Clinical Development of Deep Learning for the OtoSight

Clinical Development and Evaluation of a Deep Learning Approach to Improve Diagnostic Accuracy

The objective of this study is to clinically develop and evaluate a machine learning approach to improve the performance and data interpretation of the PhotoniCare OtoSight Middle Ear Scope in pediatric patients presenting at the primary care office for suspected ear infections. In this observational study, results of OtoSight imaging will not affect patient standard of care.

Study Overview

• Status: Completed
• Conditions: Otitis Media Acute
• Intervention / Treatment: Device: PhotoniCare OtoSight Middle Ear Scope

• Study Type: Observational
• Enrollment (Actual): 188

Contacts and Locations

Study Locations

• United States
  • Pennsylvania
    • Pittsburgh, Pennsylvania, United States, 15213
      • Children's Hospital of Pittsburgh

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 6 months to 4 years (Child)
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

Children presenting to the pediatric clinic with suspected ear infection

Description

Inclusion Criteria:

• Pediatric patients presenting for an office visit with ear-related complaints

Exclusion Criteria:

• Otoscopy contra-indicated or not possible per attending clinician's decision, Down's syndrome (due to abnormalities in ear canal anatomy)

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Pediatric patients with possible ear infections; Pediatric patients presenting with otitis media (acute otitis media or otitis media with effusion) will be imaged with the PhotoniCare OtoSight.	Device: PhotoniCare OtoSight Middle Ear Scope; PhotoniCare OtoSight imaging using a near-infrared laser

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
PhotoniCare OtoSight imaging exam	Optical coherence tomography imaging to evaluate the middle ear.	1-5 minutes; at first and only study visit

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Adverse events	Rate of adverse events	15-30 minutes; at first and only study visit

Collaborators and Investigators

• Sponsor: PhotoniCare, Inc.
• Collaborators: University of Pittsburgh; National Institute on Deafness and Other Communication Disorders (NIDCD)
• Investigators: Principal Investigator: Ryan Shelton, PhD, PhotoniCare, Inc.

Study record dates

Study Major Dates

• Study Start (Actual): January 19, 2021
• Primary Completion (Actual): September 2, 2022
• Study Completion (Actual): August 31, 2023

Study Registration Dates

• First Submitted: January 20, 2021
• First Submitted That Met QC Criteria: January 20, 2021
• First Posted (Actual): January 25, 2021

Study Record Updates

• Last Update Posted (Actual): January 23, 2024
• Last Update Submitted That Met QC Criteria: January 22, 2024
• Last Verified: May 1, 2023

More Information

Terms related to this study

• Keywords: Otitis Media; Machine Learning; Ear Infection; Otitis Media with Effusion
• Additional Relevant MeSH Terms: Otorhinolaryngologic Diseases; Ear Diseases; Otitis; Otitis Media
• Other Study ID Numbers: 000002; R44DC017422 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: Yes