Artificial larynx

Explainable Artificial Intelligence (XAI) is becoming a disruptive trend in healthcare, allowing for transparency and interpretability of autonomous decision-making. In this study, we present an innovative application of a rule-based classification model to identify the main causes of chronic cough-related quality of life (QoL) impairment in a cohort of asthmatic patients. The proposed approach first involves the design of a suitable symptoms questionnaire and the subsequent analyses via XAI. Specifically, feature ranking, derived from statistically validated decision rules, helped in automatically identifying the main factors influencing an impaired QoL: pharynx/larynx and upper airways when asthma is under control, and asthma itself and digestive trait when asthma is not controlled...

AIMS: The Post-extubation Assessment of Laryngeal Symptoms and Severity (PALSS) study systematically evaluates patient symptoms related to endotracheal intubation with mechanical ventilation, assesses laryngeal injury and voice function after extubation, and develops a screening tool to identify patients with clinically important, post-extubation laryngeal injury. DESIGN: Single-center, prospective observational cohort study conducted in 6 intensive care units (ICU)...

OBJECTIVES: This study aimed to establish an artificial intelligence (AI) system to classify vertical level differences between vocal folds during vocalization and to evaluate the accuracy of the classification. METHODS: We designed models with different depths between the right and left vocal folds using an excised canine larynx. Video files for the data set were obtained using a high-speed camera system and a color complementary metal oxide semiconductor camera with global shutter...

BACKGROUND: The Newcastle Laryngeal Hypersensitivity Questionnaire (LHQ) was developed to measure abnormal laryngeal sensation and was originally validated in a patient sample from otolaryngologic and respiratory outpatient clinics. Modification is needed for patients who are mechanically ventilated via an endotracheal tube or a tracheostomy tube. OBJECTIVES: We sought to adapt and preliminarily validate a modified version of the LHQ appropriate for nurses and other clinicians to administer in acute hospital settings called the LHQ-Acute (LHQ-A)...

OBJECTIVES: FEES is a standard procedure for diagnosing dysphagia. However, appropriate evaluation of FEES findings is difficult for inexperienced evaluators. Recent progress in deep learning has highlighted the use of artificial intelligence-assisted computer-aided diagnosis (AI-assisted CAD) in medical applications. We investigated the detection accuracy of FEES findings evaluated by inexperienced evaluators with and without the use of CAD. METHODS: The algorithm for FEES-CAD was developed using 25,630 expert-annotated images...

Early larynx cancer detection plays a crucial role in improving treatment outcomes and recent studies have shown promising results in using artificial intelligence for larynx cancer detection. Artificial intelligence also has the potential to enhance transoral larynx microsurgery. This narrative review summarizes the current evidence regarding its use in larynx cancer detection and potential applications in transoral larynx microsurgery. The utilization of artificial intelligence in larynx cancer detection with white light endoscopy and narrow-band imaging helps improve diagnostic accuracy and efficiency...

Synthetic silicone larynx models are essential for understanding the biomechanics of physiological and pathological vocal fold vibrations. The aim of this study is to investigate the effects of artificial ligament fibers on vocal fold vibrations in a synthetic larynx model, which is capable of replicating physiological laryngeal functions such as elongation, abduction, and adduction. A multi-layer silicone model with different mechanical properties for the musculus vocalis and the lamina propria consisting of ligament and mucosa was used...

OBJECTIVE: Transoral surgery (TOS) is a widely used treatment for laryngopharyngeal cancer. There are some difficult cases of setting the extent of resection in TOS, particularly in setting the vertical margins. However, positive vertical margins require additional treatment. Further, excessive resection should be avoided as it increases the risk of bleeding as a postoperative complication and may lead to decreased quality of life, such as dysphagia. Considering these issues, determining the extent of resection in TOS is an important consideration...

PURPOSE/OBJECTIVE(S): Adaptive radiation therapy (ART) has emerged as a promising method to modify treatment plans in response to structural and spatial changes that occur during a treatment course. In particular, patients with locally advanced Head and Neck (HN) Cancers often experience changes in target volumes and organs-at risk requiring replanning throughout treatment. The implementation of daily ART using daily cone-beam Cone-Beam CT (CBCT) imaging is a solution that may improve the therapeutic ratio by accounting for intra-fractional changes throughout the patient's treatment course...

PURPOSE/OBJECTIVE(S): Patients that undergo head and neck (H&N) radiation therapy (RT) require laborious delineation of organs-at-risk (OARs) on computed tomography (CT) scans in a treatment planning system (TPS) to minimize radiation to normal tissue. This task can be completed rapidly and accurately with recently developed artificial intelligence-based semantic segmentation models. The current study aims to deploy and evaluate a strategy for improving clinical practice with this technology...

Gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) analyses are two contemporary computational methods that can identify discrete changes in cell and tissue textural features. Previous research has indicated that these methods may be applicable in the pathology for identification and classification of various types of cancers. In this study, we present findings that squamous epithelial cells in laryngeal carcinoma, which appear morphologically intact during conventional pathohistological evaluation, have distinct nuclear GLCM and DWT features...

PROBLEM: Artificial intelligence has been widely investigated for diagnosis and treatment strategy design, with some models proposed for detecting oral pharyngeal, nasopharyngeal, or laryngeal carcinoma. However, no comprehensive model has been established for these regions. AIM: Our hypothesis was that a common pattern in the cancerous appearance of these regions could be recognized and integrated into a single model, thus improving the efficacy of deep learning models...

OBJECTIVE: We aimed to determine patterns of alaryngeal voice acquisition and predictive factors of vocal rehabilitation (VR) failure following total laryngectomy (TL) at a large Canadian tertiary care center. METHODS: All consecutive patients having undergone a TL between January 1st, 2011 and December 31st, 2019, at the Centre Hospitalier de l'Université de Montréal were included. RESULTS: One hundred and ninety-seven laryngectomized patients were identified...

We aimed to assess the feasibility of using confocal laser scanning microscopy (CLSM) for the real-time ex vivo examination of histological samples of laryngeal lesions and to evaluate the correlation between CLSM and definitive histological results. This preliminary study included eight consecutive patients with "suspected" laryngeal lesions who were candidates for endoscopic laryngeal surgery. The obtained samples were evaluated using CLSM and classified as "inadequate" or "adequate" (high- and low-grade dysplasia, in situ and invasive carcinoma, positive surgical margin, and inflammatory outbreaks)...

OBJECTIVE: To achieve instance segmentation of upper aerodigestive tract (UADT) neoplasms using a deep learning (DL) algorithm, and to identify differences in its diagnostic performance in three different sites: larynx/hypopharynx, oral cavity and oropharynx. METHODS: A total of 1034 endoscopic images from 323 patients were examined under narrow band imaging (NBI). The Mask R-CNN algorithm was used for the analysis. The dataset split was: 935 training, 48 validation and 51 testing images...

BACKGROUND: The objective of this study was to assess the performance and application of a self-developed deep learning (DL) algorithm for the real-time localization and classification of both vocal cord carcinoma and benign vocal cord lesions. METHODS: The algorithm was trained and validated upon a dataset of videos and photos collected from our own department, as well as an open-access dataset named "Laryngoscope8". RESULTS: The algorithm correctly localizes and classifies vocal cord carcinoma on still images with a sensitivity between 71% and 78% and benign vocal cord lesions with a sensitivity between 70% and 82%...

PURPOSE: Elective neck irradiation (ENI) has long been considered mandatory when treating head and neck squamous cell carcinoma (HNSCC) with definitive radiotherapy, but it is associated with significant dose to normal organs-at-risk (OAR). In this prospective phase II study, we investigated the efficacy and tolerability of eliminating ENI and strictly treating involved and suspicious lymph nodes (LN) with intensity-modulated radiotherapy. PATIENTS AND METHODS: Patients with newly diagnosed HNSCC of the oropharynx, larynx, and hypopharynx were eligible for enrollment...

Most recent survival prediction has been based on TNM staging, which does not provide individualized information. However, clinical factors including performance status, age, sex, and smoking might influence survival. Therefore, we used artificial intelligence (AI) to analyze various clinical factors to precisely predict the survival of patients with larynx squamous cell carcinoma (LSCC). We included patients with LSCC (N = 1026) who received definitive treatment from 2002 to 2020. Age, sex, smoking, alcohol consumption, Eastern Cooperative Oncology Group (ECOG) performance status, location of tumor, TNM stage, and treatment methods were analyzed using deep neural network (DNN) with multi-classification and regression, random survival forest (RSF), and Cox proportional hazards (COX-PH) model for prediction of overall survival...

OBJECTIVE: The endoscopic and laryngoscopic examination is paramount for laryngeal, oropharyngeal, nasopharyngeal, nasal, and oral cavity benign lesions and cancer evaluation. Nevertheless, upper aerodigestive tract (UADT) endoscopy is intrinsically operator-dependent and lacks objective quality standards. At present, there has been an increased interest in artificial intelligence (AI) applications in this area to support physicians during the examination, thus enhancing diagnostic performances...

Voice restoration following laryngectomy has a significant influence on quality of life (QOL). Three main techniques exist to provide voice: esophageal speech (ES), artificial larynx (electrolarynx [EL]), and tracheoesophageal puncture (TEP). Although the EL was historically the most used technique, TEP has quickly become the gold standard. ES remains the least frequently used technique in developed countries. Technique selection must be made on an individual basis, considering the patient's cancer history and comorbidities...