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Objectives: Nowadays, complementary treatments, particularly traditional treatments for voice disorders, have gained significant importance. Among these, herbal treatments, such as those utilizing the Echinops plant, warrant further investigation. This study examined the effects of laryngeal manual therapy, both alone and in combination with the Echinops plant treatment, by analyzing changes in mean values before and after treatment.
Study Design: Randomized Double-Blind Clinical Trial MATERIALS AND METHODS: The participants in the study were 40 patients suffering from Muscle Tension Dysphonia (MTD). The scores of Dysphonia Severity Index (DSI), Vocal Tract Discomfort (VTD), and Visual Analog Scale (VAS) were evaluated before and after the intervention. The participants were divided into two groups. The first group received laryngeal manual therapy, while the second group received both laryngeal manual therapy and the Echinops medication. Both groups underwent laryngeal manual therapy twice a week for ten sessions. However, the intervention group additionally received Echinops medication twice a day for 1 month. The results were analyzed separately within each group and between the two treatment groups.
Results: DSI, VTD, and VAS indicators were associated with an improvement in the mean scores in both the laryngeal manual therapy group and the combined laryngeal manual therapy before and after treatment. Additionally, the combined laryngeal therapy group demonstrated an increase in the mean scores for all indicators except for the pain index during vocalization.
Conclusion: These results suggest that the medicinal treatment derived from the Echinops plant may facilitate more rapid recovery from inflammation, consequently improving voice quality.
Clinical Trial Code: 67406, Iranian Registry of Clinical Trials.
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http://dx.doi.org/10.1016/j.jvoice.2025.06.018 | DOI Listing |
Laryngoscope
September 2025
Department of Otolaryngology-Head and Neck Surgery, Massachusetts Eye & Ear, Boston, Massachusetts, USA.
Objectives: Major advancements have been made in applying artificial intelligence and computer vision to analyze videolaryngoscopy data. These models are limited to post hoc analysis and are aimed at research settings. In this work, we assess the feasibility of a real-time solution for automated vocal fold tracking during in-office laryngoscopy.
View Article and Find Full Text PDFMed Dosim
August 2025
Department of Radiation Medicine, University of Kentucky, Lexington, KY 40536, USA. Electronic address:
Demonstrating the feasibility of dose escalation for stereotactic recurrent head and neck (RHN) cancers with a HyperArc-based RapidPlan (HARP) model using custom Simultaneous Integrated Boost Injector (SIBI) through Eclipse Scripting API (ESAPI) to facilitate automated treatment planning. Five previously treated RHN patients prescribed 30 to 35 Gy in 3 or 5 fractions, four single-lesion and one two-lesion, were retrospectively replanned with HyperArc geometry on a TrueBeam LINAC (6MV-FFF) using a HARP model with SIBI to escalate tumor dose. Escalation was achieved through the GTV and a central hotspot optimization structure being pushed toward 130% and 140% the prescription dose, respectively.
View Article and Find Full Text PDFIndian J Otolaryngol Head Neck Surg
August 2025
Department of Radiology, Shirdi Sai Baba Cancer Hospital and Research Centre, Manipal, Karnataka 576104 India.
Unlabelled: Laryngeal cancer, one of the top three head and neck cancers, requires timely diagnosis and staging for effective management and improved patient outcomes. Thyroid cartilage penetration indicates advanced cancer and is crucial for treatment planning. However, identifying cartilage abnormalities on CT images is challenging due to age-related changes, and use of machine learning (ML) models has been proposed as a possible way forward.
View Article and Find Full Text PDFFront Digit Health
July 2025
Faculty of Engineering and Science, Western Norway University of Applied Sciences, Bergen, Vestland, Norway.
Manual diagnostic methods for assessing exercise-induced laryngeal obstruction (EILO) contain human bias and can lead to subjective decisions. Several studies have proposed machine learning methods for segmenting laryngeal structures to automate and make diagnostic outcomes more objective. Four state-of-the-art models for laryngeal image segmentation are implemented, trained, and compared using our pre-processed dataset containing laryngeal images derived from continuous laryngoscopy exercise-test (CLE-test) data.
View Article and Find Full Text PDFCureus
June 2025
Department of Anesthesia, University of Iowa, Iowa City, USA.
Introduction Changes in a patient's position from supine to upright may alter the forces exerted by the endotracheal tube (ETT) on the larynx and potentially increase intracuff pressure. This study aimed to investigate whether positional changes from the supine to the beach chair position lead to an increase in intracuff pressure. Additionally, we examined whether the intracuff pressure, when the cuff is inflated using an air syringe, is within the recommended safe range (20-30 cm H₂O) both in the supine position after intubation and after transitioning to the beach chair position.
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