ABSTRACT
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.
ABSTRACT
The purpose of this study was to determine the prevalence, height, location and morphology of maxillary sinus septa in dentate, partially dentate and edentulous adults as well as in mixed dentition children using cone beam computed tomography [CBCT] for maxillary sinus surgical interventions. Five hundred and fifty-four sides in the CBCT scans of 272 patients [30 children and 242 adults] were retrospectively analyzed. The prevalence, location and morphology were assessed in axial, sagittal, cross-sectional and panoramic 3-dimensional images. The height of septa was measured with the angle between the direction of the septum and median palatine suture. The differences among age, localization and measurements were statistically analyzed. The prevalence of maxillary sinus segments with septa was 58%. There were a total of 13 [3.2%] septa of completely edentulous [CE], 198 [53.9%] septa of edentate and 14 [3.8%] septa of the mixed dentition maxillary segments. The location of septa observed in all study groups demonstrated a greater prevalence [69.1%] in the middle region than in the anterior and posterior regions. No statistically significant differences were observed with regard to gender or age, for septum height [p > 0.05]. However, maxillary sinus septa are higher in partially edentulous patients than edentate and CE ones [p < 0.05]. Septa of various heights and courses developed in all parts of the maxillary sinus, therefore to prevent possible complications during sinus surgery, extensive evaluation with an appropriate radiographic technique was indispensable