Raman spectroscopy recently proved a tremendous capacity to identify disease-specific markers in various (bio)samples being a non-invasive, rapid, and reliable method for cancer detection. In this study, we first aimed to record vibrational spectra of salivary exosomes isolated from oral and oropharyngeal squamous cell carcinoma patients and healthy controls using surface enhancement Raman spectroscopy (SERS). Then, we assessed this method’s capacity to discriminate between malignant and non-malignant samples by means of principal component–linear discriminant analysis (PC-LDA) and we used area under the receiver operating characteristics with illustration as the area under the curve to measure the power of salivary exosomes SERS spectra analysis to identify cancer presence. The vibrational spectra were collected on a solid plasmonic substrate developed in our group, synthesized using tangential flow filtered and concentrated silver nanoparticles, capable of generating very reproducible spectra for a whole range of bioanalytes. SERS examination identified interesting variations in the vibrational bands assigned to thiocyanate, proteins, and nucleic acids between the saliva of cancer and control groups. Chemometric analysis indicated discrimination sensitivity between the two groups up to 79.3%. The sensitivity is influenced by the spectral interval used for the multivariate analysis, being lower (75.9%) when the full-range spectra were used.

Background/Objectives: The integration of AI into dentistry holds promise for improving diagnostic workflows, particularly in the detection of dental pathologies and pre-radiotherapy screening for head and neck cancer patients. This study aimed to develop and validate an AI model for detecting various dental conditions, with a focus on identifying teeth at risk prior to radiotherapy. Methods: A YOLOv8 model was trained on a dataset of 1628 annotated panoramic radiographs and externally validated on 180 radiographs from multiple centers. The model was designed to detect a variety of dental conditions, including periapical lesions, impacted teeth, root fragments, prosthetic restorations, and orthodontic devices. Results: The model showed strong performance in detecting implants, endodontic treatments, and surgical devices, with precision and recall values exceeding 0.8 for several conditions. However, performance declined during external validation, highlighting the need for improvements in generalizability. Conclusions: YOLOv8 demonstrated robust detection capabilities for several dental conditions, especially in training data. However, further refinement is needed to enhance generalizability in external datasets and improve performance for conditions like periapical lesions and bone loss.

Experimental animal models for studying the mechanisms of periodontitis and its links are a better alternative to in vitro studies. The aim of this study is to compare two ligature induced periodontitis models and validate the best one for further use in research. An experimental study was performed on male Wistar rats that were divided into three groups: Test 1 (n = 10), incisor ligated, Test 2 (n = 10), molar ligated, and Control (n = 10). The animals were clinically evaluated at the beginning and at the end of the experiment by recording body weight, gingival bleeding index, tooth mobility score, changes in color, and consistency of gingival tissue. Two blood samples were obtained for each animal at baseline and at the end of the experiment. The hematological parameters Interleukin-1 alpha (IL-1 α), high sensitive C Reactive Protein (hsCRP), and Tumor Necrosis Factor-alpha (TNF-α) were measured. Seven days after the induction of periodontitis, the animals were sacrificed, and samples were prepared for histological evaluation. The results of this research demonstrated that the association between clinical, histological, and biochemical parameters initiate a periodontal pathology in the molar induced model in rats while the incisor experimental model initiates only a moderate and incomplete periodontal inflammation, mainly due to mechanical irritation.

The search for bone reconstruction materials and methods is an ongoing challenge. The aim of this review is to systemically search the available literature concerning the clinical performance of eggshell as a substitute material in guided bone regeneration in oral surgery. Five databases (PubMed, Cochrane, Web of Science, Scopus, and Embase) were searched up to February 2020. Clinical trials that used eggshell as a bone substitute material were included. Animal and in vivo studies were excluded. ROBINS-I was used to evaluate the risk of bias. A total of 840 studies were retrieved, out of which 55 full-text articles were screened. Five studies were finally included: one study showed critical and four serious risk of bias. A total of 74 patients and 88 intervention sites were included in the five studies. Clinical and radiological evaluation showed complete healing during the follow-ups. Statistically significant radiological and clinical evidence of new bone formation was achieved for socket preservation, grafting after third molar extraction, and cystic/apicectomy grafting. One patient with complications was reported. Histological analysis and micro computed tomography confirmed that it promotes bone regeneration. A comparison with synthetic hydroxyapatite showed similar healing characteristics. Within the limitations of the included studies, eggshell can be safely and efficiently used in guided bone regeneration procedures, but more research is needed to completely evaluate the full potential of this material.

Perineural spread (PNS) represents the tumor’s ability to disseminate along nerves. The aim of this article is to review the relevant literature about the PNS in head and neck tumors (H&N). The important information for imaging analysis is summarized in a diagnostic flow-chart. The pathogenesis, clinical signs, prognostic importance, and technical considerations for computer tomography and magnetic resonance imaging are briefly discussed. The anatomical pathways of the cranial nerves (CNs) and the main check-points are synthesized. Most commonly affected nerves are the trigeminal and facial, although any of the CNs may be involved. The described imaging features represent important clues for an optimal differential diagnosis. PNS worsens the prognosis and significantly changes the treatment, thus radiologists should be aware of this entity and be able to find it on imaging in the appropriate clinical context.