Carotid Atherosclerotic Plaque Load and Neck Circumference
- Conditions
- Atherosclerosis of ArteryMachine LearningMetabolic Syndrome
- Registration Number
- NCT05040958
- Lead Sponsor
- Sultan Abdulhamid Han Training and Research Hospital, Istanbul, Turkey
- Brief 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.
- 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.
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 300
- 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- Having cranial CTA withdrawn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
- 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
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Correlation of the machine learning model and manual interpretation 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
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Istanbul MEdeniyet University Göztepe Prof. Dr. Süleyman Yalçın City Hospital
🇹🇷Kadıköy, İstanbul, Turkey