Oral Oncology Reports最新文献

{"title":"Early-stage oral cavity cancer (T1N0) with lymphatic drainage to the retropharyngeal lymph node: A therapeutic challenge","authors":"Simon E. Thurnheer ,&nbsp;Martin W. Huellner ,&nbsp;Deniz Kasikci ,&nbsp;Grégoire B. Morand","doi":"10.1016/j.oor.2025.100713","DOIUrl":"10.1016/j.oor.2025.100713","url":null,"abstract":"<div><div>We report a case of a 54-year-old patient diagnosed with T1N0M0 oral squamous cell cancer located at the right maxillary tuberosity. The treatment plan included wide local excision with partial maxillectomy and sentinel lymph node biopsy. Preoperative single photon emission computed tomography/computed tomography (SPECT/CT) revealed lymphatic drainage to a single ipsilateral retropharyngeal lymph node (Rouvière's node/level VIIa). Due to the poor surgical accessibility of this lymph node, the decision was made to proceed with the tumor resection without sentinel lymph node excision, focusing instead on assessing the tumor's depth of infiltration to estimate the risk of metastasis. Histopathological analysis of the specimen confirmed clear margins with 2mm depth of infiltration. Consequently, the patient was placed under observation. This case represents the first reported instance of sentinel lymph node drainage to Rouvière's node in early oral squamous cell carcinoma, presenting a unique diagnostic and therapeutic challenge.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100713"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Bone Ring Technique (BRT) for 3D reconstruction in the anterior aesthetic zone after tumor surgery","authors":"Yan-Sheng Zeng ,&nbsp;Peng-Yu Lai ,&nbsp;Shan Shen","doi":"10.1016/j.oor.2024.100684","DOIUrl":"10.1016/j.oor.2024.100684","url":null,"abstract":"<div><div>Surgery and periodontitis contribute to alveolar bone loss, resulting in increased tooth mobility. This is particularly evident post-tumor surgery, where larger bone defects are commonly encountered. Adequate bone mass is crucial for successful implant restoration in missing teeth. Conventional repair methods are unable to meet patients' functional and aesthetic expectations, while the loss of alveolar bone further compromises the initial stability of the implant. In the face of these challenges, Bone Ring Technique (BRT) demonstrates significant advantages. We conducted 3D reconstruction of the anterior aesthetic zone in a patient with maxillary bone defects following excision of maxillary odontogenic fibroma using BRT, resulting in satisfactory implant stability. This suggests the potential of BRT as a promising bone grafting technique.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100684"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive identification of oral cancer using AI and machine learning","authors":"Saraswati Patel ,&nbsp;Dheeraj Kumar","doi":"10.1016/j.oor.2024.100697","DOIUrl":"10.1016/j.oor.2024.100697","url":null,"abstract":"<div><div>Oral cancer remains a significant global health issue, often diagnosed late due to limitations in traditional diagnostic methods. This study explores the application of artificial intelligence (AI) and machine learning (ML) to enhance the early detection and diagnosis of oral cancer. We investigated three data cleaning techniques missing value imputation, outlier detection, and normalization and assessed their impact on model performance. Using convolutional neural networks (CNNs), support vector machines (SVMs), and random forests, we compared the effectiveness of these techniques in improving diagnostic accuracy and mean squared error (MSE). The results demonstrated that normalization, specifically min-max scaling, was the most effective method, leading to the highest accuracy (94 %) and the lowest MSE (0.013) for CNN models. Outlier detection also improved performance, achieving 93 % accuracy and an MSE of 0.014, while missing value imputation resulted in a lower accuracy of 92 % and an MSE of 0.015. These findings underscore the importance of normalization in preprocessing for machine learning models, highlighting its role in achieving superior performance in oral cancer detection. This study underscores the potential of AI-driven methods to revolutionize diagnostic practices, offering more accurate and timely detection of oral cancer.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100697"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In reply to Promoting oral cancer awareness in LGBTQ+ communities – Diversity in oral health","authors":"John Lennon Silva Cunha,&nbsp;José Igor de Lima Pinto","doi":"10.1016/j.oor.2025.100721","DOIUrl":"10.1016/j.oor.2025.100721","url":null,"abstract":"","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100721"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic variants in immune mediators as potential molecular biomarkers for oral cancer evaluation: Insights from a systematic revaluation by computational analyses and Bayesian approaches","authors":"Juliana Campos Botelho ,&nbsp;Samuel Arcebispo Brasileiro ,&nbsp;André Victor Oliveira Monteiro ,&nbsp;Alessandro Luiz Araújo Bentes Leal ,&nbsp;Naum Neves da Costa dos Santos ,&nbsp;Gabrielly Ribeiro Alves ,&nbsp;Reyce Santos Koga ,&nbsp;Haline Alves da Silva ,&nbsp;José Rogério Souza Monteiro ,&nbsp;Denis Vieira Gomes Ferreira ,&nbsp;Adenilson Leão Pereira ,&nbsp;Ana Carolina Alves de Oliveira ,&nbsp;Márcia Socorro Silva Lima Duarte ,&nbsp;Felipe Rodolfo Pereira da Silva","doi":"10.1016/j.oor.2025.100729","DOIUrl":"10.1016/j.oor.2025.100729","url":null,"abstract":"<div><h3>Background</h3><div>Oral cancer is a complex disease in which genetic variations in immune mediator play a relevant role in its pathophysiology. This study aimed at assessing the level of false-positive rates on meta-analytic data on genetic variations in immune mediator genes related with oral cancer risk.</div></div><div><h3>Material and methods</h3><div>A systematic search was performed for meta-analyses in this field that were published before September 22, 2024. The calculations for the False-Positive Rate Probability (FPRP) and the Bayesian False Discovery Probability (BFDP) were performed to assess the noteworthiness with a statistical power of 1.2 and 1.5 of Odds Ratio (OR) at a prior probability of 10⁻³ and 10⁻⁶. A methodological evaluation by the Venice criteria was performed and <em>in silico</em> networks were designed.</div></div><div><h3>Results</h3><div>Ten meta-analyses on the <em>TNFA</em>/rs361625/rs1800629, <em>VEGF</em>/rs3025039, <em>IL4</em>/rs2070874, <em>IL6</em>/rs1800795, <em>IL8</em>/rs4073 and <em>IL10</em>/rs1800896 genes/polymorphisms and oral cancer have been included. 88 significant OR association values from the meta-analyses included allowed the performance of 336 calculations for FPRP and 176 for BFDP. We found 35 noteworthy values (10.42 %) for FPRP and 59 noteworthy values (33.52 %) for BFDP that demonstrated the variants in <em>VEGF</em> and <em>IL10</em> with noteworthiness association with oral cancer. The gene-gene and protein-protein networks evidenced the role of <em>VEGF, TNFA, IL4, IL6, IL8</em> and <em>IL10</em> genes in the physiopathology of the disease.</div></div><div><h3>Conclusions</h3><div>The Bayesian calculations and the <em>in-silico</em> analyses indicated the rs3025039 and rs1800896 polymorphisms in the <em>VEGF</em> and <em>IL10</em> genes, respectively, as noteworthy molecular biomarkers for oral cancer risk evaluation.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100729"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143436463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilization of ChatGPT as a reliable aide for differential diagnosis of histopathology in head and neck surgery","authors":"Sayyed Ourmazd Mohseni ,&nbsp;Asal Saeid ,&nbsp;Patrick Wong ,&nbsp;Timothy Neal ,&nbsp;Thomas Schlieve","doi":"10.1016/j.oor.2025.100727","DOIUrl":"10.1016/j.oor.2025.100727","url":null,"abstract":"<div><h3>Objectives</h3><div>The rise of artificial intelligence offers promising advancements in diagnostic workflows in healthcare. In oral and maxillofacial surgery, timely and accurate histopathological diagnosis is crucial for effective treatment planning. This study examines Chat Generative Pretrained Transformer (ChatGPT, OpenAI Inc., California) as an aid to providers in generating differential diagnoses for four common maxillofacial pathologies: ameloblastoma, squamous cell carcinoma, mucoepidermoid carcinoma, and pleomorphic adenoma.</div></div><div><h3>Study design</h3><div>A retrospective study was conducted with 200 de-identified histopathological cases, evenly divided across the four diagnostic categories. Each case included clinical summaries and histopathological images, which were input into ChatGPT to generate four differential diagnoses. The study evaluated the inclusion and ranking of the correct diagnosis in the differential list using a chi-square goodness-of-fit test.</div></div><div><h3>Results</h3><div>ChatGPT included the correct diagnosis in all cases (100 %), ranking it first in 49.5 %, second in 32.5 %, third in 14.5 %, and fourth in 3.5 %. Statistical analysis confirmed a significant preference for higher ranking of correct diagnoses (p &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>ChatGPT shows strong reliability in generating accurate differential diagnoses for maxillofacial histopathology, ranking the correct diagnosis in the top two positions in 82 % of cases. These results highlight AI's potential to augment diagnostic workflows and enhance efficiency.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100727"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extended total semiconservative parotidectomy with skull base resection","authors":"Bipin Thomas Varghese","doi":"10.1016/j.oor.2024.100701","DOIUrl":"10.1016/j.oor.2024.100701","url":null,"abstract":"<div><div>A case of extensive intermediate grade muco epidermoid carcinoma (MEC) of parotid gland which was optimally excised in toto, by a skull base approach in presented. A semiconservative subradical surgery combined with planned post operative radiotherapy was selected to minimise the morbidity.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100701"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of ctDNA on metastatic cancer management: Current trends and future directions","authors":"Omveer Singh ,&nbsp;Usha Kumari Sah ,&nbsp;Jay Chandra ,&nbsp;Saraswati Patel","doi":"10.1016/j.oor.2024.100705","DOIUrl":"10.1016/j.oor.2024.100705","url":null,"abstract":"<div><div>Circulating tumor DNA (ctDNA) has emerged as a transformative tool in metastatic cancer management, offering a non-invasive approach for diagnosis, monitoring, and personalized treatment. This report examines recent advancements in ctDNA technology and its impact on oncology. ctDNA enables early cancer detection with high sensitivity (up to 85 %) and specificity (95 %) and provides valuable insights into disease progression and treatment efficacy. Technological innovations, such as next-generation sequencing (NGS) and artificial intelligence (AI), have enhanced the accuracy of ctDNA analysis. Furthermore, ctDNA facilitates personalized treatment strategies by identifying specific genetic mutations, improving therapeutic outcomes. The growing acceptance of ctDNA-based tests, alongside ongoing research into cost reduction and expanded applications, underscores its potential to revolutionize cancer care. This report highlights current trends, recent research, and future directions for integrating ctDNA into routine clinical practice.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100705"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of cancer associated fibroblasts amongst different histological variants of oral squamous cell carcinoma","authors":"Reshma Poothakulath Krishnan ,&nbsp;Deepak Pandiar ,&nbsp;Pratibha Ramani ,&nbsp;Neha Kannan ,&nbsp;Selvaraj Jayaraman","doi":"10.1016/j.oor.2024.100696","DOIUrl":"10.1016/j.oor.2024.100696","url":null,"abstract":"<div><h3>Background</h3><div>Cancer associated fibroblasts are heterogenous activated fibroblasts that form the central component of the tumor microenvironment. These cells influence the behavior of the tumor by activating various signaling pathways and initiating epithelial mesenchymal transition. CAFs have been reported in oral squamous cell carcinomas (OSCC), however, very few studies have evaluated the role of CAFs in different variants of OSCC. The aim of this study was to compare the role of CAFs in conventional OSCC and different variants of OSCCs.</div></div><div><h3>Materials and methods</h3><div>Eight each of well differentiated, moderately differentiated and poorly differentiated OSCC, 5 each of verrucous carcinoma and verrucous carcinoma turning into OSCC, three each of spindle cell carcinoma, basaloid OSCC and OSCC with clear cell differentiation and 2 cases of papillary OSCC were retrieved, and immunohistochemistry was performed with α-SMA to identify and evaluate the CAFs. Kaplan Meier analysis was carried out to evaluate the overall survival of the patients.</div></div><div><h3>Results</h3><div>Progressive increase in the CAF immunostaining was noted from papillary squamous cell carcinoma [mean - 1] to basaloid squamous cell carcinoma [1.6 ± 0.5] to spindle cell carcinoma and squamous cell carcinoma with clear cell changes [2.6 ± 0.5] (p = 0.00 - statistically significant). Patients with abundant CAF expression showed lesser survival rate when compared to patients with scanty or focal CAF immunohistochemical staining.</div></div><div><h3>Conclusion</h3><div>Increased CAF immunoexpression was noted in PDSCCs, VCs turning into SCC, OSCC with clear cell changes and spindle cell carcinoma. This highlights the aggressive nature of these tumors. Screening these tumor for the presence of CAFs will help in treatment planning and will aid in treatment planning and survival analysis.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100696"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating machine learning to customize chemotherapy for oral cancer patients","authors":"Saraswati Patel ,&nbsp;Divya Yadav ,&nbsp;Dheeraj Kumar","doi":"10.1016/j.oor.2024.100711","DOIUrl":"10.1016/j.oor.2024.100711","url":null,"abstract":"<div><div>Oral cancer, particularly oral squamous cell carcinoma (OSCC), poses a significant global health burden, with over 350,000 new cases annually. Despite chemotherapy being critical for advanced-stage treatment, its lack of personalization often results in inconsistent responses, severe side effects, and limited efficacy. Current methodologies, such as rule-based systems and traditional statistical models, fail to account for the complex, nonlinear interactions between patient-specific factors and drug responses, underscoring the need for advanced solutions. This paper introduces a machine learning (ML)-driven framework to optimize chemotherapy regimens for oral cancer patients. By leveraging multi-modal datasets, including genomic profiles, clinical histories, tumor burden indices, and drug toxicity metrics, the proposed model achieves remarkable results. Utilizing an ensemble of random forests and neural networks, the framework achieves an accuracy of 92 %, outperforming existing ML methods (85 %) and traditional approaches (78 %). Additionally, it demonstrates a 25 % reduction in chemotherapy-induced toxicity and a 20 % decrease in treatment costs. Key innovations include a novel efficacy-toxicity trade-off metric and adaptability through reinforcement learning for real-time regimen refinement. To address data privacy concerns, the framework incorporates federated learning, ensuring scalability across diverse healthcare systems. Preliminary results highlight a 15–20 % improvement in treatment efficacy and a 10 % reduction in adverse effects compared to existing methods. This interdisciplinary approach bridges the gap between oncology and ML, offering a robust foundation for personalized medicine. By tailoring chemotherapy regimens, this framework aims to improve survival rates, minimize treatment-related complications, and enhance the quality of life for oral cancer patients globally.</div></div>","PeriodicalId":94378,"journal":{"name":"Oral Oncology Reports","volume":"13 ","pages":"Article 100711"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143145793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}