Carotid Atherosclerotic Plaque Load and Neck Circumference

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

300 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-09-08

Study Completion Date

2022-03-28

Brief Summary

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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.

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Detailed Description

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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.

Conditions

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Atherosclerosis of Artery Metabolic Syndrome Machine Learning

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* 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* Having cranial CTA withdrawn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

Exclusion Criteria

* 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

Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes