Introduction
Radiographic imaging is crucial in endodontics, aiding in
diagnosis, treatment planning, and assessing treatment outcomes [1]. While two-dimensional radiographs are commonly
used for imaging dentoalveolar structures, they have limitations
like geometric distortion and superimposition [2,3]. In the late
20th Century, Cone Beam Computed Tomography (CBCT) was
introduced for dental implant planning, and advancements
in image quality, reduced dosage, and cost have expanded its
use into endodontics, as endorsed by the European Society of
Endodontology and the American Association of Endodontists
[4]; ‘(AAE and AAOMR Issue Position Statement on 3-D Imaging
in Endodontics’, 2015). CBCT machines, a Modification of MultiSlice Computed Tomography (MSCT), generate images differently than conventional two-dimensional radiography. They use
a single x-ray beam that diverges like a cone around a specific
area (Figure 1).
Complex computer algorithms then reconstruct a detailed
three-dimensional image from the data received on the image
receptor [5]. Clinicians benefit from the ability to view these
images in multiple planes without superimposition, with slices
as thin as 0.5 mm, providing valuable advantages [6]. Regarding
radiation exposure, CBCT carries an average effective dose 95%
lower than MSCT imagery. Dosage can range from as low as 2
µSv to 200 µSv, depending on the justification for exposure [4].
The average small-volume CBCT presents an effective dose of
50 µSv, 50 times that of a single periapical radiograph. Recent
literature underscores CBCT’s benefits in endodontics, such as
early detection of apical pathology compared to conventional
two-dimensional radiographs [7,8]. Clinical studies reveal CBCT
makes apical pathology detection twice as likely, a finding supported by histopathology reference standards. Early detection
implies improved outcomes, as suggested by Ng et al.’s systematic review in 2008. Additionally, CBCT aids in refining case selection for pulpal preservation procedures, especially in cases of
deep carious lesions with pulpal exposure, where the absence
of periapical pathosis is crucial for successful outcomes. CBCT
significantly transforms the management of endodontic cases
compared to conventional radiography, particularly in already
root-filled teeth, by enabling the detection of missed anatomy,
root fractures, and a more precise assessment of periapical lesion extent [6]. Despite these advancements, the subsequent
impact on endodontic outcomes remains unidentified. The increased usage of CBCT among endodontists, as evidenced by
a recent survey reporting a 91.8% adoption rate, underscores
its growing popularity [9]. However, despite CBCT’s recognized
benefits like high spatial resolution and reduced anatomical noise, there is a widespread acknowledgment that reconstructed images are more susceptible to artefact production,
potentially affecting diagnostic quality and utility [10]. Notably,
the presence of artefacts has been suggested to pose a more
severe risk of misdiagnosis rather than leading to under or overdiagnosis [6]. Artefacts in CBCT images denote inconsistencies
between the reconstructed image and the actual object attenuation [11]. These artefacts can be broadly classified into unitrelated, patient-related, and beam-related categories (Table 1).
Table 1: Types of artefacts and their definition.
Artefact |
Definition |
Category |
Beam Hardening |
Hypodense streaks, halos,
and cupping
|
Beam Related |
Scatter |
Hyperdense streaks and
cupping
|
Beam Related |
Image Noise |
Unwanted
randomly/non-randomly distributed
disturbance of the image
giving it a grainy
appearance
|
Beam Related |
Motion |
Blurring of image and
anatomical structures
|
Patient Related |
Ring |
Concentric rings mainly
visible in the axial plane
around the centre of
rotation
|
Unit Related |
Aliasing |
Moiré pattern at the
periphery of the image.
|
Unit Related |
Given this understanding and the heightened health risks
associated with larger radiation doses, it becomes imperative
for clinicians to justify exposures judiciously. An in-depth comprehension of CBCT limitations is crucial, ensuring the selection
of the most appropriate radiographic examination while upholding the ALARP (as low as reasonably practicable) legislative
principle [5,12]. To gauge the potential scope of the issue, we
conducted a comprehensive literature review by performing an
extensive search on the MEDLINE database using the terms for
FIELD 1: Cone Beam Computed Tomography or CBCT; FIELD 2:
Artefact or Artifact; and FIELD 3: Dentistry or Dental.
MEDLINE was selected for its status as one of the most comprehensive health electronic databases, minimizing the risk of
overlooking pertinent publications. The search yielded 297 papers, from which those referencing artefact incidence and diagnostic quality were incorporated into data extraction tables,
encompassing both laboratory and clinical studies. The adoption of these inclusive criteria stemmed from the scarcity of relevant papers, constraining the application of stricter selection
parameters. For clarity, one table addresses artefact incidence,
while the other delves into the effects of artefacts on diagnostic quality. Considering the inaugural use of CBCT in 1998 [13], all
identified articles were deemed contemporaneous. The scrutiny of the literature exposed a dearth of well-conducted clinical research on artefact production incidence and its impact on
diagnostic image quality. The limited evidence predominantly
centres on two specific artefacts, beam hardening and motionrelated artefacts, with minimal attention to others. Regarding
incidence, only two publications using in vivo methodology
were identified. Both focused on motion artefacts, with one
presenting a literature review and the other conducting a prospective study utilizing gold standard motion detection methodology to assess artefact expression [14,15]. The methodologies
employed in these two studies stood out as the most rigorous
in terms of both data capture and analysis, as highlighted in this
review. In contrast, other studies utilized dry mandibles with
laboratory-based methodologies to examine beam hardening artefact expression [16], a context that may not perfectly
align with clinical situations. From the literature search, only
one clinical study addressing the impact of artefacts on diagnostic quality emerged. This study employed a subjective analogue scale to evaluate how age, body mass index, implants,
and other restorations affected the visualization of anatomical
structures. While the authors asserted that artefacts did not
compromise the ability to visualize anatomical structures, they
did acknowledge a reduction in the diagnostic quality of the images [17]. In the realm of endodontics and implantology, three
laboratory-based studies were identified. Two of these studies
employed similar methodologies to assess artefacts’ effects
on detecting external root resorption or vertical root fractures
[18,19]. The authors concluded that artefact expression, intensity, and location did not impede the detection of external root
resorption but adversely impacted the ability to detect vertical
root fractures, with an elevated risk of false positives closer to
the suspected fracture site [19]. The third study, loosely tied to
diagnostic quality, examined whether metal artefact reduction
algorithms improved the visualization of anatomical structures
with implants. Surprisingly, the authors found that these algorithms adversely affected the ability to locate those structures.
The methodologies across the reviewed studies varied significantly, employing both subjective and objective analyses. Additionally, the evaluation conditions for CBCT images differed,
with only a subset adhering to SEDENTEXCT guidelines for optimal viewing and dose optimization (2012). This raises concerns
about the validity and relevance of the results obtained. Most
studies were conducted in vitro, questioning whether these
methodologies truly mirror clinical situations, where factors
like motion and soft tissue may influence beam behaviour and
attenuation. Although proposed subjective artefact assessment
as the most practical given the current subjectivity in clinical
radiographic interpretation, emphasizing the need for a subjective retrospective study. This approach offers a more coherent
evaluation of artefact incidence and impact on diagnostic quality within the same dataset, specifically from an endodontic
perspective. The study aimed to investigate artefact incidence
from endodontically treated teeth on CBCT images and its consequential impact on diagnostic value.
Materials and methods
To assess the occurrence of artefacts resulting from endodontically treated teeth on CBCT scans and their impact on
endodontic diagnosis, a subjective retrospective analysis was
conducted at the University of Central Lancashire (UCLAN) Dental Clinic, spearheaded by a single researcher. Given resource
limitations, including self-funding constraints, the methodology was tailored to meet the research objectives outlined earlier.
This innovative approach is the first of its kind, allowing the recording of all known artefact types from a single sample dataset, facilitating inter-artefact type analysis to identify potential
correlations. An overview of the methodology is presented in
Figure 2. Ethical approval for the research was obtained from
the UCLAN ethics committee following the HRA decision tool assessment. Since this is a retrospective analysis of images taken
for justified clinical purposes, IRAS approval was deemed irrelevant. Patient consent for the clinic inherently encompasses the
use of imagery for educational, marketing, and research purposes.
The inclusion criteria are summarised:
CBCT images acquired at UCLAN Dental Clinic on Sirona Orthophos XG 3D from 2016 to December 2020.
Scans must encompass at least one endodontically treated
tooth.
At least one tooth unit mesial and distal to the endodontically treated tooth should be visible in the scan to facilitate artefact extent determination.
Images must be viewable from the imaging room at UCLAN
Dental Clinic.
Scans taken for clinical purposes.
The exclusion criteria are summarised:
Images captured on a different CBCT machine.
Scans lacking at least one endodontically treated tooth.
Scans where one tooth unit mesial or distal to the endodontically treated tooth is not visible.
Images taken outside the dates specified in the inclusion criteria
For sampling, images were selected randomly and anonymized by the research supervisor, utilizing a random number
generator in Microsoft Excel. The researcher remained blinded
to any patient-identifying data, while the research supervisor
ensured each scan adhered to the previously discussed inclusion criteria for the study. Images were examined under optimal low-light conditions, employing a 19-inch monitor, and adhering to ideal viewing parameters outlined in the SEDENTXCT
Guidelines (2012). The researcher underwent calibration for all
known artefacts (e.g., beam hardening, scatter, image noise,
motion, ring, and aliasing artefacts) against the primary supervisor. In cases of disagreement, the secondary supervisor provided their opinion, and a consensus decision was reached. The
reference standard for defining artefacts was derived from the
current evidence base on CBCT artefacts [4,11]. Calibration involved a pilot study utilizing a data capture grid (refer to Figure
10), and a Cohen’s Kappa calculation demonstrated a significant
inter-observer co-efficient of 0.71. Intra-observer reliability was
established through a subsequent pilot study, repeated a week
later with another set of 10 scans under the same conditions
as the main study. A Cohen’s Kappa score of 0.95 indicated
excellent intra-observer reliability. The researcher conducted
data collection over one week, working in short periods with
frequent breaks to prevent observer fatigue. To mitigate recall
bias, the researcher returned after one month to reassess 10
CBCT images to ensure result accuracy and reliability. For data
security, images were only viewable at the UCLAN Dental Clinicvia a password-protected computer, and the obtained data was
stored on the principal investigator’s password-protected folder
on the University network. No sensitive information identifying
patients or clinicians was recorded. To fulfil the study’s aims and
objectives, the researcher documented relevant information
(refer to Figure 10) on a data capture grid in Microsoft Excel.
Each image was viewed in the dental clinic imaging room under optimal low-light viewing conditions, following SEDENTXCT
guidelines (2012). The CBCT images were observed using the
proprietary viewing software, Sirona Galaxisis Version 5, provided by the machine manufacturer. The MPR view was utilized,
enabling the examination of the area of interest in three planes:
axial, coronal, and sagittal (Figure 3).
In this viewing configuration, each image underwent the following analysis to document the occurrence and impact of observed artefacts:
The researcher recorded general information, including gender, age, region of interest, purpose, image characteristics, and
restorative profile of the teeth.
Each subject tooth was categorized into crown and root sections.
The relevant section of the tooth was systematically surveyed three times in each view-initially in the axial, followed by
the coronal, and concluding with the sagittal view. Each sweep
lasted approximately 10-15 seconds.
Following each view sweep, the researcher documented
their findings in the data capture grid.
Upon completion of the assessment in all three views, the
researcher progressed to the next section.
After a thorough assessment of artefacts for each tooth,
the researcher provided a subjective overall evaluation on the
data capture grid concerning diagnostic quality and the ability
to identify conditions outlined by the ESE guidelines (2015) for
CBCT usage in endodontics.
The sweeping approach for viewing the scan, adopted by the
researcher, served to consolidate the numerous slices in a reconstructed CBCT image [5]. This motion mirrors how a clinician
is likely to view the image, as the cumulative information from
multiple slices is crucial for diagnosis and treatment planning.
Rationale for the data capture grid: The information recorded from each scan aligns with the study’s aims and objectives. As the first comprehensive study of its kind to evaluate all
known CBCT artefacts within a single data set, an occurrencebased measurement was deemed the most suitable. The literature review exposed a lack of consensus between objective and
subjective artefact measurements. Given the study’s limited
resources and [20] acknowledgment of the inherently subjective nature of radiographic analysis, the chosen capture grid
and methodology were deemed the most accurate for meeting
the study’s objectives while maintaining clinical relevance in the
profession.
Controls
Selection bias: Scans meeting inclusion criteria were chosen using a random number generator in Microsoft Excel, and
the primary researcher remained blinded to patient-identifying
data to prevent participant bias.
Measurement bias: Due to the disagreement in the literature on the most appropriate artefact measurement, a simple
occurrence-based measurement and subjective diagnostic impact assessment, proposed by [20], were adopted to minimize
measurement bias. The simplicity of the measurement aims to
reduce bias. Recall bias was minimized by repeating data collection on 10 scans a month after the initial capture to ensure
good reliability.
Optimized viewing conditions: SEDENTXCT guidelines
(2012) were adhered to.
Standardized viewing protocol: Each scan was viewed using
a standardized protocol.
Data analysis: To fulfil the research objectives, the data underwent analysis using the statistical package SPSS version 28
by IBM systems, given the quantitative nature of the study. Before analysis, a missing value analysis was conducted to ensure accurate data input into SPSS, enhancing the reliability of subsequent statistical analyses.
Results
The details of the study characteristics are given in (Table 2).
Table 2: Study characteristics and variables.
Factor/Variable |
Number of patients (n)
|
Patients (%) |
Age Under 30 |
0 |
0 |
31-50 |
13 |
32.5 |
51 and over |
27 |
67.5 |
Gender Male and Female |
17 and 23 |
42.5 and 57.5 |
Field of View (cm) 5x5, 5x8,
8x8
|
19, 15 and 6 |
47.5, 37.5 and 15 |
Dose (kVp) 90, 95 and 120
|
19, 1 and 20 |
47.5, 2.5 and 50 |
Tooth Type Incisors |
6 |
15 |
Canines |
1 |
2.5 |
Premolars |
12 |
30 |
Molars |
21 |
52.5 |
Tooth Location Maxilla and
Mandible
|
20 and 20 |
50 and 50 |
No. of Roots. 1, 2 and 3
|
19, 15 and 6 |
47.5, 37.5 and 15 |
Obturation Material. GP |
40 |
100 |
Coronal Restoration on
subject tooth
|
|
|
Composite/GIC |
7 |
17.5 |
Porcelain Bonded Crown |
27 |
67.5 |
Feldspathic/Ceramic Crown
|
4 |
10 |
Ceramic Inlay/Onlay |
1 |
2.5 |
Other |
1 |
2.5 |
Post Present on Subject
Tooth Y and N
|
10 and 30 |
25 and 75 |
Coronal Restoration on tooth
mesial to subject tooth
|
|
|
Amalgam |
1 |
2.5 |
Composite/GIC |
5 |
12.5 |
Porcelain Bonded Crown |
7 |
17.5 |
Other |
1 |
2.5 |
Unrestored |
11 |
27.5 |
Tooth Absent |
14 |
35 |
Denture Tooth |
1 |
2.5 |
Coronal Restoration on tooth
distal to subject tooth
|
|
|
Amalgam |
1 |
2.5 |
Composite/GIC |
6 |
15 |
Porcelain Bonded Crown |
5 |
12.5 |
Unrestored |
7 |
17.5 |
Tooth Absent |
20 |
50 |
Dental Implant |
1 |
2.5 |
Table 3: Incidence of artefacts.
Diagnostic Acceptability
|
|
Number of teeth |
% of teeth |
Beam Hardening in the crown
of the subject tooth
|
Yes |
49 |
86 |
No |
8 |
14 |
Beam Hardening in the root
of the subject tooth
|
Yes |
54 |
94.7 |
No |
3 |
5.3 |
Scatter in the crown of the
subject tooth
|
Yes |
57 |
100 |
No |
0 |
0 |
Scatter in the root of the
subject tooth
|
Yes |
57 |
100 |
No |
0 |
0 |
Image Noise in the crown of
the subject tooth
|
Yes |
18 |
31.6 |
No |
39 |
68.4 |
Image Noise in the root of
the subject tooth
|
Yes |
18 |
31.6 |
No |
39 |
68.4 |
Motion artefact in the crown
of the subject tooth
|
Yes |
4 |
7 |
No |
53 |
93 |
Motion artefact in the root
of the subject tooth
|
Yes |
4 |
7 |
No |
53 |
93 |
Ring artefacts in the crown
of the subject tooth
|
Yes |
0 |
0 |
No |
57 |
100 |
Ring artefacts in the root
of the subject tooth
|
Yes |
0 |
0 |
No |
57 |
100 |
Aliasing artefacts in the
crown of the tooth
|
Yes |
10 |
17.5 |
No |
47 |
82.5 |
Aliasing artefacts in the
root of the tooth
|
Yes |
10 |
17.5 |
No |
47 |
82.5 |
Artefact incidence in CBCT scans: Tables 3, 4 and 5 show incidence of artifacts, diagnostic acceptability of teeth, the incidence of artifacts and their dependence on the study characteristics. The study found a 100% incidence of scatter across all 57
subject teeth, irrespective of tooth type, field of view, dose, location, and coronal restoration. This precluded statistical analysis for scatter. Ring artefacts were absent in all 57 scans, making statistical analysis impossible for this variable as well. Beam
hardening artefacts exhibited the next highest incidence in the
dataset, with prevalence rates of 86% in the crown region and
94.7% in the root region of the subject tooth (Figures 4 and 5).
Chi-squared analysis, with a significance level set at 95%, suggested potential associations between crown beam hardening
and tooth type, location, coronal restoration type, and adjacent
teeth (Table 4). Conversely, root beam hardening appeared influenced by the coronal restoration of the subject tooth and its
mesial neighbour. Image Noise, Motion, and Aliasing artefacts
reported incidences of 31.6%, 7%, and 14%, respectively, with
no significant difference between crown and root regions. Chisquared analysis indicated associations between Image Noise
and age, as well as field of view. Motion artefacts were linked
to whether the tooth was single or multi-rooted, while Aliasing
artefacts showed associations with tooth type and location.
Influence of artefacts on diagnostic acceptability in CBCT
scans for endodontic purposes: Tables 6a and 6b outlines the
diagnostic acceptability of CBCT scans for endodontic purposes,
ranging from 45.6% to 100% depending on the view and the
purpose (detecting periapical pathology, assessing complex
trauma, and pre-endodontic surgery assessment). Conversely,
only up to 14% of CBCT scans were deemed acceptable when
exposure justification aimed to detect root resorption, root fracture, and complex or missed anatomy. Statistical analysis
revealed associations between crown beam hardening and
the ability to diagnose periapical pathology in axial and sagittal
views, as well as an influence on diagnosing complex trauma in
the sagittal view. Image Noise presence was associated with the
ability to detect periapical pathology in the coronal view. Motion artefacts were linked to visualising and detecting complex
anatomy in axial and sagittal views. Scatter and ring artefacts
did not allow for diagnostic acceptability analysis, as they were
consistently present.
Table 4: Incidence of artefacts.
Diagnostic Acceptability
|
|
Number of teeth |
% of teeth |
Root Fracture |
|
|
|
Axial |
Yes |
0 |
0 |
No |
57 |
100 |
Coronal |
Yes |
0 |
0 |
No |
57 |
100 |
Sagittal |
Yes |
1 |
1.8 |
No |
56 |
98.2 |
Detection of Periapical
Pathology
|
Axial |
Yes |
55 |
96.5 |
No |
2 |
3.5 |
Coronal |
Yes |
13 |
22.8 |
No |
44 |
77.2 |
Sagittal |
Yes |
56 |
98.2 |
No |
1 |
1.8 |
Detecting complex/missed
anatomy
|
Axial |
Yes |
8 |
14 |
No |
49 |
80 |
Coronal |
Yes |
0 |
0 |
No |
57 |
100 |
Sagittal |
Yes |
4 |
7 |
No |
53 |
93 |
Assessing Complex Trauma
|
Axial |
Yes |
51 |
89.5 |
No |
6 |
10.5 |
Coronal |
Yes |
27 |
47.4 |
No |
30 |
52.6 |
Sagittal |
Yes |
53 |
93 |
No |
4 |
7 |
Detecting Root Resorption
|
Axial |
Yes |
2 |
3.5 |
No |
55 |
96.5 |
Coronal |
Yes |
0 |
0 |
No |
57 |
100 |
Sagittal |
Yes |
2 |
3.5 |
No |
55 |
96.5 |
Axial |
Yes |
57 |
100 |
No |
0 |
0 |
Coronal |
Yes |
26 |
45.6 |
No |
31 |
54.4 |
Sagittal |
Yes |
40 |
100 |
No |
0 |
0 |
Table 5: Influence of study characteristics on artefact incidence.
|
Beam Hardening in the
crown
|
Beam Hardening in the
root
|
Scatter in the crown
|
Scatter in the root
|
Image Noise in the
crown
|
Image Noise in the root
|
Motion artefact in the
crown
|
Motion arte- fact in
the root
|
Ring artefact in the
crown
|
Ring artefact in the
root
|
Aliasing artefact in the
crown
|
Aliasing arte- fact in
the root
|
Gender |
0.102 |
0.158 |
a |
a |
0.975 |
0.975 |
0.627 |
0.627 |
a |
a |
0.92 |
0.92 |
Age |
0.519 |
0.948 |
a |
a |
0.005 |
0.005 |
0.083 |
0.083 |
a |
a |
0.277 |
0.277 |
FOV |
0.663 |
0.056 |
a |
a |
0.01 |
0.01 |
0.275 |
0.275 |
a |
a |
0.397 |
0.397 |
Tooth Type
(Incisor/Canine/Premolar/Molar)
|
0.015 |
0.578 |
a |
a |
0.473 |
0.473 |
0.364 |
0.364 |
a |
a |
0.039 |
0.039 |
Tooth Location
(Maxilla/Mandible)
|
0.033 |
0.617 |
a |
a |
0.787 |
0.787 |
0.863 |
0.863 |
a |
a |
0.023 |
0.023 |
No. of roots (single/multi
rooted)
|
0.114 |
0.574 |
a |
a |
0.631 |
0.631 |
0.042 |
0.042 |
a |
a |
0.525 |
0.525 |
Subject Tooth Coronal
Restoration
|
0.01 |
0.01 |
a |
a |
0.064 |
0.064 |
0.676 |
0.676 |
a |
a |
0.291 |
0.291 |
Coronal Restoration on
adjacent mesial tooth
|
0.03 |
0.004 |
a |
a |
0.235 |
0.235 |
0.048 |
0.048 |
a |
a |
0.304 |
0.304 |
Coronal Restoration on
adjacent distal tooth
|
0.03 |
0.264 |
a |
a |
0.162 |
0.162 |
0.84 |
0.84 |
a |
a |
0.73 |
0.73 |
Table 6a: Incidence of artefacts.
|
Ability to diagnose root
fracture
|
Ability to diagnose PA
pathology
|
Ability to diagnose
complex/missed anatomy
|
Axial |
Coronal |
Sagittal |
Axial |
Coronal |
Sagittal |
Axial |
Coronal |
Sagittal |
Beam Hardening in the crown
|
a |
A |
0.684 |
0.01 |
0.454 |
0.013 |
0.893 |
a |
0.402 |
Beam Hardening in the root
|
a |
A |
0.812 |
0.734 |
0.333 |
0.812 |
0.472 |
a |
0.625 |
Scatter artefact in the
crown
|
a |
A |
a |
a |
a |
A |
a |
a |
a |
Scatter artefact in the root
|
a |
A |
a |
a |
a |
A |
a |
a |
a |
Image Noise in the crown
|
a |
A |
0.138 |
0.568 |
0.008 |
0.493 |
0.698 |
a |
0.053 |
Image Noise in the root |
a |
A |
0.138 |
0.568 |
0.008 |
0.493 |
0.698 |
a |
0.053 |
Motion artefact in the crown
|
a |
A |
0.782 |
0.692 |
0.179 |
0.782 |
0.001 |
a |
0.001 |
Motion artefact in the root
|
a |
A |
0.782 |
0.692 |
0.179 |
0.782 |
0.001 |
a |
0.001 |
Ring artefact in the crown
|
a |
A |
a |
a |
a |
A |
a |
a |
a |
Ring artefact in the root
|
a |
A |
a |
a |
a |
A |
a |
a |
a |
Aliasing artefact in the
crown
|
a |
A |
0.642 |
0.219 |
0.058 |
0.642 |
0.159 |
a |
0.339 |
Aliasing artefact in the
root
|
a |
A |
0.642 |
0.219 |
0.058 |
0.642 |
0.159 |
a |
0.339 |
a. Where chi square statistical analysis not possible due to one variable being constant.
Table 6b: Incidence of artefacts.
|
Ability to diagnose complex
trauma
|
Ability to diagnose root
resorption
|
Suitable for pre surgical
assessment
|
Axial |
Coronal |
Sagittal |
Axial |
Coronal |
Sagittal |
Axial |
Coronal |
Sagittal |
Beam Hardening in the crown
|
0.15 |
0.172 |
0.032 |
0.561 |
A |
0.561 |
a |
0.207 |
a |
Beam Hardening in the root
|
0.542 |
0.617 |
0.625 |
0.734 |
A |
0.734 |
a |
0.661 |
a |
Scatter artefact in the
crown
|
a |
A |
a |
a |
A |
a |
a |
a |
a |
Scatter artefact in the root
|
a |
A |
a |
a |
A |
a |
a |
a |
a |
Image Noise in the crown
|
0.406 |
0.158 |
0.769 |
0.328 |
A |
0.328 |
a |
0.111 |
a |
Image Noise in the root |
0.406 |
0.158 |
0.769 |
0.328 |
A |
0.328 |
a |
0.111 |
a |
Motion artefact in the crown
|
0.477 |
0.251 |
0.569 |
0.692 |
A |
0.692 |
a |
0.221 |
a |
Motion artefact in the root
|
0.477 |
0.251 |
0.569 |
0.692 |
A |
0.692 |
a |
0.221 |
a |
Ring artefact in the crown
|
a |
A |
a |
a |
A |
a |
a |
a |
a |
Ring artefact in the root
|
a |
A |
a |
a |
A |
a |
a |
a |
a |
Aliasing artefact in the
crown
|
0.001 |
0.009 |
0.002 |
0.507 |
A |
0.507 |
a |
0.013 |
a |
Aliasing artefact in the
root
|
0.001 |
0.009 |
0.002 |
0.507 |
A |
0.507 |
a |
0.013 |
a |
b. Where chi square statistical analysis not possible due to one variable being constant.
Discussion
The widespread adoption of CBCT in endodontics, as underscored by recent reviews [4], position statements [1], and
studies [6], has significantly altered the diagnosis and treatment
planning, particularly for root-filled teeth, when compared to
conventional 2D radiography. However, the potential benefits of
CBCT are accompanied by the acknowledged susceptibility of its
reconstructed images to artefacts [21,22]. This study addresses
a notable gap in the literature by being the first to investigate
the in vivo prevalence of artefacts on CBCT images and their
impact on diagnostic quality. While scatter artefacts exhibited a
100% incidence on all subject teeth, beam hardening followed
closely, being present in 86-94.7% of cases. This contrasts with
a prior in vitro study [16], which reported lower artefact prevalence. Notably, this study’s design better reflects real-world
scenarios with diverse tooth restorations. The high incidence of
beam hardening was associated with tooth type, location, and
the restorative status of both the subject tooth and adjacent
teeth. Recommendations for improving diagnostic quality include considering the removal of highly radiopaque materials
before imaging, as they contribute to increased beam hardening
and scatter artefacts. While some studies suggested factors like
body mass index, age, and dosage influenced diagnostic quality
[19,17], further research is needed for comprehensive understanding. Motion artefacts, while showing a lower incidence of
7%, were associated with the number of roots, impacting the
ability to detect complex or missed anatomy. This emphasizes
the importance of head stability during exposure, a recognized
risk factor for motion artefacts [14]. Unit-related artefacts like
image noise, ring, and aliasing exhibited a 0-17.5% incidence
with associations noted with study characteristics such as age,
field of view, and tooth type/location. Image noise and aliasing
artefacts impacted the ability to diagnose apical pathology and
detect complex trauma, respectively. Proper unit maintenance
was stressed to prevent these artefacts [11]. While some novel
techniques, like manipulating soft tissue to reduce artefact expression, have been proposed [23], the limited evidence underscores the need for further research. Policymakers and clinicians should consider alternative measures to enhance CBCT
efficacy, particularly for endodontic purposes requiring detailed
anatomical structure visualization. Study limitations include
retrospective data derived from CBCT scans intended for dental implants, potentially influencing exposure parameters and
artefact expression. The single-machine, subjective assessment
of artefact presence through a dichotomous variable may oversimplify the situation, and future studies should explore more
objective scales for greater nuance. Prospective studies, standardized measures, and multiple CBCT units are recommended
for enhanced methodological strength and clinical relevance.
Conclusion
In conclusion, this research has unravelled a spectrum of artefact prevalence, underscoring Beam Hardening and Scatter artefacts as the most prevalent culprits. Notably, their influence,
alongside Image Noise, Motion, and Aliasing artefacts, extends
to the diagnostic acceptability of endodontic images. A nuanced
interplay of factors, from the coronal restoration of the subject
tooth to the characteristics of adjacent teeth, tooth type, location, age, and field of view, intricately moulds the expression of
these artefacts. Yet, acknowledging the constraints of limited
resources and methodological nuances, this study calls for a
resolute shift towards future research endeavours that are prospective, objective, and comprehensive. This imperative is not just about filling knowledge gaps but about fortifying the foundations upon which we build guidelines for the judicious use of
CBCT in the dynamic landscape of endodontics.
References
- Patel S, Brown J, Pimentel T, Kelly RD, Abella F and Durack C. Cone beam computed tomography in Endodontics - a review of the literature, International endodontic journal. 2019a; 52(8): 1138-1152. doi: 10.1111/iej.13115.
- Huumonen S, Kvist T, Grondahl K and Molander A. Diagnostic value of computed tomography in re-treatment of root fillings in maxillary molars, International endodontic journal. 2006; 39(10): 827-833. doi: IEJ1157 [pii].
- Patel S, Dawood A, Mannocci F, Wilson R and Pitt Ford T. Detection of periapical bone defects in human jaws using cone beam computed tomography and intraoral radiography, International endodontic journal. 2009; 42(6): 507-515. doi: 10.1111/j.1365-2591.2008.01538.x [doi].
- Patel S, Harvey S, Shemesh H and Durack C. Cone Beam Computed Tomography in Endodontics. Berlin: Quintessenz Verlag. 2019.
- Dawood A, Patel S and Brown J. Cone beam CT in dental practice, British dental journal. 2009; 207(1): 23-28. doi: 10.1038/sj.bdj.2009.560.
- Bhatt M, Coil J, Chehroudi B, Esteves A, Aleksejuniene J, et al. Clinical decision-making and importance of the AAE/AAOMR position statement for CBCT examination in endodontic cases, International endodontic journal. 2021; 54(1): 26-37. doi: 10.1111/iej.13397.
- Patel S, Brown J, Semper M, Abella F, Mannocci F. European Society of Endodontology position statement: Use of cone beam computed tomography in Endodontics: European Society of Endodontology (ESE) developed by, International endodontic journal. 2019b; 52(12): 1675-1678. doi: 10.1111/iej.13187.
- Patel S, Wilson R, Dawood A, Mannocci F. The detection of periapical pathosis using periapical radiography and cone beam computed tomography - Part 1: pre-operative status, International endodontic journal. 2012; 45(8): 702-710. doi: 10.1111/j.1365-2591.2011.01989.x.
- Setzer FC, Hinckley N, Kohli MR, Karabucak B. A Survey of Conebeam Computed Tomographic Use among Endodontic Practitioners in the United States, Journal of endodontics. 2017; 43(5): 699-704. doi: 10.1016/j.joen.2016.12.021.
- Spin-Neto R, Mudrak J, Matzen LH, Christensen J, Gotfredsen E, et al. Cone beam CT image artefacts related to head motion simulated by a robot skull: Visual characteristics and impact on image quality Wiley-Blackwell 2013.
- Nagarajappa AK, Dwivedi N, Tiwari R. Artifacts: The downturn of CBCT image Wolters Kluwer India Pvt Ltd. 2015.
- SEDENTEXCT Guideline Development Panel Cone Beam CT for Dental and Maxillofacial Radiology (Evidence Based Guidelines). European Commission: Directorate-General for Energy, Luxembourg. 2012. http://www.manchester.ac.uk/escholar/uk-acman-scw:168864 (Accessed).
- Mozzo P, Procacci C, Tacconi A, Martini PT, Andreis IA. A new volumetric CT machine for dental imaging based on the cone-beam technique: Preliminary results, European radiology. 1998b; 8(9): 1558-1564. doi: 10.1007/s003300050586 [doi].
- Spin-Neto R and Wenzel A. Patient movement and motion artefacts in cone beam computed tomography of the dentomaxillofacial region: a systematic literature review. 2016.
- Spin-Neto R, Costa C, Salgado, Daniela M R A, Zambrana NRM, Gotfredsen E and Wenzel A. Patient movement characteristics and the impact on CBCT image quality and interpretability, Dentomaxillofacial Radiology. 2018; 47(1): 1-8. doi: 10.1259/dmfr.20170216.
- Vasconcelos KF, Nicolielo LFP, Nascimento MC, Haiter‐Neto F, Bóscolo FN, et al. Artefact expression associated with several cone-beam computed tomographic machines when imaging root filled teeth Wiley-Blackwell. 2015.
- Ritter L, Mischkowski RA, Neugebauer J, Dreiseidler T, Scheer M, et al. The influence of body mass index, age, implants, and dental restorations on image quality of cone beam computed tomography. 2009.
- Freitas DQ, Nascimento EHL, Vasconcelos TV, Noujeim M. Diagnosis of external root resorption in teeth close and distant to zirconium implants: influence of acquisition parameters and artefacts produced during cone beam computed tomography, International endodontic journal. 2019; 52(6): 866-873. doi: 10.1111/iej.13065.
- Freitas DQ, Vasconcelos TV, Noujeim M. Diagnosis of vertical root fracture in teeth close and distant to implant: An in vitro study to assess the influence of artifacts produced in cone beam computed tomography Springer Nature. 2019.
- Pauwels R, Stamatakis H, Bosman H, Bogaerts R, Jacobs R, et al. Quantification of metal artifacts on cone beam computed tomography images Wiley-Blackwell. 2013.
- Schulze R, Heil U, Gross D, Bruellmann DD, Dranischnikow E, et al. A review, England: British Institute of Radiology. 2011.
- Makins SR. Artifacts interfering with interpretation of cone beam computed tomography images, United States: ElsevierHealth Sciences Division. 2014.
- Safi Y, Fazlyab M, Asgary S, Fazlalipour M. A Novel Technique for Minimizing the Metal Artifacts on Anterior Teeth in Cone-Beam Computed Tomography, Iranian Endodontic Journal. 2019; 14(1): 79-83. doi: 10.22037/iej.v14i1.21636.