Atherosclerosis of ArteryNCT05040958
Carotid Atherosclerotic Plaque Load and Neck Circumference
An observational study of Atherosclerosis of Artery and Metabolic Syndrome, run by Sultan Abdulhamid Han Training and Research Hospital, Istanbul, Turkey at 1 site in Turkey (Türkiye).
Trial summary
The aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations. Read more about this study
- Who is it for?
- Ages 18 to 90 yearsHealthy volunteers can take part
- Conditions the study is for
- Atherosclerosis of Artery, Metabolic Syndrome, Machine Learning
- How many people
- 300 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 8 Sep 2021to 28 Mar 2022
- 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 90 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: People having cranial CTA
Who may be able to join
- 18 years or older
- Having cranial CTA withdrawn
- Having blood lipids, HbA1c, blood glucose, AST, ALT measured in 3 months before and 3 months after cranial CTA
Who cannot join
- Thyroid disease
- Having had neck surgery
- Use of corticosteroids for more than 6 months
- Presence of lymph nodes in the anterior neck
- Hypertrophy of neck muscles
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site, 1 recruiting
- Recruiting
Istanbul MEdeniyet University Göztepe Prof. Dr. Süleyman Yalçın City Hospital
Kadıköy, Istanbul, 34668
Elif Yıldırım Ayaz, M.D., 05325148300
About this study
Official title: Determination of Carotid Atherosclerotic Plaque Load and Neck Circumference in Cranial CT Angiography With Machine Learning Method and Their Relationship With Each Other
The aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations.
Read the detailed description
Modeling CTA images for carotid artery segments with deep learning method and automatic carotid plaque presence and scoring will be useful and beneficial in clinical practice. The aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations.
- Keywords
- Atherosclerosis of Artery, Metabolic Syndrome, Machine Learning
- Medical subject headings
- Metabolic Syndrome
What is being measured
The primary outcome is the main question the study is designed to answer.
Correlation of the machine learning model and manual interpretation
Evaluation of the correlation of the presence of plaque in the carotid segments with manual interpretation in the model obtained by machine learning method
Measured: 1 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Sep 2021
- Study start8 Sep 2021
- Primary completion28 Mar 2022 (estimated)
- Study completion28 Mar 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Atherosclerosis of ArteryStudies of the same condition, open and under way.
- 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sultan Abdulhamid Han Training and Research Hospital, Istanbul, Turkey
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Elif Yıldırım Ayaz, Sultan Abdulhamid Han Training and Research Hospital, Istanbul, Turkey
- Investigators
- Elif Yıldırım Ayaz, M.D., Principal investigator, Sultan Abdülhamid Han Training and Research Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05040958
- Sponsor's protocol ID
- CAPNET
- Status last verified
- Sep 2021
- First submitted
- 7 Sep 2021
- Last updated
- 17 Sep 2021
- 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 17 Sep 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Determination of Carotid Atherosclerotic Plaque Load and Neck Circumference in Cranial CT Angiography With Machine Learning Method and Their Relationship With Each Other
- ClinicalTrials.gov ID
- NCT05040958
- Acronym / sponsor ID
- CAPNET
- Keywords
- Atherosclerosis of Artery, Metabolic Syndrome, Machine Learning
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Sultan Abdulhamid Han Training and Research Hospital, Istanbul, TurkeyUniversity, hospital or other
- Study start
- 8 Sep 2021 (actual)
- Primary completion
- 28 Mar 2022 (estimated)
- Study completion
- 28 Mar 2022 (estimated)
- First posted
- 10 Sep 2021 (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 aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations.
Detailed description
Modeling CTA images for carotid artery segments with deep learning method and automatic carotid plaque presence and scoring will be useful and beneficial in clinical practice. The aim of this study is to establish a deep learning model to automatically detect the presence and scoring of carotid plaques in neck CTA images, and to determine whether this model is compatible with manual interpretations.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- People having cranial CTA
Key inclusion criteria (3 listed)
- 18 years or older
- Having cranial CTA withdrawn
- Having blood lipids, HbA1c, blood glucose, AST, ALT measured in 3 months before and 3 months after cranial CTA
Key exclusion criteria (5 listed)
- Thyroid disease
- Having had neck surgery
- Use of corticosteroids for more than 6 months
- Presence of lymph nodes in the anterior neck
- Hypertrophy of neck muscles
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Correlation of the machine learning model and manual interpretation
Time frame: 1 day
Evaluation of the correlation of the presence of plaque in the carotid segments with manual interpretation in the model obtained by machine learning method
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Sep 2021.
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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.
Elif Yıldırım Ayaz, M.D. principal investigator
Sultan Abdülhamid Han Training and Research Hospital
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 Atherosclerosis of Artery and Metabolic Syndrome, run by Sultan Abdulhamid Han Training and Research Hospital, Istanbul, Turkey at 1 site in Turkey (Türkiye).
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 3 inclusion and 5 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 17 Sep 2021. 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 Turkey (Türkiye). 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 Elif Yıldırım Ayaz, M.D. (+905325148300, drelifyildirim@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Correlation of the machine learning model and manual interpretation (time frame: 1 day). 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 17 Sep 2021.