Quantitative analysis of metal artifact reduction using the auto-edge counting method in cone-beam computed tomography

Phantom study for CT artifacts of dental titanium implants and zirconia upper structures: the effects of occlusal plane angle setting and SEMAR algorithm

OBJECTIVES

The single-energy metal artifact reduction (SEMAR) algorithm effectively reduces metal artifacts in computed tomography (CT). The study aimed to evaluate the effect of the occlusal plane angle on metal artifacts caused by dental implants and zirconia upper structures, and the effectiveness of SEMAR for CT prognostic evaluation.

METHODS

Part of a bovine rib was used as the mandibular implant phantom. First, the phantom immersed in a water tank was scanned using CT to obtain the control image under certain conditions. Subsequently, three titanium implant bodies were implanted in a straight line into the phantom, and a zirconia superstructure was attached. CT scans were performed. The CT-reconstructed images were obtained with and without SEMAR processing. Twelve regions of interest (ROIs) were set at the same site on each sagittal image, and the CT values were measured at all the ROIs. The CT values of the ROIs in the control images and those of the ROIs with and without SEMAR were compared.

RESULTS

The variations in the occlusal plane angle during CT imaging negligibly affected the number of regions in which metal artifacts appeared. SEMAR improved the CT value of the trabecular bone, which was affected by metal artifacts.

CONCLUSION

This study showed that the occlusal plane angle occasionally did not affect the area of metal artifacts caused by dental implants or zirconia upper structures. Other results indicate that SEMAR is effective for accurately evaluating the alveolar bone around the implant body by reducing metal artifacts.

Introducing a new auto edge detection technique capable of revealing cervical root resorption in CBCT scans with pronounced metallic artifacts

Cervical resorption is a serious threat to the longevity of the teeth. In this study, the Canny edge-detection algorithm was applied on CBCT images to compare the accuracy of original and Canny views for diagnosing cervical resorption in endodontically treated teeth. Intracanal metallic posts were inserted in 60 extracted teeth being randomly divided into three groups: control, 0.5 mm, and 1 mm cervical resorption. CBCT scans of the teeth were presented to three observers in both original and Canny formats with the accuracy being determined by receiver operating characteristic (ROC) analysis. The DeLong test was used for paired comparisons with the significance level set at 0.05. The highest accuracy belonged to Canny images in 1 mm resorption, followed by Canny images in 0.5 mm resorption, original images in 1 mm resorption, and original images in 0.5 mm resorption, respectively. The Canny images were significantly more accurate in the diagnosis of 0.5 mm (p < 0.001) and 1 mm (p = 0.009) resorption. Application of the Canny edge-detection algorithm could be suggested as a new technique for facilitating the diagnosis of cervical resorption in teeth that are negatively affected by metallic artifacts.

Digital measuring the ocular morphological parameters of guinea pig eye in vivo with Python

AIM

To quantitatively measure ocular morphological parameters of guinea pig with Python technology.

METHODS

Thirty-six eyeballs of eighteen 3-week-old guinea pigs were measured with keratometer and photographed to obtain the horizontal, coronal, and sagittal planes respectively. The corresponding photo pixels-actual length ratio was acquired by a proportional scale. The edge coordinates were identified artificially by ginput function. Circle and conic curve fitting were applied to fit the contour of the eyeball in the sagittal, coronal and horizontal view. The curvature, curvature radius, eccentricity, tilt angle, corneal diameter, and binocular separation angle were calculated according to the geometric principles. Next, the eyeballs were removed, canny edge detection was applied to identify the contour of eyeball in vitro. The results were compared between in vivo and in vitro.

RESULTS

Regarding the corneal curvature and curvature radius on the horizontal and sagittal planes, no significant differences were observed among results in vivo, in vitro, and the keratometer. The horizontal and vertical binocular separation angles were 130.6°±6.39° and 129.8°±9.58° respectively. For the corneal curvature radius and eccentricity in vivo, significant differences were observed between horizontal and vertical planes.

CONCLUSION

The Graphical interface window of Python makes up the deficiency of edge detection, which requires too much definition in Matlab. There are significant differences between guinea pig and human beings, such as exotropic eye position, oblique oval eyeball, and obvious discrepancy of binoculus. This study helps evaluate objectively the ocular morphological parameters of small experimental animals in emmetropization research.

A Quantitative Evaluation of the Effectiveness of the Metal Artifact Reduction Algorithm in Cone Beam Computed Tomographic Images with Stainless Steel Orthodontic Brackets and Arch Wires: An Ex Vivo Study

The presence of high-density and high-atomic number materials results in the generation of artifacts in cone beam computed tomographic (CBCT) images. To minimize artifacts in CBCT images, the metal artifact reduction (MAR) tool was developed. This study aims to quantitatively evaluate the effectiveness of the MAR algorithm in CBCT images of teeth with stainless steel orthodontic brackets with or without arch wires in buccal and lingual positions obtained using the Galileos Sirona CBCT scanner. In this in vitro study, 20 stainless steel brackets were attached to the maxillary dentition from the right second premolar to the left second premolar teeth of a human skull. In the first group, 10 brackets were bonded to the buccal surface, and in the second group, 10 brackets were bonded to the palatal surface of these teeth. CBCT scans were obtained for each group with or without orthodontic stainless steel wires using a Galileos Sirona CBCT scanner with exposure parameters of 85 kVp and 21 mAs. CBCT images were obtained two times with and two times without MAR activation. The DICOM format of the CBCT images was imported to ImageJ software (version 1.54), and the contrast-to-noise ratio (CNR) was calculated and compared for each bracket in 15 and 20 mm distances and 20, 40, and 90 degrees on each side. Statistical analysis was performed using the t test (α = 0.05). CNR values of different distances and different teeth were not significantly different between the two MAR modes (p > 0.05). MAR activation had a significant impact in increasing CNR and reducing artifacts only when brackets were in palatal (p = 0.03). In the other bracket and wire positions, the effect of the MAR algorithm on CNR was not significant (p > 0.05). In conclusion, MAR activation significantly increased CNR, but only when the brackets were in a palatal position. In the other bracket and wire positions, the effect of the MAR algorithm is not significant.

Quantitative assessment of image artifacts from zygoma implants on CBCT scans using different exposure parameters

This study was aimed at quantifying artifacts from zygoma implants in cone-beam computed tomography (CBCT) images using different exposure parameters. Two cadaver heads, one with two zygoma implants on each side and the other for control, were scanned using 18 different exposure parameters. Quantitative analysis was performed to evaluate the hypodense and hyperdense artifact percentages calculated as the percentage of the area. Hyperdense artifacts and hypodense artifacts were detected, followed by the calculation of the hyperdense and hypodense artifact percentages in the image. In the qualitative analysis of the artifacts, the scores used were as follows: absence (0), moderate presence (1), or high presence (2) for hypodense halos, thin hypodense lines, and hyperdense lines. Artifact analysis was performed qualitatively and quantitatively using the post-hoc Tukey and Two-way ANOVA tests. As a result, in the qualitative analyses, zygoma implants showed a significant difference compared to the control group with regard to hyperdense and hypodense artifacts (p < 0.05). There was a significant difference between the means according to the FOV size arithmetic averages (p < 0.05). In terms of voxel size, the difference was found to be significant, where 400 microns showed the highest hypodense artifact while 200 microns showed the lowest hypodense artifact. In conclusion, hypodense and hyperdense artifacts were significantly higher in cadavers with zygoma implants than in controls. As FOV and voxel size increase, more hypodense artifacts are produced by zygoma implants so smaller FOV and voxel sizes should be used to prevent poor image quality of adjacent teeth.

Deep learning synthesis of cone-beam computed tomography from zero echo time magnetic resonance imaging

Cone-beam computed tomography (CBCT) produces high-resolution of hard tissue even in small voxel size, but the process is associated with radiation exposure and poor soft tissue imaging. Thus, we synthesized a CBCT image from the magnetic resonance imaging (MRI), using deep learning and to assess its clinical accuracy. We collected patients who underwent both CBCT and MRI simultaneously in our institution (Seoul). MRI data were registered with CBCT data, and both data were prepared into 512 slices of axial, sagittal, and coronal sections. A deep learning-based synthesis model was trained and the output data were evaluated by comparing the original and synthetic CBCT (syCBCT). According to expert evaluation, syCBCT images showed better performance in terms of artifacts and noise criteria but had poor resolution compared to the original CBCT images. In syCBCT, hard tissue showed better clarity with significantly different MAE and SSIM. This study result would be a basis for replacing CBCT with non-radiation imaging that would be helpful for patients planning to undergo both MRI and CBCT.

A diagnostic accuracy study on an innovative auto-edge detection technique for identifying simulated implant fractures on radiographic images

Implant fracture is a rare but devastating complication of treatment in partially or fully edentulous patients which requires prompt diagnosis. Nevertheless, studies on defining the most accurate technique for the detection of implant fractures are lacking. In the present study, the Canny edge detection algorithm was applied on multiple radiographic modalities including parallel periapical (PPA), oblique periapical (OPA), and cone beam CT (CBCT) with and without metal artifact reduction (MAR) to examine its accuracy for diagnosis of simulated implant fractures. Radiographs were taken from 24 intact implants and 24 implants with artificially created fractures. Images were evaluated in their original and Canny formats. The accuracy of each radiograph was assessed by comparison with a reference standard of direct observation of the implant. The greatest area under the receiver operating characteristic curve belonged to Canny CBCT with MAR (0.958), followed by original CBCT with MAR (0.917), original CBCT without MAR = Canny CBCT without MAR = Canny OPA (0.875), Canny PPA (0.833), original PPA = original OPA (0.792), respectively. The Canny edge detection algorithm is suggested as an innovative method for accurate diagnosis of clinically suspected implant fractures on CBCT and periapical radiographies.

Endodontic treatment of various palatal root in maxillary molars: Case series and clinical experience

BACKGROUND AND OVERVIEW

The purpose of this article is to present the variations in maxillary molar palatal root canals and provide a reference for the possible variations in root canal treatment.

CASE DESCRIPTION

Five rare cases with palatal canal variation presented in this case series received nonsurgical endodontic treatment successfully. These case reports highlight that understanding and managing the different types of canal configurations in palatal roots of maxillary molars is essential to successful root canal treatment. We tried 2 methods of examining the palatal canal variation to provide examples for clinicians in diagnosing and treating similar cases.

CONCLUSIONS AND PRACTICAL IMPLICATIONS

The outline form of the access cavity and the shape of the pulp chamber floor are important factors for identifying variations in root canal number. Moreover, cone-beam computed tomography can help in detecting variations in root canals.

Accuracy of digital model generated from CT data with metal artifact reduction algorithm

This study investigated whether metal artifact reduction (MAR) applied computed tomography (CT) scans could be used to generate precise digital models and explored possible correlations between the amount of metal artifact and model accuracy. Thirty maxillofacial CT scans were randomly selected and a MAR algorithm was applied. By subtracting the original and MAR-applied CT images, the amount of metal artifact was quantified. Digital models were generated from the original and the MAR-applied CT data. Paired digital models were superimposed and shape deviation in planar surface was measured at 10 points in 4 planes. Statistical analyses were performed to compare deviations and to assess correlations between the amount of artifact and deviation. The MAR algorithm reduced metal artifact in all cases. The overall mean deviation of the MAR-applied models was 0.0868 mm, with no significant difference according to the reference plane. The amount of artifact did not significantly influence the accuracy of the digital models. MAR-applied CT is a convenient source for digital modeling with clinically acceptable accuracy. The MAR algorithm can be used regardless of the amount of metal artifact, which are generated by dental prostheses, for the quick and convenient manipulation of dental digital models.

Application of an auto-edge counting method for quantification of metal artifacts in CBCT images: a multivariate analysis of object position, field of view size, tube voltage, and metal artifact reduction algorithm

OBJECTIVE

The objective was to assess the effects of object position, field of view (FOV) size, peak kilovoltage (kVp), and a metal artifact reduction (MAR) algorithm on metal artifacts in cone beam computed tomography (CBCT) as measured with an auto-edge counting method.

STUDY DESIGN

A titanium implant and a stainless steel intracanal post in a root were inserted in bovine rib blocks. CBCT scans were acquired with changes in object position (incisor, canine, and premolar-molar areas), FOV, kVp, and MAR (on or off) mode. Images were quantitatively analyzed in MATLAB by using the Canny edge detection algorithm. Four-way analysis of variance and Tukey tests were applied for data analysis.

RESULTS

The implant produced no significant differences in number of artifacts among the object positions through changing the kVp and MAR mode for all FOV sizes (P > .05). The intracanal post scanned with the medium-sized FOV, high kVp, and MAR off mode generated significant differences among object positions (P = .033). Among the variables assessed, FOV size and MAR mode had a significant influence on the number of artifacts (P ≤ .039).

CONCLUSION

Reduction of FOV size and application of the MAR tool significantly decreased the number of streak artifacts. The Canny edge detection algorithm could be an efficient method of metal artifact quantification.