Purpose: The aim of this study was to objectively detect simulated tooth ankylosis using a novel method involving cone-beam computed tomography (CBCT). Materials and Methods: Tooth ankylosis was simulated in single-rooted human permanent teeth, and CBCT scans were acquired at different current levels (5, 6.3, and 8 mA) and voxel sizes (0.08, 0.125, and 0.2). In axial reconstructions, a line of interest was perpendicularly placed over the periodontal ligament space of 21 ankylosed and 21 non-ankylosed regions, and the CBCT grey values of all voxels along the line of interest were plotted against their corresponding X-coordinates through a line graph to generate a profile. The image contrast was increased by 30% and 60% and the profile assessment was repeated. The internal area of the resulting parabolas was obtained from all images and compared between ankylosed and non-ankylosed regions under different contrast enhancement conditions, voxel sizes, and mA levels using multi-way analysis of variance with the Tukey post hoc test (α=0.05). Results: The internal area of the parabolas of all non-ankylosed regions was significantly higher than that of the ankylosed regions (P<0.05). Contrast enhancement led to a significantly greater internal area of the parabolas of non-ankylosed regions (P<0.05). Overall, voxel size and mA did not significantly influence the internal area of the parabolas (P>0.05). Conclusion The proposed novel method revealed a relevant degree of applicability in the detection of simulated tooth ankylosis; increased image contrast led to greater detectability.

Purpose: The aim of this study was to assess the influence of kilovoltage- peak (kVp) and the metal artifact reduction (MAR) tool on the detection of buccal and lingual peri-implant dehiscence in the presence of titanium-zirconia (Ti-Zr) and zirconia (Zr) implants in cone-beam computed tomography (CBCT) images. Materials and Methods: Twenty implant sites were created in the posterior region of human mandibles, including control sites (without dehiscence) and experimental sites (with dehiscence). Individually, a Ti-Zr or Zr implant was placed in each implant site. CBCT scans were performed using a Picasso Trio device, with variation in the kVp setting (70 or 90 kVp) and whether the MAR tool was used. Three oral radiologists scored the detection of dehiscence using a 5-point scale. The area under the receiver operating characteristic (ROC) curve, sensitivity, and specificity were calculated and compared by multi-way analysis of variance (α= 0.05). Results: The kVp, cortical plate involved (buccal or lingual cortices), and MAR did not influence any diagnostic values (P>0.05). The material of the implant did not influence the ROC curve values (P>0.05). In contrast, the sensitivity and specificity were statistically significantly influenced by the implant material (P<0.05) with Zr implants showing higher sensitivity values and lower specificity values than Ti-Zr implants. Conclusion The detection of peri-implant dehiscence was not influenced by kVp, use of the MAR tool, or the cortical plate. Greater sensitivity and lower specificity were shown for the detection of peri-implant dehiscence in the presence of a Zr implant.