Revealing molecular and cellular heterogeneity in hypopharyngeal carcinogenesis through single-cell RNA and TCR/BCR sequencing.

Introduction: Hypopharyngeal squamous cell carcinoma (HSCC) is one of the malignant tumors with the worst prognosis in head and neck cancers. The transformation from normal tissue through low-grade and high-grade intraepithelial neoplasia to cancerous tissue in HSCC is typically viewed as a progressive pathological sequence typical of tumorigenesis. Nonetheless, the alterations in diverse cell clusters within the tissue microenvironment (TME) throughout tumorigenesis and their impact on the development of HSCC are yet to be fully understood.

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

Objective: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL).

Methods: The AI system was developed, trained and validated on 5362 images of 551 patients from three hospitals. Automated regions of interest (ROI) segmentation algorithm was utilized to construct image-level features.

Narrow band imaging-based radiogenomics for predicting radiosensitivity in nasopharyngeal carcinoma.

Objectives: This study aims to assess the efficacy of narrow band imaging (NBI) endoscopy in utilizing radiomics for predicting radiosensitivity in nasopharyngeal carcinoma (NPC), and to explore the associated molecular mechanisms.

Materials: The study included 57 NPC patients who were pathologically diagnosed and underwent RNA sequencing. They were categorized into complete response (CR) and partial response (PR) groups after receiving radical concurrent chemoradiotherapy.

Laryngoscopy-based scoring system for the diagnosis of vocal fold leukoplakia.

Objective: To propose a scoring system based on laryngoscopic characteristics for the differential diagnosis of benign and malignant vocal fold leukoplakia.

Methods: Laryngoscopic images from 200 vocal fold leukoplakia cases were retrospectively analysed. The laryngoscopic signs of benign and malignant vocal fold leukoplakia were compared, and statistically significant features were assigned and accumulated to establish the leukoplakia finding score.

Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

Objectives: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to monitor blind spots during esophagogastroduodenoscopy. This study aimed to test the performance of AI-driven intelligent laryngoscopy monitoring assistant (ILMA) for landmark anatomical sites identification on laryngoscopic images and videos based on a convolutional neural network (CNN).

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow-Band Imaging Endoscopy.

Objectives/hypothesis: To develop a deep-learning-based automatic diagnosis system for identifying nasopharyngeal carcinoma (NPC) from noncancer (inflammation and hyperplasia), using both white light imaging (WLI) and narrow-band imaging (NBI) nasopharyngoscopy images.

Study Design: Retrospective study.

Methods: A total of 4,783 nasopharyngoscopy images (2,898 WLI and 1,885 NBI) of 671 patients were collected and a novel deep convolutional neural network (DCNN) framework was developed named Siamese deep convolutional neural network (S-DCNN), which can simultaneously utilize WLI and NBI images to improve the classification performance.

Laryngoscopic characteristics related to the risk of cancerization of vocal cord leukoplakia.

Background: The diagnosis of vocal cord leukoplakia mainly relies on laryngoscopy. The morphology of vocal cord leukoplakia under laryngoscope is closely related to the pathological nature of leukoplakia. The specific manifestations associated with high-risk vocal cord leukoplakia remain to be explored.

Diagnosis of vocal cord leukoplakia: The role of a novel narrow band imaging endoscopic classification.

Objectives: The purpose of this study was to introduce a new narrow band imaging (NBI) endoscopic classification for the diagnosis of vocal cord leukoplakia.

Study Design: Case series.

Methods: From January 2010 to February 2018, a total of 120 cases of vocal cord leukoplakia were enrolled in this study.

[Clinical features and prognostic factors in patients with leptomeningeal metastases].

Objective: To investigate the clinical characteristics and prognostic factors of leptomeningeal metastases (LM) from solid tumors and to develop better treatment strategies.

Methods: The clinical characteristics and follow-up results of 77 cases of leptomeningeal metastases (LM) from solid tumors diagnosed and treated in our hospital from 2002 to 2011 were retrospectively analyzed. Clinical characteristics, treatment methods and overall survival were analyzed using Kaplan-Meier method and Cox regression model.

[Relationship of serum level of creatine kinase of MB type to cardiac function of patients with advanced tumors and its prognostic value].

Background & Objective: Patients with advanced tumors usually suffer from cardiac dysfunction. Monitoring cardiac function is important for these patients. Serum creatine kinase of MB type (CK-MB) is a biochemical marker of cardiac damage.