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(1) Background: A free gingival graft (FGG) is a common technique used to reconstruct or enhance the area of keratinized mucosa, while a connective tissue graft (CTG) is utilized to boost soft tissue thickness, thereby promoting stability in interproximal marginal bone levels. Most reported complications following FGG procedure are associated with the donor site. In addition to a painful, open wound in the palate, the most frequent complications linked to FGG harvesting include excessive bleeding, postoperative bone exposure, and recurrent herpes lesions. Numerous methods for securing the donor site after a free gingival graft surgery have been documented in research publications. The main objective of this systematic review was to assess various techniques for protecting the palate after graft harvesting and their impact on patient experience, with a focus on pain management. The secondary objective was to evaluate these techniques in relation to donor site wound healing. (2) Methods: The search was performed across four databases: Medline (PubMed Central), Scopus, Web of Science, and Embase, in accordance with PRISMA guidelines and the recommendations set forth in the Cochrane Handbook for Systematic Reviews of Interventions. The initial search took place on 9 October 2023, followed by an update on 28 June 2024. The search utilized the following keywords: (“wound” OR “injury”) AND (“graft” OR “free gingival graft” OR “graft harvesting”) AND (“healing” OR “recovery”) AND “palate”. (3) Results: After conducting the follow-up search, a total of 958 papers were identified: 193 from PubMed, 314 from Scopus, 101 from Web of Science, and 350 from Embase. Ultimately, of the 49 papers that remained, 11 were excluded due to not fulfilling the inclusion criteria, leaving 38 full-text papers on free gingival grafts (FGG) for qualitative analysis. (4) Conclusions: Various methods for palatal protection after free gingival grafts (FGG) are described in the literature, stemming from biological, physical, or chemical sources. Most studies in this review examined platelet-rich fibrin and suggested that it provides no benefits for patients’ subjective experiences or wound healing outcomes. While photobiomodulation appears to support wound epithelialization, it does not influence pain perception. Alternatives such as propolis, hyaluronic acid, and medicinal plant extracts show potential for palatal protection; however, further research is needed to thoroughly evaluate their effectiveness.

Background/Objectives: To assess the impact of a vendor-agnostic deep learning model (DLM) on image quality parameters and noise reduction in dental cone-beam computed tomography (CBCT) reconstructions. Methods: This retrospective study was conducted on CBCT scans of 93 patients (41 males and 52 females, mean age 41.2 years, SD 15.8 years) from a single center using the inclusion criteria of standard radiation dose protocol images. Objective and subjective image quality was assessed in three predefined landmarks through contrast-to-noise ratio (CNR) measurements and visual assessment using a 5-point scale by three experienced readers. The inter-reader reliability and repeatability were calculated. Results: Eighty patients (30 males and 50 females; mean age 41.5 years, SD 15.94 years) were included in this study. The CNR in DLM reconstructions was significantly greater than in native reconstructions, and the mean CNR in regions of interest 1-3 (ROI1-3) in DLM images was 11.12 ± 9.29, while in the case of native reconstructions, it was 7.64 ± 4.33 (p < 0.001). The noise level in native reconstructions was significantly higher than in the DLM reconstructions, and the mean noise level in ROI1-3 in native images was 45.83 ± 25.89, while in the case of DLM reconstructions, it was 35.61 ± 24.28 (p < 0.05). Subjective image quality assessment revealed no statistically significant differences between native and DLM reconstructions. Conclusions: The use of deep learning-based image reconstruction algorithms for CBCT imaging of the oral cavity can improve image quality by enhancing the CNR and lowering the noise.

The purpose of this study was to evaluate whether intravoxel incoherent motion (IVIM) parameters can enhance the diagnostic performance of MRI in differentiating normal pancreatic parenchyma from solid pancreatic adenocarcinomas. This study included 113 participants: 66 patients diagnosed with pancreatic adenocarcinoma and 47 healthy volunteers. An MRI was conducted at 1.5 T MR unit, using nine b-values. Postprocessing involved analyzing both conventional monoexponential apparent diffusion coefficient (ADC) and IVIM parameters (diffusion coefficient D-pure molecular diffusion coefficient, perfusion-dependent diffusion coefficient D*-pseudodiffusion coeffitient, and perfusion fraction coefficient (f)) across four different b-value selections. Significantly higher parameters were found in the control group when using high b-values for the pure diffusion analysis and all b-values for the monoexponential analysis. Conversely, in the study group, the parameters were affected by low b-values. Most parameters could differentiate between normal and cancerous tissue, with D* showing the highest diagnostic performance (AUC 98–100%). A marked decrease in perfusion in the patients with pancreatic cancer, indicated by the significant differences in the D* medians between groups, was found. In conclusion, standard ADC maps alone may not suffice for a definitive pancreatic cancer diagnosis, and incorporating IVIM into MRI protocols is recommended, as the reduced tissue perfusion detected by the IVIM parameters is a promising marker for pancreatic adenocarcinoma.