Performance of a commercially available Generative Pre-trained Transformer (GPT) in describing radiolucent lesions in panoramic radiographs and establishing differential diagnoses.

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.

Mapping artifacts generated in a tooth adjacent to titanium and zirconia implants located in the endomass and exomass in cone beam computed tomography: an ex vivo study.

OBJECTIVE: We evaluated artifact expression in a root adjacent to a dental implant located in the endomass or exomass in cone beam computed tomography (CBCT). STUDY DESIGN: We placed a single titanium or zirconia implant adjacent to a premolar root in a dried human mandible and acquired CBCT scans using an OP300 Maxio and a Picasso Trio 3D unit exposing a 5x5cm field of view with the implant in the endomass or exomass (implant groups) or without an implant (control group). We measured the mean gray values (MGVs) for 8 lines of interest (LOIs) around the root canal of the premolar and compared the MGVs by analysis of variance, with significance established at P < 0.05. RESULTS: For the OP300 Maxio scans, the MGVs of both implant groups in the endomass were lower than the MGVs of the control group. In the exomass, the titanium group had MGVs similar to the control group, but the zirconia group produced significantly lower MGVs than control and titanium groups (P <.0001), indicating the presence of hypodense artifacts. For the Picasso Trio 3D scans, the MGVs of both implant groups in the endomass were similar to the MGVs of the control group. In the exomass, the zirconia group generated lower MGVs than control and titanium groups (P <.0001), indicating hypodense artifacts. CONCLUSIONS: When performing CBCT examination, titanium implants produce less artifact expression in the exomass, and zirconia implants have less artifact expression in the endomass.

Does low bone mineral density have an association with head and neck soft tissue calcifications?

OBJECTIVES: To evaluate whether low bone mineral density (BMD) has an association with the presence of head and neck soft tissue calcifications (STC), aging, and impaired mandibular canal cortices visibility. MATERIALS AND METHODS: Panoramic radiographs of 1000 women aged between 50 and 75 years old were evaluated by two examiners to classify BMD using mandibular cortical index (C1- normal, C2-moderately eroded and C3-severely eroded), the presence of STC, and also the mandibular canal cortices visibility at the ramus region. Chi-square test evaluated the association between the variables (α = 5%). RESULTS: There was no association between bone loss and the presence of head and neck soft tissue calcifications, except for calcified thyroid cartilage, which was less visualized at C3 group than others (p < 0.05). Women aged 61 to 70 years old presented higher bone loss than those between 50 and 60 (p < 0.05). The mandibular canal was more poorly visualized at C3 group than C1 and C2 (p < 0.05). CONCLUSIONS: In general, no association between BMD and the presence of STC was found. However, greater bone loss had a positive correlation with aging and impaired mandibular canal cortices visibility. CLINICAL RELEVANCE: No relationship between bone mineral density and the existence of soft tissue calcifications was found. Nevertheless, increased bone loss was positively associated with aging and a reduced mandibular canal cortices visibility. This finding highlights the clinical importance of considering bone density factors when planning treatment strategies for patients with related disorders.