Over the last 2 decades, the paradigm of laryngeal cancer management has pivoted toward preserving laryngeal function without sacrificing oncologic outcomes. Transoral laser microsurgery has diminished the role of open laryngeal surgery. For early-stage laryngeal cancer, the common primary modalities are endoscopic laryngeal surgery and narrow field radiation. Total laryngectomy followed by either radiation or chemoradiation is option for advanced laryngeal cancer. In experienced hands and following meticulous patient selection, supracricoid laryngectomy may serve as a viable alternative to total laryngectomy to preserve laryngeal function. Total laryngectomy is still the recommended treatment in those with airway compromise and/or laryngeal dysfunction.

OBJECTIVE: To explore the influence of mindfulness-based stress reduction (MBSR) training on the negative emotions and social functioning of patients with laryngeal cancer post-operation.
METHODS: Sixty-five patients with laryngeal cancer admitted to our hospital from January 2017 to December 2019 were selected and divided into an observation group of 33 cases and a control group of 32 cases according to the patient\'s wishes. The control group received routine intervention, while the observation group received mindfulness decompression training in addition to the control group. Both groups were evaluated after 8 weeks of intervention. The research tools included the self-rating anxiety scale (SAS), self-rating depression scale (SDS), Pittsburgh Sleep Quality Index (PSQI), Social Disability Screening Schedule (SDSS), Social Support Rating Scale (SSRS), and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30), all of the scores of them were used to verify the foregoing scale. The effects of MBSR were evaluated by the differences between the post- and pre-intervention scores in each scale. T-test was used for mean comparison and Pearson test was used for rate comparison χ2 inspection.
METHODS: Patients will have negative emotions during the surgical treatment of laryngeal malignancies (Literature 1), which will affect their mental health (literature 2, 3, 4, 5, 6, 7). Mindfulness decompression training (literature 10, 11) can reduce the depression and anxiety of patients with malignant tumors (literature 14, 15). According to the inclusion criteria and exclusion criteria (literature 16 and 17), two groups of patients were selected in this study, and the scores were obtained using research tools including SAS (literature 19), SDS (literature 20), PSQI (literature 21), SDSS (literature 22) and QLQ-C30 (literature 24 and 25). The effect of MBSR was evaluated by the difference before and after the intervention scores in each scale.
RESULTS: After the intervention, the scores of the SAS and SDS in the two groups were lower than before (P < 0.05), the PSQI score of the two groups was lower than before (P < 0.05), the SDSS score of the two groups was lower than before (P < 0.05), and the scores of the QLQ-C30 in the two groups were higher than before intervention (P < 0.05).
CONCLUSIONS: Mindfulness-based stress reduction training can reduce the negative emotions of patients with laryngeal cancer and improve their quality of sleep, social functioning, and quality of life. It is worthy of clinical application.

Background: Narrow-band imaging is an advanced endoscopic technology used to detect changes on the laryngeal tissue surface, employing a comparative approach alongside white-light endoscopy to facilitate histopathological examination. Objective: This study aimed to assess the utility and advantages of NBI (narrow-band imaging) in identifying malignant laryngeal lesions through a comparative analysis with histopathological examination. Methods: We conducted a systematic literature review, utilizing databases such as PubMed, the CNKI database, and Embase for our research. Results: We analyzed the articles by reviewing their titles and abstracts, selecting those we considered relevant based on determined criteria; in the final phase, we examined the relevant studies according to the specific eligibility criteria. Conclusions: Narrow-band imaging is an advanced endoscopic technology that demonstrates its efficacy as a tool for diagnosing malignant laryngeal lesions and comparing them to premalignant lesions. The European Society of Laryngology has implemented a standardized classification system for laryngeal lesions to enhance data correlation and organization.

Laryngeal cancer exhibits a notable global health burden, with later-stage detection contributing to a low mortality rate. Laryngeal cancer diagnosis on throat region images is a pivotal application of computer vision (CV) and medical image diagnoses in the medical sector. It includes detecting and analysing abnormal or cancerous tissue from the larynx, an integral part of the vocal and respiratory systems. The computer-aided system makes use of artificial intelligence (AI) through deep learning (DL) and machine learning (ML) models, including convolution neural networks (CNN), for automated disease diagnoses and detection. Various DL and ML approaches are executed to categorize the extraction feature as healthy and cancerous tissues. This article introduces an automated Laryngeal Cancer Diagnosis using the Dandelion Optimizer Algorithm with Ensemble Learning (LCD-DOAEL) method on Biomedical Throat Region Image. The LCD-DOAEL method aims to investigate the images of the throat region for the presence of laryngeal cancer. In the LCD-DOAEL method, the Gaussian filtering (GF) approach is applied to eliminate the noise in the biomedical images. Besides, the complex and intrinsic feature patterns can be extracted by the MobileNetv2 model. Meanwhile, the DOA model carries out the hyperparameter selection of MobileNetV2 architecture. Finally, the ensemble of three classifiers such as bidirectional long short-term memory (BiLSTM), regularized extreme learning machine (ELM), and backpropagation neural network (BPNN) models, are utilized for the classification process. A comprehensive set of simulations is conducted on the biomedical image dataset to highlight the efficient performance of the LCD-DOAEL technique. The comparison analysis of the LCD-DOAEL method exhibited a superior accuracy outcome of 97.54% over other existing techniques.

Lemierre\'s syndrome, a rare complication of oropharyngeal infections, is characterized by septic thrombophlebitis primarily affecting the internal jugular vein, which can lead to septicemia, thrombotic obstruction, and potential dissemination to distant sites. We present the case of a 54-year-old male with a history of chronic smoking and newly diagnosed laryngeal carcinoma, complicated by Lemierre\'s syndrome. Initial symptoms included odynophagia, dyspnea, and cervical swelling, with subsequent diagnosis confirming thrombosis of the internal jugular vein via ultrasound, CT, and MRI. Treatment included broad-spectrum antibiotics and anticoagulation, followed by oncological management for the carcinoma. This case underscores the diagnostic challenge posed by concurrent malignancy and highlights the critical role of early recognition and comprehensive treatment involving antibiotics, anticoagulation, and oncological therapy. Multidisciplinary collaboration is crucial for optimizing outcomes in complex cases like this, emphasizing the need for heightened clinical suspicion and prompt intervention involving proper imaging diagnosis, appropriate antibiotic coverage, and timely microbiological recognition for adjustment of antimicrobial therapy.

Laryngeal cancer remains a significant global health concern, with poor prognosis for advanced-stage disease highlighting the need for novel diagnostic, prognostic, and therapeutic approaches. Circular RNAs (circRNAs), a class of covalently closed non-coding RNAs, have emerged as important regulators of gene expression and cellular processes in various cancers, including laryngeal cancer. This review summarizes the current understanding of circRNAs in laryngeal cancer, covering their biogenesis, regulatory mechanisms, and potential clinical applications. We explore the diverse functions of circRNAs, including their roles as miRNA sponges, protein interactors, and direct mRNA regulators, and their influence on key cellular processes such as proliferation, invasion, and metastasis. The review highlights promising circRNAs as diagnostic and prognostic biomarkers, as well as potential therapeutic targets. We also outline current strategies for circRNA modulation, including suppression techniques like RNA interference and CRISPR/Cas systems, and overexpression methods using vectors and synthetic circRNAs.

OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of laryngologists and limited computer resources. We present the intelligent laryngeal cancer detection system (ILCDS), a deep learning-based solution tailored for effective LC screening in resource-constrained rural areas.
METHODS: We compiled a dataset comprised of 2023 laryngoscopic images and applied data augmentation techniques for dataset expansion. Subsequently, we utilized eight deep learning models-AlexNet, VGG, ResNet, DenseNet, MobileNet, ShuffleNet, Vision Transformer, and Swin Transformer-for LC identification. A comprehensive evaluation of their performances and efficiencies was conducted, and the most suitable model was selected to assemble the ILCDS.
RESULTS: Regarding performance, all models attained an average accuracy exceeding 90 % on the test set. Particularly noteworthy are VGG, DenseNet, and MobileNet, which exceeded an accuracy of 95 %, with scores of 95.32 %, 95.75 %, and 95.99 %, respectively. Regarding efficiency, MobileNet excels owing to its compact size and fast inference speed, making it an ideal model for integration into ILCDS.
CONCLUSIONS: The ILCDS demonstrated promising accuracy in LC detection while maintaining modest computational resource requirements, indicating its potential to enhance LC screening accuracy and alleviate the workload on otolaryngologists in rural areas.

The absence of improvement in survival rates across various cancers, including laryngeal cancer, has led to an increasing interest in understanding the immune response to cancer. In head and neck cancers, immune modulatory mechanisms such as immune microenvironment and immune infiltration are important in cancer pathogenesis. This study aims to explore the distribution of tumor-infiltrating lymphocyte (TIL) subgroups in the immune microenvironment and evaluate their impact on tumor histopathological characteristics and prognosis. The study included 50 patients who underwent laryngectomy for laryngeal squamous cell carcinoma, in Istanbul University - Cerrahpaşa, Faculty of Medicine Department of Otorhinolaryngology, between January 2016 and January 2018. Pathology specimens were evaluated using immunohistochemistry to assess the expressions of the CD3, CD20, CD8, CD4, CD25, and FoxP3 markers, identifying subgroups of TILs. The investigation aimed to uncover how these subgroups influence tumor histopathological features and survival outcomes. The high infiltration of CD3, CD20, and CD4 had a positive impact on disease-specific survival, disease-free survival, and recurrence-free survival. In addition, overall survival was positively affected by high CD3 and CD4 infiltrations. However, no significant relationship was observed between the expressions of CD8, FoxP3, and CD25 and any of the survival parameters. The infiltration of CD3, CD20, and CD4 positive cells indicative of a robust antitumoral immune response-emerged as favorable prognostic factors in laryngeal cancer. These findings suggest that enhancing the infiltration of CD3, CD20, and CD4 lymphocytes could be a therapeutic strategy worth exploring in clinical trials.

Laryngeal cancer (LC) represents a substantial world health problem, with diminished survival rates attributed to late-stage diagnoses. Correct treatment for LC is complex, particularly in the final stages. This kind of cancer is a complex malignancy inside the head and neck region of patients. Recently, researchers serving medical consultants to recognize LC efficiently develop different analysis methods and tools. However, these existing tools and techniques have various problems regarding performance constraints, like lesser accuracy in detecting LC at the early stages, additional computational complexity, and colossal time utilization in patient screening. Deep learning (DL) approaches have been established that are effective in the recognition of LC. Therefore, this study develops an efficient LC Detection using the Chaotic Metaheuristics Integration with the DL (LCD-CMDL) technique. The LCD-CMDL technique mainly focuses on detecting and classifying LC utilizing throat region images. In the LCD-CMDL technique, the contrast enhancement process uses the CLAHE approach. For feature extraction, the LCD-CMDL technique applies the Squeeze-and-Excitation ResNet (SE-ResNet) model to learn the complex and intrinsic features from the image preprocessing. Moreover, the hyperparameter tuning of the SE-ResNet approach is performed using a chaotic adaptive sparrow search algorithm (CSSA). Finally, the extreme learning machine (ELM) model was applied to detect and classify the LC. The performance evaluation of the LCD-CMDL approach occurs utilizing a benchmark throat region image database. The experimental values implied the superior performance of the LCD-CMDL approach over recent state-of-the-art approaches.

Nuclear protein in testis (NUT) carcinoma is a rare neoplasm arising mainly from midline structures. It is an aggressive type of carcinoma associated with poor survival despite the use of multiple treatment modalities. Here, we present a case of a 17-year-old paediatric patient with NUT carcinoma of larynx, which is even rarer among all reported cases. The patient underwent surgery followed by radiotherapy and systemic treatment and he died 15 months after the diagnosis. The management of this rare disease requires further investigation.