AI Diagnostic Support for Ear Infections

(IMAGE Trial)

Not yet recruiting at 1 trial location

Overseen By Nader Shaikh, MD, MPH

Age: < 18

Sex: Any

Trial Phase: Academic

Sponsor: Timothy Shope

Must not be taking: Antimicrobials

Disqualifiers: No URI, Otorrhea, Tympanostomy tubes

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 2

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial examines a new method for diagnosing ear infections in young children using an AI app. The goal is to determine if this app, which analyzes photos of eardrums, can enhance doctors' ability to diagnose and treat ear infections in children with cold symptoms. The trial aims to ensure antibiotics are used only when necessary. It is suitable for children aged 6-24 months with a cold or similar upper respiratory symptoms. As an unphased trial, this study provides a unique opportunity to contribute to innovative research that could improve diagnostic methods for young children.

Will I have to stop taking my current medications?

The trial does not specify if you need to stop taking your current medications, but if your child is currently taking antimicrobials (medications that kill or stop the growth of microorganisms), they cannot participate in the study.

What prior data suggests that this AI app is safe for diagnosing ear infections in children?

Studies have shown that the AI app used to diagnose ear infections is very accurate. This tool analyzes short videos of the eardrum taken during an exam, aiding doctors in making more accurate diagnoses of ear infections. Past research indicates that the app performs well and could be highly beneficial in clinics.

Since the AI app only reviews images and does not directly treat patients, no reports of harm or side effects exist. It simply assists doctors in making more informed decisions. Having been tested for accuracy and showing promise in diagnosing ear infections, it appears safe for use in studies like this one. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Most treatments for ear infections involve a clinical exam by a doctor who visually examines the ear and decides on a treatment, often antibiotics. But this new AI app offers something different. It uses artificial intelligence to assist in diagnosing ear infections, potentially increasing accuracy and consistency. Researchers are excited because the AI app provides a second opinion alongside the standard exam, which could lead to better treatment decisions and reduce unnecessary antibiotic use. Plus, it's a tech-forward approach that might streamline the diagnostic process for busy clinics.

What evidence suggests that this AI app is effective for diagnosing ear infections?

In this trial, participants will have their ear infections diagnosed using both an AI app and a standard clinical exam. Studies have shown that the AI app excels at diagnosing ear infections, particularly acute otitis media (AOM), in children. Research suggests that this AI tool can sometimes outperform trained doctors in identifying these infections. Using the app may reduce unnecessary antibiotic use by ensuring antibiotics are only prescribed for actual infections. The app also allows users to save and share videos of the diagnosis, aiding learning and improving diagnostic accuracy. Overall, this app represents a promising advancement in accurately and efficiently diagnosing ear infections in young children. ^{5 6 7 8 9}

Who Is on the Research Team?

Timothy R Shope, MD, MPH

Principal Investigator

UPMC Children's Hospital

Are You a Good Fit for This Trial?

This trial is for young children aged 6-24 months who are showing symptoms of upper respiratory infections, such as colds or swimmer's ear. The study aims to include those who may have difficulty with traditional ear exams due to small ear canals or restlessness.

Inclusion Criteria

I currently have an upper respiratory infection.

My child is between 6 to 24 months old.

Exclusion Criteria

I do not have an upper respiratory infection.

I am currently on antibiotics.

Presence of tympanostomy tubes

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

1 visit (in-person)

Enrollment and Initial Assessment

Participants undergo initial ear examination using the AI app and standard clinical exam

1 day

1 visit (in-person)

Follow-up

Participants are monitored for symptom resolution and side effects of antimicrobial use

10 days

Daily symptom monitoring (remote)

Extended Follow-up

Participants are monitored for acute otitis media recurrences

3 months

What Are the Treatments Tested in This Trial?

Interventions

• AI app

Trial Overview

The trial is testing the effectiveness of an AI app in diagnosing ear infections compared to standard clinical exams. Photos of eardrums taken during visits will be analyzed by the AI to see if it changes diagnosis and treatment decisions.

How Is the Trial Designed?

Group I: AI App + Standard of care clinical exam Experimental Treatment 2 Interventions

Using a within subject design, each child's ear will be in the experimental and standard care group. Each ear will be examined by the AI app and a clinician (blinded to the AI app diagnosis) to provide a diagnosis and treatment recommendation.

Who Is Running the Clinical Trial?

Timothy Shope

Lead Sponsor

Trials

1

Recruited

300+

Merck Sharp & Dohme LLC

Industry Sponsor

Trials

4,096

Recruited

5,232,000+

Chirfi Guindo

Merck Sharp & Dohme LLC

Chief Marketing Officer since 2022

Degree in Engineering from Ecole Centrale de Paris, MBA from New York University Stern School of Business

Robert M. Davis

Merck Sharp & Dohme LLC

Chief Executive Officer since 2021

JD from Northwestern University Pritzker School of Law, MBA from Northwestern University Kellogg Graduate School of Management, Bachelor's in Finance from Miami University

Published Research Related to This Trial

A new handheld optical coherence tomography (OCT) system can non-invasively assess middle ear infections by detecting effusions and bacterial biofilms, improving upon traditional subjective diagnostic methods.

The integration of a real-time machine learning classifier allows for consistent and accurate categorization of middle ear conditions, making the OCT system more user-friendly and effective for diagnosing infections in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Handheld Briefcase Optical Coherence Tomography with Real-Time Machine Learning Classifier for Middle Ear Infections. Won, J., Monroy, GL., Dsouza, RI., et al.[2021]

Citations

1.

upmcphysicianresources.com

upmcphysicianresources.com/news/030424-ai-tool

New AI Smartphone Tool Accurately Diagnoses Ear ...

The new AI tool offers a simple and effective solution that could be more accurate than trained clinicians.

2.

health.pitt.edu

health.pitt.edu/news/pitt-led-team-s-ai-phone-app-diagnoses-kids-ear-infections

Pitt-Led Team's AI Phone App Diagnoses Kids' Ear Infections

A new smartphone app that uses artificial intelligence (AI) to accurately diagnose ear infections, or acute otitis media (AOM), could help decrease unnecessary ...

3.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC11200698/

Smartphone-Based Artificial Intelligence for the Detection ...

In conclusion, digital smartphone otoscopes and multiple smartphone-based systems appear useful for improving AOM and OME diagnosis. Further ...

4.

mssny.org

mssny.org/new-ai-smartphone-tool-accurately-diagnoses-ear-infections/

New AI Smartphone Tool Accurately Diagnoses Ear Infections

This app not only aids in precise diagnosis but also serves as an educational tool by allowing the storage and sharing of diagnostic videos, ...

5.

bmj.com

bmj.com/content/384/bmj.q572

AI app that can diagnose acute otitis media may cut ...

A smartphone app that uses artificial intelligence (AI) to help accurately diagnose acute otitis media could reduce unnecessary antibiotic use in young ...

6.

cidrap.umn.edu

cidrap.umn.edu/antimicrobial-stewardship/artificial-intelligence-tool-shows-high-accuracy-diagnosing-ear

Artificial-intelligence tool shows high accuracy ... - CIDRAP

An artificial intelligence (AI)-based tool to help interpret tympanic membrane (TM, or eardrum) videos during the clinical exam may boost accuracy.

7.

upmc.com

upmc.com/media/news/030424-ai-diagnoses-infections

New AI Smartphone Tool Accurately Diagnoses Ear ...

The new AI tool, which makes a diagnosis by assessing a short video of the eardrum captured by an otoscope connected to a smartphone camera, ...

8.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC10531728/

Image-Based Artificial Intelligence Technology for ...

These findings suggest that AI technologies hold promise for improving otitis media diagnosis, offering benefits for telemedicine and primary care settings.

9.

sciencedirect.com

sciencedirect.com/science/article/abs/pii/S0165587624003082

Artificial intelligence as an auxiliary tool in pediatric otitis ...

In the field of otolaryngology, AI technology has been applied to clinical data, including gene expression profiles, audiological data, and endoscopic and ...