5: Three-Dimensional Imaging in Orthodontics


Three-Dimensional Imaging in Orthodontics

Chung How Kau, Stephen Richmond

The advances of three-dimensional (3D) technology have accelerated at a tremendous pace over the last two decades with newer machines and advanced software support. This now means that applications for the clinical settings can be created and used in routine diagnosis, treatment planning, and patient education. Orthodontists will find that these advances will also impact the profession, and this chapter aims to give the reader the basic foundation on which to understand this interesting and exciting topic.

1 Imaging techniques and devices—what do these mean to the orthodontist?

New technologies reach the commercial and clinical environments on a daily basis and filter through every aspect of the medical and dental field. Orthodontists too are exposed to this fast pace of change, and these advancements have allowed innovative methods for facial diagnosis, treatment planning, and clinical application.

With continuing innovations and the use of powerful computer software tools, the last two decades have seen a reintroduction of both hard and soft tissue imaging devices in rapid succession. The orthodontist needs to embrace these new methods of diagnosis and treatment planning, since the images produced add a new dimension to present day concepts and test the foundations of our knowledge.

2 What does it mean to have a three-dimensional image and how is it obtained?

Three-dimensional image reconstruction is a complex task using mathematical principles. The 3D image is essentially an object that appears to have an extension in depth. In photography, a 3D image is reconstructed by the principles of stereoscopic vision when two images are pieced together from two or more cameras at known distances and angles. In radiography, multi-slice or multi-views of an object are cleverly reconstructed using complex mathematical algorithms to produce a representation of the object.

3 What is a possible classification of these devices?

Three-dimensional images may be obtained in a variety of ways. A possible classification system is listed in < ?xml:namespace prefix = "mbp" />Table 5-1.

TABLE 5-1 Tabular Representation of Surface Imaging Devices

Direct Contact Manual Probe
a. Polhemus 3 Space Digitizer
Photo-grammetry Conventional photography
a. Stereo-photogrammetry
Lasers 670 – 690 nm Class I or II FDA approved laser lights
a. Fixed Units

    Medical Graphics and Imaging Group, UCL
    Cyberware Laboratory 3030 / SP
  670 – 690 nm Class I or II FDA approved laser lights
b. Portable and Mobile

    Minolta Systems (Model versions 700, 900, 910, 9i)
    Polhemus hand-held (FASTSCAN)
Structured Light Distorted light patterns and photogrammetric light capture
a. Single Camera
b. Multiple Camera

    Moire patterns
    OGIS Range Finder RFX-IV
    CAM, three-dimensional Shape system
    C3D-dimensional Stereo-photogrammetry (Glasgow)—Computer aided
    3dMD™ Face System
Video-Imaging Video sequencing
a. Motion-Analysis™
Radiation Sources Radiation pulses
a. CT Scans
b. Cone Beam CTs
a. MRI
b. Ultrasound

4 What are some clinical applications?

There are a number of reported and possible clinical applications. These will be discussed under two main headings: surface imaging and hard tissue imaging.


Facial Growth

Significant investigations have been done in the past on hard tissue growth of the cranial skeleton. However, reported studies focusing on and analyzing soft tissue morphology and growth are comparatively small in relation to the general orthodontic literature.1 Yet the external profile is by far the most visible entity from which clinicians and lay people make perceptions and formulate judgments. In this current day and age, with a greater emphasis being placed on the balance between the hard and soft tissues, it is important to have reliable and readily available data on the external soft tissue profile. At present, there is a lack of emphasis on the longitudinal development of the soft tissues. Most of the available data on the changing soft tissue profile have been obtained from cephalometric data with an additional small number from limited 3D data. Soft tissue studies are difficult and the tissue structures are inevitably affected by movements and distortions. However, careful patient positioning and good technical detailing have allowed these images to be reproducible to a high level of clinical acceptability.

Early 3D imaging research has shown that the growth of facial structures broadly follows in line with gender and age. Growth is present in a number of facial structures and may be visualized as surface and volume changes (Fig. 5-1). Furthermore, the system is so sensitive that asymmetric growth is identified in 33% of 11- to 12-year-olds. In the vast majority of these cases, the asymmetrical growth levels out over 1 year of assessment. However, there are a small proportion of children who continue to grow asymmetrically (Fig. 5-2).


FIG 5-1 Facial growth as illustrated by average facial changes in males and females. Red areas indicate positive changes, whereas blue areas indicate negative changes.


FIG 5-2 Asymmetrical growth of a child’s face over a 2-year growth period. Note the asymmetrical shuffling of the mandible.

Average Faces and Superimposition

Average faces of 3D images from a cohort of same-age individuals may also be created.2,3 This procedure involves pre-alignment of the images by determining their principal axes (based on computing the tensor of inertia of each 3D image) followed by best fit alignment of the images and then by averaging the image coordinates normally to the facial plane. For each point representing the obtained average facial plane, the standard deviations are calculated allowing construction of the “standard deviation” faces that indicate variation from the average face. The results obtained may be used for the identification of facial anomalies in patients (Fig. 5-3). The face examined is superimposed onto the average face using the best fit technique, and then a divergence map can be constructed showing the regions with abnormal deviations. The deviations can be identified and quantified in terms of linear, area, and volumetric measurements.


FIG 5-3 A-C, 11-year-old girl with right unilateral cleft lip and palate. D, Superimposition of patient on the average 11-year-old face; color map indicating the magnitude of deviation around the cleft region (red, 10.9 mm; green, 6.5 mm; cyan, 3.3 mm retrusive compared with the average face). E, Zona/>

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Jan 1, 2015 | Posted by in Orthodontics | Comments Off on 5: Three-Dimensional Imaging in Orthodontics
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