Iron-deficiencyCaFerIANCT05395468
Diagnosis of Iron Deficiency by Artificial Intelligence Analysis of Eye Photography.
An observational study of Iron-deficiency, run by University Hospital, Clermont-Ferrand at 2 sites in France.
Trial summary
The objective of our work is to predict the value of ferritin from the eye, thus constituting an original, non-invasive diagnostic method of iron deficiency. To be usable in real life, the algorithm must be comparable to the performance of the reference diagnostic test (determination of ferritin), allowing to obtain a… Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Iron-deficiency
- What is being tested?
- photographs of each eye
- How many people
- 200 participants
- Where
- 2 sitesFrance
- Study dates
- Sep 2022to Jun 2024
- 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 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Women 18 years or older with iron deficiency
Who may be able to join
- Female sex
- Age ≥ 18 years old
- Able to express non-opposition to participation in rese
- Patients affiliated to a social security scheme
- Screenng for iron deficiency within 15 days of inclusion, including
- Blood count : value of hemoglobin, mean blood volume
- Serum ferritin
Who cannot join
- Personal history of severe trauma or surgery of both eyes (apart from refractive surgery performed more than 3 months ago)
- Personal history of hereditary connective tissue pathology including Marfan's disease, Ehler Danlos syndrome, imperfect osteogenesis.
- Personal history of pathology responsible for chronic hemolysis due to yellow coloration induced by hyperbilirubinemia: sickle cell disease, major thalassemia.
- Prolonged treatment with minocycline (> 1 month).
- Oral or intravenous martial supplementation started more than 15 days prior to taking the sclera photographs.
- Person deprived of liberty by administrative or judicial decision or placed under judicial protection (guardianship or supervision)
- Pregnant or breastfeeding woman
- Expression of opposition to research.
Trial locations and contacts
2 sites in 1 country.
France2 sites
CHU Clermont-Ferrand
Clermont-Ferrand
Lise Laclautre
Hervé LOBBES
SSU Université Clermont Auvergne
Clermont-Ferrand
Lise Laclautre
Laurent GERBAUD
About this study
The objective of our work is to predict the value of ferritin from the eye, thus constituting an original, non-invasive diagnostic method of iron deficiency. To be usable in real life, the algorithm must be comparable to the performance of the reference diagnostic test (determination of ferritin), allowing to obtain a sensitivity of about 90% and a specificity > 95%.
Read the detailed description
Currently, the diagnosis of iron deficiency is invasive, as it requires a venous puncture for serum ferritin assay and blood count analysis to diagnose iron deficiency anemia. This dosage is expensive and represents a major brake in the large-scale screening of iron deficiency, especially in developing countries. Most of the clinical signs of iron deficiency (asthenia, cheilitis, glossitis, alopecia, restless legs syndrome) are not very specific and the diagnosis is most often fortuitous or carried out as part of screening in a population at risk.
Iron is essential for many functions of the body, including the synthesis of collagen: in case of deficiency, it is produced with an altered and finer structure. In the eyes, the sclera consists of collagen type IV, whose thinning causes the visualization of the choroidal vessels responsible for a characteristic blue tint. A preliminary work carried out by our team made it possible to measure the increase in the amount of blue color in the sclera of deficient patients, objectifying this clinical sign for the first time. From photographs of patients' eyes, we extracted the percentile of blue contained in the pixels of the digital images of the sclera. This work continued with the automation of the recognition of eye structures, especially the sclera.
In order to improve the diagnostic performance of this original and non-invasive method, we want to apply deep-learning methods, which have already been proven in several areas: related to ophthalmology but also in a very encouraging way in the non-invasive diagnosis of anemia.
The objective of our work is to predict the value of ferritin from the eye, thus constituting an original, non-invasive diagnostic method of iron deficiency. To be usable in real life, the algorithm must be comparable to the performance of the reference diagnostic test (determination of ferritin), allowing to obtain a sensitivity of about 90% and a specificity > 95%.
- Conditions
- Iron-deficiency
- Being tested
- photographs of each eye
- Keywords
- Iron deficiency, eyes, women
- Medical subject headings
- Anemia, Iron-Deficiency, Iron Deficiencies
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
photographs of each eyeOther
All subjects included will take 5 photographs of each eye according to a standardised procedure in terms of distance, lighting and framing
What is being measured
The primary outcome is the main question the study is designed to answer.
Validate in a real clinical situation (systematic screening for iron deficiency)
Validate in a real clinical situation (systematic screening for iron deficiency) a tool for predicting ferritin levels based on digital photographs of the ocular sclera, with confrontation of a learning base treated by deep learning, and a test base
Measured: evaluation 15 day after diagnostic
Secondary outcomes (2)
To study the informational value of photographic data
To study the informational value of photographic data from the sclera concerning (in pixels) other biological parameters, in particular hemoglobin levels (in g/dl).
Measured: evaluation 15 day after diagnostic
Identify external factors influencing the quality of the ferritin
Identify external factors influencing the quality of the ferritin prediction algorithm (in particular, exposure and light polarization, which will be data automatically recorded by the camera allowing shooting, but also phototype according fitzpatrick classification)
Measured: evaluation 15 day after diagnostic
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 May 2022
- Study startSep 2022 (estimated)
- Primary completionDec 2023 (estimated)
- Study completionJun 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Iron-deficiencyStudies of the same condition, open and under way.
- More trials run by University Hospital, Clermont-FerrandThe 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 only
- Time perspective
- Prospective
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital, Clermont-Ferrand
- Sponsor type
- University, hospital or other
- Collaborators
- Université d'Auvergne
- Responsible party
- Sponsor
- Investigators
- Hervé LOBBES, Principal investigator, University Hospital, Clermont-Ferrand
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05395468
- Sponsor's protocol ID
- AOI 2021 LOBBES
- Other IDs
- 2021-A03087-34
- Acronym
- CaFerIA
- Status last verified
- May 2022
- First submitted
- 12 May 2022
- Last updated
- 25 Jul 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 25 Jul 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Diagnosis of Iron Deficiency by Artificial Intelligence Analysis of Eye Photography.
- ClinicalTrials.gov ID
- NCT05395468
- Acronym / sponsor ID
- CaFerIA / AOI 2021 LOBBES
- Conditions
- Iron-deficiency
- Keywords
- Iron deficiency, eyes, women
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- University Hospital, Clermont-FerrandUniversity, hospital or other
- Collaborators
- Université d'Auvergne
- Study start
- Sep 2022 (estimated)
- Primary completion
- Dec 2023 (estimated)
- Study completion
- Jun 2024 (estimated)
- First posted
- 27 May 2022 (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.
The objective of our work is to predict the value of ferritin from the eye, thus constituting an original, non-invasive diagnostic method of iron deficiency. To be usable in real life, the algorithm must be comparable to the performance of the reference diagnostic test (determination of ferritin), allowing to obtain a sensitivity of about 90% and a specificity > 95%.
Detailed description
Currently, the diagnosis of iron deficiency is invasive, as it requires a venous puncture for serum ferritin assay and blood count analysis to diagnose iron deficiency anemia. This dosage is expensive and represents a major brake in the large-scale screening of iron deficiency, especially in developing countries. Most of the clinical signs of iron deficiency (asthenia, cheilitis, glossitis, alopecia, restless legs syndrome) are not very specific and the diagnosis is most often fortuitous or carried out as part of screening in a population at risk.
Iron is essential for many functions of the body, including the synthesis of collagen: in case of deficiency, it is produced with an altered and finer structure. In the eyes, the sclera consists of collagen type IV, whose thinning causes the visualization of the choroidal vessels responsible for a characteristic blue tint. A preliminary work carried out by our team made it possible to measure the increase in the amount of blue color in the sclera of deficient patients, objectifying this clinical sign for the first time. From photographs of patients' eyes, we extracted the percentile of blue contained in the pixels of the digital images of the sclera. This work continued with the automation of the recognition of eye structures, especially the sclera.
In order to improve the diagnostic performance of this original and non-invasive method, we want to apply deep-learning methods, which have already been proven in several areas: related to ophthalmology but also in a very encouraging way in the non-invasive diagnosis of anemia.
The objective of our work is to predict the value of ferritin from the eye, thus constituting an original, non-invasive diagnostic method of iron deficiency. To be usable in real life, the algorithm must be comparable to the performance of the reference diagnostic test (determination of ferritin), allowing to obtain a sensitivity of about 90% and a specificity > 95%.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Women 18 years or older with iron deficiency
Key inclusion criteria (7 listed)
- Female sex
- Age ≥ 18 years old
- Able to express non-opposition to participation in rese
- Patients affiliated to a social security scheme
- Screenng for iron deficiency within 15 days of inclusion, including
Key exclusion criteria (8 listed)
- Personal history of severe trauma or surgery of both eyes (apart from refractive surgery performed more than 3 months ago)
- Personal history of hereditary connective tissue pathology including Marfan's disease, Ehler Danlos syndrome, imperfect osteogenesis.
- Personal history of pathology responsible for chronic hemolysis due to yellow coloration induced by hyperbilirubinemia: sickle cell disease, major thalassemia.
- Prolonged treatment with minocycline (> 1 month).
- Oral or intravenous martial supplementation started more than 15 days prior to taking the sclera photographs.
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 |
|---|---|---|
| photographs of each eyeAll subjects included will take 5 photographs of each eye according to a standardised procedure in terms of distance, lighting and framing | Other | – |
Primary outcome
Validate in a real clinical situation (systematic screening for iron deficiency)
Time frame: evaluation 15 day after diagnostic
Validate in a real clinical situation (systematic screening for iron deficiency) a tool for predicting ferritin levels based on digital photographs of the ocular sclera, with confrontation of a learning base treated by deep learning, and a test base
2 secondary outcomes
To study the informational value of photographic data
Time frame: evaluation 15 day after diagnostic
Identify external factors influencing the quality of the ferritin
Time frame: evaluation 15 day after diagnostic
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Jul 2022.
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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.
Hervé LOBBES principal investigator
University Hospital, Clermont-Ferrand
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Iron-deficiency, run by University Hospital, Clermont-Ferrand at 2 sites 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 7 inclusion and 8 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 25 Jul 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites 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?
Contact Lise Laclautre (+33 473 754 963, promo_interne_drci@chu-clermontferrand.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Validate in a real clinical situation (systematic screening for iron deficiency) (time frame: evaluation 15 day after diagnostic). 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 25 Jul 2022.