Jaime Orejas-Pérez

Background/Objectives: The increasing use of digital manufacturing techniques in prosthodontics has raised concerns regarding the long-term esthetic performance of provisional restorations. This in vitro study aimed to compare the color stability of provisional restorations fabricated by additive (3D-printed) and subtractive (milled) manufacturing techniques after immersion in common staining beverages. Methods: Eighty polymethyl methacrylate (PMMA)-based specimens (16 × 1 mm) were fabricated and divided into two groups: additive (n = 40) and subtractive (n = 40). Each group was immersed in coffee, red wine, green tea, or cola for 60 and 120 h at 37 °C. Color measurements were recorded using a spectrophotometer in the CIE LCh* system, and color differences (ΔE₀₀) were calculated using the CIEDE2000 formula. Data were analyzed using repeated-measures analysis of variance (ANOVA) and Tukey post hoc tests (α = 0.05). Results: Additively manufactured specimens showed significantly higher color change (ΔE₀₀) values than subtractively milled specimens across all immersion media and time intervals (p < 0.05). Red wine and coffee caused the greatest discoloration, whereas cola produced the least effect. Conclusions: Within the limitations of this study, additive manufacturing resulted in lower color stability than subtractive fabrication. Subtractive PMMA materials exhibited superior optical behavior, suggesting their suitability for long-term provisionalization in esthetically demanding clinical situations.

Background and Objectives: The growing academic interest within the biomedical sciences regarding the diagnostic capabilities of multimodal language models, such as ChatGPT-4o, is clear. However, their ability to interpret oral clinical images remains insufficiently explored. This exploratory pilot study aimed to provide preliminary observations about the diagnostic validity of ChatGPT-4o in identifying oral squamous cell carcinoma (OSCC), oral leukoplakia (OL), and oral lichen planus (OLP) using only clinical photographs, without the inclusion of additional clinical data. Materials and Methods: Two general dentists selected 23 images of oral lesions suspected to be OSCC, OL, or OLP. ChatGPT-4o was asked to provide a probable diagnosis for each image on 30 occasions, generating a total of 690 responses. The responses were then evaluated against the reference diagnosis set up by an expert to calculate sensitivity, specificity, predictive values, and the area under the ROC curve. Results: ChatGPT-4o demonstrated high specificity across the three conditions (97.1% for OSCC, 100% for OL, and 96.1% for OLP), correctly classifying 90% of OSCC cases (AUC = 0.81). However, this overall accuracy was largely driven by correct negative classifications, while the clinically relevant sensitivity for OSCC was only 65%. In spite of that, sensitivity was highly variable: 60% for OL and just 25% for OLP, which limits its usefulness in a clinical setting for ruling out these conditions. The model achieved positive predictive values of 86.7% for OSCC and 100% for OL. Given the small dataset, these findings should be interpreted only as preliminary evidence. Conclusions: ChatGPT-4o demonstrates potential as a complementary tool for the screening of OSCC in clinical oral images. Nevertheless, the pilot nature of this study and the reduced sample size highlight that larger, adequately powered studies (with several hundred cases per pathology) are needed to obtain robust and generalizable results. Nevertheless, its sensitivity remains insufficient, as a significant proportion of true cases were missed, underscoring that the model cannot be relied upon as a standalone diagnostic tool.

Pérez JO, et al. J Adv Prosthodont. 2025 Oct;17(5):279-291. https://doi.org/10.4047/jap.2025.17.5.279

Benabdallah-M’RabatMeriem, et al. J Adv Prosthodont. 2025 Oct;17(5):292-303. https://doi.org/10.4047/jap.2025.17.5.292

(1) Gingival inflammation is an ongoing challenge in tooth-supported fixed restorations, especially when the prosthetic margin does not consider the supracrestal tissues of patients. This case report aimed to present the case of a patient who was periodontally compromised due to a previous invasion of the supracrestal tissue attachment with fixed restorations and evaluate the healing response of periodontal tissues to a vertical edgeless preparation technique: bleeding upon probing (BOP), periodontal probing depth (PPD) and clinical attachment level (CAL). (2) After tooth preparation, the new restorations were adapted, this time without invading the supracrestal space of the patient, and CAD/CAM monolithic zirconia crowns were fabricated. (3) Optimal maturation of the soft tissue was observed, achieving correction of the marginal contour of periodontal tissues and improvement of periodontal indexes. (4) It can be concluded that the BOPT technique combined with a full digital workflow is a valid option for the correction and remodeling of gingival architecture.