Oral mucosa - an examination map for confocal laser endomicroscopy within the oral cavity: an experimental clinical study.

OBJECTIVES: Confocal laser endomicroscopy (CLE) is an optical method that enables microscopic visualization of oral mucosa. Previous studies have shown that it is possible to differentiate between physiological and malignant oral mucosa. However, differences in mucosal architecture were not taken into account. The objective was to map the different oral mucosal morphologies and to establish a "CLE map" of physiological mucosa as baseline for further application of this powerful technology. MATERIALS AND METHODS: The CLE database consisted of 27 patients. The following spots were examined: (1) upper lip (intraoral) (2) alveolar ridge (3) lateral tongue (4) floor of the mouth (5) hard palate (6) intercalary line. All sequences were examined by two CLE experts for morphological differences and video quality. RESULTS: Analysis revealed clear differences in image quality and possibility of depicting tissue morphologies between the various localizations of oral mucosa: imaging of the alveolar ridge and hard palate showed visually most discriminative tissue morphology. Labial mucosa was also visualized well using CLE. Here, typical morphological features such as uniform cells with regular intercellular gaps and vessels could be clearly depicted. Image generation and evaluation was particularly difficult in the area of the buccal mucosa, the lateral tongue and the floor of the mouth. CONCLUSION: A physiological "CLE map" for the entire oral cavity could be created for the first time. CLINICAL RELEVANCE: This will make it possible to take into account the existing physiological morphological features when differentiating between normal mucosa and oral squamous cell carcinoma in future work.

Application of gel based on medical image inspection in total closure resection of oral cancer patients.

Oral cancer is a common malignant tumor, and total closed resection is a common treatment. However, it has always been a challenge to determine the exact extent of excision during surgery. The application of medical image examination in surgery can provide important reference information, but the current methods still have some limitations. This study explored the application of gels based on medical image examination in the total closed resection of oral cancer patients to improve the accuracy of resection range and surgical treatment effect. The study collected medical image data of patients with oral cancer for image enhancement and determination of resection boundaries. By comparing the results of the experimental group and the control group, the application effect of gel in operation was evaluated. Through the application of medical image inspection technology, the determination of surgical resection boundary is more accurate, and the positive incisal margin of patients is effectively avoided. Gel technology improves the success rate and efficacy of surgery, and this method helps to improve the accuracy of surgery and the certainty of the scope of resection, which is of great significance for improving the surgical treatment effect and the survival rate of patients.

Performance of cone-beam computed tomography (CBCT) in comparison to conventional computed tomography (CT) and magnetic resonance imaging (MRI) for the detection of bone invasion in oral squamous cell cancer (OSCC): a prospective study.

BACKGROUND: Oral squamous carcinoma (OSCC) is often diagnosed at late stages and bone erosion or invasion of the jawbone is frequently present. Computed tomography (CT) and magnetic resonance imaging (MRI) are known to have high diagnostic sensitivities, specificities, and accuracies in detecting these bone affections in patients suffering from OSCC. To date, the existing data regarding the impact of cone-beam computed tomography (CBCT) have been weak. Therefore, this study aimed to investigate whether CBCT is a suitable tool to detect bone erosion or invasion in patients with OSCC. METHODS: We investigated in a prospective trial the impact of CBCT in the diagnosis of bone erosion or invasion in patients with OSCC who underwent surgery. Every participant received a CBCT, CT, and MRI scan during staging. Imaging modalities were evaluated by two specialists in oral and maxillofacial surgery (CBCT) and two specialists in radiology (CT and MRI) in a blinded way, to determine whether a bone affection was present or not. Reporting used the following 3-point system: no bony destruction ("0"), cortical bone erosion ("1"), or medullary bone invasion ("2"). Histological examination or a follow-up served to calculate the sensitivities, specificities, and accuracies of the imaging modalities. RESULTS: Our results revealed high diagnostic sensitivities (95.6%, 84.4%, and 88.9%), specificities (87.0%, 91.7%, and 91.7%), and accuracies (89.5%, 89.5%, and 90.8%) for CBCT, CT, and MRI. A pairwise comparison found no statistical difference between CBCT, CT, and MRI. CONCLUSION: Our data support the routine use of CBCT in the diagnosis of bone erosion and invasion in patients with OSCC as diagnostic accuracy is equal to CT and MRI, the procedure is cost-effective, and it can be performed during initial contact with the patient.

FD-Net: Feature Distillation Network for Oral Squamous Cell Carcinoma Lymph Node Segmentation in Hyperspectral Imagery.

Oral squamous cell carcinoma (OSCC) has the characteristics of early regional lymph node metastasis. OSCC patients often have poor prognoses and low survival rates due to cervical lymph metastases. Therefore, it is necessary to rely on a reasonable screening method to quickly judge the cervical lymph metastastic condition of OSCC patients and develop appropriate treatment plans. In this study, the widely used pathological sections with hematoxylin-eosin (H&E) staining are taken as the target, and combined with the advantages of hyperspectral imaging technology, a novel diagnostic method for identifying OSCC lymph node metastases is proposed. The method consists of a learning stage and a decision-making stage, focusing on cancer and non-cancer nuclei, gradually completing the lesions' segmentation from coarse to fine, and achieving high accuracy. In the learning stage, the proposed feature distillation-Net (FD-Net) network is developed to segment the cancerous and non-cancerous nuclei. In the decision-making stage, the segmentation results are post-processed, and the lesions are effectively distinguished based on the prior. Experimental results demonstrate that the proposed FD-Net is very competitive in the OSCC hyperspectral medical image segmentation task. The proposed FD-Net method performs best on the seven segmentation evaluation indicators: MIoU, OA, AA, SE, CSI, GDR, and DICE. Among these seven evaluation indicators, the proposed FD-Net method is 1.75%, 1.27%, 0.35%, 1.9%, 0.88%, 4.45%, and 1.98% higher than the DeepLab V3 method, which ranks second in performance, respectively. In addition, the proposed diagnosis method of OSCC lymph node metastasis can effectively assist pathologists in disease screening and reduce the workload of pathologists.

Malignant Lesions of the Oral Region.

This article focuses on the radiographic presentations of various malignant conditions that affect the oral region and delineates the role of CT, MR imaging, and PET in oral cancer imaging.

Improved intraoperative identification of close margins in oral squamous cell carcinoma resections using a dual aperture fluorescence ratio approach: first in-human results.

Significance: Surgical excision is the main treatment for solid tumors in oral squamous cell carcinomas, where wide local excision (achieving a healthy tissue margin of >5 mm around the excised tumor) is the goal as it results in reduced local recurrence rates and improved overall survival. Aim: No clinical methods are available to assess the complete surgical margin intraoperatively while the patient is still on the operating table; and while recent intraoperative back-bench fluorescence-guided surgery approaches have shown promise for detecting "positive" inadequate margins (<1 mm), they have had limited success in the detection of "close" inadequate margins (1 to 5 mm). Here, a dual aperture fluorescence ratio (dAFR) approach was evaluated as a means of improving detection of close margins. Approach: The approach was evaluated on surgical specimens from patients who were administered a tumor-specific fluorescent imaging agent (cetuximab-800CW) prior to surgery. The dAFR approach was compared directly against standard wide-field fluorescence imaging and pathology measurements of margin thickness in specimens from three patients and a total of 12 margin locations (1 positive, 5 close, and 6 clear margins). Results: The area under the receiver operating characteristic curve, representing the ability to detect close compared to clear margins (>5 mm) was found to be 1.0 and 0.57 for dAFR and sAF, respectively. Improvements in dAFR were found to be statistically significant (p<0.02). Conclusions: These results provide evidence that the dAFR approach potentially improves detection of close surgical margins.

Automated evaluation of masseter muscle volume: deep learning prognostic approach in oral cancer.

BACKGROUND: Sarcopenia has been identified as a potential negative prognostic factor in cancer patients. In this study, our objective was to investigate the relationship between the assessment method for sarcopenia using the masseter muscle volume measured on computed tomography (CT) images and the life expectancy of patients with oral cancer. We also developed a learning model using deep learning to automatically extract the masseter muscle volume and investigated its association with the life expectancy of oral cancer patients. METHODS: To develop the learning model for masseter muscle volume, we used manually extracted data from CT images of 277 patients. We established the association between manually extracted masseter muscle volume and the life expectancy of oral cancer patients. Additionally, we compared the correlation between the groups of manual and automatic extraction in the masseter muscle volume learning model. RESULTS: Our findings revealed a significant association between manually extracted masseter muscle volume on CT images and the life expectancy of patients with oral cancer. Notably, the manual and automatic extraction groups in the masseter muscle volume learning model showed a high correlation. Furthermore, the masseter muscle volume automatically extracted using the developed learning model exhibited a strong association with life expectancy. CONCLUSIONS: The sarcopenia assessment method is useful for predicting the life expectancy of patients with oral cancer. In the future, it is crucial to validate and analyze various factors within the oral surgery field, extending beyond cancer patients.

Demographic and imaging features of oral squamous cell cancer in Serbia: a retrospective cross-sectional study.

BACKGROUND: The mortality of oral squamous cell cancer (OSCC) in Serbia increased in the last decade. Recent studies on the Serbian population focused mainly on the epidemiological aspect of OSCC. This study aimed to investigate the demographic and imaging features of OSCC in the Serbian population at the time of diagnosis. METHODS: We retrospectively analyzed computed tomography (CT) images of 276 patients with OSCC diagnosed between 2017 and 2022. Age, gender, tumor site, tumor volume (CT-TV, in cm3), depth of invasion (CT-DOI, in mm), and bone invasion (CT-BI, in %) were evaluated. TNM status and tumor stage were also analyzed. All parameters were analyzed with appropriate statistical tests. RESULTS: The mean age was 62.32 ± 11.39 and 63.25 ± 11.71 for males and females, respectively. Male to female ratio was 1.63:1. The tongue (36.2%), mouth floor (21.0%), and alveolar ridge (19.9%) were the most frequent sites of OSCC. There was a significant gender-related difference in OSCC distribution between oral cavity subsites (Z=-4.225; p < 0.001). Mean values of CT-TV in males (13.8 ± 21.5) and females (5.4 ± 6.8) were significantly different (t = 4.620; p < 0.001). CT-DOI also differed significantly (t = 4.621; p < 0.001) between males (14.4 ± 7.4) and females (10.7 ± 4.4). CT-BI was detected in 30.1%, the most common in the alveolar ridge OSCC. T2 tumor status (31.4%) and stage IVA (28.3%) were the most dominant at the time of diagnosis. Metastatic lymph nodes were detected in 41.1%. CONCLUSION: Our findings revealed significant gender-related differences in OSCC imaging features. The predominance of moderate and advanced tumor stages indicates a long time interval to the OSCC diagnosis.

Serial assessment and long-term radiographic evaluation of the maxillary sinus after inferior maxillectomy and soft tissue free flap reconstruction in patients with oral cancer.

PURPOSE: This study evaluates serial radiographic changes in the maxillary sinus of patients with oral cancer after an inferior maxillectomy and a soft tissue free flap reconstruction. METHODS: Fifty-six patients were evaluated between Oct 2005 and Mar 2017 from an institutional database. Preoperative and surveillance imaging was reviewed at set time-points. Maxillary sinus scores were allotted based on a modification of the Lund-MacKay staging system. Patients were evaluated for change in sinus score. A univariate (UV) and multivariate (MV) analysis was performed. RESULTS: There were 53.5% T3/T4 category tumors and 68% received adjuvant treatment. Median follow-up was 24.4 months. Preoperative mean sinus score was 0.27 ± 0.44 and postoperative mean sinus score at 24 months was 1.2 ± 1.3 (p = <0.001). On UV analysis advanced T-stage at 12 months (OR 6.7, 95% CI 1.2-50.3, p = 0.01) and 24 months (OR 5.2, 95% CI 1.03-36.8, p = 0.04) was associated with significantly higher sinus score. On MV analysis, advanced T-stage continued to be associated with increased odds for higher sinus score (OR 4.9, 95% CI 1.1-26.8, p = 0.039). CONCLUSION: A mild increase in postoperative sinus score is seen in this cohort of patients. Advanced T-stage is associated with increased odds for higher sinus scores.

Fluorescent Guided Sentinel Lymph Mapping of the Oral Cavity with Fluorescent-Labeled Tilmanocept.

OBJECTIVE: With the shift toward utilization of sentinel lymph node biopsy (SLNB) in oral cavity cancer, improved techniques for intraoperative sentinel node identification are needed. This study investigates the feasibility of fluorescently labeled tilmanoscept in SLNB in an oral cancer rabbit model. METHODS: An animal study was designed using 21 healthy male New Zealand rabbits. Gallium-68-labeled tilmanocept labeled with IRDye800CW was injected submucosally into the buccal mucosa (n = 6) or lateral tongue (n = 7) followed by PET imaging. One hour after injection, SLNB was performed using fluorescence imaging followed by a bilateral neck dissection and sampling of non-nodal surrounding tissue. All tissues were measured for radioactivity and fluorescence. In addition, eight rabbits were injected with delayed SLNB performed 48 h after injection. RESULTS: Buccal injections all had ipsilateral SLN drainage and tongue injections exhibited 18.2% contralateral drainage. An average of 1.9 ± 1.0 SLN (range 1-5) were identified. In addition, an average of 16.9 ± 3.3 non-sentinel lymph nodes were removed per animal. SLNs had an average of 0.69 ± 0.60 percent-of-injected dose (%ID) compared with non-sentinel nodes with 0.012 ± 0.025 %ID and surrounding tissue with 0.0067 ± 0.015 %ID. There was 98.0% agreement between sentinel lymph nodes identified using fluorescence compared to radioactivity with Cohen's kappa coefficient of 0.879. In 48-h delayed SLNB, results were consistent with 97.8% agreement with radioactivity and Cohen's Kappa coefficient of 0.884. Fluorescence identified additional lymph nodes that were not identified by radioactivity, and with one false negative. CONCLUSION: Fluorescent-labeled Tc-99 m-tilmanocept represents a highly accurate adjunct to enhance SLNB for oral cavity cancer. LEVEL OF EVIDENCE: N/A Laryngoscope, 134:1299-1307, 2024.

CT predictors of sub-centimeter occult lymph node metastases in oral cavity squamous cell carcinoma: A case-control study.

BACKGROUND: For patients with oral cavity squamous cell carcinoma (OCSCC) without evidence of nodal metastasis (cN0) on pre-operative evaluation, there are no clear guidelines who should undergo elective neck dissection (END) versus clinical surveillance. OBJECTIVE: To identify CT imaging characteristics of sub-centimeter lymph nodes that would help predict the likelihood of nodal metastases on pathology. METHODS: Retrospective review of cN0 OCSCC patients at a tertiary academic medical center was performed. Inclusion criteria included elective neck dissection, pre-operative CT imaging and presence of metastatic disease within lymph nodes. Control group consisted of patients without nodal metastases on pathology. CT features that were evaluated included asymmetric size, disrupted fatty hilum, asymmetric number, presence of cortical nodule, cortical nodule size, and round/oval shape. We evaluated the associations between CT LN features and the presence of metastases using multi-level mixed-effects logistic regression models. Model evaluation was performed using 5-fold cross-validation. The positive predictive value (PPV) and negative predictive value (NPV) were calculated. RESULTS: 26 patients in each study and control groups were included. Three-level mixed-effects logistic regression models indicated round/oval shape (OR = 1.39, p = .01), asymmetric number (OR = 7.20, p = .005), and disrupted fatty hilum (OR = 3.31, p = .04) to be independently predictive in a 3-variable model with sensitivity = 38.0%, specificity = 92.0%, and PPV = 93.8%. CONCLUSIONS: In cN0 OCSCC patients undergoing END, round/oval shape, asymmetric number, and disrupted fatty hilum of lymph nodes on pre-operative CT imaging are novel and highly predictive of occult nodal disease.

Artificial intelligence-integrated optical coherence tomography for screening and early detection of oral cancer.

Early detection of oral cancer is essential for improving patient survival rates and leads to higher chances of successful treatment, reduced cost of complex treatments, and improved quality of life of patients. Oral cancer often arises from oral potentially malignant disorders (OPMDs), among which leukoplakia is the most common. Numerous chairside diagnostic aids and imaging modalities have been reviewed for screening detection of OPMDs and oral cancer, but these techniques have limitations. Novel optical diagnostic modalities work on the assumption that neoplastic and dysplastic tissues have different absorbance and reflectance properties when exposed to specific wavelengths of light. Optical coherence tomography (OCT) imaging is a promising new technology in the field of oral oncology. The ability of OCT to provide real-time, nondestructive, high-resolution, radiation-free images makes it an ideal modality for screening and detection of neoplastic changes in the oral mucosa, but interpretation of OCT images requires training and expertise. To overcome this limitation, artificial intelligence-based diagnostic algorithms are being combined with OCT imaging to assist professionals in achieving high-accuracy interpretation of OCT images. This review highlights the applications and scope of artificial intelligence in OCT imaging for the screening and detection of early-stage oral cancer.

Hypervascular floor of mouth tumor: Rare presentation of oral cavity squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common malignancy affecting the oral cavity and commonly presents as an exophytic lesion with red or white granular ulcerations. Most diagnoses are confirmed by biopsy and clinical features; however, early SCC has been shown to hide within benign appearing lesions, such as vascular tumors, resulting in missed diagnoses and delay in treatment. The following case report will discuss a patient who presented with a mass in the floor of the mouth which appeared as a vascular tumor on exam and imaging. This was originally thought to be benign based on FNA findings however was found to harbor invasive squamous cell carcinoma on final pathology. The goal of this case report is to provide a background on the variable presentations of OSCC, vascular tumors, and uncommon presentations for which specialists should be aware of in their practice.

Identification of CT-based non-invasive radiomic biomarkers for overall survival prediction in oral cavity squamous cell carcinoma.

This study addresses the limited non-invasive tools for Oral Cavity Squamous Cell Carcinoma (OSCC) survival prediction by identifying Computed Tomography (CT)-based biomarkers to improve prognosis prediction. A retrospective analysis was conducted on data from 149 OSCC patients, including CT radiomics and clinical information. An ensemble approach involving correlation analysis, score screening, and the Sparse-L1 algorithm was used to select functional features, which were then used to build Cox Proportional Hazards models (CPH). Our CPH achieved a 0.70 concordance index in testing. The model identified two CT-based radiomics features, Gradient-Neighboring-Gray-Tone-Difference-Matrix-Strength (GNS) and normalized-Wavelet-LLL-Gray-Level-Dependence-Matrix-Large-Dependence-High-Gray-Level-Emphasis (HLE), as well as stage and alcohol usage, as survival biomarkers. The GNS group with values above 14 showed a hazard ratio of 0.12 and a 3-year survival rate of about 90%. Conversely, the GNS group with values less than or equal to 14 had a 49% survival rate. For normalized HLE, the high-end group (HLE > - 0.415) had a hazard ratio of 2.41, resulting in a 3-year survival rate of 70%, while the low-end group (HLE ≤ - 0.415) had a 36% survival rate. These findings contribute to our knowledge of how radiomics can be used to predict the outcome so that treatment plans can be tailored for patients people with OSCC to improve their survival.

A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.

OBJECTIVES: In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical lymph node metastasis (LNM) using contrast-enhanced computed tomography (CECT). MATERIALS AND METHODS: CECT scans of 100 patients with OSCC (217 metastatic and 1973 non-metastatic cervical lymph nodes: development set, 76 patients; internally independent test set, 24 patients) who received treatment at the Peking University School and Hospital of Stomatology between 2012 and 2016 were retrospectively collected. Clinical diagnoses and pathological findings were used to establish the gold standard for metastatic cervical LNs. A reader study with two clinicians was also performed to evaluate the lymph node status in the test set. The performance of the proposed models and the clinicians was evaluated and compared by measuring using the area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). RESULTS: A fusion model combining deep learning with radiomics showed the best performance (ACC, 89.2%; SEN, 92.0%; SPE, 88.9%; and AUC, 0.950 [95% confidence interval: 0.908-0.993, P < 0.001]) in the test set. In comparison with the clinicians, the fusion model showed higher sensitivity (92.0 vs. 72.0% and 60.0%) but lower specificity (88.9 vs. 97.5% and 98.8%). CONCLUSION: A fusion model combining radiomics and deep learning approaches outperformed other single-technique models and showed great potential to accurately predict cervical LNM in patients with OSCC. CLINICAL RELEVANCE: The fusion model can complement the preoperative identification of LNM of OSCC performed by the clinicians.

Multimodal Prediction of Cervical Lymph Node Metastasis and Recurrence in Oral Squamous Cell Carcinoma.

BACKGROUND/AIM: Oral squamous cell carcinoma (OSCC) is the most common malignancy in the head/neck region, and cervical lymph node (CLN) metastasis is a strong poor-prognosis factor. In addition, many patients with OSCC experience recurrence despite multidisciplinary treatment. We sought to identify factors associated with CLN metastasis and recurrence in patients with OSCC. PATIENTS AND METHODS: We evaluated a total of 45 patients and 233 target CLNs. The longest diameter of the target CLN, the shortest diameter of the target CLN (LS), the area of the target CLN, and the relative computed tomography (CT) values of the target CLNs calculated based on the CT values of the internal jugular vein (LCT) were obtained from preoperative CT images, and the maximum standardized uptake values of the primary tumor (pSUV) and target CLN (nSUV) were obtained from preoperative 18F-fluorodeoxyglucose-positron emission tomography/CT images. We performed immunohistochemical staining for cytokeratin 13 (CK13) and 17 (CK17) on neck dissection tissues. RESULTS: A discrimination equation was used that can predict CLN metastasis with a 92.2% discrimination rate using LS, LCT, pSUV, and nSUV. The CLNs were divided into discrimination and non-discrimination groups based on discriminant equations and CK13 and CK17 were used as the objective variables. A significantly higher recurrence rate was observed in the non-discrimination group (CK13: 5-year recurrence rate 28.6% vs. 64.3%, p<0.01; CK17: 5-year recurrence rate 28.0% vs. 76.0%, p<0.01). CONCLUSION: CLN metastases in OSCC can be assessed by combining preoperative imaging. The combined use of CK13 and CK17 expression with imaging findings offers an integrated approach to predict OSCC recurrence.

ανß3 integrin-targeted ICG-derived probes for imaging-guided surgery and photothermal therapy of oral cancer.

Indocyanine green (ICG), as the only Federal Drug Administration (FDA) approved fluorescence imaging agent, has been widely applied in clinics for near-infrared (NIR) fluorescence imaging-guided surgery and photothermal therapy of cancers. However, its lack of target specificity and poor photo and photothermal stabilities seriously restrict its wide application in clinical practice. Herein, we developed ICG-derived NIR fluorescent probes consisting of a cypate fluorophore and one or two cyclic-(arginine-glycine-aspartic acid) (cRGD) peptides that can specifically target αvß3 integrin for accurate diagnosis and therapy of oral tumors. Probe Cy-2RGD has been demonstrated to possess bright NIR emission, great tumor targeting capability and a photothermal effect. Moreover, it could be successfully used for effective imaging-guided surgical resection as well as photothermal therapy of oral tumors. This work could provide a valuable tool for sensitive detection and accurate treatment of malignant tumors.

Diagnostic accuracy of contrast-enhanced computed tomography in assessing cervical lymph node status in patients with oral squamous cell carcinoma.

OBJECTIVE: Accurate preoperative prediction of lymph node (LN) status plays a pivotal role in determining the extension of neck dissection (ND) required for patients with oral squamous cell carcinoma (OSCC). This study aims to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) in detecting LN metastases (LNMs) and to explore clinicopathological factors associated with its reliability. METHODS: Data from 239 patients with primary OSCC who underwent preoperative CT and subsequent radical surgery involving ND were retrospectively reviewed. Suspicious LNs were categorized into three groups: accentuated (< 10 mm), enlarged (≥ 10 mm), and melted. Statistical analysis encompassing correlation and comparative analysis, and determination of sensitivity, specificity, PPV, and NPV were performed. RESULTS: Overall, sensitivity was significantly higher in the accentuated LNs group (83.54%) compared to the melted LNs group (39.24%, p < 0.05, t test). Conversely, specificity was significantly higher in the melted LNs group (98.19%) compared to the accentuated LNs group (55.15%, p < 0.05, t test). Accentuated LNs exhibited a false negative rate of 13.00%. False positive rates were 51.80%, 30.26% and 8.82%, respectively. Diagnostic accuracy for detecting LNMs in level IIa and IIb exceeded that of level III. Patients with solely accentuated LNs were more likely to have a small, well-differentiated tumor. However, no distinctions emerged in terms of the occurrence of T4 tumors among the three groups. CONCLUSION: CT proves sufficient to predict LNMs in patients with OSCC. Looking ahead, the potential integration of artificial intelligence and deep learning holds promise to further enhance the reliability of CT in LNMs detection. However, this prospect necessitates further investigation.

Contribution of FDG-PET in the diagnostic assessment of cervical lymph node metastasis in Oral Cavity Squamous Cell Carcinoma (OCSCC).

INTRODUCTION: The main objective of this study was to evaluate the contribution of FDG-PET in the diagnostic assessment of cervical lymph node metastasis in Oral Cavity Squamous Cell Carcinoma (OCSCC) and to advance a diagnostic threshold value for SUVmax in carcinomatous cervical lymph node. METHODS: 47 patients with OCSCC and suspicious cervical lymph node involvement (cN+) on FDG-PET were included in this retrospective study. The primary outcome was cervical lymph node SUVmax based on histological cervical metastatic disease (« gold standard ¼). RESULTS: Among the 77 cervical lymph nodes considered suspicious on patients' FDG-PET, 50 were really metastatic on histological examination. The lymph node SUVmax with metastatic involvement on histological examination was 4.6 ± 3.9 [2.6 - 23.7] versus 3.6 ± 1.2 [2 - 7.3] without carcinomatous involvement (p = 0.004). The lymph node size was not statistically significant according to metastatic disease (p = 0.28). DISCUSSION: A cervical lymph node SUVmax value of less than 2.6 on FDG-PET would suggest non-metastatic lymph node involvement. Supra Omohyoid Neck Dissection (SOHND) could therefore be performed in OCSCC when the SUVmax of the cervical lymph node is below this value in order to reduce the surgical morbidity of dissection of the lower internal jugular chain (Level IV).