Oral squamous cell carcinoma (OSCC) is the most common cancer of the oral cavity and constitutes 95% of all cancers of this area. Men are affected twice as commonly as women, primarily if they are over 50 years of age. Forty percent of the lesions are localized in the tongue and 30% in the floor of the oral cavity. OSCC often affects upper and lower gingiva, buccal mucous membrane, the retromolar triangle and the palate. The prognosis is poor and the five-year survival rate ranges from 20% (OSCC in the floor of the mouth) to 60% (OSCC in the alveolar part of the mandible). Treatment is difficult, because of the localization and the invasiveness of the available methods. The diagnosis is made based on a histopathological examination of a biopsy sample. The low detection rate of early oral SCC is a considerable clinical issue. Although the oral cavity can be easily examined, in the majority of cases oral SCC is diagnosed in its late stages. It is difficult to diagnose metastases in local lymph nodes and distant organs, which is important for planning the scope of resection and further treatment, graft implantation, and differentiation between reactive and metastatic lymph nodes as well as between disease recurrence and scars or adverse reactions after surgery or radiation therapy. Imaging studies are performed as part of the routine work-up in oral SCC. However, it is difficult to interpret the results at the early stages of the disease. The following imaging methods are used - dental radiographs, panoramic radiographs, magnetic resonance imaging with diffusion-weighted and dynamic sequences, perfusion computed tomography, cone beam computed tomography, single-photon emission computed tomography, hybrid methods (PET/CT, PET/MRI, SPECT/CT) and ultrasound. Some important clinical problems can be resolved with the use of novel modalities such as MRI with ADC sequences and PET. The aim of this article is to describe oral squamous cell carcinoma as it appears in different imaging methods considering both their advantages and limitations.
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http://dx.doi.org/10.12659/PJR.900892 | DOI Listing |
J Appl Oral Sci
January 2025
Nanjing University, Research Institute of Stomatology, Affiliated Hospital of Medical School, Nanjing Stomatological Hospital, Department of Oral and Maxillofacial Trauma Orthognathic Plastic Surgery, Nanjing, China.
Objectives: Depth of invasion (DOI) in oral squamous cell carcinoma (OSCC) guides treatment and prognosis but lacks three-dimensional (3D) insight. Thus, this study aimed to investigate the feasibility and accuracy of Lugol's iodine-enhanced micro-computed tomography (CT) for the 3D measurement of DOI in OSCC samples.
Methodology: In total, 50 in vitro OSCC samples from Nanjing Stomatological Hospital (July 2022 to January 2024) were subjected to micro-CT imaging with a slice thickness of 50 μm following 3% Lugol iodine staining for 12 h, followed by pathological examination and staining.
Extracell Vesicles Circ Nucl Acids
December 2024
Department of Otorhinolaryngology, Head and Neck Surgery, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong 00000, China.
Current approaches to oral cancer diagnosis primarily involve physical examination, tissue biopsy, and advanced computer-aided imaging techniques. However, despite these advances, patient survival rates have not significantly improved. Hence, there is a critical need to develop minimally invasive tools with high sensitivity and specificity to improve patient survival and quality of life.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Department of Oral Biology, University Clinic of Dentistry, Medical University of Vienna, 1090, Vienna, Austria.
Objective: Titanium surface modifications improve osseointegration in dental and orthopedic implants. However, soft tissue cells can also reach the implant surface in immediate loading protocols. While previous research focused on osteogenic cells, the early response of soft tissue cells still needs to be better understood.
View Article and Find Full Text PDFSupport Care Cancer
January 2025
Oral Diagnosis Department, Faculdade de Odontolodia de Piracicaba, Universidade de Campinas (UNICAMP), Piracicaba, São Paulo, Brazil.
Purpose: Oral mucositis (OM) reflects a complex interplay of several risk factors. Machine learning (ML) is a promising frontier in science, capable of processing dense information. This study aims to assess the performance of ML in predicting OM risk in patients undergoing head and neck radiotherapy.
View Article and Find Full Text PDFJ Dent Sci
December 2024
Blood Transfusion Haematology Hospital No. 2, Ho Chi Minh City, Viet Nam.
Background/purpose: Oral squamous cell carcinoma (OSCC) is notorious for its low survival rates, due to the advanced stage at which it is commonly diagnosed. To enhance early detection and improve prognostic assessments, our study harnesses the power of machine learning (ML) to dissect and interpret complex patterns within mRNA-sequencing (RNA-seq) data and clinical-histopathological features.
Materials And Methods: 206 retrospective Vietnamese OSCC formalin-fixed paraffin-embedded (FFPE) tumor samples, of which 101 were subjected to RNA-seq for classification based on gene expression.
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