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ORL J Otorhinolaryngol Relat Spec
January 2025
Introduction Laryngeal cancer (LC) is the most common malignancy in otolaryngology, comprising 30-40% of head and neck malignancies. With an increasing incidence worldwide over the past few decades, LC has resulted in substantial strain on the NHS. There have been notable advancements in the treatment of LC over the years, particularly with the adoption of non-surgical methods, which emerged after the 1991 study conducted by the Veterans Affairs.
View Article and Find Full Text PDFBMJ Open
December 2024
Department of Head and Neck Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Objectives: To evaluate the effectiveness of nurse-led coaching in self-care (SC) interventions for elderly patients undergoing total laryngectomy (TL) using multidimensional parameters.
Design: This was a double-arm randomised, single-centre trial that met the requirements of the CONSORT statement.
Setting: Head and neck department in a tertiary A-level hospital.
Oral Oncol
January 2025
Department of Otolaryngology - Head & Neck Surgery Foch Hospital Suresnes France; School of Medicine, UFR Simone Veil, Université Versailles Saint-Quentin-en-Yvelines (Paris Saclay University), 2 Av. de la Source de la Bièvre 78 180 Montigny-le-Bretonneux, France; Phonetics and Phonology Laboratory (UMR 7018 CNRS & Université Sorbonne nouvelle), Paris, France.
Objective: To compare the surgical, functional and oncological outcomes of Transoral Laser Microsurgery (TLM) and Transoral Robotic Surgery (TORS) for the treatment of supraglottic squamous cell carcinoma.
Study Design: Retrospective case series with prospective data.
Settings: Tertiary Academic Medical Center.
Head Neck
January 2025
THANC (Thyroid, Head and Neck Cancer) Foundation, New York, New York, USA.
Tracheoesophageal puncture (TEP) with voice prosthesis (VP) placement is commonly used to restore voice in laryngectomy patients. The conventional procedure utilizes a rigid esophagoscope to open and visualize the pharyngeal inlet. However, this approach is challenging in patients with postradiation changes, reduced neck extension, or trismus.
View Article and Find Full Text PDFInt J Radiat Oncol Biol Phys
January 2025
Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.
Purpose: Deep learning is a promising approach to increase reproducibility and time-efficiency of GTV delineation in head and neck cancer, but model evaluation primarily relies on manual GTV delineations as reference annotation, which are subjective and tend to overestimate tumor volume. This study aimed to validate a deep learning model for laryngeal and hypopharyngeal GTV segmentation with pathology and to compare its performance with clinicians' manual delineations.
Materials And Methods: A retrospective dataset of 193 laryngeal and hypopharyngeal cancer patients was used to train a deep learning model with clinical GTV delineations as reference.
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