3D space requires three mutually perpendicular axes to define any point in space. MPR slices fulfil this requisite and are used for accurate landmark identification in three dimensions. The conventional cephalograms are ray-sum images, and landmark definition and plotting involve only two dimensions in sagittal view, namely X and Y (anteroposterior and superoinferior, respectively). These 2D landmark definitions do not help while analysing a 3D volumetric image. The third dimension, ‘Z axis’, may lead to uncertainties in landmark plotting. 3D landmarks need, in contrast to conventional landmark definitions, to be defined in three planes for each 2D slice, axial, coronal and sagittal, for accurate landmark identification ( Table 38.2a–c ; Fig. 38.7 ).

TABLE 38.2a

Definition of hard tissue landmarks in 3D imaging

S. no. Landmark Abbreviation Definition of the skull Sagittal slice Axial slice Coronal slice Remarks
1. Nasion N Most anterior point of the fronto-nasal suture in the mid-sagittal plane Anterior most point Middle-anterior most point on the anterior contour Middle point Plotted on 3D volumetric data and confirmed on MPR views
2. Orbitale left Or L The lowest point in the inferior margin of the left orbit Anterior-superior most point – – Plotted on 3D volumetric data and confirmed on MPR views
3. Orbitale right Or R The lowest point in the inferior margin of the right orbit Anterior-superior most point – – Plotted on 3D volumetric data and confirmed on MPR views
4. A-point A-point The point at the deepest midline concavity on the maxilla between the anterior nasal spine and the dental alveolus Posterior-most point Middle-anterior most point on the anterior contour The middle point is determined by the sagittal and axial slices Plotted through MPR views and confirmed on 3D volumetric data
5. Anterior nasal spine ANS The most anterior midpoint of the anterior nasal spine of the maxilla Most anterior point Anterior point and middle point Middle point Plotted through MPR views and confirmed on 3D volumetric data
6. Posterior nasal spine PNS The sharp posterior extremity of the nasal crest of the hard palate Most posterior point Posterior point and midpoint – Plotted through MPR views and confirmed on 3D volumetric data
7. B-point B-point Most posterior point in the concavity along the anterior border of the mandibular symphysis Posterior-most point Middle-anterior most point on the anterior contour The middle point is determined by the sagittal and axial slices Plotted through MPR views and confirmed on 3D volumetric data
8. Pogonion Pog/Pg Most anterior point on mandibular symphysis Anterior-most point Middle-anterior-most point on the anterior contour The middle point is determined by the sagittal and axial slices Plotted through MPR views and confirmed on 3D volumetric data
9. Menton Me A most inferior point on the mandibular symphysis Inferior-most point Middle most point Middle-inferior-most point Plotted through MPR views and confirmed on 3D volumetric data
10. Gnathion Gn Midpoint of the curvature of the pogonion and menton Anterior-inferior most point Middle-anterior most point Middle-inferior-most point Plotted through MPR views and confirmed on 3D volumetric data
11. Gonion left Go L Most inferior and posterior point on the left mandibular corpus Inferior and posterior most point Posterior most point Inferior most point Plotted on 3D volumetric data and confirmed on MPR views
12. Gonion right Go R Most inferior and posterior point on the right mandibular corpus Inferior and posterior most point Posterior most point Inferior most point Plotted on 3D volumetric data and confirmed on MPR views
13. Condylion left Co L The most superior point on the left mandibular condyle Superior-most point The midpoint determined by the sagittal and coronal slices Middle superior-most point Plotted through MPR views and confirmed on 3D volumetric data
14. Condylion right Co R The most superior point on the right mandibular condyle Superior-most point The midpoint is determined by the sagittal and coronal slices Middle superior-most point Plotted through MPR views and confirmed on 3D volumetric data
15. R1 left R1 L The deepest point on the curve of the anterior border of the left ramus Deepest point Anterior point – Plotted on 3D volumetric data and confirmed on MPR views
16. R1 right R1 R The deepest point on the curve of the anterior border of the right ramus Deepest point Anterior point – Plotted on 3D volumetric data and confirmed on MPR views
17. Sella S Midpoint of sella-turcica Middle point of the pituitary fossa Middle point of the anteroposterior and lateral width of the pituitary fossa The middle point of the lateral width of the fossa is determined by the sagittal and axial slices. Plotted through MPR views and confirmed on 3D volumetric data
18. Basion B The most anterior point on the anterior margin of the foramen magnum in the mid-sagittal plane Inferior-posterior most point Anterior most point Middle point Plotted through MPR views and confirmed on 3D volumetric data
19. Zygomatic point left Zy L The most lateral point on the left outline of the left zygomatic arch – Anterior lateral point Most lateral and superior point Plotted on 3D volumetric data and confirmed on MPR views
20. Zygomatic point right Zy R The most lateral point on the right outline of the right zygomatic arch – Anterior lateral point Most lateral and superior point Plotted on 3D volumetric data and confirmed on MPR views
21. Frontozygomatic left Fz L The most medial and anterior point of the left frontozygomatic suture at the level of the lateral orbital rim Most anterior Most anterior Medial point Plotted on 3D volumetric data and confirmed on MPR views
22. Frontozygomatic right Fz R The most medial and anterior point of the right frontozygomatic suture at the level of the lateral orbital rim Most anterior Most anterior Medial point Plotted on 3D volumetric data and confirmed on MPR views
23. Jugal point left J L The deepest midpoint of the left jugal process of the maxilla Inferior most point – Deepest point Plotted through MPR views and confirmed on 3D volumetric data
24. Jugal point right J R The deepest midpoint of the right jugal process of the maxilla Inferior most point – Deepest point Plotted through MPR views and confirmed on 3D volumetric data
25. Bolton Bo The most posterior point of the foramen magnum in the mid-sagittal plane Anterior point of the posterior border of foramen magnum Mid and posterior most point Middle point Plotted through MPR views and confirmed on 3D volumetric data
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May 10, 2026 | Posted by in Orthodontics | 0 comments

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