UNASSIGNED: Magnetic resonance imaging (MRI) is a routinely used imaging modality for pre-treatment radiologic evaluation of tongue carcinoma, providing accurate information regarding the extent of the disease.
UNASSIGNED: To investigate the role of MRI-derived depth of invasion and tumor thickness evaluation in squamous cell carcinoma of the tongue, and to assess if any correlation exists between depth of invasion, tumor thickness, nodal metastasis, muscles, and space involved.
UNASSIGNED: Thirty-three patients with oral squamous cell carcinoma of the tongue who had undergone pre-treatment MRI and excisional biopsy were included. The tumor thickness (TT) and depth of invasion (DOI) were evaluated on MRI and histopathologic images.
UNASSIGNED: The relation between different methodologies for assessing showed a very high correlation for the tumor tissue thickness (r = 0.99, p < 0.05) and depth of invasion (r = 0.82, p < 0.05). The tumor thickness and the depth of invasion increased with the loss of differentiation in the carcinoma histopathologically. As the depth of invasion increases, the extent of the spread of the carcinoma to tongue musculature, lingual septum, and spaces also increases.
UNASSIGNED: The present study has depicted a high correlation between the tumor thickness and the depth of invasion between MRI and histopathological findings and is the first of its kind to correlate DOI to the invasiveness of the disease.

OBJECTIVE: This study evaluates the efficacy of two advanced Large Language Models (LLMs), OpenAI\'s ChatGPT 4 and Google\'s Gemini Advanced, in providing treatment recommendations for head and neck oncology cases. The aim is to assess their utility in supporting multidisciplinary oncological evaluations and decision-making processes.
METHODS: This comparative analysis examined the responses of ChatGPT 4 and Gemini Advanced to five hypothetical cases of head and neck cancer, each representing a different anatomical subsite. The responses were evaluated against the latest National Comprehensive Cancer Network (NCCN) guidelines by two blinded panels using the total disagreement score (TDS) and the artificial intelligence performance instrument (AIPI). Statistical assessments were performed using the Wilcoxon signed-rank test and the Friedman test.
RESULTS: Both LLMs produced relevant treatment recommendations with ChatGPT 4 generally outperforming Gemini Advanced regarding adherence to guidelines and comprehensive treatment planning. ChatGPT 4 showed higher AIPI scores (median 3 [2-4]) compared to Gemini Advanced (median 2 [2-3]), indicating better overall performance. Notably, inconsistencies were observed in the management of induction chemotherapy and surgical decisions, such as neck dissection.
CONCLUSIONS: While both LLMs demonstrated the potential to aid in the multidisciplinary management of head and neck oncology, discrepancies in certain critical areas highlight the need for further refinement. The study supports the growing role of AI in enhancing clinical decision-making but also emphasizes the necessity for continuous updates and validation against current clinical standards to integrate AI into healthcare practices fully.

Patients with long-standing autoimmune diseases like systemic lupus erythematosus (SLE) are at a higher risk of developing hematological malignancies. However, chronic myeloid leukemia (CML) has rarely been reported in patients with SLE. Advancements in medical diagnostics and treatment have led to the life expectancy of SLE and CML patients moving closer to that of the general population, and it is not uncommon to encounter more than one malignancy in a cancer survivor. Although squamous cell carcinoma (SCC) of the skin has been reported in CML patients, mucosal SCC of the head and neck has rarely only been reported in CML survivors. The objective of this case report is to share our experience in treating a patient with dual metachronous primary malignancies, CML, and tongue carcinoma, along with long-standing SLE, managed by a multidisciplinary team.

Squamous cell carcinoma is the most predominant type of malignancy in the head and neck region with neuroendocrine carcinomas (NECs) being a rare occurrence. Here we report a rare case of small cell non-keratinizing NEC (WHO grade 3), TNM (tumor, node, and metastasis) stage T3N1M0, involving the larynx and the base of the tongue, in a 54-year-old male patient, demonstrating its rarity in an uncommon anatomical site and an aggressive and relatively uncommon pattern of spread for this tumor, over a period of two months. NECs in the head and neck region, especially those affecting the larynx and the posterior third of the tongue, remain exceedingly rare, comprising only a small fraction of malignancies in this region. The aggressive nature and distinct pattern of spread observed in this case underscore the importance of recognizing such unusual presentations for appropriate diagnosis and management. Given the rarity of this tumor type, a comprehensive understanding of its clinicopathological features is essential for guiding effective treatment strategies. We also discuss the treatment.

Three-dimensional (3D) ultrasound can assess the margins of resected tongue carcinoma during surgery. Manual segmentation (MS) is time-consuming, labour-intensive, and subject to operator variability. This study aims to investigate use of a 3D deep learning model for fast intraoperative segmentation of tongue carcinoma in 3D ultrasound volumes. Additionally, it investigates the clinical effect of automatic segmentation. A 3D No New U-Net (nnUNet) was trained on 113 manually annotated ultrasound volumes of resected tongue carcinoma. The model was implemented on a mobile workstation and clinically validated on 16 prospectively included tongue carcinoma patients. Different prediction settings were investigated. Automatic segmentations with multiple islands were adjusted by selecting the best-representing island. The final margin status (FMS) based on automatic, semi-automatic, and manual segmentation was computed and compared with the histopathological margin. The standard 3D nnUNet resulted in the best-performing automatic segmentation with a mean (SD) Dice volumetric score of 0.65 (0.30), Dice surface score of 0.73 (0.26), average surface distance of 0.44 (0.61) mm, Hausdorff distance of 6.65 (8.84) mm, and prediction time of 8 seconds. FMS based on automatic segmentation had a low correlation with histopathology (r = 0.12, p = 0.67); MS resulted in a moderate but insignificant correlation with histopathology (r = 0.4, p = 0.12, n = 16). Implementing the 3D nnUNet yielded fast, automatic segmentation of tongue carcinoma in 3D ultrasound volumes. Correlation between FMS and histopathology obtained from these segmentations was lower than the moderate correlation between MS and histopathology.

Cancer of the tongue is an uncommon cancer site, with only 31,378 cases in the SEER 1975-2017 database, fewer than 1% of all reported cancers. This article updates trends in incidence, prevalence, short and long-term survival and mortality of tongue carcinoma.

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To compare postoperative complications, functional rehabilitation, surgical outcomes of the radial artery forearm free flap (RAFFF) and split thickness skin graft (STSG) reconstruction of postsurgical defect in T2 lesions of cancer oral cavity. Observational Prospective comparative study. Academic tertiary referral centre. In our study of forty four patients, after tumour resection, half underwent reconstruction using RAFFF (Group I) and another half by STSG (Group II). All of the patients were followed postoperatively to determine and compare their functional outcomes related to donor site and recipient site complications, speech, deglutition and mouth opening. The speech intelligibility and deglutition were each assessed using Articulation Handicap Index and Vedio-fluoroscopy using the Functional oral intake scale. Operative time for STSG reconstruction was shorter at 2.2 ± 0.97 SD hours compared to 5.9 ± 1.24 SD hours for RAFFF reconstruction. Hospital stay was 8.3 ± 1.19 SD days for STSG patients and 12.6 ± 1.7 SD days for RAFFF patients. The functional outcomes of speech quality and swallowing were near comparable in both groups but the donor site complications were significant in the RAFFF group. Operative time, hospital stay and donor site complications are both significantly reduced with the STSG as opposed to RAFF. Functional and oncologic results of both methods are near comparable. To conclude, STSG can be used for reconstruction of the post-surgical defects in T2 lesions of the tongue.

The aim of this study was to investigate the correlation between pre-treatment inflammatory biomarkers and the post-operative depth of invasion (DOI) and worst pattern of invasion (WPOI) in early-stage oral tongue squamous cell carcinoma (OTSCC) by means of positive sentinel lymph node biopsy (SLNB). A retrospective analysis of patients affected by cN0 T1-T2 OTSCC who had undergone an SLNB at the National Cancer Institute of Naples was performed. The patients were studied using an evaluation of the pre-treatment neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), and a histopathological analysis of the DOI and WPOI. The statistical analysis showed that among the prognostic biomarkers, the NLR was a significant predictor of high WPOI values (p = 0.002). The cut-off NLR value was 2.52 with a probability of developing a positive sentinel lymph node biopsy (SLNB) of 30.3%. In contrast, the DOI value was 5.20 with a probability of developing a positive SLNB of 31.82%. Regarding the WPOI, increasing the WPOI class increased the likelihood of a positive SLNB occurrence, and a positive significant correlation was found between the WPOI and SLNB (Csp = 0.342; p < 0.001). Pre-treatment NLR, together with post-surgical DOI and WPOI, can be a reliable predictor of occult neck metastasis in patients affected by early-stage OTSCC with a clinically negative neck. Further prospective studies with a larger series will be needed to confirm the results obtained and to better define the NLR, WPOI and DOI cut-off values in order for elective neck dissection to be recommended in relation to a clinically negative neck.

Differential diagnosis of neuropsychiatric symptoms in a patient with an underlying malignancy is exhaustive. 5-fluorouracil (5-FU) is one of the most widely used chemotherapy agents and it is often used as the first-line regimen in head and neck malignancies. We present a case of an elderly female with an underlying locally advanced p16-positive squamous cell carcinoma of the tongue who presented with manic symptoms for one week after cycle 2 of chemotherapy. Multidisciplinary management by otorhinolaryngologists with psychiatrist and oncologist led to the cessation of 5-FU, administration of antipsychotics, and replacement with a different chemotherapy agent, leading to complete resolution of manic symptoms. Possible mechanisms of the 5-FU-induced manic episode with its treatment are discussed in this report.