Digital Otoscopy With Computer‐Aided Composite Image Generation: Impact on the Correct Diagnosis, Confidence, and Time-Reference-Cited by-同舟云学术

Digital Otoscopy With Computer‐Aided Composite Image Generation: Impact on the Correct Diagnosis, Confidence, and Time

Published:2024-09-02 Issue: Volume: Page:
ISSN:0194-5998
Container-title:Otolaryngology–Head and Neck Surgery
language:en
Short-container-title:Otolaryngol.--head neck surg.

Author:

Camalan Seda¹^ORCID,Langefeld Carl D.²,Zinnia Amy²,McKee Brigham³,Carlson Matthew L.⁴,Deep Nicholas L.⁵,Harris Michael S.⁶,Jan Taha A.⁷,Kaul Vivian F.⁸,Lindquist Nathan R.⁹,Mattingly Jameson K.¹⁰,Shah Jay¹¹,Zhan Kevin Y.¹²,Gurcan Metin N.¹,Moberly Aaron C.⁷

Affiliation:

1. Center for Artificial Intelligence Research Wake Forest University School of Medicine Winston‐Salem North Carolina USA

2. Department of Biostatistics and Data Science, Bowman Gray Center for Medical Education Wake Forest University School of Medicine Winston‐Salem North Carolina USA

3. Bowman Gray Center for Medical Education Wake Forest University School of Medicine Winston‐Salem North Carolina USA

4. Department of Otolaryngology–Head and Neck Surgery Mayo Clinic School of Medicine Rochester Minnesota USA

5. Department of Otolaryngology–Head and Neck Surgery Mayo Clinic Phoenix Arizona USA

6. Department of Otolaryngology and Communication Sciences Medical College of Wisconsin Milwaukee Wisconsin USA

7. Department of Otolaryngology–Head and Neck Surgery Vanderbilt University Medical Center Nashville Tennessee USA

8. Department of Otolaryngology UTHealth Houston Houston Texas USA

9. Department of Otolaryngology Baylor College of Medicine Houston Texas USA

10. Otology/Neurotology ENT Consultants of East Tennessee Knoxville Tennessee USA

11. Department of Otolaryngology University Hospitals Cleveland Medical Center Case Western Reserve University Cleveland Ohio USA

12. Department of Otolaryngology Northwestern Medicine Chicago Illinois USA

Abstract

AbstractObjectiveThis study investigated the comparative performance of ear, nose, and throat (ENT) physicians in correctly detecting ear abnormalities when reviewing digital otoscopy imaging using 3 different visualization methods, including computer‐assisted composite images called “SelectStitch,” single video frame “Still” images, and video clips. The study also explored clinicians' diagnostic confidence levels and the time to make a diagnosis.Study DesignClinician diagnostic reader study.SettingOnline diagnostic survey of ENT physicians.MethodsNine ENT physicians reviewed digital otoscopy examinations from 86 ears with various diagnoses (normal, perforation, retraction, middle ear effusion, tympanosclerosis). Otoscopy examinations used artificial‐intelligence (AI)‐based computer‐aided composite image generation from a video clip (SelectStitch), manually selected best still frame from a video clip (Still), or the entire video clip. Statistical analyses included comparisons of ability to detect correct diagnosis, confidence levels, and diagnosis times.ResultsThe ENT physicians' ability to detect ear abnormalities (33.2%‐68.7%) varied depending on the pathologies. SelectStitch and Still images were not statistically different in detecting abnormalities (P > .50), but both were different from Video (P < .01). However, the performance improvement observed with Videos came at the cost of significantly longer time to determining the diagnosis. The level of confidence in the diagnosis was positively associated with correct diagnoses, but varied by particular pathology.ConclusionThis study explores the potential of computer‐assisted techniques like SelectStitch in enhancing otoscopic diagnoses and time‐saving, which could benefit telemedicine settings. Comparable performance between computer‐generated and manually selected images suggests the potential of AI algorithms for otoscopy applications.

Publisher

Wiley

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