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U. Meyer
Fig. 11.2 CBCT images of different kinds of asymmetric: top: asymmetric alignment (normal dysgnathia); bottom: object asymmetry of maxilla and mandible (hemifacial hypertrophy)
Limitations ofGateno’s Classication System
orofacial clefts, and craniofacial scoliosis, so they are not easily included in such a classica­tion. (3) The embryologic development of the
Gateno’s precise geometric classication has a high precision to dene the geometric altera­tions of teeth and jaws in most dysgnathic patients, but it has limitations in three aspects, especially relevant in patients suffering from a craniofacial deformity: (1) to include an unal­tered anatomy of the skull base as one reference system, (2) to refer to a dened symmetry plane of the patient’s skull as a second plane, and (3) the use of the maxilla as one anatomical unit. (1) As the classication of geometric deviations from normal is based on a reference system where the skull base is normal (in position, size, and angulation), patients with craniosynostosis and branchial arch diseases fail to be included in the classication. (2) Facial symmetry is not given in patients with branchial arch diseases,
maxilla distinguishes three parts, two lateral sided parts and one medial part. Patients with bilateral clefts cannot be properly described through such a classication.
The question arises as to how patients with craniofacial malformations can be properly classied. Craniofacial malformations can be grouped according to their underlying patho­physiology. The display features of malforma­tion are according to the affected bony and soft tissue structures. One option is to refer and com­pare the dysgnathic situation towards a three­dimensional anatomy of normal (norm) patients. Table 11.3 indicates the geometric alteration towards the normal anatomy, the relevant imag­ing measures to display these deformities, and the reference anatomical unit. Craniofacial sco-
11 Classication ofJaw Malformations (Dysgnathias) inCraniofacially Malformed Patients
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Table 11.3 Aspects of disease-based skull deformation and resulting diagnostic protocols
Maxillary
Skull
Malformation Craniosynostosis No Yes Yes CBCT/CT Virtual skull (VS) Branchial arch diseases No No No CBCT/CT VS/mirrored skull Orofacial clefts Unilateral Ye s No Yes CBCT/CT or VS Bilateral Yes Yes (minor) Ye s Lateral-front
Asymmetric dysgnathias (alignment) Symmetric dysgnathias Ye s Ye s Yes Lateral ceph Norm lateral ceph
base
Yes Yes Ye s Lateral-front
symmetry
Mandibular symmetry
Analysis ReferenceObject (plain) symmetry
ceph
ceph
Norm lateral-front ceph
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Fig. 11.3 X-ray and CBCT of patient with severe craniofacial scoliosis. The facial axis differs extremely towards the cranial axis
liosis is additionally a seldom disease entity, where the cranial- facial phenotype is distorted (Fig.11.3).
Various new technical approaches enable to compare two 3D models. Superimposition is a measure to relate a normal skull to a diseased one. As landmarks are commonly used for this
process, landmark denition is a prerequisite for a superimposition protocol. From a disease­based approach, landmarks should be dened for each disease entity. They should be located at an anatomical area, which is not involved by the underlying disease (Figs. 11.4, 11.5, 11.6,
11.7, and 11.8).
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objects
syndromalCraniosynostosis
objects
branchialarch disease
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Fig. 11.4 Disease­based involvement of anatomical objects: syndromal craniosynostosis
Fig. 11.5 Disease­based involvement of anatomical objects: branchial arch diseases
-Apert syndrome -
1
2
3
2
4
6
- Goldenhar syndrome -
U. Meyer
Disease relatedcraniofacial
involved anatomical unit
2
5
7
- cranial vault1
- skullbase2
- orbit3
- zygoma 4
- maxilla5
Unaffectedanatomicalunit
-mandible6
-chin7
Disease relatedcraniofacial
1
2
2
4
2
3
5
involved anatomicalunit
- skullbase2
- orbit 3
- zygoma 4
- maxilla 5
- mandible6
- chin 7
6
7
Unaffectedanatomicalunit
- cranial vault1
objects
orofacialcles
s
asymmetric alignement dysgnathia
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- bilateral CLP -
1
3
2
2
4
5
6
Fig. 11.6 Disease-based involvement of anatomical objects: orofacial clefts
Fig. 11.7 Disease-
based involvement of anatomical objects: asymmetric alignment dysgnathias
Disease relatedcraniofacial
involved anatomical unit
- maxilla 5
2
unaffectedanatomicalunit
- cranial vault 1
- skull base 2
- orbit 3
- zygoma 4
7
-Hypercondylie -
1
2
2
4
6
2
3
5
7
- mandible 6
- chin 7
Disease relatedcraniofacial object
involved anatomical unit
- maxilla 5
- mandible 6
- chin 7
unaffectedanatomicalunit
- cranial vault1
- skull base 2
- orbit3
- zygoma 4
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bjects
symmetric dysgnathias
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Fig. 11.8 Disease­based involvement of anatomical objects: symmetric dysgnathias
U. Meyer
Disease relatedcraniofacialo
1
2
2
3
4
6
2
5
7
involved anatomicalunit
- maxilla5
- mandible 6
- chin 7
Unaffectedanatomicalunit
- cranial vault1
- skullbase2
- orbit3
- zygoma 4
Diagnostic Tools
The common classication is based on the analy­sis of (1) lateral cephalograms, (2) photographs, and (3) plaster models. Given the abundance of hard and soft tissue information contained within lateral cephalometric images, most phenotypic characterization has been done in two dimen­sions. Different analytical methods have been employed, including shape analyses, and princi­pal components and cluster analyses. Of these, lateral cephalometric radiographs and clinical photographs are the most abundant and thus are likely to be the primary data source for large­scale genotype–phenotype correlation projects. (1) Cephalometric radiographs are taken by orthodontists to quantitatively evaluate the skel­etal relationship between the cranial base and the maxilla or mandible, the relationship between maxilla and mandible, and the dentoalveolar rela­tionship [68]. It has supplied clinicians useful information, especially regarding classication­based orthodontic treatment planning [915]. Different authors established parameters leading to internationally recognized skeletal classica­tion types. Single authors like Delaire developed special cephalometric analysis for patients with a distorted skull base. The Delaire’s whole-skull analysis can be applicated to patients with cra­niosynostoses, since the common analysis meth­ods fail as they are related to a normal skull base [1619]. As some authors [18] realized the limits
of classifying patients with lateral cephalometry, they integrated in an extended approach anterior– posterior crane cephalometry as well. (2) Although 2D photographs have dimensional errors due to variations in projection and patient positioning, 2D photographs are in use for facial phenotyping through estimates of facial propor­tions, angles, and shape analyses. (3) The third mainstay of orthodontic classication is the anal­ysis of plaster casts. The two major drawbacks of such a diagnostic approach (use of lateral cepha­lograms, photographs, plaster model) are (a) the inability of a 3D phenotype representation and (b) the disjunction of the dental, skeletal, and facial data.
Changing from 2D to 3D is a new process, enabled through the development of digital data acquisition and advances in matching algo­rithms. The use of CBCT, intraoral scanning, and facial surface detection by extraoral scan­ners is becoming routine in orthodontics and cranio- maxillofacial surgery (Fig. 11.9). Shifting from 2D to 3D is rendered possible thanks to 3D images obtained employing com­puted tomography or cone-beam computerized tomography (CBCT) [20, 21]. The digital 3D study of the cranium starting from the axial, sagittal, and coronal images and the correspond­ing 3D renderings of the volumes as well as 3D facial surface imaging offer more accurate data, without errors due to projection distortion or patient positioning [2224]. Such a diagnostic
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a b
c d
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Fig. 11.9 Integration of a) dental scan, b) CBCT data, and c) facial scan into one d) complex phenotype dataset
approach is much closer to reality. Different authors established that the reproducibility of a landmark differs on the three spatial planes (x; y; z); this means that some points are easily identied on one or two planes but difcult to do so on the “z” plane. The construction of a correct midsagittal plane has been the focus of various studies [2533]. In many studies, to evaluate facial asymmetry on the 3D basis, three-dimensional reference planes (horizontal, midsagittal, and coronal reference planes) were established and x, y, and z coordinates of the landmarks to the reference planes were used
[3439]. Figure11.10 displays a skull mirrored at the midsagittal plane. The midsagittal plane can be calculated at landmarks that are not involved in the pathology. However, the method of establishing reference planes according to the clinician’s preferences could make the same problem which happened in 2D analysis. The fundamental progress from the acquisition of 3D images and visualization via volumetric ren­dering enables the employment of appropriate cephalometric parameters to measure skeletal structures so as to establish statistical ranges regarding norms and variations.
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One of the crucial points in all (2D or 3D) cephalometric analysis is the difculty to x limits between what is considered normal and deviation from it. Nearly all methods of analysis refer to an ideal facial model. Variability in the phenotype of the cranium is extremely high, and its architectural balance can be obtained via numerous, even innite, possibilities of adapta­tion among the parts of which it is composed. Therefore, dening a “norm” skull anatomy is an intrinsic problem of all cephalometric analy-
Fig. 11.10 Mirroring of a skull at an ideal midsagittal plane. The analysis displays a high congruency between the left and right side. Landmarks at the cranial skull are used as references
sis. To assess the altered 3D phenotype (skull, jaw, teeth, occlusion) in craniofacially diseased patients, one solution is to superimpose an age­and growth-adjusted “normal” skull. Through this approach, geometric differences can be dened, and their size calculated. 3D virtual models constructed from CBCT scans of cranio­facially diseased patients can be superimposed with norm skulls manually by registering com­mon stable landmarks or by best t of stable anatomical regions. Three general methods of 3D cephalometric superimposition are well pub­lished and used for clinical diagnosis and assess­ment of orthodontic treatment outcomes: (1) voxel based, (2) point/landmark based, and (3) surface based. For overall superimposition, these methods use parts of the anterior cranial base, as a reference structure for CBCT super­imposition, a structure known to have completed most of its growth before the adolescent growth spurt, therefore making it a quite stable refer­ence structure for superimposition in patients with complex craniofacial diseases [4047]. Most of the limitations of 3D superimposition techniques are related to variability in imaging and landmark identication aws and software/ hardware- related errors (Fig. 11.11). In addi­tion, most of the methods that have currently been proposed for clinical settings are quite time-consuming.
abc
Fig. 11.11 Superimposition (a, craniosynostosis patient), mirroring (b, patient with Goldenhar syndrome), and the combined use of superimposition and mirroring (c, patient with Goldenhar syndrome) in craniofacial analysis
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The integration of articial intelligence in the analysis of CBCT or CT data and the mathemati­cal methods to automatically superimpose norm skulls to the diseased skulls open new options to ease such approaches [4852].
New Classication
With all these issues in mind, we have developed a new malocclusion/dysgnathia classication system, focusing on the inclusion of patients with craniofacial malformations. The new system fol­lows two modern aspects: (a) the morphometric approach of considering biological forms as geo­metric objects and (b) the phenotyping of patients on a three-dimensional basis. Both approaches enable a more precise determination of anatomi­cal alterations. Whereas the rst aspect leads to a more dened nomenclature as the basis for clas­sication, the second one enables the anatomical determination of anatomy in the 3D space. Imaging measures like CT or CBCT for the soft tissue and hard tissue components of the investi­gated volume, as well as scanning of the facial surface and intraoral scanning of the dental and alveolar structures, are based on digital data
acquisition. Through this type of data, matching algorithms allow the integration of the different analytical methods in one facial model. Matching of dentoalveolar data generated from scanned dental casts or intraoral scanners with CBCT data and facial surface data leads to a high-resolution phenotyping of patients. Through this approach, it overcomes the two major drawbacks of the present diagnostic approach (the use of lateral cephs, photographs, plaster casts): (a) the inabil­ity of a 3D phenotype representation and (b) the disjunction of the dental, skeletal, and facial sur­face data. The added value is an opportunity to assess morphology, measurements, and position of the live subject and be able to diagnose ana­tomical parameters on a virtual model in high resolution that resembles the real subject totally. This is of special relevance in all patients with craniofacial malformations.
The new classication system (Table 11.4) gives respect (a) to the 3D nature of the disease anatomy and (b) to inherent problems of classi­cation towards anatomical norms (intact skull base, dened midsagittal plane). It is also focused on the use of appropriated diagnostic tools. The diagnostic tools can also serve as the technical basis for virtual treatment planning and craniofa-
Table 11.4 New classication scheme of patients having craniofacial malformations
Class Denition Imaging Analysis Diseases A Dysgnathias with symmetric
alignment
B Dysgnathias with
nonsymmetric alignment
C Dysgnathias with altered
object symmetry CBCT Mirroring CBCT Orofacial clefts
D Dysgnathias with altered skull
base
E Dysgnathias with altered skull
base and midfacial plane
Lateral ceph 1 plane ceph analysis Normal dysgnathias
Lateral+frontal ceph Lateral+frontal ceph
CBCT/CT Superimposition norm skull Craniosynostosis
CBCT/CT Mirroring
2 plane ceph analysis Hypercondylie, jaw
tilting
2 plane ceph analysis CLP
Branchial arch CBCT+superimposition norm skull
diseases
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abc
Fig. 11.12 Modern approach of a) data use, b) planning, and c) execution of craniofacial reconstruction procedures
cial reconstruction surgery (PSI-based orthogna­thic surgery and PSI bone augmentation, Fig.11.12).
Conclusion
Common malocclusion classication systems fail to determine a precise phenotyping of cranio­facial malformed patients. The combined appli­cation of a geometric based jaw/skull classication system and the use of a disease­related extended phenotyping protocol by digital data acquisition (CBCT/dental scan, facial scan) allows a precise classication of patients with craniofacial malformations.
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