The Effect of Cone Beam CT Voxel Size on the Identification of Vertical and Horizontal Root Fractures: an In-Vitro Study

The Effect of Cone Beam CT Voxel Size on the Identification of Vertical and Horizontal Root Fractures: An In-Vitro Study

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

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.

ii 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.

iii 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

iv 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

v 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

vi 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

vii 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

viii 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

ix 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

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.

!!!!!!!!!!!!A!!!!!!!!!!!!!!!!!!!!B!!!!!!!!!!!!!!!!!!C!!!!!!!!!!!!!!!!D!!!!!!!!!!!!!!!!!!!!!!!E! 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

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

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

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

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

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

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

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

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

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

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

Study Sample Cone beam CT imaging system Results

Hassan et al., 200940 80 extracted teeth (40 i-CAT, 0.25 mm voxel size. Specificity: 97.5% premolars and 40 molars) Sensitivity: 80.0% placed in dry human

mandible. Varshosaz et al., 201035 100 single-rooted teeth placed Promax 3D, 0.30 mm voxel size. ROC curve area: 0.91 in dry human mandible.

Valizadeh et al., 201153 120 extracted single-rooted NewTom 3G, 0.16 mm voxel size. Specificity: 76.9% teeth placed in acrylic blocks. Sensitivity: 66.7%

Ozer, 201142 60 extracted maxillary i-CAT, 0.125 mm, 0.20 mm, 0.30 0.125 mm voxel size premolar teeth placed in dry mm, 0.40 mm voxel sizes. Specificity: 96% human mandible. Sensitivity: 98% Accuracy: 97%

0.20 mm voxel size Specificity: 96% Sensitivity: 97% Accuracy: 96%

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 i-CAT, 0.20 mm, 0.30 mm and 0.20 mm voxel teeth placed in acrylic blocks. 0.40 mm voxel sizes. 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%

Kambungton et al., 60 extracted single-rooted Veraviewpocs 3D, 0.125 mm ROC curve area: 0.81 201254 teeth placed in dry human voxel mandible.

Khedmat et al., 201256 100 extracted single-rooted Promax 3D, 0.30 mm voxel Specificity: 88% teeth placed in acrylic blocks. Sensitivity: 92% Accuracy: 90%

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

Study Sample Cone beam CT imaging system Result

Kamburoğlu et al., 36 incisor teeth placed in dry Accuitomo 80, 0.08 mm voxel Specificity: 97% 34 2009 human maxillae. Sensitivity: 92% Iikubo et al., 200920 28 maxillary anterior teeth PSR-9000N Dental CT, 0.117 mm Specificity: 91% with 13 fractured placed in 7 voxel Sensitivity: 96% beagle dogs’ maxillae. Accuracy: 93% Avsever et al., 201325 82 extracted human Accuitomo 170, 0.08 mm voxel 3D Accuitomo maxillary incisors with 31 Specificity: 97% fractured placed in dry Sensitivity: 94% human maxillae. Accuracy: 93%

NewTom 3G, 0.18 mm voxel NewTom 3G Specificity: 89% Sensitivity: 89% Accuracy: 87%

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

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

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 i-CAT, 0.25 mm voxel Specificity: 87.5% and 40 molars) with root canal Sensitivity: 78.8% treatment placed in dry human mandible. Melo et al., 201019 180 single-rooted teeth with i-CAT, 0.20 mm or 0.30 mm 0.20 mm voxel (GP) presence of gutta percha (GP) and voxel sizes Specificity: 73% metallic post (MP) placed in dry human skull. 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%

Hassan et al., 201057 80 extracted teeth (40 premolars NewTom 3G, 0.20 mm voxel NewTom 3G and 40 molars) with root canal Specificity: 95% treatment placed in posterior region Sensitivity: 30.4% of dry human mandible. Accuracy: 62.7%

i-CAT, 0.25 mm voxel i-CAT Specificity: 91.3% Sensitivity: 77.5% Accuracy: 84.4%

Galileos 3D, 0.30 mm voxel Galileos 3D Specificity: 85% Sensitivity: 18.8% Accuracy: 53.8%

Scanora 3D, 0.20 mm voxel Scanora 3D Specificity: 85% Sensitivity: 57.5% Accuracy: 71.3%

3D Accuitomo, 0.25 mm voxel 3D Accuitomo Specificity: 90.7% Sensitivity: 48.1%

Accuracy: 69.4%

Da Silveira et al., 60 extracted single-rooted teeth i-CAT, 0.20, 0.30 and 0.40 mm 0.20 mm voxel 55 with presence of gutta percha (GP) 2013 voxel sizes. Specificity (GP): 93% or metallic post (MP) placed in acrylic blocks. 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%

Accuracy (MP): 57%

Khedmat et al., 201256 100 extracted single-rooted teeth Promax 3D, 0.16 mm voxel Specificity (GP): 64% placed in acrylic blocks. Sensitivity (GP): 80% Accuracy (GP): 72% Ferreira et al., 201258 59 extracted maxillary ﬁrst i-CAT, 0.125 mm voxel i-CAT premolars with fiber-resin (FR) or Specificity (FR): 74% titanium (T) posts placed in acrylic blocks. Sensitivity (FR): 85% Accuracy (FR): 78% Specificity (T): 75% Sensitivity (T): 72% Accuracy (T): 73%

Scanora 3D, 0.133 mm voxel Scanora 3D Specificity (FR): 71% Sensitivity (FR): 73% Accuracy (FR): 71% Specificity (T): 76% Sensitivity (T): 73% Accuracy (T): 74%

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

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., 33 teeth in 29 patients i-CAT, 0.125 mm voxel or Endodontic Specificity: 75% 59 2011 with clinical signs and 3D Accuitomo, 0.080 mm voxel surgery Sensitivity: 88% symptoms suspicious of Accuracy: 84% vertical root fracture. Wang et al., 2011 49 teeth with clinical 3D Accuitomo, 0.125 mm voxel Surgical Specificity: 100% 14 signs and symptoms intervention Sensitivity: 71.4% suspicious of vertical

root fracture Metska et al., 39 teeth from 39 patients 3D Accuitomo, 0.08 mm voxel Orthograde 3D Accuitomo 30 2012 with clinical and or NewTom 3G, 0.20 mm voxel retreatment, Specificity: 80% radiographic signs and endodontic Sensitivity: 100% symptoms suspicious of microsurgery, vertical root fracture. or extraction of Accuracy: 93% the tooth NewTom 3G Specificity: 56% Sensitivity: 75% Accuracy: 68%

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

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.

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.

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).

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.

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.

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).

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

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

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.,

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

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 76 µm 100 µm 200 µm 300 µm

Test Results

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%

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

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 76 µm 100 µm 200 µm 300 µm

Test Results

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%

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

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 76 µm 100 µm 200 µm 300 µm

Test Results

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%

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

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).

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).

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

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

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 radiologists (Tables 3.12, 3.13).

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

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.

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

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

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

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

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 Oral Oral Oral Radiology Radiologists Radiology Radiologists graduate graduate students students

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

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

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

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

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

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.

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.

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

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

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.

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Appendix 1 Copy of the ethics approval of the research

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

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: ______

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 22 75 % within Gold 70.7% 29.3% 100% With fracture Count 53 97 150 % within Gold 35.3% 64.7% 100% 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 18 75 % within Gold 76.0% 24.0% 100%

With fracture Count 51 99 150 % within Gold 34.0% 66.0% 100% Total Count 108 117 225 % within Gold 48.0% 52.0% 100%

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 22 75 % within Gold 70.7% 29.3% 100% With fracture Count 56 94 150 % within Gold 37.3% 62.7% 100% 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 19 75 % within Gold 74.4% 25.3% 100% With fracture Count 69 81 150 % within Gold 46.0% 54.0% 100% Total Count 125 100 225 % within Gold 55.6% 44.4% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 76 µm voxel 50.0% 18.5% 33.3% size With Count 53 97 150 fracture % within 76 µm voxel 50.0% 81.5% 66.7% 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 With fracture fracture Gold No fracture Count 57 18 75 standard % within 100 µm 52.8% 15.4% 33.3% voxel size With Count 51 99 150 fracture % within 100 µm 47.2% 84.6% 66.7% voxel size Total Count 108 117 225 % within 100 µm voxel size 100% 100% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 200 µm 48.6% 19.0% 33.3% voxel size With Count 56 94 150 fracture % within 200 µm 51.4% 81.0% 66.7% 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 With fracture fracture Gold No fracture Count 56 19 75 standard % within 300 µm 44.8% 19.0% 33.3% voxel size With Count 69 81 150 fracture % within 300 µm 55.2% 81.0% 66.7% voxel size Total Count 125 100 225 % within 300 µm voxel size 100% 100% 100%

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 22 75 % within Gold 70.6% 29.3% 100% With fracture Count 27 48 75 % within Gold 36.0% 64.0% 100% 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 18 75 % within Gold 76% 24% 100% With fracture Count 25 50 75 % within Gold 33.3% 66.7% 100% Total Count 82 68 150 % within Gold 54.6% 45.4% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 70.6% 29.4% 100% Gold With Count 29 46 75 fracture % within 38.7% 61.3% 100% 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 19 75 % within Gold 74.6% 25.4% 100% With fracture Count 37 38 75 % within Gold 49.3% 50.7% 100% Total Count 93 57 150 % within Gold 62% 38% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 76 µm voxel 66.2% 31.5% 50% size With Count 27 48 75 fracture % within 76 µm voxel 33.8% 68.5% 50% 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 With fracture fracture Gold No fracture Count 57 18 75 standard % within 100 µm 69.5% 26.5% 50% voxel size With Count 25 50 75 fracture % within 100 µm 30.5% 73.5% 50% voxel size Total Count 82 68 150 % within 100 µm voxel size 100% 100% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 200 µm 64.6% 32.3% 50% voxel size With Count 29 46 75 fracture % within 200 µm 35.4% 67.7% 50% 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 With fracture fracture Gold No fracture Count 56 19 75 standard % within 300 µm 60.2% 33.3% 50% voxel size With Count 37 38 75 fracture % within 300 µm 39.8% 66.7% 50% voxel size Total Count 93 57 150 % within 300 µm voxel size 100% 100% 100%

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 22 75 % within Gold 70.6% 29.4% 100% With fracture Count 41 34 75 % within Gold 54.7% 45.3% 100% 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 18 75 % within Gold 76.0% 24% 100% With fracture Count 44 31 75 % within Gold 58.7% 41.3% 100% Total Count 101 49 150 % within Gold 67.3% 32.7% 100%

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 22 75 % within Gold 70.6% 29.4% 100% With fracture Count 42 33 75 % within Gold 56% 44% 100% 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 19 75 % within Gold 74.6% 25.4% 100% With fracture Count 53 22 75 % within Gold 70.7% 29.3% 100% Total Count 109 41 150 % within Gold 72.6% 27.4% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 76 µm voxel 56.4% 39.3% 100% size With Count 41 34 75 fracture % within 76 µm voxel 43.6% 60.7% 100% 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 With fracture fracture Gold No fracture Count 57 18 75 standard % within 100 µm 56.4% 36.7% 100% voxel size With Count 44 31 75 fracture % within 100 µm 43.6% 63.3% 100% voxel size Total Count 101 49 150 % within 100 µm voxel size 100% 100% 100%

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 With fracture fracture Gold No fracture Count 53 22 75 standard % within 200 µm 55.8% 40.0% 100% voxel size With Count 42 33 75 fracture % within 200 µm 44.8% 60.0% 100% 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 With fracture fracture Gold No fracture Count 56 19 75 standard % within 300 µm 51.4% 46.3% 100% voxel size With Count 53 22 75 fracture % within 300 µm 48.6% 53.7% 100% voxel size Total Count 109 41 150 % within 300 µm voxel size 100% 100% 100%