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AI-Based IMT Study

NCT06768398 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 80

Last updated 2025-01-10

No results posted yet for this study

Summary

Cerebro-vascular and heart diseases have together ranked 4th and 5th place in the 2022 top ten leading causes of death in Hong Kong, taking up more than 15% of the total in an unceasing trend. While conventional carotid ultrasound imaging is nothing short of comprehensive, it is highly operator-dependent and is worsened by the shortage of medical staff in Hong Kong.

The seemingly long queue for the expensive health screenings has put the high-risk groups, including but not limited to the elderly, in a vulnerable position as they can hardly perform regular and frequent check-ups.

In light of this, our team is determined to research a solution that is conducive to the preventive healthcare of strokes and cardiovascular diseases through one of the newly proposed devices: PyrocksTM Tag Lite.

This study aims to investigate an approach for developing a robust deep learning model for analysing ultrasound images and incorporate the model into our established prototype to perform intima-media thickness measurement and risk assessment.

Main points that the clinical trial can assist in solving the existing problem:

The acquisition procedures are non-invasive, painless, and safe for the participants. Clinical trials \& test data will assist in testing and training our neural network model.

Conditions

Sponsors & Collaborators

  • Chinese University of Hong Kong

    lead OTHER

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-09-15
Primary Completion
2024-12-31
Completion
2025-01-31

Countries

  • Hong Kong

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06768398 on ClinicalTrials.gov