Objectives: This study aimed to define the prevalence and characteristics of skull base anomalies and the features of sphenoid sinus pneumatization (SSP). Materials and Methods: Five hundred cone-beam computed tomography scans were evaluated retrospectively for the presence of fossa navicularis magna (FNM), canalis basilaris medianus (CBM), sphenoid emissary foramen (SEF), and/or Onodi cells (OC). Patterns of the SSP and sphenoid sinus mucosa dimensions (SSMD) were also recorded. Results: The prevalence of FNM, CBM, SEF, and OC was 26.0%, 22.4%, 47.4%, and 18.4%, respectively. Two hundred sixty-two (52.4%) sellartype SSP were defined, followed by post-sellar 191 (38.2%), pre-sellar 31 (6.2%), and conchal 16 (3.2%) types. The frequency of SSMD less than 1 mm, 1-3 mm, and greater than 3 mm was 40.6%, 38.4%, and 21.0%, respectively. An SEF was detected more frequently in females, while SSMD greater than 3 mm was more frequent in males. An FNM was more prevalent in the 18-29 and 30-39 age groups and SEF was significantly less frequent in patients over 60 years of age compared to other age groups. A sinus mucosa larger than 3 mm was more common in the younger than 18 year group. The frequency of post-sellar-type pneumatization was lower in patients younger than 18 years. Conclusion Skull-base anomalies are common and may be detected incidentally during imaging procedures. The sphenoid sinus, its variations, and pneumatization patterns should also be taken into consideration in imaging procedures performed for various purposes.

Objectives: We compared changes in fractal dimension (FD) and grayscale value (GSV) of peri-implant alveolar bone on digital panoramic radiography (DPR) and cone-beam computed tomography (CBCT) immediately after implant surgery and 12 months postoperative. Materials and Methods: In this retrospective study, 16 patients who received posterior mandibular area dental implants with CBCT scans taken about 2 weeks after implantation and one year after implantation were analyzed. A region of interest was selected for each patient. FDs and GSVs were evaluated immediately after implant surgery and at 12-month follow-up to examine the functional loading of the implants. Results: There were no significant differences between DPR and CBCT measurements of FD values (P>0.05). No significant differences were observed between FD values and GSVs calculated after implant surgery and at the 12-month follow-up (P>0.05). GSVs were not correlated with FD values (P>0.05). Conclusion The DPR and reconstructed panoramic CBCT images exhibit similar image quality for the assessment of FD. There were no changes in FD values or GSVs of the peri-implant trabecular bone structure at the 12-month postoperative evaluation of the functional loading of the implant in comparison to values immediately after implantation. GSVs representing bone mass do not align with FD values that predict bone microstructural parameters. Therefore, GSVs and FDs should be considered different parameters for assessing bone quality.

Objectives: This micro-computed tomographic (CT) study aimed to compare the shaping abilities of ProTaper Next (PTN), One Shape (OS), and One Curve (OC) files in 3-dimensionally (3D)-printed mandibular molars. Materials and Methods: In order to ensure standardization, 3D-printed mandibular molars with a consistent mesiobuccal canal curvature (45°) were used in the present study (n = 18).Specimens were instrumented with the OC, OS, or PTN files. The teeth were scanned preand post-instrumentation using micro-CT to detect changes of the canal volume and surface area, as well as to quantify transportation of the canals after instrumentation. Two-way analysis of variance was used for statistical comparisons. Results: No statistically significant differences were found between the OC and OS groups in the changes of the canal volume and surface area before and after instrumentation (p > 0.05). The OC files showed significantly less transportation than the OS or PTN systems for the apical section (p < 0.05). In a comparison of the systems, similar values were found at the coronal and middle levels, without any significant differences (p > 0.05). Conclusions These 3 instrumentation systems showed similar shaping abilities, although the OC file achieved a lesser extent of transportation in the apical zone than the OS and PTN files. All 3 file systems were confirmed to be safe for use in mandibular mesial canals.

Objectives: This micro-computed tomographic (CT) study aimed to compare the shaping abilities of ProTaper Next (PTN), One Shape (OS), and One Curve (OC) files in 3-dimensionally (3D)-printed mandibular molars. Materials and Methods: In order to ensure standardization, 3D-printed mandibular molars with a consistent mesiobuccal canal curvature (45°) were used in the present study (n = 18).Specimens were instrumented with the OC, OS, or PTN files. The teeth were scanned preand post-instrumentation using micro-CT to detect changes of the canal volume and surface area, as well as to quantify transportation of the canals after instrumentation. Two-way analysis of variance was used for statistical comparisons. Results: No statistically significant differences were found between the OC and OS groups in the changes of the canal volume and surface area before and after instrumentation (p > 0.05). The OC files showed significantly less transportation than the OS or PTN systems for the apical section (p < 0.05). In a comparison of the systems, similar values were found at the coronal and middle levels, without any significant differences (p > 0.05). Conclusions These 3 instrumentation systems showed similar shaping abilities, although the OC file achieved a lesser extent of transportation in the apical zone than the OS and PTN files. All 3 file systems were confirmed to be safe for use in mandibular mesial canals.

Purpose: This study aimed to assess texture analysis (TA) of cone-beam computed tomography (CBCT) images as a quantitative tool for the differential diagnosis of odontogenic and non-odontogenic maxillary sinusitis (OS and NOS, respectively). Materials and Methods: CBCT images of 40 patients diagnosed with OS (N=20) and NOS (N=20) were evaluated. The gray level co-occurrence (GLCM) matrix parameters, and gray level run length matrix texture (GLRLM) parameters were extracted using manually placed regions of interest on lesion images. Seven texture parameters were calculated using GLCM and 4 parameters using GLRLM. The Mann-Whitney test was used for comparisons between the groups, and the Levene test was performed to confirm the homogeneity of variance (α=5%). Results: The results showed statistically significant differences (P<0.05) between the OS and NOS patients regarding 3 TA parameters. NOS patients presented higher values for contrast, while OS patients presented higher values for correlation and inverse difference moment. Greater textural homogeneity was observed in the OS patients than in the NOS patients, with statistically significant differences in standard deviations between the groups for correlation, sum of squares, sum of entropy, and entropy. Conclusion TA enabled quantitative differentiation between OS and NOS on CBCT images by using the parameters of contrast, correlation, and inverse difference moment.

Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs (PRs), as well as to assess the appropriateness of its treatment recommendations. Materials and Methods: PRs from 100 patients (representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, includingcanal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth. Results: The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, thesensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs. Conclusion Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications.

Purpose: This study was performed to introduce an in vivo hybrid multimodality technique involving the coregistration of micro-computed tomography (micro-CT) and high-resolution magnetic resonance imaging (HR-MRI) to concomitantly visualize and quantify mineralization and vascularization at follow-up in a rat model. Materials and Methods: Three adult female rats were randomly assigned as test subjects, with 1 rat serving as a control subject. For 20 weeks, the test rats received a weekly intravenous injection of 30 μg/kg zoledronic acid, and the control rat was administered a similar dose of normal saline. Bilateral extraction of the lower first and second molarswas performed after 10 weeks. All rats were scanned once every 4 weeks with both micro-CT and HR-MRI. Micro-CT and HR-MRI images were registered and fused in the same 3-dimensional region to quantify blood flow velocity and trabecular bone thickness at T0 (baseline), T4 (4 weeks), T8 (8 weeks), T12 (12 weeks), T16 (16 weeks), and T20 (20 weeks). Histological assessment was the gold standard with which the findings were compared. Results: The histomorphometric images at T20 aligned with the HR-MRI findings, with both test and control rats demonstrating reduced trabecular bone vasculature and blood vessel density. The micro-CT findings were also consistent with the histomorphometric changes, which revealed that the test rats had thicker trabecular bone and smaller marrow spaces than the control rat. Conclusion The combination of micro-CT and HR-MRI may be considered a powerful non-invasive novel technique for the longitudinal quantification of localized mineralization and vascularization.