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The Effect of Cone Beam CT Voxel Size on the Identification of Vertical and Horizontal Root Fractures:
An In-Vitro Study
by
Niloufar Amintavakoli
A thesis submitted in conformity with the requirements for the Degree of Master of Science in Oral and Maxillofacial Radiology
Discipline of Oral and Maxillofacial Radiology, Faculty of Dentistry University of Toronto
© Copyright by Niloufar Amintavakoli 2013
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The Effect of Cone Beam CT Voxel Size on the
Identification of Vertical and Horizontal Root Fractures:
An In-Vitro Study
Niloufar Amintavakoli
Master of Science in Oral and Maxillofacial Radiology
Discipline of Oral and Maxillofacial Radiology, Faculty of Dentistry
University of Toronto
2013
Abstract
Objective: The purpose of this study is to determine the relationship between cone beam CT
(CBCT) voxel size and tooth root fracture detection. Materials and Methods: Vertical and
horizontal root fractures were induced in a total of 30 teeth, and 15 teeth were left intact.
Teeth were imaged with projection digital radiography and the Kodak 9000 3D CBCT
system with a native voxel size of 76 μm. The CBCT voxels were then downsampled to 100
μm, 200 μm and 300 μm. Five blinded observers evaluated both sets of images with a 1
week washout interval between each set of observations. Results: CBCT outperformed the
projection images for fracture detection for all voxel sizes except 300 μm (p<0.05). No
significant differences were found between the different voxel sizes (p>0.05). Conclusion:
Although voxel size does not impact the interpretation of root fractures, in vitro, CBCT
outperformed projection imaging for voxel sizes less than 300 μm.
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Acknowledgments
I would like to express my sincere gratitude to my advisor Dr. Ernest Lam for his
support and guidance in all the time of research and writing of this thesis and also throughout
the three years of my graduate study.
A special thanks to my research committee members Drs. Pharoah and Basrani for
their constructive comments and encouragements.
My sincere thanks also goes to Drs Mariam Baghdady, Masoud Varshosaz, Catherine
Nolet-Levesque and Daniel Turgeon for their kindness in volunteering their time and
experience in this project.
Last but not the least, an extraordinary thanks to my parents, Farideh and Mohammad,
who are my life long teachers and my husband, Siamak, for his unconditional support and
encouragements.
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Table of Contents
Abstract .................................................................................................................................... ii
Acknowledgments .................................................................................................................. iii
Table of Contents .................................................................................................................... iv
List of Tables ........................................................................................................................... vi
List of Figures .......................................................................................................................... ix
List of Appendices .................................................................................................................... x
Chapter 1: Introduction .......................................................................................................... 1
1.1 Overview .................................................................................................................. 1
1.2 Vertical Root Fractures ............................................................................................ 2
1.3 Horizontal Root Fractures ........................................................................................ 4
1.4 Radiographic Features of Root Fractures ................................................................ 5
1.5 Cone Beam CT ......................................................................................................... 7
1.6 Cone Beam CT in the Diagnosis of Root Fractures in Non-Endodontically-
Treated Teeth .................................................................................................................... 11
1.7 Cone Beam CT in the Diagnosis of Root Fractures in Endodontically-Treated
Teeth ................................................................................................................................. 18
1.8 Statement of the Problem ....................................................................................... 26
1.9 Objectives and Hypotheses .................................................................................... 27
1.10 Null Hypotheses ................................................................................................... 27
Chapter 2: Methods and Materials ...................................................................................... 29
2.1 Sample Preparation ................................................................................................ 29
2.2 Image Acquisition .................................................................................................. 31
2.3 Image Evaluations .................................................................................................. 32
2.4 Projection Radiography Study ............................................................................... 33
2.5 Data Analysis ......................................................................................................... 35
2.6 Observers Agreement ............................................................................................. 35
Chapter 3: Results .................................................................................................................. 37
3.1 Diagnostic Test Results for CT Images ................................................................. 37
3.2 Comparison of Voxel Sizes and Fracture Detection .............................................. 43
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3.3 Comparison of the Observers ................................................................................. 49
3.4 Comparison of Type of Tooth ................................................................................ 51
3.5 Comparison of Time .............................................................................................. 54
3.6 Diagnostic Test for Digital Periapical Images ....................................................... 55
3.7 Observers Agreement ............................................................................................. 55
Chapter 4: Discussion and Conclusion ................................................................................ 57
4.1 Overview ................................................................................................................ 57
4.2 Study Limitations ................................................................................................... 62
4.3 Future Directions ................................................................................................... 63
4.4 Clinical Implications and Conclusion .................................................................... 63
References ................................................................................................................................ 64
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List of Tables
Table 1.1: Summary of the results of in vitro studies of non-endodontically-treated teeth
using cone beam CT for the diagnosis of vertical root fractures. Where other manipulations
were performed (endodontic treatment or metal post placement), only the results of the non-
endodontically-treated teeth are summarized ..................................................................... 13-15
Table 1.2: Summary of the results of in vivo studies of non-endodontically-treated teeth using
cone beam CT for the diagnosis of horizontal root fractures. Where other manipulations were
performed (endodontic treatment or metal post placement), only the results of the non-
endodontically-treated teeth are summarized. .......................................................................... 17
Table 1.3: Summary of the results of in vitro studies of endodontically-treated teeth using
cone beam CT for the diagnosis of vertical root fractures. ................................................ 20-23
Table 1.4: Summary of the results of in vivo studies of endodontically-treated teeth using
cone beam CT for the diagnosis of vertical root fractures. ....................................................... 25
Table 3.1: Specificities, sensitivities, positive and negative predictive values for each
resolution and all root fractures for the cone beam CT images. .............................................. 37
Table 3.2 Areas under the receiver operator curves for different voxel resolutions and all root
fractures. .................................................................................................................................... 38
Table 3.3: Specificities, sensitivities, positive and negative predictive values for each
resolution and vertical root fractures for the cone beam CT images. ....................................... 39
Table 3.4: Areas under the receiver operator curves for different voxel resolutions and
vertical root fractures only. ....................................................................................................... 40
Table 3.5: Specificities, sensitivities, positive and negative predictive values for each
resolution and horizontal root fractures for the cone beam CT images. ................................... 41
Table 3.6: Area under the receiver operator curves for different voxel resolutions and
horizontal root fractures only. ................................................................................................... 42
Table 3.7: Comparison between each pair of voxel sizes in detection of all root fractures for
all observers. ............................................................................................................................ 43
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Table 3.8: Comparison of voxel sizes in detection of vertical root fractures only for all
observers. .................................................................................................................................. 44
Table 3.9: Comparison of voxel sizes in detection of vertical root fractures only in the oral
radiology graduate student group. ............................................................................................. 45
Table 3.10: Comparison of voxel sizes in detection of vertical root fractures only in the oral
radiologist group. ...................................................................................................................... 46
Table 3.11: Comparison of voxel sizes in detection of horizontal root fractures only for all
observer groups. ........................................................................................................................ 47
Table 3.12: Comparison of voxel sizes in detection of horizontal root fractures only in the
oral radiology graduate student group. ..................................................................................... 48
Table 3.13: Comparison of voxel sizes in detection of horizontal root fractures only in the
oral radiologist group. .............................................................................................................. 49
Table 3.14: Comparison of oral radiology graduate students and oral radiologists in detection
of both types of fractures with each voxel size (df: 1/n: 150). ................................................. 50
Table 3.15: Comparison of oral radiology graduate students and oral radiologists in detection
of vertical fractures with each voxel size (df: 1/n: 150). .......................................................... 50
Table 3.16: Comparison of oral radiology graduate students and oral radiologists in detection
of horizontal fractures with each voxel size (df: 1/n: 150). ..................................................... 51
Table 3.17: Comparison of detection of root fractures between teeth in voxel size 76 µm
(df:1). ........................................................................................................................................ 51
Table 3.18: Comparison of detection of root fractures between teeth in voxel size 100 µm
(df:1), ....................................................................................................................................... 52
Table 3.19: Comparison of detection of root fractures between teeth in voxel size 200 µm
(df:1). ....................................................................................................................................... 52
Table 3.20: Comparison of detection of root fractures between teeth in voxel size 300 µm
(df:1). ....................................................................................................................................... 53
Table 3.21: Comparison of detection of root fractures between teeth in periapical radiographs
(df:1). ....................................................................................................................................... 53
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Table 3.22: Comparison of the mean time (seconds) spent by oral radiology graduate students
and oral radiologists in the detection of root fractures with each voxel size (df:223) .............. 54
Table 3.23: Comparison of each voxel size with periapical radiographs in detection of root
fractures (df:1/n:90). ................................................................................................................. 55
Table 3.24: Kappa values for the intra and inter observer agreement for each resolution and
periapical radiographs. .............................................................................................................. 56
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List of Figures
Figure 1.1: Complete and incomplete vertical tooth fracture patterns.
(adapted from Rivera et al.4). ...................................................................................................... 2
Figure 1.2: Schematic diagram of horizontal fractures (based on 33 fracture lines caused by
frontal impacts) (from Andreasen24
) ........................................................................................... 5
Figure 2.1: The bench vice used to induce vertical fractures .................................................. 30
Figure 2.2: Five teeth mounted in stone in the same manner as inside the mouth .................. 30
Figure 2.3: Samples were centered in the center of the field of view ...................................... 31
Figure 2.4: Bucco-lingual cross section slices of a molar with a vertical root fracture at voxel
sizes A) 76 μm, B) 100 μm, C) 200 μm, D) 300 μm ................................................................ 32
Figure 2.5: Bucco-lingual cross section slices of a molar with a horizontal root fracture at
voxel sizes A) 76 μm, B) 100 μm, C) 200 μm, D) 300 μm ...................................................... 32
Figure 2.6: Periapical images of a molar with a vertical root fracture (presented in figure 2.4)
with angulations of A) zero degrees and B) 15 degrees to the long axis of the tooth .............. 34
Figure 2.7: Periapical images of a central incisor with a horizontal root fracture (presented in
figure 2.5) with angulations of A) zero degrees and B) 15 degrees to the long axis of the
tooth .......................................................................................................................................... 34
Figure 3.1: ROC curves for all root fractures and all voxel resolutions .................................. 38
Figure 3.2: ROC curves for vertical root fractures only and all voxel resolutions .................. 40
Figure 3.3: ROC curves for horizontal root fractures only and all voxel resolutions .............. 42
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List of Appendices
Appendix 1: Copy of the ethics approval of the research ........................................................ 72
Appendix 2: Consent Form for the observers .......................................................................... 73
Appendix 3: Tables of raw data ............................................................................................... 75
1
Chapter 1
1 Introduction
1.1 Overview
Tooth fractures represent splits or breaks in tooth structure that can involve the crown
and/or the root, enamel, dentin, cementum and/or pulp1, and numerous classification schemes
have been proposed over the years.2 Andreasen and Andreasen (1994) classified fractures into
5 subgroups based on the type(s) of tissue(s) involved, and complexity of the fracture pattern:
enamel fracture, uncomplicated enamel and dentin fracture, complicated enamel and dentin
fracture, crown and root fracture, and root fracture.3 In another scheme, Talim and Gohil
classified tooth fractures into those involving enamel (class 1), those involving enamel and
dentin without involving pulp (class 2), those involving enamel and dentin involving the pulp
(class 3), and those involving the roots (class 4). Walton looked specifically at longitudinal
tooth fractures, and classified these into 5 subgroups based on their extension: (1) craze lines,
(2) fractured cusp, (3) cracked tooth, (4) split tooth, and (5) vertical root fracture.4 (Figure 1.1)
Root fractures themselves have been further classified as being coronal, mid-root or apical
types based on their location, and/or vertical, horizontal or oblique.5 Furthermore, vertical root
fractures could involve the pulp or not, and horizontal root fractures could involve the
cervical, middle or apical thirds.2,6
Suffice it to say, there is a wide range and variability in the
way clinicians report fractures of teeth.
2
Figure 1.1: Incomplete and complete vertical tooth fracture patterns (adapted from
Rivera et al.4).
1.2 Vertical Root Fractures
A vertical root fracture is characterized by a cleavage plane that extends through the
long axis of the root, generally in an apical-coronal direction.7,8
Vertical root fractures can be
complete or incomplete; a complete fracture extends extends through the root structure and
involves both root surfaces and an incomplete fracture involves only one surface of the root.9
The prevalence of vertical root fractures has been reported to vary between 2% and 5% in
clinical studies of endodontically-treated teeth.10
The prevalence of vertical root fracture in the
extracted endodontically-treated teeth has been reported to be 10.9%.11
Recently, there has
been an increase in the prevalence of vertical root fractures being diagnosed, and this has been
ascribed to a decrease in the number of tooth extractions and improvements in the diagnosis of
the fractures.4
The etiologic factors contributing to vertical root fractures can be either non-iatrogenic
or iatrogenic. The loss of tooth structure as a result of previous pathosis and anatomical
variations of teeth are the primary non-iatrogenic factors predisposing teeth to vertical root
!!!!!!!!!!!!A!!!!!!!!!!!!!!!!!!!!B!!!!!!!!!!!!!!!!!!C!!!!!!!!!!!!!!!!D!!!!!!!!!!!!!!!!!!!!!!!E!
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fractures. Changes in the dentinal tubules during aging and the gradual infill of the dentinal
tubules with minerals over time are the secondary non-iatrogenic cause of vertical root
fractures in teeth.10,12,13
Iatrogenic causes of vertical root fractures can be the result of loss of
tooth structure during endodontic treatment, the effects of chemicals or intra-canal
medications, and restorative procedures.12
The stress distribution in an endodontically-treated tooth is different from one that has
not been endodontically-treated. One of the factors that makes endodontically-treated teeth
more prone to fracture is the excessive removal of healthy tooth structure in curved and
narrow root canals during endodontic treatment.12
A discrepancy between the elastic moduli of
the post-crown system and tooth structure may change the distribution of stresses and strains
in the tooth, and this may predispose it to fracture.10
Furthermore, the loading angle of the
crown, type of material used in the core, features of the remaining tooth structure, shape and
diameter of the post, and the adhesion of the post to dentin are additional factors that may
predispose a tooth to fracture.12
Clinically, a tooth with a vertical fracture may display a wide range of signs and
symptoms including spontaneous pain, history of pain on biting, local swelling, sinus tract
formation, exacerbation of chronic inflammation, development of a periodontal pocket, and
sensitivity to percussion and palpation.9,14,15
Tamse et al. evaluated 92 extracted
endodontically-treated teeth with vertical root fracture, and pain (51%) and abscess (31%)
were the major complaints of the patients with vertical root fractures. The most common sign
of vertical root fracture was a deep periodontal pocket (67.4%), followed by sensitivity to
percussion, mobility, and fistula formation. The combination of both a deep pocket and fistula
formation was also reported in this series of patients.16
The presence of a sinus tract was
reported in 13% to 42% of the vertical root fracture cases, and these were usually located close
to the gingival margin of the osseous defect.9,10
The presence of two sinus tracts in both the
buccal and lingual cortices is another sign associated with vertical root fracture, and this may
be considered a pathognomonic feature of vertical root fractures.9,15
A periapical radiograph
made with gutta percha inserted into the area of the orifice may allow the sinus tract to be
traced to the location of the fracture.10,17
Also, periodontal pocket probing in vertical root
fractures is more localized compared to bone loss due to periodontal disease, which is more
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generalized and can involve more than one surface of the tooth.9 Although definitive diagnosis
of vertical root fracture is made by direct visualization of the fracture, transillumination,
periodontal probing, staining, bite testing and radiographic examination are the most common
clinical procedures used to diagnose vertical root fractures.9,10,15
During surgical intervention,
an area of dehiscence or fenestration may be observed in the adjacent bone surface,18
and if
the overlying bone is intact, an apicectomy may be attempted to better visualize the fracture.9
The prognosis of vertical root fractures is usually poor, although this may depend on
the degree of separation of the fragments and involvement of the pulp.4 The release of bacteria
in the area and consequent destruction of the surrounding tissues make any treatment other
than extraction impossible, especially in single rooted teeth.9,17
In teeth with multiple roots,
hemi-section or root amputation in order to remove the fractured root is the treatment of
choice.4 In general, the prognosis of vertical root fractures in single root teeth is usually poor,
so an early, definitive diagnosis is important to reduce damage to the adjacent tissues.7,19
1.3 Horizontal Root Fractures
Horizontal root fractures are usually associated with acute trauma, and these fracture
planes are generally oriented orthogonally to the long axis of the tooth root (Figure 1.2).20
Horizontal fractures are most commonly seen in the middle third of the root, and in teeth with
completely formed roots and root apices.21
A horizontally fractured root may appear clinically
normal, although it may be extruded or its crown displaced. In the case of trauma, soft tissue
swelling may also be seen, and this may make the clinical evaluation of the area difficult.22
The degree of displacement of the fracture fragments is related to both severity of the injury
and the location of the fracture. The closer the fracture is to the crown, the greater is the
degree of tooth displacement.23
5
Figure 1.2: Schematic diagram of horizontal fractures (based on 33 fracture lines caused by
frontal impacts) (from Andreasen24
)
The treatment of horizontal root fractures depends on whether or not there is
communication of the fracture with the oral cavity. In the case of communication, the coronal
fragment should be extracted and the rest of the tooth can be either extruded or extracted. If
communication with the oral cavity is not present, reduction and alignment of the displaced
segments and stabilization can be done.21
The treatment may, however, be followed by pulp
necrosis, root canal calcification or obliteration, root resorption or fracture non-healing.21
Prognosis is usually influenced by different factors including age of the patient, stage of root
formation and closure of the apex, degree of dislocation of the coronal fragment, mobility of
the coronal and apical fragments, and distance between the fragments.25
A radiographic
evaluation is usually required for the follow-up as well as diagnosis.
1.4 Radiographic Features of Root Fractures
Radiography may not definitively identify a fractured root. Clinicians often base their
diagnoses on the patient’s clinical signs and symptoms, and on features identified on
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conventional radiographs. The radiographic features of vertical root fracture are divided into
direct and indirect signs. The presence of a radiolucent line confined to and between the
fragments of a fractured root or root filling material, separation of root fragments, space
adjacent to a root filling or a post are direct radiographic features of root fracture.15,26
Without
the presence of separation of the tooth fragment, the direct diagnosis of fracture is generally
very difficult radiographically.10
A fracture line may not be visible on a conventional
radiograph if the x-ray beam does not pass through or is not aligned with the fracture plane.
Consequently, usually more than one periapical radiograph made at two or more different
horizontal angulations may be necessary to detect the radiolucent fracture line.10,27
The indirect radiographic features of vertical root fracture include localized widening
of the periodontal ligament space, and periapical or periradicular rarefaction.28
As well, there
may be periodontal bone loss adjacent to the fracture area in the early stages.10
The pattern of
bone resorption associated with a root fracture may show different appearances including
periapical radiolucency, isolated perilateral radiolucency, “halo” radiolucency, periodontal
radiolucency, vertical bone loss, and also bifurcation radiolucency.18,29,30
Tamse et al. in a
study of 49 extracted teeth with vertical root fracture found halo radiolucency (37%) and
periodontal radiolucency (29%) to be the most commonly associated signs of root fracture.29
Displacement of retrograde filling material into the surrounding tissue may also indicate the
presence of root fracture.10
There have been few studies evaluating the use of conventional and digital radiography
in the diagnosis of vertical root fracture. In a study with 60 extracted teeth, Tsesis et al.
reported specificities of 0.89 and 0.87 for film and digital radiography using a charge coupled
device, respectively, and sensitivities of 0.48 and 0.38, respectively. There was no significant
difference between these two modalities in their abilities to diagnose root fractures.31
The radiographic diagnosis of horizontal root fractures usually requires more than one
image. A radiographic follow up may also be required in the case of horizontal root fracture in
order to evaluate the consequences of treatment. Andreasen et al. stated that usually a
combination of an occlusal radiograph and a conventional periapical radiograph with
bisecting-the-angle technique is required for diagnosis of horizontal root fractures.32
The
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occlusal radiograph is more reliable in diagnosis of oblique fractures in the apical and middle
third of the root and the periapical radiograph is a better diagnostic device in diagnosis of
horizontally angled coronal root fractures.21
The recommendation of the International
Association of Dental Traumatology is to obtain several radiographs in several angulations
based on the clinician’s judgment. This combination may include a periapical radiograph with
a 90˚ horizontal angle, occlusal view, and a periapical radiograph with lateral angulations from
the mesial or distal aspects of the tooth in question as well as a cone beam CT study in
complicated cases.22
As conventional radiographs are two-dimensional images of a three-dimensional
object, it may be difficult at times to detect radiographic features of fracture on these
images.33,34
Moreover, fracture detection may also be hindered by superimposition of adjacent
tissues, morphologic variations of tooth roots, magnification distortion, surrounding bone
density, x-ray angulation, and radiographic contrast.25,26,35
The inability of conventional two-dimensional imaging systems encouraged
researchers to find alternative ways to diagnose root fractures. Medical multidetector helical
computed tomography (CT) using a fan-shape x-ray beam has been used for this purpose.
Youssefzadeh et al., in an in vivo study, in the evaluation of 42 teeth suspected of vertical root
fracture imaged with medical CT, reported specificity and sensitivity to be 100% and 70%,
respectively. These workers also reported that medical CT was superior to conventional
images in the diagnosis of root fractures.36
The limitation of this study is that all the fractures
were displaced; incomplete and non-displaced fractures, which are more difficult to diagnose,
were not examined.37
Recently, clinicians have turned to cone beam CT to evaluate tooth
fractures because of rapid acquisition time, lower relative patient radiation dose, a more
highly-collimated x-ray beam, and higher image resolution with cone beam CT.38
1.5 Cone Beam CT
Cone beam CT is a three-dimensional imaging modality in which a cone-shaped x-ray
beam rotates around the patient’s head.33,39
The three-dimensional nature of cone beam CT is
reported to result in better visualization of both direct and indirect radiographic signs of root
8
fracture.33,40
The divergent cone-shaped x-ray beam is directed through the area of interest and
the attenuated beam is detected. During the single rotation of the x-ray source and detector
around a fixed fulcrum, multiple planar “basis” projection images are acquired of the field of
view.33,38,41
Three-dimensional image volumes are made up of volume elements or voxels, as
the smallest elements of these images. The size of each voxel is determined by its height,
width and thickness. A cone beam CT voxel is isotropic, meaning its height, width and
thickness are all equal.42
The voxel sizes of different cone beam CT systems vary from 0.076
mm (76 μm) to 0.40 mm (400 m), and this value is what determines the spatial resolution of
a cone beam CT system; the smaller the voxel size, the higher the spatial resolution.33,38,41
Choosing the optimal voxel resolution in cone beam CT is task-specific.33
Liedka et al. in their
in vitro study evaluating 60 human mandibular incisors with simulated external root resorption
reported that a voxel resolution of 0.30 mm is the optimal voxel resolution for diagnosis.43
In
another in vitro study, Bauman et al. used 24 extracted human maxillary molars and scanned
them at four voxel resolutions with the iCAT Classic (Imaging Sciences International,
Hatfield, PA, USA). Five endodontic postgraduate students and two endodontic staff then
evaluated 96 videos generated from horizontal images of these studies.44
They reported that
detection of the mesio-buccal canal in the maxillary molars increased from 60.1% to 93.3% by
decreasing voxel size from 0.40 mm to 0.125 mm. Amongst the many cone beam CT systems
available on the market, the Kodak 9000 3D (Carestream, Rochester, NY, USA) has the
highest reported native spatial resolution (76 μm).33
Michetti et al., using a Kodak 9000 3D
(Carestream, Rochester, NY, USA) to explore root canal anatomy, scanned nine extracted
teeth (14 canals) and then compared the outlined canals with the canals obtained using areas
and Feret’s diameters from histologic sections. These researchers reported strong to very
strong correlations between the cone beam reconstructions and the histologic sections for
canal diameter (r=0.890) and area (r=0.928).45
The spatial resolution of periapical radiographs is determined by the size of the pixel in
digital imaging systems, or the size and number of the silver halide crystals in the
conventional imaging systems. In a study of comparison of 18 different x-ray detectors used in
dentistry, Farman et al. reported that the pixel size of x-ray detectors currently used in
dentistry varies between 18.5 to 40 μm, which is smaller compared with the smallest voxel
9
size available with cone beam CT.46
In comparison, the size of the silver halide crystal is even
smaller than the smallest pixel size available, varying between 1.0 to 1.8 μm.47
Variations in
the sizes of imaging elements result in spatial resolutions of between 5 and more than 20 line
pairs per millimeter.38,46,47
Minimizing radiation risk injury is a primary concern when choosing the type of
imaging to perform. The effective dose of cone beam CT scans is affected by several factors
including the imaging parameters used (kVp, mA), whether x-ray beam emission is pulsed or
continuous, the amount, type, and shape of x-ray beam filtration, the number of basis images
required to create the volume, and the size of the field of view.33
One way that radiation risk
can be quantified for different modalities is by examining effective radiation dose from
different imaging modalities.33
The range of effective doses to the mandible and maxillae in
medical CT scans based on a combination of both maxillae and mandible scans and hyoid to
skull base scans is 1320 to 3324 μSv (mandible) and 1031 to 1420 μSv (maxillae).41
By
limiting the volume of tissue imaged, the effective radiation dose can decrease substantially.
For these smaller field-of-view cone beam CT units, effective radiation doses have been
reported to vary between 5.3 to 488 μSv depending on the imaging site and system.33
For
example, Ludlow calculated the lowest dose from the Kodak 9000 3D system (Carestream,
Rochester, NY, USA) to be 5.3 Sv in the anterior maxilla, and a higher effective dose was
calculated for the Planmeca Promax 3D (Planmeca OY, Helsinki, Finland). 48
Scattering of the x-ray beam is a drawback of cone beam CT systems. Scatter radiation
refers to the askew radiation which degrades the image quality by increasing image noise and
decreasing the image contrast, and increases patient radiation without a concomitant patient
benefit.38,49
Because medical CT beams are collimated in a fan shape rather than a cone shape,
the amount of scattered radiation is lower compared to the cone beam CT systems. The ratio
of scatter to primary radiation can be as high as 3 in large field of view cone beam CT scans,
however, this ratio is 0.2 for multidetector medical CT systems.49
Other factors that contribute
to the quality of the images are contrast-to-noise ratio and signal-to-noise ratios. Daly et al in
their study showed that contrast to noise ratio increases as the square root of dose and voxel
size, decreases as the inverse of the reconstruction filter relative cutoff frequency.50
Signal to
10
noise ratio represents the ratio of the signal to background noise. Increasing the number of
projection data and frame rate increases the signal to noise ratio. 38
As well as scatter radiation, CT image-related artifacts can also affect the quality of
images. These artifacts can be classified being patient-related, scanner-related, those specific
to the cone beam CT system used and x-ray beam-related.33,38
Patient-related artifacts may be
related to the presence of high attenuation materials such as gutta percha or metallic
restorations, including crowns.30
Metal objects can degrade the quality of CT images by
creating alternating radiopaque and radiolucent “bright tracks” that can overlap the tooth root
and mimic root fractures.51
Since the restoration of endodontically-treated teeth often requires
the insertion of a metallic intra-canal post, the presence of such artifacts is one of the major
limitations of cone beam CT in diagnosis of root fractures.40
Partial volume averaging is a machine-related artifact that is a feature of both medical
fan beam and cone beam CT systems. This artifact occurs when the voxel size is greater than
the size of an object being imaged. In the resultant image, the voxel represents a weighted
average of the densities of the different tissues contained within that voxel. Therefore, if the
object is smaller than the size of the voxel, the numerical value of the voxel will represent an
average of the portion of the voxel filled by the object and whatever other material is
contained within the voxel. By using systems with smaller voxel sizes, the potential of partial
volume averaging is less.38,52
Studies focusing on the application of cone beam CT to diagnose root fractures began
appearing in the literature in 2009. These studies evaluated the role of cone beam CT scan in
both endodontically and non-endodontically-treated teeth. Despite the reported higher
specificity and sensitivity of cone beam CT compared to conventional radiography for the
detection of root fractures, the limitations of cone beam CT may include an increased radiation
dose, the presence of image artifacts, and the lower spatial resolution compared to periapical
radiographs.33,39
11
1.6 Cone Beam CT in the Diagnosis of Root Fractures in Non-Endodontically-Treated Teeth
Hassan et al. investigated vertical root fractures in an in vitro model using teeth
fractured with a hammer and tapered chisel inserted into the root canal space. This study of
root filled and non-filled teeth was performed using an i-CAT cone beam CT system (Imaging
Sciences, Hatfield, PA, USA) with voxel size of 0.25 mm. They reported the specificity and
sensitivity of cone beam CT in the absence of root filling material to be 97.5% and 80.0%,
respectively. Furthermore, cone beam CT had significantly higher sensitivity (79.4%) but not
specificity compared with periapical radiographs (37.1%).40
In a similar study, Varshosaz et
al. used the Promax 3D (Planmeca, Helsinki, Finland) operating at a voxel size of 0.30 mm,
and found that the area under the receiver operator curve (ROC) to be 0.91.35
Using a small
voxel size of 0.16 mm, Valizadeh et al. reported an area under the ROC curve of 0.74, and
detection specificity of 76.9% and sensitivity of 66.7%.53
Kambungton et al. used the
Veraviewepocs 3D (Morita Mfg. Corp., Kyoto, Japan), a system with an even smaller voxel
size of 0.125 mm. These workers found the mean areas under the ROC curves for cone beam
CT to be 0.81 compared with film (0.80) and a digital sensor (0.77); there were no
statistically-significant differences between the 3 modalities.54
In a more extensive in vitro study of voxel size effects, Ozer used the Imaging
Sciences International i-CAT (Imaging Sciences, Hatfield, PA, USA) and observed no
significant differences in specificities and sensitivities between the different voxel sizes they
investigated, but reported higher positive likelihood ratios for 0.125 mm and 0.20 mm voxel
sizes compared with 0.30 mm and 0.40 mm voxel sizes.42
Da Silveira et al. used the same
cone beam CT system and studied non-root filled teeth, root filled and teeth containing a metal
post in an in vitro study at three different voxel sizes (0.20 mm, 0.30 mm, 0.40 mm).
Conventional radiography performed equally well to cone beam CT images acquired at 0.20
mm and 0.30 mm voxel resolutions of teeth that were not endodontically-treated; the
calculated values of specificity, sensitivity, and accuracy (true positives and true negatives)
were all similar.55
Khedmat et al. compared the diagnostic ability of digital radiography, multidetector
medical CT and cone beam CT in the diagnosis of vertical root fracture in both the absence
12
and presence of gutta percha. Using a system with a smaller 0.16 mm voxel resolution
(Planmeca Promax 3D, Roselle, IL, USA), these workers reported cone beam CT specificity
and sensitivity to be 88% and 92%. The specificity and accuracy of cone beam CT was
significantly higher than digital radiography and medical CT. There were, however, no
significant differences among the sensitivities of the three modalities.56
13
Table 1.1: Summary of the results of in vitro studies of non-endodontically-treated teeth using cone beam CT for the diagnosis of
vertical root fractures. Where other manipulations were performed (endodontic treatment or metal post placement), only the results of
the non-endodontically-treated teeth are summarized.
Study Sample Cone beam CT imaging system Results
Hassan et al., 200940
80 extracted teeth (40
premolars and 40 molars)
placed in dry human
mandible.
i-CAT, 0.25 mm voxel size. Specificity: 97.5%
Sensitivity: 80.0%
Varshosaz et al., 201035
100 single-rooted teeth placed
in dry human mandible.
Promax 3D, 0.30 mm voxel size. ROC curve area: 0.91
Valizadeh et al., 201153
120 extracted single-rooted
teeth placed in acrylic blocks.
NewTom 3G, 0.16 mm voxel size. Specificity: 76.9%
Sensitivity: 66.7%
Ozer, 201142
60 extracted maxillary
premolar teeth placed in dry
human mandible.
i-CAT, 0.125 mm, 0.20 mm, 0.30
mm, 0.40 mm voxel sizes.
0.125 mm voxel size
Specificity: 96%
Sensitivity: 98%
Accuracy: 97%
0.20 mm voxel size
Specificity: 96%
Sensitivity: 97%
Accuracy: 96%
14
0.30 mm voxel size
Specificity: 93%
Sensitivity: 93%
Accuracy: 93%
0.40 mm voxel size
Specificity: 93%
Sensitivity: 91%
Accuracy: 92%
Da Silveira et al., 201355
60 extracted single-rooted
teeth placed in acrylic blocks.
i-CAT, 0.20 mm, 0.30 mm and
0.40 mm voxel sizes.
0.20 mm voxel
Specificity: 100%
Sensitivity: 97%
Accuracy: 98%
0.30 mm voxel
Specificity: 97%
Sensitivity: 87%
Accuracy: 92%
0.40 mm voxel
Specificity: 80%
Sensitivity: 76%
Accuracy: 77%
15
Kambungton et al.,
201254
60 extracted single-rooted
teeth placed in dry human
mandible.
Veraviewpocs 3D, 0.125 mm
voxel
ROC curve area: 0.81
Khedmat et al., 201256
100 extracted single-rooted
teeth placed in acrylic blocks.
Promax 3D, 0.30 mm voxel Specificity: 88%
Sensitivity: 92%
Accuracy: 90%
16
Finally, in an in vivo study, Wang et al. investigated vertical root fractures in 86 teeth
with the 3D Accuitomo 80 (J. Morita, Kyoto, Japan) that uses a voxel size of 0.125 mm. The
fractures were also confirmed by surgery. These workers reported specificity and sensitivity of
94.7% and 97%, respectively, for cone beam CT, and 100.0% and 26.3%, respectively, for
periapical radiographs. 14
Only a few studies have investigated the specificity and sensitivity of cone beam CT in
the diagnosis of horizontal root fractures. Kamburoğlu et al. used the 3D Accuitomo 80 (0.08
mm voxel size) (J. Morita, Kyoto, Japan) and compared these images with intraoral
radiographs in an in vitro study. They failed to report any significant differences between the
reported specificities, however, they reported significant differences in the sensitivities of the
two methods.34
A similar study by Avsever et al. compared two different cone beam CT
systems (the 3D Accuitomo 170 cone beam CT [J. Morita, Kyoto, Japan] and the NewTom 3G
cone beam CT [QR SLR, Verona, Italy]) with the VistaScan photostimulable phosphor system
(Dürr Dental GmbH & Co. KG, Germany), a charge couple device sensor (Trophy Radiologie
Inc., Paris, France) and conventional film (Kodak Insight Film, Eastman Kodak Co.,
Rochester, NY). They reported that the specificity and sensitivity of the 3D Accuitomo 170
cone beam CT (97% and 94%, respectively) were higher than the NewTom 3G cone beam CT,
as well as the digital image detectors and conventional film.25
Iikubo et al. also reported higher
sensitivity with limited field-of-view cone beam CT incorporating a 0.117 mm voxel size
compared with intraoral radiography or multidetector helical CT at slice thicknesses of 0.63
mm and 1.25 mm in a study on 28 maxillary anterior teeth.20
17
Table 1.2: Summary of the results of in vivo studies of non-endodontically-treated teeth using cone beam CT for the diagnosis of
horizontal root fractures. Where other manipulations were performed (endodontic treatment or metal post placement), only the results
of the non-endodontically-treated teeth are summarized.
Study Sample Cone beam CT imaging system Result
Kamburoğlu et al.,
200934
36 incisor teeth placed in dry
human maxillae.
Accuitomo 80, 0.08 mm voxel Specificity: 97%
Sensitivity: 92%
Iikubo et al., 200920
28 maxillary anterior teeth
with 13 fractured placed in 7
beagle dogs’ maxillae.
PSR-9000N Dental CT, 0.117 mm
voxel
Specificity: 91%
Sensitivity: 96%
Accuracy: 93%
Avsever et al., 201325
82 extracted human
maxillary incisors with 31
fractured placed in dry
human maxillae.
Accuitomo 170, 0.08 mm voxel
NewTom 3G, 0.18 mm voxel
3D Accuitomo
Specificity: 97%
Sensitivity: 94%
Accuracy: 93%
NewTom 3G
Specificity: 89%
Sensitivity: 89%
Accuracy: 87%
18
1.7 Cone Beam CT in the Diagnosis of Root Fractures in Endodontically-Treated Teeth
Since root fractures are most commonly seen in endodontically-treated teeth and the
presence of root canal filling material and posts are sources of artifact in cone beam CT
images, it is reasonable to evaluate the efficacy of cone beam CT scan in diagnosis of root
fractures in endodontically treated teeth.
Khedmat et al. in an in vitro study found that in the presence of gutta percha, the
specificity of dental radiography (100%) and multidetector medical CT (88%) were
significantly higher than cone beam CT (64%). However, there were no significant differences
between the sensitivities of these modalities in the presence of gutta-percha. The accuracy of
multidetector medical CT (78%) for the detection of vertical root fractures was significantly
higher than that of cone beam CT (72%) and digital radiography (64%). Furthermore, these
workers showed that the accuracy, specificity and sensitivity of cone beam CT was
significantly reduced in the presence of gutta-percha although gutta-percha had no effect on
accuracy, specificity and sensitivity of multidetector medical CT.56
Hassan et al. imaged 80 extracted teeth for vertical root fractures in root canal filled
teeth using the i-CAT cone beam CT system (Imaging Sciences, Hatfield, PA, USA) with
voxel size of 0.25 mm, and reported a specificity and sensitivity of 87.5% and 78.8%,
respectively.40
Mello et al. evaluated the effect of the presence of cast-gold posts and gutta
percha on the diagnostic ability of cone beam CT to identify vertical root fractures with two
different voxel sizes. They reported the 0.20 mm voxel resolution showed greater sensitivity
(82%) than a 0.30 mm voxel size (51%) for fracture detection, but concluded that although
cast-gold posts and gutta percha decreased the overall diagnostic ability of cone beam CT, this
was not statistically significant.19
In another in vitro study, Hassan et al. compared five different cone beam CT systems:
the NewTom 3G (QR SLR, Verona, Italy), the i-CAT (Imaging Sciences, Hatfield, PA, USA),
the Galileos 3D (Sirona Germany, Bensheim, Germany), the Scanora 3D (Soredex, Tuusula,
Finland), and the 3D Accuitomo (J. Morita, Kyoto, Japan) for detection of vertical root
fractures in teeth in both the absence and presence of gutta percha. The voxel sizes varied
19
from 0.20 to 0.30 mm with the lowest being the NewTom 3G and Scanora 3D (0.20 mm). The
authors reported significant differences between different systems, and greater accuracy of
axial slices to detect the vertical root fractures. The i-CAT imaging system (0.25 mm) resulted
in the highest overall specificity and sensitivity. They argued that field-of-view size or voxel
size differences explained the variation in the results.57
Da Silveira et al. showed in teeth with
root canal treatment and a post that the sensitivity was higher when 0.20 mm voxel size was
used. The specificity and sensitivity reported for 0.20 mm voxel size in the presence of root
canal treatment was 97% and 93%, respectively. These values were 83% and 80% in presence
of metallic post with the same voxel size.55
Recently, Ferreira et al. evaluated 59 teeth for the detection of vertical root fracture in
the presence of fiber-resin or titanium posts In an in vitro study. They imaged the teeth before
and after producing the fractures using two different cone beam systems with flat panel image
detectors; the i-CAT Next Generation (Imaging Sciences, Hatfield, PA, USA) and Scanora 3D
(Soredex, Tuusula, Finland). They reported a significant higher sensitivity for diagnosis of
fracture in the roots with fiber-resin posts using the i-CAT system (85%) compared to of the
metal post.58
20
Table 1.3: Summary of the results of in vitro studies of endodontically-treated teeth using cone beam CT for the diagnosis of vertical
root fractures.
Study Sample Cone beam CT imaging system Results
Hassan et al., 200940
80 extracted teeth (40 premolars
and 40 molars) with root canal
treatment placed in dry human
mandible.
i-CAT, 0.25 mm voxel Specificity: 87.5%
Sensitivity: 78.8%
Melo et al., 201019
180 single-rooted teeth with
presence of gutta percha (GP) and
metallic post (MP) placed in dry human skull.
i-CAT, 0.20 mm or 0.30 mm
voxel sizes
0.20 mm voxel (GP)
Specificity: 73%
Sensitivity: 93%
0.30 mm voxel size (GP)
Specificity: 70%
Sensitivity: 47%
0.20 mm voxel size (MP)
Specificity: 66%
Sensitivity: 70%
0.30 mm voxel size (MP)
Specificity: 63%
Sensitivity: 53%
21
Hassan et al., 201057
80 extracted teeth (40 premolars
and 40 molars) with root canal
treatment placed in posterior region
of dry human mandible.
NewTom 3G, 0.20 mm voxel
i-CAT, 0.25 mm voxel
Galileos 3D, 0.30 mm voxel
Scanora 3D, 0.20 mm voxel
3D Accuitomo, 0.25 mm voxel
NewTom 3G
Specificity: 95%
Sensitivity: 30.4%
Accuracy: 62.7%
i-CAT
Specificity: 91.3%
Sensitivity: 77.5%
Accuracy: 84.4%
Galileos 3D
Specificity: 85%
Sensitivity: 18.8%
Accuracy: 53.8%
Scanora 3D
Specificity: 85%
Sensitivity: 57.5%
Accuracy: 71.3%
3D Accuitomo
Specificity: 90.7%
Sensitivity: 48.1%
22
Accuracy: 69.4%
Da Silveira et al.,
201355
60 extracted single-rooted teeth
with presence of gutta percha (GP)
or metallic post (MP) placed in
acrylic blocks.
i-CAT, 0.20, 0.30 and 0.40 mm
voxel sizes.
0.20 mm voxel
Specificity (GP): 93%
Sensitivity (GP): 97%
Accuracy (GP): 95%
Specificity (MP): 80%
Sensitivity (MP): 83%
Accuracy (MP): 82%
0.30 mm voxel
Specificity (GP): 74%
Sensitivity (GP): 67%
Accuracy (GP): 70%
Specificity (MP): 91%
Sensitivity (MP): 63%
Accuracy (MP): 68%
0.40 mm voxel
Specificity (GP): 70%
Sensitivity (GP): 60%
Accuracy (GP): 65%
Specificity (MP): 59%
Sensitivity (MP): 57%
23
Accuracy (MP): 57%
Khedmat et al., 201256
100 extracted single-rooted teeth
placed in acrylic blocks.
Promax 3D, 0.16 mm voxel Specificity (GP): 64%
Sensitivity (GP): 80%
Accuracy (GP): 72%
Ferreira et al., 201258
59 extracted maxillary first
premolars with fiber-resin (FR) or
titanium (T) posts placed in acrylic
blocks.
i-CAT, 0.125 mm voxel
Scanora 3D, 0.133 mm voxel
i-CAT
Specificity (FR): 74%
Sensitivity (FR): 85%
Accuracy (FR): 78%
Specificity (T): 75%
Sensitivity (T): 72%
Accuracy (T): 73%
Scanora 3D
Specificity (FR): 71%
Sensitivity (FR): 73%
Accuracy (FR): 71%
Specificity (T): 76%
Sensitivity (T): 73%
Accuracy (T): 74%
24
In in vivo studies, the role of cone beam CT was evaluated in the diagnosis of vertical
root fractures in endodontically-treated teeth. Edlund et al. investigated the presence of
vertical root fracture in 33 teeth in 29 patients with clinical signs and symptoms suspicious of
vertical root fracture with either the i-CAT (Imaging Sciences, Hatfield, PA, USA) unit or the
3D Accuitomo unit (J. Morita, Kyoto, Japan). The radiologic findings were then correlated
with surgical exploration. This study reported specificity and sensitivity of 75% and 88%,
respectively.59
In another study, Metska et al. evaluated 39 endodontically-treated teeth with
the clinical and radiographic signs and symptoms of vertical root fracture with two cone beam
CT systems. Twenty-five teeth were scanned with a NewTom 3G (QR SLR, Verona, Italy)
with voxel size of 0.20 mm and fourteen were scanned with a 3D Accuitomo (J. Morita,
Kyoto, Japan) with voxel size of 0.08 mm. The NewTom 3G has an image intensifier/charge
coupled device detector and a voxel size of 0.20 mm, and the 3D Accuitomo 170 incorporates
a flat panel detector and a voxel size of 0.08 mm. The specificity and sensitivity reported for
the 3D Accuitomo was 80% and 100%, respectively, and 56% and 75% for the NewTom 3G.
They postulated that these differences were attributed by three factors: the quality of the scans,
the presence of metal artifacts, and the experience of observers.30
Also Wang et al. in a study
of evaluation of 49 endodontically-treated teeth with signs and symptoms of root fracture and
using 3D Accuitomo 80 (J. Morita, Kyoto, Japan) with voxel size of 0.125 mm reported
specificity and sensitivity of 100% and 71.4%, respectively. The diagnosis was then confirmed
by surgical intervention as a part of the treatment such as extraction, amputation or root-end
resection.14
25
Table 1.4: Summary of the results of in vivo studies of endodontically-treated teeth using cone beam CT for the diagnosis of vertical
root fractures.
Study Sample Cone beam CT imaging system Gold standard Results
Edlund et al.,
201159
33 teeth in 29 patients
with clinical signs and
symptoms suspicious of
vertical root fracture.
i-CAT, 0.125 mm voxel or
3D Accuitomo, 0.080 mm voxel
Endodontic
surgery
Specificity: 75%
Sensitivity: 88%
Accuracy: 84%
Wang et al., 2011 14
49 teeth with clinical
signs and symptoms
suspicious of vertical
root fracture
3D Accuitomo, 0.125 mm voxel Surgical
intervention
Specificity: 100%
Sensitivity: 71.4%
Metska et al.,
201230
39 teeth from 39 patients
with clinical and
radiographic signs and
symptoms suspicious of
vertical root fracture.
3D Accuitomo, 0.08 mm voxel
or NewTom 3G, 0.20 mm voxel
Orthograde
retreatment,
endodontic
microsurgery,
or extraction of
the tooth
3D Accuitomo
Specificity: 80%
Sensitivity: 100%
Accuracy: 93%
NewTom 3G
Specificity: 56%
Sensitivity: 75%
Accuracy: 68%
26
In the only study that evaluated teeth for horizontal root fractures in the presence of
intra-canal metallic posts, Costa et al. using the PaX Uni3D (Vatech, Suwon, Korea) with a
voxel size of 0.20 mm reported a significant reduction of both specificity and sensitivity of
cone beam CT. The specificity of horizontal root fracture detection in absence and presence of
intra-canal metallic post ranged from 60% to 95% and 45% to 85%, respectively. They also
reported sensitivity ranges of 65% to 85% in the absence of metallic posts with three different
observers. When a metallic post was present, sensitivity significantly decreased to between
40% and 65%. 51
Bernardes et al. conducted a study of 20 patients of endodontically-treated teeth with
suspected root fractures using the 3D Accuitomo (J. Morita, Kyoto, Japan). Only 15 out of 18
root fractures were symptomatic. These workers found root fractures in 18 cases while
conventional periapical radiographs showed the presence of such fractures in only 8 cases,
although the types of fracture were not specified. A significant weakness of this study was that
the radiologic findings were not confirmed surgically.39
1.8 Statement of the Problem
While there have been several publications related to the identification of root fractures
using cone beam CT, many of the variables in these studies have been poorly controlled.
Some studies have been performed in vitro and others, in vivo, and some studies have had
anatomical correlation, while others have not. In some studies, the methods used to induce the
fractures (e.g., chisel and hammer, disc and hammer) were not be reliable, resulting in
fragmentation of tooth material and loss of some particles. In some studies, images of different
voxel sizes were used as well as systems with different image receptors and field-of-view
sizes. Some studies incorporated teeth that have been endodontically-treated or have had metal
posts inserted. In some studies, images were evaluated by radiologists, in some by
endodontists and in some by a combination of both.
Coupled with a more precise method for inducing predictable fractures, our study was
designed to compare the specificity, sensitivity, and positive and negative predictive values of
projection digital intra-oral radiography with cone beam CT images acquired using four
27
different voxel sizes in the detection of vertical and horizontal root fractures using the same
set of radiologic phantoms and the same imaging system.
1.9 Objectives and Hypotheses
The primary objective of this study is to determine if voxel size affects the detection of
vertical and horizontal root fractures on cone beam CT images.
The secondary objectives are:
1. To calculate the specificity, sensitivity, and positive and negative predictive
values of different resolutions of cone beam CT scan in detection of vertical
and horizontal root fractures.
2. To determine if the detection of root fracture is influenced by the level of
experience of the observers.
3. To determine if the detection of root fractures is influenced by the type of the
tooth.
4. To compare the cone beam CT of different resolutions with projection
periapical images made using a complementary metal-oxide
semiconductor (CMOS) detector for the identification of root fractures.
1.10 Null Hypotheses
Our primary hypothesis was that there are no differences between different voxel sizes
for detection of horizontal or vertical root fractures using cone beam CT.
The secondary hypotheses of this study are:
1. There are no differences in specificity, sensitivity, and positive and negative
predictive values of cone beam CT images made with lower voxel size and
cone beam CT studies with higher voxel sizes.
2. There are no differences between observers with different levels of experience
in their abilities to detect root fractures.
28
3. There are no differences in root fracture detection between different teeth
imaged with cone beam CT.
4. There are no differences in root fracture detection between a complementary
metal-oxide semiconductor (CMOS) detector and cone beam CT scans made
with different voxel sizes.
29
Chapter 2
2 Methods and Materials
2.1 Sample Preparation
This study has been approved by the Health Sciences Research Ethics Board of
university of Toronto. Forty-five intact, extracted human teeth were used in this study, of
which there were 9 incisors, 18 premolars and 18 molars. The teeth were stored in 1%
formalin solution after extraction. Teeth with gross caries or restorations were not used. The
teeth were also evaluated for the presence of a root fracture with a disclosing agent, methylene
blue (Vista-Blue, Vista Dental Products, Racine, WI). The teeth were then randomly divided
into three groups of 15 teeth each. Vertical root fractures were induced in one group of 15
teeth, horizontal root fractures were induced in a second group, and 15 teeth were left intact.
A sample size calculation was performed addressing the primary objective of
examining the ability of cone beam CT to detect root fractures.43
The targeted significance
level of the test was 0.05 with a minimum 90% power. A sample size of 30 fractured teeth and
15 non-fractured achieves 99% power to detect a difference of 0.217 between the area under
curve under the null hypothesis and the area under curve under the alternative hypothesis
using a two-sided z-tests.
To induce vertical root fractures, a “bench vice” was used to apply a force along the
long axis of the tooth (Figure 2.1). The vertical root fractures were incomplete and in the cases
where the forces result in a complete separation of the two fragments, the tooth was discarded.
To induce horizontal root fractures, the teeth were fractured manually. So that the fragments
could be placed into the tooth block, the fragments of the horizontally-fractured teeth were
then glued back together in their original relationship with Advanced Instant Glue (Elmer’s
products, Toronto, ON, CA).
30
Figure 2.1: The bench vice used to induce vertical fractures
The disclosing dye, methylene blue (Vista-Blue, Vista Dental Products, Racine, WI),
was used to trace the fractures induced by the fracture methods. The teeth were also checked
for the presence of more than one fracture, and the teeth with more than one fracture were
discarded.
All the teeth were then covered with a 0.5 to 1 mm layer of rose wax in order to mimic
the periodontal ligament space radiographically, and also to produce the image contrast
between tooth structure and surrounding stone. The teeth were then randomly divided into 9
groups of 5 teeth, with each group consisting of one incisor, two premolars and two molars.
The teeth were then fixed in a straight line in a box filled with stone (Microstone Golden,
Whip Mix Corp, Louisville, KY) (Figure 2.2).
Figure 2.2: Five teeth mounted in stone in the same manner as inside the mouth.
31
2.2 Image Acquisition
Each group of teeth was then scanned with the Kodak 9000 3D cone beam CT system
(Carestream, Rochester, NY, USA) operating at 65 kVp and 2.5 mA at the native voxel size of
76 μm. The samples were positioned on the edentulous chin rest with the central line being
centered on the sample. (Figure 2.3)
Figure 2.3: Samples were centered in the center of the field of view.
The raw images were then downsampled to voxel sizes of 100, 200, and 300 μm. The
downsampling was performed using the Kodak Dental Imaging software (Carestream,
Rochester, NY, USA) (Figures 2.4 and 2.5). These voxel sizes were chosen based on the
available downsampling options in the Kodak Dental Imaging software.
32
A B C D
Figure 2.4: Bucco-lingual cross sectional slices of a molar with a vertical root fracture at
voxel sizes A) 76 μm; B) 100 μm; C) 200 μm; and D) 300μm.
A B C D
Figure 2.5: Bucco-lingual cross sectional slices of an incisor with a horizontal root fracture at
voxel sizes A) 76 μm; B) 100 μm; C) 200 μm; and D) 300 μm.
2.3 Image Evaluation
The images were anonymized using OsiriX software (Version 3, Pixmeo SARL,
Geneva, Switzerland) and were coded on the basis of the sequence of each observation
session. The sequences of the images were randomized for each observer using Microsoft
Excel software (Microsoft Corp., Redmond, WA, USA).
33
A total of five observers were used for this study. Two second year oral radiology
graduate students, one non-certified oral radiologist with 18 years experience and two certified
oral radiologists, one with 19 years experience and one with 5 years experience, reviewed the
randomized images at weekly intervals over a four week period with a one week washout
period between each group of observations. The observers were blinded to the presence or
absence of a fracture, and voxel size (resolution). The images were reviewed using In Vivo 5.2
software (Anatomage, San Jose, CA, USA.) under dimly-lit lighting conditions using the same
Dell (Dell Corporation, Round Rock, TX, USA) 23” UltraSharp monitor. The observers were
free to manipulate the images using contrast and brightness settings, and zoom in the software.
The observers were asked to record the absence or presence of a fracture in each tooth.
If a fracture was seen, observers were asked to determine if it was vertical or horizontal. A
fracture was considered vertical if it was angled at less than 45 degrees relative to the long
axis of the tooth. A fracture was considered to be horizontal if the angle of the fracture was
greater than 45 degrees relative to the long axis of the tooth. The observers were also asked to
provide a level of confidence from one to 10, with one representing the lowest and 10
representing the highest level of confidence for all teeth. And finally, observers were asked to
record the amount of the time they spent on each tooth making a determination.
2.4 Projection Radiography Study
To take full advantage of the experimental material, 90 periapical images were
obtained from the samples using the CDR digital sensor (Schick Technologies Inc., Long
Island City, NY, USA) with the pixel size of 40 μm. The exposures were made using a
Progeny Preva intra oral x-ray system (Progeny, A Midmark Company, Lincolnshire, IL,
USA) operating at 65 kVp and 5 mA with a focus-to-object distance of 15 centimeter and
focal spot size of 0.4 mm. The exposure time chosen for the incisors and premolars was 0.4
sec and the exposure time for the molars was 0.5 sec. Two periapical images were made of
each tooth from two different angulations; one at zero degrees and a second at 15 degrees to
the long axis of the tooth (Figures 2.6 and 2.7). In order to increase the quality of the
34
periapical images, the thickness of the stone was reduced to 15 mm by trimming 9 mm of
thickness.
A B
Figure 2.6: Periapical images of a molar with a vertical root fracture (presented in Figure 2.4)
with angulations of A) zero degrees; and B) 15 degrees to the long axis of the
tooth.
A B
Figure 2.7: Periapical images of a central incisor with a horizontal root fracture (presented in
Figure 2.5) with angulations of A) zero degrees; and B) 15 degrees to the long
axis of the tooth.
The paired image files were saved in .jpg format and then exported into a PowerPoint®
(Microsoft Corp., Redmond, WA, USA) file. Both 0 degree and 15 degree images of each
35
tooth were presented in the same .pdf (Adobe Corp., San Jose, CA, USA) image. The same
five evaluators evaluated the images in the same way that they did for the cone beam CT
study.
2.5 Data Analysis
Statistical analysis was performed using the SPSS Statistics software, version 21.0
(IBM SPSS, Chicago, Il, USA). Specificity, sensitivity, positive predictive value and negative
predictive value were calculated for the vertical and horizontal root fracture group, and for the
2 groups, combined. Specificity and sensitivity are measurements of binary tests; Specificity
shows the part of true negatives and sensitivity indicates the part of true positives which have
been correctly identified by the test . A positive predictive value represents the proportion of
subjects with positive results and a negative predictive value represents the proportion of
subjects with negative results which are correctly diagnosed.
Receiver operating characteristic (ROC) curves were generated for each resolution,
and for the fractures together as a group, and separately (vertical and horizontal). In a ROC
curve, sensitivity is plotted as function of 100 - specificity. McNemar’s test was used to
determine if there were statistically significant differences between voxel sizes for the
detection of fractures as a group, and separately (vertical and horizontal). Also, a Chi-square
test was used to determine if there were differences between the observer groups in the
detection of fractures. An independent sample t-test was used to compare the time spent by
each observer group in detection of the fractures. Finally, a Chi-square test was also used to
compare the results of periapical radiographs with each voxel size.
2.6 Observers Agreement
In order to evaluate the intra-observer agreement, one of the observers volunteered to
review a subset of the images the second time. Eight cone beam CT studies and 10 periapical
images were randomly chosen to review by this observer. Microsoft Excel (Microsoft Corp.,
36
Redmond, WA, USA) software was used to randomize the images. For the periapical images,
the first 10 image pairs were chosen after randomization for this purpose. For the cone beam
CT studies, two scans was chosen for each voxel size. Kappa (κ) test was used to measure the
intra-observer agreement as well as the inter-observer agreement. The inter-observer
agreement was measured using the average of the values of Kappa (κ) for pairs of observers. 60
37
Chapter 3
3 Results
3.1 Diagnostic Test Results for CT Images
The results of the specificity, sensitivity, positive predictive value and negative
predictive value of each resolution of all observers and for all fractures are provided in Table
3.1, and the receiver operating characteristic (ROC) curves of each resolution are provided in
Figure 3.1. The areas under the ROC curves are shown in Table 3.2. Higher specificity,
sensitivity, and positive and negative predictive values were found for the 100 µm voxel size
and for the area under the 100 m voxel size ROC curve.
Table 3.1 Specificities, sensitivities, positive and negative predictive values for each :
resolution and all root fractures for the cone beam CT images.
Voxel Size
Test Results
76 µm
100 µm
200 µm
300 µm
Specificity 70.7% 76.0% 70.7% 74.7%
Sensitivity 64.7% 66.0% 62.7% 54.0%
Positive Predictive Value 81.5% 84.6% 81.0% 81.0%
Negative Predictive Value 50.0% 52.8% 48.6% 44.8%
38
Figure 3.1: ROC curves for all root fractures and all voxel resolutions.
Table 3.2 Areas under the receiver operator curves for different voxel resolutions and all root :
fractures.
Area Under Curve
76 µm 0.565
100 µm 0.593
200 µm 0.557
300 µm 0.558
39
The results of the specificity, sensitivity, positive predictive value and negative
predictive value of each resolution of all observers and vertical fractures are provided in Table
3.3, and the receiver operating characteristic (ROC) curves of each resolution are provided in
Figures 3.2. The area under curve is provided in Table 3.4 associated with Figure 3.2.
Higher specificity, sensitivity, and positive and negative predictive values were found
for the 100 µm voxel size and for the area under the 100 m voxel size ROC curve. 200 m
voxel size also showed higher specificity.
Table 3.3 Specificities, sensitivities, positive and negative predictive values for each .
resolution and vertical root fractures for the cone beam CT images.
Voxel Size
Test Results
76 µm
100 µm
200 µm
300 µm
Specificity 70.6% 76.0% 70.6% 74.6%
Sensitivity 64.0% 66.7% 61.3% 50.7%
Positive Predictive Value 68.5% 73.5% 67.7% 66.7%
Negative Predictive Value 66.2% 69.5% 64.6% 60.2%
40
Figure 3.2: ROC curves for vertical root fractures only and all voxel resolutions.
Table 3.4 Areas under the receiver operator curves for different voxel resolutions and vertical :
root fractures only.
Area Under Curve
76 µm 0.609
100 µm 0.629
200 µm 0.598
300 µm 0.607
41
The results of the specificity, sensitivity, positive predictive value and negative
predictive value of each resolution of all observers and horizontal fractures are provided in
Table 3.5, and the receiver operating characteristic (ROC) curves of each resolution are
provided in Figures 3.3. The area under curve is provided in Table 3.6 associated with Figure
3.3. Higher specificity and positive predictive value were found for the 100 m voxel sizes,
higher sensitivity was found for 76 m, and higher negative predictive value was found for
100 m and 76 m. The area under the 100 m voxel size ROC curve was also highest
amongst the different voxel sizes.
Table 3.5 Specificities, sensitivities, positive and negative predictive values for each .
resolution and horizontal root fractures for the cone beam CT images.
Voxel Size
Test Results
76 µm
100 µm
200 µm
300 µm
Specificity 70.6% 76.0% 70.6% 74.6%
Sensitivity 45.3% 41.3% 44.0% 29.3%
Positive Predictive Value 60.7% 63.3% 60.0% 53.7%
Negative Predictive Value 56.4% 56.4% 55.8% 51.4%
42
Figure 3.3: ROC curves for horizontal root fractures only and all voxel resolutions.
Table 3.6 Area under the receiver operator curves for different voxel resolutions and :
horizontal root fractures only.
Area Under Curve
76 µm 0.520
100 µm 0.558
200 µm 0.515
300 µm 0.510
43
3.2 Comparison of Voxel Sizes and Fracture Detection
McNemar’s test was performed to determine if there is any significant difference
between the voxel sizes in the detection of root fractures. The test failed to indicate a
significant difference between the voxel sizes (see Table 3.7). Voxel size had no impact on
fracture detection.
Table 3.7: Comparison between each pair of voxel sizes in detection of all root fractures for
all observers.
Voxel Size p value
76 µm vs. 100 µm 1.000
76 µm vs. 200 µm 0.453
76 µm vs. 300 µm 0.146
100 µm vs. 200 µm 0.754
100 µm vs. 300 µm 0.180
200 µm vs. 300 µm 0.581
McNemar’s test was performed to determine if there is any significant difference
between the voxel sizes in the detection of horizontal and vertical root fractures. The test
failed to indicate a significant difference between the voxel sizes (see Tables 3.8 and 3.11).
44
A Chi-square test was performed to compare the abilities to detect vertical and
horizontal root fractures. This test showed that the detection of vertical root fractures was
significantly better than the detection of horizontal root fractures (p<0.001).
Table 3.8: Comparison of voxel sizes in detection of vertical root fractures only for all
observers.
Voxel Size p value
76 µm vs.100 µm 1.000
76 µm vs. 200 µm 1.000
76 µm vs. 300 µm 0.125
100 µm vs. 200 µm 1.000
100 µm vs. 300 µm 0.250
200 µm vs. 300 µm 0.250
Using McNemar’s tests, a significant difference was indicated between the voxel sizes
of 100 µm and 300 µm in the graduate student group (p value<0.05) in detection of vertical
root fractures (Tables 3.9, 3.10).
45
Table 3.9: Comparison of voxel sizes in detection of vertical root fractures only in the oral
radiology graduate student group.
Voxel Size p value
76 µm vs.100 µm 0.629
76 µm vs. 200 µm 0.442
76 µm vs. 300 µm 0.189
100 µm vs. 200 µm 0.832
100 µm vs. 300 µm 0.041*
200 µm vs. 300 µm 1.000
*
p value <0.05
46
Table 3.10: Comparison of voxel sizes in detection of vertical root fractures only in the oral
radiologist group.
Voxel Size p value
76µm vs.100µm 0.791
76µm vs. 200µm 0.424
76µm vs. 300µm 0.092
100µm vs. 200µm 0.774
100µm vs. 300µm 0.180
200µm vs. 300µm 0.549
47
Table 3.11 : Comparison of voxel sizes in detection of horizontal root fractures only for all
observer groups.
Voxel Size p value
76µm vs.100µm 0.688
76µm vs. 200µm 0.250
76µm vs. 300µm 0.344
100µm vs. 200µm 1.000
100µm vs. 300µm 0.754
200µm vs. 300µm 1.000
McNemar’s tests showed that there was no significant difference between voxel size in
the detection of horizontal root fractures by either oral radiology graduate students or oral
(Tables 3.12, 3.13). radiologists
48
Table 3.12 : Comparison of voxel sizes in detection of horizontal root fractures only in the
oral radiology graduate student group.
Voxel Size p value
76µm vs.100µm 0.481
76µm vs. 200µm 1.000
76µm vs. 300µm 0.728
100µm vs. 200µm 0.711
100µm vs. 300µm 1.000
200µm vs. 300µm 0.856
49
Table 3.13: Comparison of voxel sizes in detection of horizontal root fractures only in the
oral radiologist group.
Voxel Size p value
76µm vs.100µm 0.607
76µm vs. 200µm 0.481
76µm vs. 300µm 0.064
100µm vs. 200µm 1.000
100µm vs. 300µm 0.210
200µm vs. 300µm 0.359
3.3 Comparison of the Observers
The results of comparison of oral radiology graduate students and oral radiologists in
the detection of both types of fractures, and then vertical and horizontal fractures separately,
are reported in Tables 3.14, 3.15 and 3.16, respectively.
Oral radiologists detected all fractures at 300 m voxel resolution more effectively
than the oral radiology graduate students. For vertical fractures, oral radiologists outperformed
oral radiology residents at 76 m, 200 m and 300 m voxel sizes. For horizontal fractures
there was no difference between the two groups.
50
Table 3.14: Comparison of oral radiology graduate students and oral radiologists in detection
of both types of fractures with each voxel size (df: 1/n: 150).
Voxel Size Chi Square value p value
76 µm 2.025 0.155
100 µm 1.468 0.226
200 µm 0.146 0.699
300 µm 7.242 0.007*
* p value <0.05
Table 3.15: Comparison of oral radiology graduate students and oral radiologists in detection
of vertical fractures with each voxel size (df: 1/n: 150).
Voxel Size Chi Square value p value
76 µm 6.916 0.009*
100 µm 0.087 0.768
200 µm 3.882 0.049*
300 µm 8.781 0.003*
* p value <0.05
51
Table 3.16: Comparison of oral radiology graduate students and oral radiologists in detection
of horizontal fractures with each voxel size (df: 1/n: 150).
Voxel Size Chi Square value p value
76 µm 1.331 0.249
100 µm 0.543 0.461
200 µm 3.357 0.067
300 µm 1.977 0.160
3.4 Comparison of Type of Tooth
The result of comparisons of diagnostic efficacy of fractures based on the tooth type
(incisor, molar and premolar) is presented in the Tables 3.17, 3.18, 3.19, 3.20, and 3.21. There
were no differences in fracture detection based on tooth type.
Table 3.17: Comparison of detection of root fractures between teeth in voxel size 76 µm
(df:1).
Voxel Size Chi Square value p value n
Incisors vs. Premolars 0.386 0.535
27
Incisors vs. Molars 0.089 0.766 27
Premolars vs. Molars 0.148 0.700
36
52
Table 3.18: Comparison of detection of root fractures between teeth in voxel size 100 µm
(df:1).
Voxel Size Chi Square value p value n
Incisors vs. Premolars 3.068 0.080 27
Incisors vs. Molars 3.857 0.050 27
Premolars vs. Molars 0.131 0.717 36
Table 3.19: Comparison of detection of root fractures between teeth in voxel size 200 µm
(df:1).
Voxel Size Chi Square value p value n
Incisors vs. Premolars 0.386 0.535 27
Incisors vs. Molars 0.079 0.778 27
Premolars vs. Molars 1.178 0.278 36
53
Table 3.20: Comparison of detection of root fractures between teeth in voxel size 300 µm
(df:1).
Voxel size Chi Square value p value n
Incisors vs. Premolars 1.918 0.166
27
Incisors vs. Molars 0.096 0.756 27
Premolars vs. Molars 1.870 0.171
36
Table 3.21: Comparison of detection of root fractures between teeth in periapical radiographs
(df:1).
Voxel size Chi Square value p value n
Incisors vs. Premolars 1.985 0.159 27
Incisors vs. Molars 0.074 0.785 27
Premolars vs. Molars 1.870 0.171 36
54
3.5 Comparisons of Time
The mean time spent on each tooth in detection of the root fracture for voxel sizes 76
µm, 100 µm, 200 µm, and 300 µm was 90.1, 85. 6, 91.0 and 84.1 seconds, respectively. The
independent sample T-test indicated that the mean time spent by the oral radiology graduate
students evaluating 300 µm voxel size (99.9 ± 124.0 sec) was significantly higher than the
mean time spent by oral radiologists (73.6 ± 66.2 sec). This was significant to p<0.05.
However, there was no significant difference between time spent on each tooth by the oral
radiology graduate students and oral radiologists in detection of root fractures with any other
voxel sizes (Table 3.22).
Table 3.22: Comparison of the mean time (seconds) spent by oral radiology graduate students
and oral radiologists in the detection of root fractures with each voxel size
(df:223).
Voxel Size Mean SD p value
Oral
Radiology
graduate
students
Oral
Radiologists
Oral
Radiology
graduate
students
Oral
Radiologists
76µm 97.8 84.9 97.1 91.5 0.312
100µm 96.64 78.2 116.5 84.1 0.169
200µm 86.68 93.9 84.7 94.6 0.560
300µm 99.87 73.6 124.0 66.2 0.040*
*p value< 0.05
55
3.6 Diagnostic Test for Digital Periapical Images
Significant difference was observed between observers’ abilities to detect fractures on
periapical radiographs compared to voxel sizes of 76 µm, 100 µm, and 200 µm (p < 0.05).
These results are summarized in Table 3.23.
Table 3.23: Comparison of each voxel size with periapical radiographs in detection of root
fractures (df:1/n:90).
Voxel Size Chi Square value p value
Periapical radiographs vs. 76 µm 4.630 0.031*
Periapical radiographs vs. 100 µm 5.657 0.017*
Periapical radiographs vs. 200 µm 4.295 0.038*
Periapical radiographs vs. 300 µm 2.217 0.136
*p value< 0.05
3.7 Observers Agreement
The results of intra and inter observer agreement are provided in the table 3.24. The
strength of the Kappa (κ) values was interpreted using the guidelines provided by Landis and
Koch (<0.00, poor; 0.00 to 0.20, slight; 0.21 to 0.40, fair; 0.41 to 0.60, moderate; 0.61 to 0.80,
substantial; 0.81 to 1.00, almost perfect).59
56
Table 3.24: Kappa values for the intra and inter observer agreement for each resolution and
periapical radiographs.
Imaging Type Inter-Observer Intra-Observer
Kappa (κ) Interpretation Kappa (κ) Interpretation
All cone beam CT 0.3 Fair 0.62 Substantial
76 µm 0.4 Fair 0.49 Moderate
100 µm 0.33 Fair 0.56 Moderate
200 µm 0.34 Fair 0.7 Substantial
300 µm 0.23 Fair 0.69 Substantial
Periapical 0.44 Moderate 0.7 Substantial
57
Chapter 4
4 Discussion
4.1 Overview
There have been multiple studies evaluating the role of cone beam CT in the detection
of root fractures, yet there has been little or no general consistency in the methodologies.
Some studies have been performed using in vitro models and others have involved patients.
Some studies have examined only vertical or horizontal fractures, and some have examined
endodontically-treated teeth while others have examined teeth with metal posts in place.
Some have used smaller field-of-view cone beam CT systems with small voxel sizes while
others have used larger field-of-view systems with larger voxel sizes. The number of different
variables in these studies has made the body of literature on this topic very confusing.
The literature evaluating tooth fractures using cone beam CT has reported wide ranges
of results. The specificity and sensitivity of cone beam CT for the detection of vertical root
fractures varies from 56% to 100% and 18.8% to 100%. By comparison, the specificity and
sensitivity for horizontal root fractures varies from 45% to 97% and 40% to 94%. These
variations suggest that there are multiple factors that may be involved in the accuracy of
diagnosis of root fractures with cone beam CT. These factors can be classified into factors
related to the cone beam CT system itself, observer experience, and factors related to the
patient. Although it is not possible to control every variable, we have attempted, in the present
study, to control as many as possible so that direct comparisons can be made.
The production of cone beam CT images involves four stages: 1) acquisition; 2) image
detection; 3) image reconstruction; and 4) image display. 38
The factors involved in each of
these stages may influence the quality of the cone beam CT volume and rendered images.
Each cone beam CT system has its own set of unique features including the type of the
detector, native voxel size field-of-view, and operating parameters (kVp and mA).
Two types of image detectors are used in cone beam CT systems to acquire the images;
the image intensifier tube/charge couple device detector and the flat-panel detector.57
Miles et
58
al. stated that the quality of images of cone beam CT systems with flat-panel detectors is
higher than those with image intensifier tube/charge couple device due to higher x-ray photon
collection efficiency. This is reported to be 50% for the image intensifier/charge couple device
detector and 98% for flat-panel detectors.61
The detector used in Kodak 9000 3D is also
amorphous flat panel.
Another factor involved in the reported higher performance of imaging systems is the
voxel size of the image detector. Hassan et al. evaluated vertical root fractures using 5 cone
beam CT systems, and reported a significantly higher sensitivity with i-CAT (Imaging
Sciences, Hatfield, PA, USA) (77.5%) and Scanora 3D (Soredex, Tuusula, Finland) (57.5%)
in comparison to the three other systems evaluated. In both systems, the detector type used
was flat-panel.57
The voxel size used for the i-CAT in their study was 0.25 mm and the voxel
size for the Scanora 3D was 0.20 mm. The voxel size used for the NewTom 3G system (QR
SLR, Verona, Italy) in this same study was also 0.20 mm (detector type for the NewTom 3G
system is a flat-panel detector). Since the overall sensitivity of this system (30.4%) is lower in
comparison to the two other systems, there may be other internal or external factors (including
the number of the basis projections, data reconstruction algorithms and machine-specific
artifacts).51
In this same study, only the Galileos 3D system (Sirona Germany, Bensheim,
Germany) showed significantly better diagnosis efficacy in detecting fractures between
endodontically-treated and non-treated teeth, suggesting that this system may be more capable
of artifact suppression.
In the present study, we used the same Kodak 9000 3D system for all of our cone beam
CT acquisitions, which operates at a native voxel resolution of 76 m. We were then able to
downsample the native resolution images to images of lower resolution using the imaging
system’s own software without affecting the positions of the phantoms. Our results agree with
the work of Ozer42
, who found higher specificity and sensitivity with voxel sizes 0.125 and
0.20 mm. In our study, we found higher specificity and sensitivity of fracture detection with a
voxel size of 0.10 mm. In another study evaluating the effect of voxel size in detection of
stimulated external root resorption with different sizes, Liedke et al.43
did not find any
differences between voxel sizes of 0.20, 0.30 and 0.40 mm. These workers considered the size
0.30 mm voxel size to be the most effective for the diagnosis of external root resorption
59
because both diagnostic performance and patient radiation dose were balanced. Unlike our
study, both the Ozer and Liedke results were based on different acquisitions with different
acquisition times for the same phantom which could potentially confound their results. In the
only study evaluating the effect of different cone beam CT exposure parameter on the
accuracy of the cone beam CT images, Vandenberghe et al. found that exposure time and
voxel size have a significant role in differentiation of cortical borders and transition with
surrounding soft tissue in the jaw bone models.62
This may also influence the result of
the previous studies evaluating the role of voxel size in detection of root fractures,
since they used different exposure time.
The specificities, sensitivities, and positive and negative predictive values we reported
are within the ranges reported in previous studies.14,34,40,53,55,57
These results agree with the
results from previous studies. We did, however, find that the 100 µm voxel size performed
better than the others; even the smaller 76 m size. Although the use of smaller voxel sizes
result in higher resolution images, less “blurring” of the image and less potential for volume
averaging, smaller voxel sizes increase image noise and contribute to a reduction of the
contrast-to-noise ratio.50
With a marginally larger voxel size, there may be less noise
degradation of image quality, and this may reduce the difficulty of fracture detection. The
variation between higher specificity and sensitivity in our study in comparison with other
studies may be attributed, in part, to the method used to induce the fractures in our study;
Factors including the degree of separation of fragments and loss of some tooth particles may
play role in detection of root fractures. In the present study, we tried to keep the loss of tooth
particles as low as possible. That the treatment of teeth with root fracture can vary between
endodontic treatment and extraction, the higher specificity of cone beam CT is an important
outcome.
In the present study, we also compared the ability of detection of root fractures using
cone beam CT with periapical radiographs made at two angulations. The detection of root
fractures with voxel sizes 76 µm, 100 µm and 200 µm was significantly better than periapical
radiographs (p<0.05). No significant difference was observed in the detection of root fractures
between periapical radiographs and a voxel size of 300 µm. These results show that the
elimination of superimposition of adjacent structure including the surrounding material (e.g.
60
stone and bone) and other roots in three-dimensional images, manipulation of the images and
changing the angle of the image slice to align with possible fractures are some of the factors
that may play a major role in detection of root fracture. However, this is not the only factor
having a role in the detection of root fractures. Others who have compared cone beam CT with
periapical radiographs have also reported significant differences between fracture
detection.14,20,25,34
On the other hand, Silveira et al. in their study did not find any statistical
difference among the images in diagnosis of vertical root fractures. In their study, they
compared i-CAT (Imaging Sciences, Hatfield, PA, USA) images made with two voxel sizes
0.20 mm and 0.30 mm with images made using ANSI D speed films made using three
different horizontal angulations. They did not provide any specific reason for lack of
difference in their study.54
In the present study, the efficacy of detection of vertical root fractures was
significantly better than the detection of horizontal root fractures (p<0.001). This could be
due, in part, to the methods to create the tooth block phantoms. For horizontal root fractures,
the exact matching fragments had to be glued together in order to enable us to place them in
the stone without the 2 fragments separating from one another. Consequently, this made the
separation of the horizontal fracture fragments similar to cracks, making fracture detection
more challenging. This is the same method used by Ozer to induce cracks in his study
evaluating the effect of thickness of fracture lines in their diagnosis by cone beam CT scan.63
In the teeth with vertical root fractures, glue was not used because these fragments did not
separate when placed into the stone. The significant difference between the detection of
vertical and horizontal root fractures underpins the importance of the effect of separation on
the ability to detect fractures.
No significant differences were observed in detection of root fractures between
different types of teeth. We hypothesized that detection of root fractures in multi-rooted teeth
is more difficult because of superimposition of other roots on the fracture line. This, however,
was not the case, likely because the tomographic method abrogated any potential for
superimposition.
61
We achieved fair inter-observer agreement in detection of root fractures with cone
beam CT scan and moderate inter-observer agreement in detection of fractures with periapical
radiographs. The higher inter-observer with periapical radiographs can be attributed to greater
familiarity of the observers with two-dimensional images and also the different level of
experience between the observers. The intra-observer agreement of cone beam CT studies and
periapical radiographs was moderate to substantial, which can be contributed to the level of
experience of the observer who did the second session of the observations.
In order to improve diagnosis using cone beam CT images, the clinician must be
familiar with the three dimensional display of anatomy and image manipulation.58
Our results
indicated that there was no significant difference in detection of both types of root fractures
between oral radiology graduate students and oral radiologists at any voxel sizes except for
300 µm. Although we did not find any significant difference in detection of horizontal root
fracture between the two observer groups we did find a significant difference in detection of
vertical root fractures at all voxel sizes except for 100 µm for both groups. To date, there has
been no previous study evaluating the effect of experience on the diagnosis of root fractures.
The mean time spent on each tooth in detection of root fractures by the oral radiology
graduate students was significantly higher than the mean time spent by the oral radiologist
group with a voxel size of 300 µm. The significant difference between the time spent by these
two groups shows the importance of the role of level of experience in the pace of detection of
root fractures, particularly at higher voxel sizes. In this study, oral radiologists had five years
or more experience.
Clinically, fractures without displacement of the fragment are difficult to diagnose;
consequently the diagnosis of this type of fracture may rely to a greater degree on clinical
observations.5,22,58
Ozer in his study evaluated the efficacy of cone beam CT in the diagnosis
of cracked teeth, with 0.20 mm and 0.40 mm fracture thicknesses. Although he did not find
any significant difference in the diagnostic ability of cone beam CT scan to detect fractures
under either condition, the separation of vertical root fracture fragments was inversely related
to the accuracy of cone beam CT in diagnosing them.63
The significantly better result in the
62
detection of the vertical root fractures as well as the methods we used in preparation of the
vertical and horizontal root fractures is a confirmation of this finding.
Although we did not find any significant difference in detection of root fractures with
different voxel sizes, there are other factors which should be considered when deciding the
type of the cone beam CT machine in diagnosis of root fractures. These factors include dose to
the patient and cone beam CT system availability. There is a large variation in radiation dose
received by the patient with different cone beam CT scan systems. It has been reported that
the radiation exposure reduces as the voxel size reduces.19
There is wide variation in effective radiation dose with different types of cone beam
CT systems. Factors that contribute to this variation include the imaging parameters used
(kVp, mAs), a pulsed versus continuous beam, the amount, type, and shape of the beam
filtration, the number of basis images created, field-of-view size and voxel size.33
Lower voxel
resolution acquisitions require less scanning time, and this decreases patient radiation dose as
well.43
Thus, not only was the highest performance observed with a voxel size of 100 µm in
our study, but the fact that the radiation exposure was comparably lower indicate that it may
be the best voxel size to use in detection of root fractures, balancing the risks and benefits
associated with that.
4.2 Study Limitations
One of the limitations of this study is that fractures induced in vitro may be different
from the fractures encountered clinically. The most challenging cases to diagnose clinically
are those without displacement of the fracture fragments. By the nature of the study design, no
considerations were given to the contributions of indirect signs of fracture that could
potentially be evaluated in an intact biological system. For example, useful indirect
information that could suggest fracture might include changes to the periodontal ligament
space, the presence of areas of rarefying osteitis developing at the site of fracture or at the
tooth root apex, the development of a fistula, changes to the position of the coronal fragment
in the dental arches, and changes to the response of the tooth to temperature or percussion, to
63
name a few. Also, the density of the surrounding stone may not be exactly same as the density
of bone and soft tissue together and it may show different absorption in compared to real
situation. Due to time restrictions, only one of the observers were able to review the images
for the second time to calculate the intra-observer agreement.
4.3 Future Directions
Future studies should focus objectively evaluating image quality of different voxel
resolution images, and relate this to the diagnostic efficacy of fracture detection. Although we
used a very small native voxel size, high resolution images compromise image signal-to-noise.
Although this may be difficult to mimic in an in vitro study, thought could be given to
designing a model of tooth fracture where fragments could be displaced linearly or at variable
angles to on another. Conducting a prospective clinical study, but with anatomical verification
of fracture, using an image evaluation protocol similar to the one used in this study could also
be performed. Finally, a future study may also determine the influence of indirect signs of
fractures on fracture detection rates.
4.4 Clinical Implications and Conclusions
With recent advances in cone beam CT technology as well as the increasing
availability of different types of cone beam CT systems, small field-of-view high resolution
imaging systems like the one used in these experiments is becoming more popular among
dentists. Our study suggests that for the detection of root fractures, the 100 µm voxel size may
be the most optimal for this task balancing image noise and contrast. However, lack of
statistically significant differences between different voxel sizes in detection of root fractures
encourages the clinicians to consider other factors such as radiation dose in their decision.
64
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Appendix 1
Copy of the ethics approval of the research
73
Appendix 2
Consent Form for the observers
Title
The effect of the voxel size on the identification of vertical and horizontal root fractures by cone beam computed tomography in an in-vitro study.
Introduction
The aim of this study is to determine the effects of the voxel size on the identification of vertical and horizontal root fractures by cone beam CT scan in an in vitro study.
Study Procedure
If you agree, you will be asked to participate in four sessions, each one week apart, for evaluation of the cone beam CT studies. In each session, you will review nine series of images; each series contains five teeth, some of which have a fracture and some that do not. You will be asked to decide if the fracture is present or not, and in the cases that the fracture is present you will be ask to classify that as a vertical type or horizontal type. You will be asked to record the time after evaluation of each tooth. The estimated time for each session is 5 hours.
Benefits and Risks
There are no known risks to you from participating in this study. The results do not reflect your academic or professional abilities.
Subject Rights
Your participation in this study is voluntary. You may withdraw from the study at any time without penalty. If you are a graduate student, your refusal or withdrawal from the study will not affect any academic evaluations. You will be provided with an email address if you need to ask questions about the study at any time.
Confidentiality
All information collected about you and your observations in this study will be confidential. No individual information will be disclosed. The data will be securely stored. No one will have access to these data except the primary investigator. Ten years after completion of the study, all information will be destroyed. Researchers will use the results of this study to write scientific papers and present at scientific conferences.
Contact
74
Dr. Niloufar Amintavakoli is the principal investigator under the supervision of Dr. Ernest Lam ([email protected]). If you need any further information about the study, you can contact Dr. Niloufar Amintavakoli by email at ([email protected]).
Consent Agreement
I acknowledge that the procedures of this study have been explained to me clearly. I had the opportunity to ask questions, and any questions were answered to my satisfaction. I am aware that I may ask further questions at any point. I have been provided with contact information for the research supervisor of this study. I am aware that my participation is voluntarily. I can withdraw from the study at any time. In addition, my participation or withdrawal will not affect my academic evaluation.
A I agree to participate
B. Disagree to participate
C. Name (please print): ________________________
D. Signature: __________________________
E. Date: ___________________
75
Appendix 3: Tables of Raw Data
Appendix Table 1: Specificity, sensitivity, false positive and false negative for resolution 76
µm and all root fractures for the cone beam CT images.
76 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 53
70.7%
22
29.3%
75
100% % within Gold
With fracture Count 53
35.3%
97
64.7%
150
100% % within Gold
Total Count 106 119 225
% within Gold 47.1% 52.9% 100%
Appendix Table 2: Specificity, sensitivity, false positive and false negative for resolution 100
µm and all root fractures for the cone beam CT images.
100 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 57
76.0%
18
24.0%
75
100% % within Gold
With fracture Count 51
34.0%
99
66.0%
150
100% % within Gold
Total Count 108 117 225
% within Gold 48.0% 52.0% 100%
76
Appendix Table 3: Specificity, sensitivity, false positive and false negative for resolution 200
µm and all root fractures for the cone beam CT images.
200 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 53
70.7%
22
29.3%
75
100% % within Gold
With fracture Count 56
37.3%
94
62.7%
150
100% % within Gold
Total Count 109 116 225
% within Gold 48.4% 51.6% 100%
Appendix Table 4: Specificity, sensitivity, false positive and false negative for resolution 300
µm and all root fractures for the cone beam CT images.
300 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 56
74.4%
19
25.3%
75
100% % within Gold
With fracture Count 69
46.0%
81
54.0%
150
100% % within Gold
Total Count 125 100 225
% within Gold 55.6% 44.4% 100%
77
Appendix Table 5: Positive predictive value and negative predictive for resolution 76 µm and
all root fractures for the cone beam CT images.
76 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
50.0%
22
18.5%
75
33.3% % within 76 µm voxel size
With fracture
Count 53
50.0%
97
81.5%
150
66.7% % within 76 µm voxel size
Total Count 106 119 225
% within 76 µm voxel size 100% 100% 100%
Appendix Table 6: Positive predictive value and negative predictive for resolution 100 µm
and all root fractures for the cone beam CT images.
100 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 57
52.8%
18
15.4%
75
33.3% % within 100 µm voxel size
With fracture
Count 51
47.2%
99
84.6%
150
66.7% % within 100 µm voxel size
Total Count 108 117 225
% within 100 µm voxel size 100% 100% 100%
78
Appendix Table 7: Positive predictive value and negative predictive for resolution 200 µm
and all root fractures for the cone beam CT images.
200 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
48.6%
22
19.0%
75
33.3% % within 200 µm voxel size
With fracture
Count 56
51.4%
94
81.0%
150
66.7% % within 200 µm voxel size
Total Count 109 116 225
% within 200 µm voxel size 100% 100% 100%
Appendix Table 8: Positive predictive value and negative predictive for resolution 300 µm
and all root fractures for the cone beam CT images.
300 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 56
44.8%
19
19.0%
75
33.3% % within 300 µm voxel size
With fracture
Count 69
55.2%
81
81.0%
150
66.7% % within 300 µm voxel size
Total Count 125 100 225
% within 300 µm voxel size 100% 100% 100%
79
Appendix Table 9: Specificity, sensitivity, false positive and false negative for resolution 76
µm and vertical root fractures for the cone beam CT images.
76 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 53
70.6%
22
29.3%
75
100% % within Gold
With fracture Count 27
36.0%
48
64.0%
75
100% % within Gold
Total Count 80 70 150
% within Gold 53.3% 46.7% 100%
Appendix Table 10: Specificity, sensitivity, false positive and false negative for resolution
100 µm and vertical root fractures for the cone beam CT images.
100 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 57
76%
18
24%
75
100% % within Gold
With fracture Count 25
33.3%
50
66.7%
75
100% % within Gold
Total Count 82 68 150
% within Gold 54.6% 45.4% 100%
80
Appendix Table 11: Specificity, sensitivity, false positive and false negative for resolution
200 µm and vertical root fractures for the cone beam CT images.
200 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
70.6%
22
29.4%
75
100% % within Gold
With fracture
Count 29
38.7%
46
61.3%
75
100% % within Gold
Total Count 82 68 150
% within Gold 54.6% 45.4% 100%
Appendix Table 12: Specificity, sensitivity, false positive and false negative for resolution
300 µm and vertical root fractures for the cone beam CT images.
300 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 56
74.6%
19
25.4%
75
100% % within Gold
With fracture Count 37
49.3%
38
50.7%
75
100% % within Gold
Total Count 93 57 150
% within Gold 62% 38% 100%
81
Appendix Table 13: Positive predictive value and negative predictive for resolution 76 µm
and vertical root fractures for the cone beam CT images.
76 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
66.2%
22
31.5%
75
50% % within 76 µm voxel size
With fracture
Count 27
33.8%
48
68.5%
75
50% % within 76 µm voxel size
Total Count 80 70 150
% within 76 µm voxel size 100% 100% 100%
Appendix Table 14: Positive predictive value and negative predictive for resolution 100 µm
and vertical root fractures for the cone beam CT images.
100 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 57
69.5%
18
26.5%
75
50% % within 100 µm voxel size
With fracture
Count 25
30.5%
50
73.5%
75
50% % within 100 µm voxel size
Total Count 82 68 150
% within 100 µm voxel size 100% 100% 100%
82
Appendix Table 15: Positive predictive value and negative predictive for resolution 200 µm
and vertical root fractures for the cone beam CT images.
200 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
64.6%
22
32.3%
75
50% % within 200 µm voxel size
With fracture
Count 29
35.4%
46
67.7%
75
50% % within 200 µm voxel size
Total Count 82 68 150
% within 200 µm voxel size 100% 100% 100%
Appendix Table 16: Positive predictive value and negative predictive for resolution 300 µm
and vertical root fractures for the cone beam CT images.
300 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 56
60.2%
19
33.3%
75
50% % within 300 µm voxel size
With fracture
Count 37
39.8%
38
66.7%
75
50% % within 300 µm voxel size
Total Count 93 57 150
% within 300 µm voxel size 100% 100% 100%
83
Appendix Table 17: Specificity, sensitivity, false positive and false negative for resolution 76
µm and horizontal root fractures for the cone beam CT images.
76 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 53
70.6%
22
29.4%
75
100% % within Gold
With fracture Count 41
54.7%
34
45.3%
75
100% % within Gold
Total Count 94 56 150
% within Gold 62.6% 37.4% 100%
Appendix Table 18: Specificity, sensitivity, false positive and false negative for resolution
100 µm and horizontal root fractures for the cone beam CT images.
100 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 57
76.0%
18
24%
75
100% % within Gold
With fracture Count 44
58.7%
31
41.3%
75
100% % within Gold
Total Count 101 49 150
% within Gold 67.3% 32.7% 100%
84
Appendix Table 19: Specificity, sensitivity, false positive and false negative for resolution
200 µm and horizontal root fractures for the cone beam CT images.
200 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 53
70.6%
22
29.4%
75
100% % within Gold
With fracture Count 42
56%
33
44%
75
100% % within Gold
Total Count 95 55 150
% within Gold 63.3% 36.7% 100%
Appendix Table 20: Specificity, sensitivity, false positive and false negative for resolution
300 µm and horizontal root fractures for the cone beam CT images.
300 µm voxel size Total
No fracture With fracture
Gold standard No fracture Count 56
74.6%
19
25.4%
75
100% % within Gold
With fracture Count 53
70.7%
22
29.3%
75
100% % within Gold
Total Count 109 41 150
% within Gold 72.6% 27.4% 100%
85
Appendix Table 21: Positive predictive value and negative predictive for resolution 76 µm
and horizontal root fractures for the cone beam CT images.
76 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
56.4%
22
39.3%
75
100% % within 76 µm voxel size
With fracture
Count 41
43.6%
34
60.7%
75
100% % within 76 µm voxel size
Total Count 94 56 150
% within 76 µm voxel size 100% 100% 100%
Appendix Table 22: Positive predictive value and negative predictive for resolution 100 µm
and horizontal root fractures for the cone beam CT images.
100 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 57
56.4%
18
36.7%
75
100% % within 100 µm voxel size
With fracture
Count 44
43.6%
31
63.3%
75
100% % within 100 µm voxel size
Total Count 101 49 150
% within 100 µm voxel size 100% 100% 100%
86
Appendix Table 23: Positive predictive value and negative predictive for resolution 200 µm
and horizontal root fractures for the cone beam CT images.
200 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 53
55.8%
22
40.0%
75
100% % within 200 µm voxel size
With fracture
Count 42
44.8%
33
60.0%
75
100% % within 200 µm voxel size
Total Count 95 55 150
% within 200 µm voxel size 100% 100% 100%
Appendix Table 24: Positive predictive value and negative predictive for resolution 300 µm
and horizontal root fractures for the cone beam CT images.
300 µm voxel size Total
No fracture
With fracture
Gold standard
No fracture Count 56
51.4%
19
46.3%
75
100% % within 300 µm voxel size
With fracture
Count 53
48.6%
22
53.7%
75
100% % within 300 µm voxel size
Total Count 109 41 150
% within 300 µm voxel size 100% 100% 100%