Objectives: To evaluate the performance of a commercially available Generative Pre-trained Transformer (GPT) in describing and establishing differential diagnoses for radiolucent lesions in panoramic radiographs. Materials and methods: Twenty-eight panoramic radiographs, each containing a single radiolucent lesion, were evaluated in consensus by three examiners and a commercially available ChatGPT-3.5 model. They provided descriptions regarding internal structure (radiodensity, loculation), periphery (margin type, cortication), shape, location (bone, side, region, teeth/structures), and effects on adjacent structures (effect, adjacent structure). Diagnostic impressions related to origin, behavior, and nature were also provided. The GPT program was additionally prompted to provide differential diagnoses. Keywords used by the GPT program were compared to those used by the examiners and scored as 0 (incorrect), 0.5 (partially correct), or 1 (correct). Mean score values and standard deviation were calculated for each description. Performance in establishing differential diagnoses was assessed using Rank-1, -2, and − 3. Results: Descriptions of margination, affected bone, and origin received the highest scores: 0.93, 0.93, and 0.87, respectively. Shape, region, teeth/structures, effect, affected region, and nature received considerably lower scores ranging from 0.22 to 0.50. Rank-1, -2, and − 3 demonstrated accuracy in 25%, 57.14%, and 67.85% of cases, respectively. Conclusion: The performance of the GPT program in describing and providing differential diagnoses for radiolucent lesions in panoramic radiographs is variable and at this stage limited in its use for clinical application. Clinical relevance: Understanding the potential role of GPT systems as an auxiliary tool in image interpretation is imperative to validate their clinical applicability.

Objectives:To assess the influence of artefacts arising from metallic materials in the exomass on cone beam CT (CBCT) voxel values.Methods:CBCT scans were taken of a phantom composed of 16 tubes filled with a homogeneous hyperdense solution and metallic materials of different compositions (titanium, cobalt–chromium and amalgam) and numbers (one, two and three). The phantom was centred in a 5 × 5 cm field of view such that the metallic materials were located in the exomass, using three CBCT units. Voxel values were obtained from the 16 homogeneous areas and averaged. Also, standard deviation was calculated to measure voxel value variability. Analysis of variance in a factorial scheme with additional treatment 3 × 3 + 3 (material × number + control) was performed, followed by Tukey’s test for multiple comparisons, and Dunnett’s test for comparisons with the control groups, at a level of significance of 5%.Results:Metallic material in the exomass significantly reduced the mean voxel value in the CS9300 and P...