OtosclerosisOtoIANCT05987215
Interest of Using Deep Learning Algorithm for Otosclerosis Detection on Temporal Bone High Resolution CT
An observational study of Otosclerosis, run by Hospices Civils de Lyon at 1 site in France.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 110 yearsHealthy volunteers can take part
- Conditions the study is for
- Otosclerosis
- What is being tested?
- Radiologic diagnosis and Artificial intelligence diagnosis
- How many people
- 240 participants
- Where
- 1 siteFrance
- Study dates
- 1 Jul 2022to 1 Oct 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 110 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study population will include cases from a group of patients who have undergone surgery for otosclerosis at the Lyon Sud hospital in France, and controls who have had a high resolution temporal bone CT scan at the Lyon Sud hospital with no clinical suspicion for otosclerosis and considered normal.
Who may be able to join
- age over 18
- high resolution temporal bone CT scan available for analysis
- for the "case" group : surgical confirmation of positive diagnosis for otosclerosis
- 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
Who cannot join
- age under 18
- no high resolution temporal bone CT scan available for analysis
- unwillingness to participate in the study
Trial locations and contacts
1 site in 1 country.
France1 site
Hospices Civils de Lyon, Centre Hospitalier Lyon sud, Service d'ORL, d'otoneurchirurgie et de chirurgie cervico-facaile
Pierre-Bénite, 69310
About this study
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.
Read more
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.
Read the 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.
- Conditions
- Otosclerosis
- Being tested
- Radiologic diagnosis, Artificial intelligence diagnosis
- Keywords
- otosclerosis, IA, deep learning, temporal bone CT
- Medical subject headings
- Otosclerosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Radiologic diagnosisCombination product
Each CT scan is interpreted by a radiologist and is assigned as positive or negative for the diagnosis of otosclerosis
Artificial intelligence diagnosisDiagnostic test
Each CT scan is screened by the deep learning algorithm and is assigned as positive or negative for the diagnosis of otosclerosis
| Study group | Role | What they receive |
|---|---|---|
| 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 Receives: Combination Product: Radiologic diagnosis; Diagnostic Test: Artificial intelligence diagnosis | |
| CONTROL | Random patients with a high resolution computed tomography scan of temporal bone performed without suspicion of otosclerosis and considered normal Receives: Combination Product: Radiologic diagnosis; Diagnostic Test: Artificial intelligence diagnosis |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
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
Measured: through study completion, an average of 5 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Aug 2023
- Study start1 Jul 2022
- Primary completion1 May 2023
- Study completion1 Oct 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for OtosclerosisStudies of the same condition, open and under way.
- More trials run by Hospices Civils de LyonThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 240 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hospices Civils de Lyon
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Maxime FIEUX, MD, Principal investigator, Hospices Civils de Lyon
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05987215
- Sponsor's protocol ID
- 22-5019 / 69HCL22_1193
- Acronym
- OtoIA
- Status last verified
- May 2023
- First submitted
- 17 May 2023
- Last updated
- 14 Aug 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 14 Aug 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Interest of Using Deep Learning Algorithm for Otosclerosis Detection on Temporal Bone High Resolution CT
- ClinicalTrials.gov ID
- NCT05987215
- Acronym / sponsor ID
- OtoIA / 22-5019 / 69HCL22_1193
- Conditions
- Otosclerosis
- Keywords
- otosclerosis, IA, deep learning, temporal bone CT
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 240 participants (estimated)
- Lead sponsor
- Hospices Civils de LyonUniversity, hospital or other
- Study start
- 1 Jul 2022 (actual)
- Primary completion
- 1 May 2023 (actual)
- Study completion
- 1 Oct 2023 (estimated)
- First posted
- 14 Aug 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| CASE | – | Combination Product: Radiologic diagnosis, Diagnostic Test: Artificial intelligence diagnosisPatients 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 |
| CONTROL | – | Combination Product: Radiologic diagnosis, Diagnostic Test: Artificial intelligence diagnosisRandom patients with a high resolution computed tomography scan of temporal bone performed without suspicion of otosclerosis and considered normal |
Who may qualify
- Ages
- 18 to 110 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study population will include cases from a group of patients who have undergone surgery for otosclerosis at the Lyon Sud hospital in France, and controls who have had a high resolution temporal bone CT scan at the Lyon Sud hospital with no clinical suspicion for otosclerosis and considered normal.
Key inclusion criteria (4 listed)
Key exclusion criteria (3 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Radiologic diagnosisEach CT scan is interpreted by a radiologist and is assigned as positive or negative for the diagnosis of otosclerosis | Combination product | CASE, CONTROL |
| Artificial intelligence diagnosisEach CT scan is screened by the deep learning algorithm and is assigned as positive or negative for the diagnosis of otosclerosis | Diagnostic test | CASE, CONTROL |
Primary outcome
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
Time frame: 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
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 Aug 2023.
Related trials for Otosclerosis
Active, not recruiting
Cone-beam CT in the Diagnosis and Surgical Treatment of Otosclerosis.
Otosclerosis, Cone Beam Computed Tomography
Not yet recruiting
Surgical and Audiological Outcomes of Endoscopic Stapes Surgery
Otosclerosis
RecruitingObservational study
Investigating the Relationship Between Temporal Bone CT, Bone Density, and Hearing Loss in Otosclerosis Patients
Otosclerosis of Middle Ear, Bone Density
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Maxime FIEUX, MD principal investigator
Hospices Civils de Lyon
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Otosclerosis, run by Hospices Civils de Lyon at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 14 Aug 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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 (time frame: through study completion, an average of 5 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 14 Aug 2023.