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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 34  |  Issue : 4  |  Page : 428-431

Prevalence of artifacts in cone-beam computed tomography: A retrospective study


Department of Oral Medicine and Radiology, JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, Karnataka, India

Date of Submission09-May-2022
Date of Decision09-Sep-2022
Date of Acceptance16-Nov-2022
Date of Web Publication09-Dec-2022

Correspondence Address:
K P Mahesh
Department of Oral Medicine and Radiology, JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore - 570 015, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jiaomr.jiaomr_142_22

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   Abstract 


Introduction: In dentistry, cone-beam computed tomography (CBCT) is an essential diagnostic technique. To use CBCT imaging technology efficiently, it is vital to understand its benefits and limits. Artifacts are discrepancies between the reconstructed visual image and the actual content of the subject that can reduce anatomic accuracy. Aims and Objectives: This study aimed to assess the prevalence of artifacts in CBCT images. Materials and Methods: Three hundred sixty-five CBCT images were retrospectively studied to identify artifacts, and the prevalence of different artifacts was recorded. Frequency and percentages are used for descriptive statistics. The Chi-square test was used for interventional statistics. Results: Artifacts were observed in two hundred forty-five images examined. The most prevalent image artifact recorded was the beam hardening artifact that falls under the physics-based category. Conclusion: Physics-based and scanner-based artifacts may be avoided by concentrating on X-ray parameters and scanner detector state, respectively. To limit the frequency of patient-based artifacts in CBCT images, patients should be instructed to remove any metallic jewelry and be stabilized appropriately. Scan time should be maintained to a minimum.

Keywords: Artifacts, cone-beam computed tomography, metal artifact, noise


How to cite this article:
Mahesh K P, Deshpande P, Viveka S. Prevalence of artifacts in cone-beam computed tomography: A retrospective study. J Indian Acad Oral Med Radiol 2022;34:428-31

How to cite this URL:
Mahesh K P, Deshpande P, Viveka S. Prevalence of artifacts in cone-beam computed tomography: A retrospective study. J Indian Acad Oral Med Radiol [serial online] 2022 [cited 2023 Jan 28];34:428-31. Available from: http://www.jiaomr.in/text.asp?2022/34/4/428/363014




   Introduction Top


Cone-beam computed tomography (CBCT) is becoming a standard for diagnostic procedures because it produces excellent high-resolution, three-dimensional images of oral bony structures.[1] The required radiation dose for CBCT is lower than that of computed tomography (CT) if we consider images made for the same purposes.[2]

Although CBCT can provide three-dimensional images such as those obtained using conventional CT, it is more susceptible to artifacts due to its low radiation dose and cone-shaped X-ray source. Artifacts in radiographic imaging are discrepancies between the reconstructed visual image and the actual content of the subject being studied.[3] Furthermore, structures that do not exist in the subject may appear within images.[4] Artifacts in CBCT are divided into three main categories, physics-based, patient-based, and scanner-based. Physics-based artifacts result from the physical processes involved in acquiring CBCT data. Patient-based artifacts occur due to factors related to the patient's form or function. Scanner-based artifacts result from imperfections in scanner operation.


   Methodology Top


Very few studies focus on the different types of artifacts identified in CBCT, the incidence of various artifacts, and how they can be minimized. The aims and objectives of our study are to assess the prevalence of different artifacts, identify their source, and be familiar with their characteristic appearances to enhance the extraction of diagnostic information from cone beam images, so that repeated exposure of the patient can be avoided.

Materials and methods

The protocol was approved by the Institutional Human Ethics Committee [JSSDCH IEC Research Protocol No. 29/2021 dated 13-12-2021). CBCT images satisfying the eligibility criteria were procured from the Department of Oral Medicine and Radiology. The study lasted 4 months, from January 2022 to April 2022. The images of 365 subjects who had undergone CBCT examination for preoperative assessment, treatment planning, and post-operative assessment were included. The CBCT images taken from April 2021 to April 2022, were retrieved from archival records. CBCT images were obtained using Planmeca ProMax 3D Mid. Volumetric images were acquired using the large-, medium-, and small-field view modes. Exposure parameters were 90 kV and 6 mA. A 360° scan was obtained, the total scan time was 18–26 s, and the reconstruction time of the volumetric images was approximately 15 s. The voxel size was 0.08 mm.

The formula used to determine the sample size was

Quantitative variable (mean): N = Z1-α/22 s2/E2

N = sample size in each group

Z = the z-score corresponding to the degree of confidence

S = standard deviation

α = level of significance

E = estimated error

CBCT images were evaluated in coronal, axial, and sagittal views for analyzing the prevalence of various artifacts and were classified into three major types identifying the source of artifacts [Figure 1]. The data were subjected to statistical analysis.
Figure 1: Classification of artifacts based on source

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Beam hardening artifacts: dark streaks and bands between dense objects in an image. Appear as dark bands or streaks in the adjacent areas to high-density structures.

Noise: grainy appearance on cross-sectional imaging.

Partial volume artifact: some of the cone beam data penetrating portions of the object other than the region-of-interest [ROI] are missing. When the entire volume is not covered by the detector, shading artifacts can be visualized.

Metal artifacts: appear as linear radiopacities emitted from a metallic material.

Motion artifacts: double or un-sharpness of bony contours.

Ring artifacts: These artifacts typically present as circular or concentric rings centered on the location of the axis of rotation.

Statistical analysis

The data obtained were tabulated and analyzed using the SPSS 22.0 software. Descriptive statistics and a Chi-square test were performed. P value <0.05 is statistically significant.


   Results Top


This study examined CBCT images of 365 subjects of both genders (male = 188, female = 177) [Table 1].
Table 1: Prevalence of artifacts in gender

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Among 365 images, artifacts were detected in 67.1% of images. The most prevalent artifact was beam hardening artifact 31.8% (n = 116) followed by noise 19.5% (71%), both of which fall under the physics-based artifact category. The partial volume, which falls under the physics-based category, was found in 33% (n = 33). Under the patient-based type, the most prevalent was metal artifact 13.2% (n = 48), followed by motion artifact 20 (5.5%). Our study encountered scanner-based ring artifacts in 0.8% (n = 3) [Table 2].
Table 2: Prevalence of different types of artifacts

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   Discussion Top


CBCT is an imaging technique in dentistry with diagnostic accuracy. Therefore, it is important to fully understand the limitations or drawbacks of CBCT imaging to achieve the full benefits of this technique. Four criteria may describe basic image quality characteristics: spatial resolution, contrast, noise, and artifacts. Artifact is any distortion or error in the image unrelated to the (tissues/organs of the) subject being studied. Artifacts can be categorized based on their purpose [Figure 1].

Noise is defined as an undesirable, nonrandomly distributed signal disruption that tends to hide the signal's information content from the observer. Noise reduces the contrast resolution of CBCT images, making it harder to distinguish low-density tissues and limiting the ability to segment accurately.

Beam hardening manifests as two different artifacts within the reconstructed image, a cupping artifact, and the appearance of dark bands or streaks.[5] Due to the increased quantity of material the beam must penetrate, X-rays passing through the center of a large object become harder than those passing through the object's edges, causing cupping artifacts. The resulting profile of the linear attenuation coefficients appears like a “cup” because the beam becomes harder at the object's center. When a uniform cylindrical object is imaged, the cupping effect artifact is evident. Dark streaks and bands between dense objects in an image are the second forms of beam hardening phenomenon.[6] This type of artifact can be detected in dental imaging between two implants in the same jaw near each other. Metal artifact reduction (MAR) programs for CBCT devices have recently been developed. The MAR algorithm was created to minimize the artifacts caused by metals. This removes voxels that are too high or too low gray values and reconstructs the region until its values match those of surrounding voxels.[7],[8] Artificial intelligence in CBCT imaging is evolving; however, currently, there is no proposed algorithm for its application in metal artifact reduction.

Partial volume artifact occurs because some of the cone beam data penetrating portions of the object other than the region-of-interest (ROI) are missing because of the insufficient size of the detector. When the entire volume is not covered by the detector, shading artifacts can be visualized.

Metal items in the scan field can result in significant streaking artifacts.[1] They arise when the density of the metal exceeds the typical range that the computer can handle, resulting in incomplete attenuation profiles. This artifact can be caused by metallic items such as dental restorations, surgical plates, dental implants and pins, and radiographic markers.

Patient motion can cause misregistration artifacts within the image. Motion artifacts may appear as strip-like ring patterns, double contours, and unsharpened images, depending on the type and nature of the movement. If an object moves during the scanning phase, the reconstruction does not account for that movement because no movement information is included in the reconstruction process.

A study by Akay et al.[9] concluded that artifacts were present in 585 out of 600 images, which is the highest compared to other studies.

Beam hardening or streak artifacts [Figure 2]a constituted 67.1% of the total artifacts in our study. Beam hardening artifacts are caused by the beam's preferential absorption of low-energy photons, with the effects being stronger in areas with more attenuation.[10],[11] Siewerdsen et al.[12] tested anti-scatter grids in a linear accelerator-coupled CBCT system and discovered that image quality improved only in high-scatter situations, such as with large field of view covering a large anatomic site or in input quantum-limited situations, such as with high-dose or low spatial resolution. Antiscatter grids enhance soft tissue contrast and artifacts to some extent; however, they also increase noise, reducing the overall image quality.
Figure 2: (a) Beam hardening artifact appears as streaks and dark bands. (b) Noise appears as a grainy image. (c) Partial volume artifact

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In CBCT imaging, noise is one of the most prevalent artifacts. In research by Syam et al., 10 out of 42 (23.81%) CBCT images were affected by noise artifacts [Figure 2]b; however, in our investigation, we found noise in 71 out of 365 images (19.5%). Noise is considerable in CBCT devices due to the lower mA utilized and the large quantity of dispersed radiation due to the lack of post-patient collimation.

Partial volume artifacts were reported by Syam et al.[10] at a rate of 14.29%, compared to 9.0% in our study [Figure 2]c. Currently, methods attempt to address this issue by calculating the remaining linear attenuation coefficients for regions that have yet to be entirely scanned.[13]

In their study, Kim et al.[7] found that 28.5% had metal artifacts, whereas, in our study, metal artifacts were detected in 13.2% of images. Before scanning, patients are usually advised to remove any detachable metal items, such as jewelry [Figure 3]a. When scanning the required anatomy without including metal items is impractical, increasing technology, particularly kilovoltage, may assist in penetrating some objects, and employing thin sections will lessen the contribution due to partial volume artifact.
Figure 3: (a) Metal artifacts: appear as linear radiopacities emitted from the metal jewelry. (b) Motion artifact appears as double or un-sharpness of bony contours. (c) Ring artifact appears as concentric rings around the axis of rotation

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Joseph and Spital[14] concluded that motion artifacts accounted for 15% of the repeated images; however, in our analysis, they accounted for 13.2%. Fast scanning, gating, tube alignment, corrective reconstruction, or post-processing of scans can help to avoid these artifacts that have a negative impact on image quality.[15] Patient-based motion artifacts accounted for 5.5% of our study [Figure 3]b. Bhagia et al.[16] concluded that excessive anxiety had been demonstrated to influence motion artifacts produced during CBCT imaging. As a result, it is advised that an attempt should be made to make the patient comfortable and minimize anxiety before CBCT imaging to avoid re-exposure to radiation.

Joseph reported that 6% of artifacts were related to the scanner and incorrect calibrations, and in our study, 0.8% were detected. Scanner-related artifacts have been widespread, particularly those resulting from detector measurement mistakes or imbalances. When a detector's intercalibration is not precise, the back projection of each ring varies, resulting in ring-shaped artifacts [Figure 3]c. Repair and good preventative maintenance can fix these issues.[17]

Limitations

Despite having major strengths, our study exhibits some limitations. All images in our study were taken using the same CBCT machine. We cannot generalize our findings to other CBCT scanners. The patient's perception of CBCT differs by geographical location and age. Therefore, this is most likely one of the reasons for the variance in results between different studies.

Future prospects

Future efforts should focus on shortening scan time, including soft tissue contrast, incorporating task-specific protocols to reduce patient dose, and incorporating artifact reduction software to improve image quality.


   Conclusion Top


Artifacts originate from various sources and can degrade the quality of CBCT images to varying degrees. However, there are many instances where careful patient positioning and the optimum selection of scan parameters are the most important factors in avoiding image artifacts. For a radiologist, it is important to understand the cause, recognize and diagnose the faults and artifacts in the image, and thus prevent their occurrence in subsequent images.

Key message

Understanding the cause of various artifacts' occurrence will help us minimize them.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Jaju P, Jain M, Singh A, Gupta A. Artefacts in cone beam CT. Open J Stomatol 2013;3:292-7.  Back to cited text no. 1
    
2.
Sinha A, Mishra A, Srivastava S, Sinha PM, Chaurasia A. Understanding artifacts in cone beam computed tomography. IP Int J Maxillofac Imaging 2016;2:51-4.  Back to cited text no. 2
    
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Nardi C, Borri C, Regini F, Calistri L, Castellani A, Lorini C, et al. Metal and motion artifacts by cone beam computed tomography (CBCT) in the dental and maxillofacial study. Radiol Med 2015;120:618-26.  Back to cited text no. 3
    
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Schulze R, Heil U, Gross D, Bruellmann DD, Dranischnikow E, Schwanecke U, et al. Artefacts in CBCT: A review. Dentomaxillofac Radiol 2011;40:265-73.  Back to cited text no. 4
    
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Miracle AC, Mukherji SK. Conebeam CT of the head and neck, part 1: Physical principles. AJNR Am J Neuroradiol 2009;30:1088-95.  Back to cited text no. 5
    
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Barrett JF, Keat N. Artifacts in CT: Recognition and avoidance. Radiographics 2004;24:1679-91.  Back to cited text no. 6
    
7.
Kim YH, Lee C, Han SS, Jeon KJ, Choi YJ, Lee A. Quantitative analysis of metal artifact reduction using the auto-edge counting method in cone-beam computed tomography. Sci Rep 2020;10:8872.  Back to cited text no. 7
    
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Johari M, Abdollahzadeh M, Esmaeili F, Sakhamanesh V. Metal artifact suppression in dental cone beam computed tomography images using image processing techniques. J Med Signals Sens 2018;8:12-24.  Back to cited text no. 8
[PUBMED]  [Full text]  
9.
Akay G, Sait Karatas M, Karadag O, Ucok, O, Gungor K. The incidence of artifacts in cone beam computed tomography images: A pilot study. Ann Med Res 2021;26:2581-6.  Back to cited text no. 9
    
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Syam S, Maheswari TN. Artifacts in cone beam computed tomography – A retrospective study. J Pharm Sci Res 2019;11:1914-7.  Back to cited text no. 10
    
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Esmaeili F, Johari M, Haddadi P, Vatankhah M. Beam hardening artifacts: Comparison between two cone beam computed tomography scanners. J Dent Res Dent Clin Dent Prospects 2012;6:49-53.  Back to cited text no. 11
    
12.
Siewerdsen JH, Moseley DJ, Bakhtiar B, Richard S, Jaffray DA. The influence of anti-scatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors. Med Phys 2004;31:3506-20.  Back to cited text no. 12
    
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Kim JH, Arita ES, Pinheiro LR, Yoshimoto M, Watanabe PCA, Cortes ARG. Computed tomographic artifacts in maxillofacial surgery. J Craniofac Surg 2018;29:78-80.  Back to cited text no. 13
    
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Joseph PM, Spital RD. The exponential edge-gradient effect in x-ray computed tomography. Phys Med Biol 1981;26:473-87.  Back to cited text no. 14
    
15.
Ludlow JB, Timothy R, Walker C, Hunter R, Benavides E, Samuelson DB, et al. Effective dose of dental CBCT—A meta-analysis of published data and additional data for nine CBCT units. Dentomaxillofac Radiol 2015;44:20140197.  Back to cited text no. 15
    
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Bhagia P, Menon I, Puri N, Arora V, Goyal J, Ashraf A. Effect of dental anxiety on motion artefacts in CBCT imaging amongst adult patients of Muradnagar, Ghaziabad. Int J Adv Sci Technol 2020;29:2601-8.  Back to cited text no. 16
    
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Nagarajappa AK, Dwivedi N, Tiwari R. Artifacts: The downturn of CBCT image. J Int Soc Prevent Communit Dent 2015;5:440-5.  Back to cited text no. 17
[PUBMED]  [Full text]  


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2]



 

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