Clinical Trials Logo

Clinical Trial Summary

Feasibility of structural and functional imaging of the middle ear and its constituents by optical coherence tomography.


Clinical Trial Description

Rationale: Various middle ear diseases can affect anatomical structures of the middle ear in different ways. Unfortunately, current methods for assessing the structure and function of the constituents of the middle ear are limited and often fail to provide all clinically relevant data. Optical coherence tomography (OCT) is a technology that can provide valuable, additional information with a newly developed prototype OCT-device for structural and functional imaging of the middle ear. Objective: To assess the feasibility and the clinical potential of structural and functional OCT imaging with a newly developed OCT-device in patients with various middle ear problems. Study design: Observational study Study population: Adult patients presenting with various middle ear complaints at the Ear Nose Throat department of the Department of Otorhinolaryngology and Head and Neck Surgery, Erasmus Medical Center, Rotterdam, the Netherlands. Main study parameters/endpoints: Percentage of patients in which structural OCT imaging was feasible (i.e., the OCT images showed a discernible tympanic membrane (TM) and at least one of the ossicles). Nature and extent of the burden and risks associated with participation, benefit and group relatedness: The burden is minimal: patient examination with Aurisvue is similar to the conventional examination with a standard otoscope and will take approximately 5 to 10 minutes. The risks are negligible: imaging is done with light levels well below the maximum permissible exposure level and sound levels to induce movement of the TM and the ossicular chain are well below the hazardous threshold. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05445388
Study type Interventional
Source Erasmus Medical Center
Contact
Status Not yet recruiting
Phase N/A
Start date August 1, 2022
Completion date December 1, 2023

See also
  Status Clinical Trial Phase
Completed NCT03291964 - Rapid MRI for Acute Pediatric Head Trauma
Completed NCT03129516 - Turkish Version of the Movement Imagery Questionnaire-3 N/A
Recruiting NCT04214522 - Reliability and Validity of the Kinesthetic and Visual Imagery Questionnaire in Acute Stroke Patients
Terminated NCT03219567 - Whole Eye Optical Coherence Tomography (OCT) to Improve Refractive Surgery and Eye Care
Completed NCT04193072 - Imagery Ability in Obstetric Brachial Plexus Palsy
Completed NCT05196776 - Diagnostic Accuracy of Handheld vs Traditional Ultrasound N/A
Recruiting NCT05353309 - Iliac Angioplasties: Impact of the Fusion of Images on the Irradiation Rate N/A
Recruiting NCT05355558 - A Novel Functional Imaging Technique With FLT-PET/MRI For Staging, Response Assessment and Radiation Treatment Planning in Cervix Cancer N/A
Recruiting NCT04944680 - Dual Channel Rehabilitation Technology Promotes Rapid Recovery of Upper Limbs After Stroke N/A
Completed NCT05215938 - Evaluation of Intra Organ Sodium Levels by Magnetic Resonance Imaging
Recruiting NCT04490317 - CARbon monoxidE intoxiCatiOn in Korea: Prospective Cohort (CARE CO Cohort)
Completed NCT03870932 - Effects of a Motor Imagery Exercise Protocol in Patients With Fibromyalgia N/A
Not yet recruiting NCT05999565 - Investigation of the Effect of Motor Imagery Training in Individuals With Cervical Discogenic Pain N/A
Completed NCT04009356 - Impact of Bariatric Surgery in Patients With Morbid Obesity
Completed NCT03120858 - Turkish Version of the Kinesthetic and Visual Imagery Questionnaire N/A
Recruiting NCT05622565 - Explainable Ocular Fundus Diseases Report Generation System
Completed NCT03648151 - Influence of PET/CT Radiomic Features on the Outcome of Lung Cancer Patients
Recruiting NCT04528875 - Augmenting Ultrasound Imaging in Order to Replace Fluoroscopy in Image Guided Pain Procedures
Recruiting NCT05215132 - Investigational MRI Clinical Software and Hardware Phase 4
Not yet recruiting NCT04461990 - Clinical Study of Imaging Genomics Based on Machine Learning for BCIG