Imaging Science in Dentistry最新文献

Purpose: Periarticular and generalized osteoporosis are well-known comorbidities of rheumatoid arthritis (RA), associated with either the disease itself or glucocorticoid therapy. This study was performed to quantitatively evaluate changes in the jawbones of patients with RA using fractal analysis (FA).

Materials and methods: The study comprised 186 participants, including 144 women and 42 men. Of these, 93 were patients with RA and 93 were healthy controls. For the RA group, disease duration, laboratory findings, and medication use were recorded. Measurements of fractal dimension (FD), lacunarity (Lac), bone area fraction (BA/TA), and trabecular thickness (Tb.Th) were taken at the mandibular condyle and angle. These measurements were obtained from panoramic radiographs using ImageJ version 1.52p (National Institutes of Health, Bethesda, MD, USA).

Results: Relative to control participants, patients with RA exhibited higher FD values for both mandibular condyle and angle regions (P<0.05). Conversely, the RA group displayed lower Lac values for both regions (P<0.05). Similarly, Tb.Th values were significantly lower in the RA patient group for both the condyle and the angle (P<0.05). Furthermore, a significant negative correlation was identified between disease duration and FD at the mandibular condyle (P<0.05).

Conclusion: The results demonstrate that FA can be used to quantitatively assess changes in trabecular bone in the jawbones of patients with RA. Image analysis parameters derived from panoramic radiographs, including FA, Lac, BA/TA, and Tb.Th, hold promise in guiding patients with RA toward appropriate medical examinations.

Purpose: This review aimed to explore the scientific literature concerning the methodologies and applications of artificial intelligence (AI) in the field of endodontics. The findings may equip dentists with the necessary technical knowledge to understand the opportunities presented by AI.

Materials and methods: Articles published between 1992 and 2023 were retrieved through an electronic search of Medline via the PubMed, Scopus, and Google Scholar databases. The search, which was limited to articles published in English, aimed to identify relevant studies by employing the following keywords: "artificial intelligence," "machine learning," "deep learning," "endodontic," "root canal treatment," and "radiography." Ultimately, 71 studies that addressed the application of AI in endodontics were selected.

Results: Numerous studies have demonstrated the effectiveness of AI applications in endodontics. These uses encompass the identification of root fractures and periapical lesions, assessment of working length, investigation of root canal system anatomy, prediction of retreatment success, and evaluation of dental pulp stem cell viability.

Conclusion: AI technology is poised to advance aspects of endodontics including scheduling, patient care, management of drug-drug interactions, prognostic diagnosis, and the emerging area of robotic endodontic surgery. AI methods have demonstrated accuracy and precision in the identification, assessment, and prediction of diseases. Thus, AI can significantly improve endodontic diagnosis and treatment, increasing the overall efficacy of endodontic therapy.

Purpose: The study was performed to examine the error associated with image superimposition when computed tomography (CT) images of the dental region are substituted with dental scan data, according to the block-out material used in dental impressions.

Materials and methods: A typodont model was created by bonding orthodontic brackets to teeth on plaster dental stones using melted dental base-plate wax. In the experiment, 2 groups were compared: one using wax and the other using putty as the block-out material to prevent tearing of the impression material during the acquisition of dental impressions. In the wax group, dental cast digital data were superimposed onto the CT data of the typodont model using a tooth occlusal surface-based registration method. In the putty group, a surface-based registration method was used that incorporated not only the occlusal surfaces of the teeth, but also the area where the radiopaque putty covered the orthodontic brackets. The absolute value of the error on the dental surfaces was measured for comparisons.

Results: Analysis of the scanned areas used for replacement in dental CT images revealed fewer superimposition errors when considering only the tooth occlusal surface area, excluding the area containing putty impression material.

Conclusion: The clinical recommendation is to block out the orthodontic bracket with radiolucent wax when obtaining dental impressions. Furthermore, only dental occlusal surface-based registration should be used for the superimposition and replacement of the CT image of the dental area with scanned data from a dental cast model.

Purpose: This study investigated the impact of the field of view (FOV), voxel size, and exposure parameters on the contrast-to-noise ratio (CNR) in cone-beam computed tomography (CBCT).

Materials and methods: A SedentexCT phantom was scanned using 3D Accuitomo 170 across 3 FOVs (40×40 mm, 60×60 mm, 80×80 mm). Each FOV had 4 settings for kVp and 3 for mA. Volumes were reconstructed with voxel sizes from 80 to 250 µm. The CNR was calculated using ImageJ (ver. 1.41, National Institutes of Health, Bethesda). Statistical analyses included Pearson correlation coefficients and regression (R²).

Results: Positive correlations were observed in the 40×40 FOV between voxel size, kVp, mA, rotation degree, and CNR. The 60×60 FOV showed positive correlations between mA, kVp, and CNR, while the 80×80 FOV exhibited correlations for voxel size, kVp, and mA. In the 40×40 (R²=0.551) and 80×80 (R²=0.550) FOVs, mA, kVp, and voxel size influenced CNR. For the 60×60 FOV, mA and kVp were significant contributors (R²=0.389). Using a constant 80-µm voxel size, both mA and kVp significantly influenced CNR (R²=0.467); neither FOV nor rotation degree had substantial impacts.

Conclusion: CNR increased with higher mA, kVp, and larger voxel sizes for 40×40 and 80×80 FOVs. mA was the most influential factor across all FOVs. Regression models showed significant effects of mA and kVp on CNR with 80-µm voxels, while FOV had no effect.

Purpose: This study aimed to evaluate the number of roots and type of root canals in maxillary first and second premolars within a selected Korean population utilizing cone-beam computed tomography (CBCT). Additionally, it sought to investigate potential differences in these features according to sex and tooth type.

Materials and methods: CBCT images of 585 maxillary first premolars and 578 maxillary second premolars from 303 patients were retrospectively reviewed. The number of roots was classified based on root morphology, and canal configurations were categorized into 8 types according to the Vertucci classification. For statistical analysis, chi-square or Fisher exact tests were employed to compare root number and canal morphology according to sex and tooth type.

Results: CBCT analysis revealed that 71.5% of maxillary first premolars and 97.6% of maxillary second premolars had 1 root. The most common canal configuration in maxillary first premolars was Vertucci type IV (42.6%), whereas type I predominated in maxillary second premolars (76.5%). Significant differences in root number and canal configurations were found between men and women (P<0.05), with single roots and Vertucci type I canals more commonly observed in women.

Conclusion: Both maxillary first premolars and maxillary second premolars typically had 1 root, with a smaller percentage possessing 2 roots. Significant sex differences were observed in root number and canal type. This study highlights the variability in root number and canal configuration, emphasizing the importance of recognizing these variations to achieve successful endodontic treatment.

Purpose: This study was performed to evaluate the expression of beam hardening artifacts generated by high atomic number materials in stitched cone-beam computed tomography (CBCT) images, compared to the traditional acquisition mode.

Materials and methods: CBCT volumes were acquired using an acrylic resin phantom embedded with pairs of cylinders made from amalgam dental alloy, cobalt-chromium alloy, gutta-percha, titanium, and zirconium. These cylinders were placed within the overlapping zones of the stitching reconstruction area. For each material, 3 acquisitions were conducted: 1 utilizing the automatic stitching process with a FOV of 80×37 mm, and 2 with smaller FOVs of 50×37 mm. For the smaller FOVs, 1 scan targeted the anterior region, while the other focused on the left posterior region. Thus, 3 groups were formed: stitched FOV, anterior FOV, and posterior FOV. Artifact expression was assessed by calculating the means and standard deviations (SDs) of the gray values in 4 regions of interest located anteriorly, posteriorly, medially, and laterally to the cylinders. Analysis of variance was used to compare the data, with an alpha level of 5%.

Results: The stitched FOV exhibited lower SD values than the posterior and anterior FOVs (P<0.05). Regarding the materials evaluated, amalgam, cobalt-chromium, and zirconium generally demonstrated higher SDs of the gray values than gutta-percha and titanium (P<0.05).

Conclusion: Horizontally stitched CBCT images demonstrated lower artifact expression compared to the traditional mode of acquisition.

Purpose: This study aimed to evaluate the quality of clinically indicated digital dental panoramic radiographs (DPRs) of children with mixed dentition. Despite the likely widespread use of this modality, recent research detailing errors on DPRs is scarce.

Materials and methods: A consecutive case series was performed, including 178 DPRs from patients aged 6 to 12 years. Each DPR was reviewed for 10 distinct errors. The findings were analyzed to identify potential solutions.

Results: Nearly three-quarters of the DPRs contained multiple errors. Linear regression analysis indicated that the number of errors decreased with increasing patient age; however, this trend was not statistically significant. Notably, 3 groups of errors (2 errors each) frequently appeared together on the same DPR. When similar errors were grouped, the error incidence decreased significantly with age. Both leftward head tilting and rightward head rotation were observed, likely attributable to the design of the DPR room and the door location. The inter-rater and intra-rater reliability agreements were deemed "substantial" or "almost perfect, beyond chance" for the detection of most errors, particularly the most frequent types, which involved the "chin," "tongue," and "lips-open" positions.

Conclusion: As a pediatric patient ages, the number of DPR errors decreases. The results suggest several pre-exposure strategies that could reduce the error rate. These include, monitoring for a "lips-open" position as an indicator of a potential "tongue" error (occluding the palate-glossal space), and implementing dry runs. Asymmetries observed on DPR must be documented and should prompt re-examination, as they may be genuine.

Purpose: This study was performed to introduce, evaluate, and compare various novel assessment protocols designed for straightforward, reliable, and reproducible measurement of alveolar bone levels. These protocols are intended for standardized periodontal assessment and follow-up, utilizing cone-beam computed tomography (CBCT) images and manipulation of Digital Imaging and Communications in Medicine (DICOM) viewer software.

Materials and methods: Two experienced oral and maxillofacial radiologists developed 5 distinct radiographic measurement protocols. These techniques were established to assess the alveolar bone level of a periodontally affected upper central incisor using a method that is consistently repeatable across observers. Two additional assessors, blinded to the details of the study, independently applied the protocols to retrieved DICOM files that met the eligibility criteria. A scoring system with 3 subscores was created and used to compare the protocols.

Results: Statistically excellent inter-observer reliability was observed for all protocols, other than protocol 1, which demonstrated moderate reliability. The average discrepancy between measurements taken by the 2 observers was 1.2 mm for protocol 1, 0.81 mm for protocol 2, and less than 0.5 mm for the remaining 3 protocols. All approaches except protocol 4 were straightforward to apply.

Conclusion: This study introduces multiple reliable protocols for the evaluation of periodontal bone levels that ensure consistency across observers. Based on the findings, the double axial lines and incisocrestal distance protocols are recommended. These new assessment approaches, along with any future modifications, may be useful in periodontal assessment, dental implant follow-up, orthodontic evaluation, research, and artificial intelligence model generation.

Purpose: This study aimed to evaluate the impact of a metal artifact reduction (MAR) algorithm on cone-beam computed tomography (CBCT) scans of titanium and zirconia implants, both within and outside the field of view (FOV).

Materials and methods: In this in vitro study, a dry human mandible was positioned in a CBCT scanner with only its left quadrant included in the FOV. Each type of implant (titanium and zirconia) was placed once in the right second premolar extraction socket and once in the left second premolar extraction socket of the mandible. CBCT scans were acquired with and without MAR. Three regions of interest (ROIs) were defined in relation to a resin block, and the contrast-to-noise ratio (CNR) was calculated for each ROI. Data were analyzed using 2-way analysis of variance with an alpha level of 0.05.

Results: Application of a MAR algorithm significantly increased the CNR within and outside the FOV for both implant types (P<0.05). Relative to titanium implants, zirconia implants were associated with significantly lower CNRs in both positions (P<0.05) and generated more artifacts. Implant placement outside the FOV was associated with slightly lower image quality than positioning within the FOV, although this finding was not significant (P>0.05).

Conclusion: The results suggest that application of a MAR algorithm in CBCT significantly impacts artifact generation. Titanium implants exhibited significantly lower metal artifact generation compared to zirconia implants. Positioning either implant type outside the FOV, as opposed to inside it, slightly increased artifact generation; however, this was not statistically significant.