OtoIA: Interest of Using Deep Learning Algorithm for Otosclerosis Detection on Temporal Bone High Resolution CT
Study Details
Study Description
Brief Summary
Otosclerosis is a relatively frequent pathology, of multifactorial origin with genetic and hormonal part, predominantly in women. This disease causes a disorder of the bone metabolism of the middle and inner ear, responsible for a progressive deafness, which can become severe.
Several elements are necessary to make the diagnosis of otosclerosis: the clinical examination and questioning, the audiometric assessment, and finally the temporal bone CT.
The CT scan allows to detect foci of otosclerosis within the bone of the middle or inner ear. This diagnosis is sometimes difficult and requires interpretation by a trained radiologist.
The investigators would like to evaluate the ability of a deep learning algorithm to detect these foci of otosclerosis, and to compare its diagnostic performance with a trained radiologist.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
Detailed Description
Otosclerosis is a relatively frequent pathology, of multifactorial origin with genetic and hormonal part, predominantly in women. This disease causes a disorder of the bone metabolism of the middle and inner ear, responsible for a progressive deafness, which can become severe.
Several elements are necessary to make the diagnosis of otosclerosis: the clinical examination and questioning, the audiometric assessment, and finally the temporal bone CT.
The CT scan allows to detect foci of otosclerosis within the bone of the middle or inner ear. This diagnosis is sometimes difficult and requires interpretation by a trained radiologist.
The investigators would like to evaluate the ability of a deep learning algorithm to detect these foci of otosclerosis, and to compare its diagnostic performance with a trained radiologist.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| CASE Patients with surgically confirmed otosclerosis who initially consulted for conductive hearing loss with normal otoscopy, and with a high resolution computed tomography of temporal bone available |
Combination Product: Radiologic diagnosis
Each CT scan is interpreted by a radiologist and is assigned as positive or negative for the diagnosis of otosclerosis
Diagnostic Test: Artificial intelligence diagnosis
Each CT scan is screened by the deep learning algorithm and is assigned as positive or negative for the diagnosis of otosclerosis
|
| CONTROL Random patients with a high resolution computed tomography scan of temporal bone performed without suspicion of otosclerosis and considered normal |
Combination Product: Radiologic diagnosis
Each CT scan is interpreted by a radiologist and is assigned as positive or negative for the diagnosis of otosclerosis
Diagnostic Test: Artificial intelligence diagnosis
Each CT scan is screened by the deep learning algorithm and is assigned as positive or negative for the diagnosis of otosclerosis
|
Outcome Measures
Primary Outcome Measures
- Diagnostic performance of the artificial intelligence algorithm compared to the diagnostic performance of the radiologist : sensitivity, specificity, positive and negative predictive value, area under the ROC curve [through study completion, an average of 5 months]
These diagnostic performances will be established from the positive or negative diagnoses of the algorithm and the radiologist, compared to the "case" or "control" status of each patient included in the study
Eligibility Criteria
Criteria
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Inclusion Criteria * :
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age over 18
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high resolution temporal bone CT scan available for analysis
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for the "case" group : surgical confirmation of positive diagnosis for otosclerosis
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for the "control" group : a first radiological analysis in favor of a normal temporal bone CT scanner and an initial radiologic report considered normal as well
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Exclusion Criteria * :
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age under 18
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no high resolution temporal bone CT scan available for analysis
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unwillingness to participate in the study
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Hospices Civils de Lyon, Centre Hospitalier Lyon sud, Service d'ORL, d'otoneurchirurgie et de chirurgie cervico-facaile | Pierre-Bénite | France | 69310 |
Sponsors and Collaborators
- Hospices Civils de Lyon
Investigators
- Principal Investigator: Maxime FIEUX, MD, Hospices Civils de Lyon
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- 22-5019 / 69HCL22_1193