Machine Learning-Based Estimation of Hoarseness Severity Using Acoustic Signals Recorded During High-Speed Videoendoscopy.

Objectives: This study investigates the use of sustained phonations recorded during high-speed videoendoscopy (HSV) for machine learning-based assessment of hoarseness severity (H). The performance of this approach is compared with conventional recordings obtained during voice therapy to evaluate key differences and limitations of HSV-derived acoustic recordings.

Methods: A database of 617 voice recordings with a duration of 250 ms was gathered during HSV examination (HS).

Extent and Effect of Covering Laryngeal Structures with Synthetic Laryngeal Mucus via Two Different Administration Techniques.

Objective: The first goal of this study was to investigate the coverage of laryngeal structures using two potential administration techniques for synthetic mucus: inhalation and lozenge ingestion. As a second research question, the study investigated the potential effects of these techniques on standardized voice assessment parameters.

Methods: Fluorescein was added to throat lozenges and to an inhalation solution to visualize the coverage of laryngeal structures through blue light imaging.

Long-term performance assessment of fully automatic biomedical glottis segmentation at the point of care.

Deep Learning has a large impact on medical image analysis and lately has been adopted for clinical use at the point of care. However, there is only a small number of reports of long-term studies that show the performance of deep neural networks (DNNs) in such an environment. In this study, we measured the long-term performance of a clinically optimized DNN for laryngeal glottis segmentation.

A single latent channel is sufficient for biomedical glottis segmentation.

Glottis segmentation is a crucial step to quantify endoscopic footage in laryngeal high-speed videoendoscopy. Recent advances in deep neural networks for glottis segmentation allow for a fully automatic workflow. However, exact knowledge of integral parts of these deep segmentation networks remains unknown, and understanding the inner workings is crucial for acceptance in clinical practice.

OpenHSV: an open platform for laryngeal high-speed videoendoscopy.

High-speed videoendoscopy is an important tool to study laryngeal dynamics, to quantify vocal fold oscillations, to diagnose voice impairments at laryngeal level and to monitor treatment progress. However, there is a significant lack of an open source, expandable research tool that features latest hardware and data analysis. In this work, we propose an open research platform termed OpenHSV that is based on state-of-the-art, commercially available equipment and features a fully automatic data analysis pipeline.

Salvage laryngectomy after primary radio- and radiochemotherapy : A retrospective study.

Background: Recurrent and residual laryngeal cancer after organ-preserving radio- or radiochemotherapy is associated with a poor prognosis. Salvage surgery is the most important therapeutic option in these cases.

Objective: The study assessed rates of recurrence and residual tumor as well as survival and complication rates after salvage laryngectomy at the authors' academic cancer center.

A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis.

Purpose High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders because of the lack of dedicated software to analyze the data. HSV allows to quantify the vocal fold oscillations by segmenting the glottal area. This challenging task has been tackled by various studies; however, the proposed approaches are mostly limited and not suitable for daily clinical routine.

[Salvage laryngectomy after primary radio- and radiochemotherapy : A retrospective study. German version].

Background: Recurrent and residual laryngeal cancer after organ-preserving radio- or radiochemotherapy is associated with a poor prognosis. Salvage surgery is the most important therapeutic option in these cases.

Objective: The study assessed rates of recurrence and residual tumor as well as survival and complication rates after salvage laryngectomy at the authors' academic cancer center.

Interdependencies between acoustic and high-speed videoendoscopy parameters.

In voice research, uncovering relations between the oscillating vocal folds, being the sound source of phonation, and the resulting perceived acoustic signal are of great interest. This is especially the case in the context of voice disorders, such as functional dysphonia (FD). We investigated 250 high-speed videoendoscopy (HSV) recordings with simultaneously recorded acoustic signals (124 healthy females, 60 FD females, 44 healthy males, 22 FD males).

Machine learning based identification of relevant parameters for functional voice disorders derived from endoscopic high-speed recordings.

In voice research and clinical assessment, many objective parameters are in use. However, there is no commonly used set of parameters that reflect certain voice disorders, such as functional dysphonia (FD); i.e.

BAGLS, a multihospital Benchmark for Automatic Glottis Segmentation.

Laryngeal videoendoscopy is one of the main tools in clinical examinations for voice disorders and voice research. Using high-speed videoendoscopy, it is possible to fully capture the vocal fold oscillations, however, processing the recordings typically involves a time-consuming segmentation of the glottal area by trained experts. Even though automatic methods have been proposed and the task is particularly suited for deep learning methods, there are no public datasets and benchmarks available to compare methods and to allow training of generalizing deep learning models.

Determination of Clinical Parameters Sensitive to Functional Voice Disorders Applying Boosted Decision Stumps.

Background: Various voice assessment tools, such as questionnaires and aerodynamic voice characteristics, can be used to assess vocal function of individuals. However, not much is known about the best combinations of these parameters in identification of functional dysphonia in clinical settings.

Methods: This study investigated six scores from clinically commonly used questionnaires and seven acoustic parameters.

Secondary Tracheoesophageal Puncture After Laryngectomy Increases Complications With Shunt and Voice Prosthesis.

Objectives/hypothesis: To evaluate the demographics, clinical features, management, and prognostic indicators of tracheoesophageal puncture complications in patients undergoing placement of voice prosthesis following cancer treatment.

Study Design: Retrospective analysis.

Methods: A retrospective analysis was conducted of cases from a tertiary referral center diagnosed between 1996 and 2015.

Investigation of phonatory characteristics using ex vivo rabbit larynges.

Quantitative analysis of phonatory characteristics of rabbits has been widely neglected. However, preliminary studies established the rabbit larynx as a potential model of human phonation. This study reports quantitative data on phonation using ex vivo rabbit larynx models to achieve more insight into dependencies of three main components of the phonation process, including airflow, vocal fold dynamics, and the acoustic output.

Impact of Superparamagnetic Iron Oxide Nanoparticles on Vocal Fold Fibroblasts: Cell Behavior and Cellular Iron Kinetics.

Purpose: The voice is the most important instrument of communication. Tissue defects in the vocal fold (VF) area lead to serious reduction in quality of life, but thus far, no satisfactory VF implant exists. Therefore, we aim to establish a functional VF implant in a rabbit model by magnetic tissue engineering (MTE) using superparamagnetic iron oxide nanoparticles (SPION).

Optical π phase shift created with a single-photon pulse.

A deterministic photon-photon quantum logic gate is a long-standing goal. Building such a gate becomes possible if a light pulse containing only one photon imprints a phase shift of π onto another light field. We experimentally demonstrate the generation of such a π phase shift with a single-photon pulse.

Effect of BSA-coated Superparamagnetic Iron Oxide Nanoparticles on Granulosa Cells.

Background: Since superparamagnetic iron oxide nanoparticles (SPION) possess unique features, they provide a huge platform for medical applications, especially for cancer diagnosis and therapy (e.g. imaging, and drug targeting).

Magnetic Tissue Engineering for Voice Rehabilitation - First Steps in a Promising Field.

Background/aim: The voice is one of the most important instruments of communication between humans. It is the product of intact and well-working vocal folds. A defect of these structures causes dysphonia, associated with a clear reduction of quality of life.

Magnetic nanoparticle-based drug delivery for cancer therapy.

Nanoparticles have belonged to various fields of biomedical research for quite some time. A promising site-directed application in the field of nanomedicine is drug targeting using magnetic nanoparticles which are directed at the target tissue by means of an external magnetic field. Materials most commonly used for magnetic drug delivery contain metal or metal oxide nanoparticles, such as superparamagnetic iron oxide nanoparticles (SPIONs).

Boron containing magnetic nanoparticles for neutron capture therapy--an innovative approach for specifically targeting tumors.

The selective delivery of (10)B into the tumor tissue remains to be further improved for successful and reliable Boron Neutron Capture Therapy applications. Magnetic Drug Targeting using intraarterially administered superparamagnetic nanoparticles and external magnetic fields already exhibited convincing results in terms of highly efficient and selective drug deposition. Using the same technique for the targeted (10)B delivery is a promising new approach.

Flow cytometry for intracellular SPION quantification: specificity and sensitivity in comparison with spectroscopic methods.

Due to their special physicochemical properties, iron nanoparticles offer new promising possibilities for biomedical applications. For bench to bedside translation of super-paramagnetic iron oxide nanoparticles (SPIONs), safety issues have to be comprehensively clarified. To understand concentration-dependent nanoparticle-mediated toxicity, the exact quantification of intracellular SPIONs by reliable methods is of great importance.

Single-photon transistor using a Förster resonance.

An all-optical transistor is a device in which a gate light pulse switches the transmission of a target light pulse with a gain above unity. The gain quantifies the change of the transmitted target photon number per incoming gate photon. We study the quantum limit of one incoming gate photon and observe a gain of 20.

Development and characterization of magnetic iron oxide nanoparticles with a cisplatin-bearing polymer coating for targeted drug delivery.

A highly selective and efficient cancer therapy can be achieved using magnetically directed superparamagnetic iron oxide nanoparticles (SPIONs) bearing a sufficient amount of the therapeutic agent. In this project, SPIONs with a dextran and cisplatin-bearing hyaluronic acid coating were successfully synthesized as a novel cisplatin drug delivery system. Transmission electron microscopy images as well as X-ray diffraction analysis showed that the individual magnetite particles were around 4.

Single-photon switch based on Rydberg blockade.

All-optical switching is a technique in which a gate light pulse changes the transmission of a target light pulse without the detour via electronic signal processing. We take this to the quantum regime, where the incoming gate light pulse contains only one photon on average. The gate pulse is stored as a Rydberg excitation in an ultracold atomic gas using electromagnetically induced transparency.

Efficient drug-delivery using magnetic nanoparticles--biodistribution and therapeutic effects in tumour bearing rabbits.

Unlabelled: To treat tumours efficiently and spare normal tissues, targeted drug delivery is a promising alternative to conventional, systemic administered chemotherapy. Drug-carrying magnetic nanoparticles can be concentrated in tumours by external magnetic fields, preventing the nanomaterial from being cleared by metabolic burden before reaching the tumour. Therefore in Magnetic Drug Targeting (MDT) the favoured mode of application is believed to be intra-arterial.