Evaluating outcomes of unruptured brain arteriovenous malformations using multimodal CT
Official title: Evaluation of Clinical Outcomes of Unruptured Brain Arteriovenous Malformations Treated With Medical Management Alone Based on Multimodal Computer Tomography: A Long-term Multicenter Prospective Cohort Study
Run by Beijing Tiantan Hospital · NCT05449106 · Data updated 2026-11-12
This study is testing how well medical treatment works for people with unruptured brain arteriovenous malformations by using advanced imaging techniques to see how these conditions affect their health over time.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 3 Years to 80 Years |
| Sex | All |
| Enrollment | 200 (estimated) |
| Sponsor | Beijing Tiantan Hospital Academic / other |
| Locations | 4 sites (Beijing, Beijing Municipality and 3 other locations) |
| Status | Recruiting |
| Started | May 25, 2022 |
| Main results expected | May 25, 2027 |
| Study ends | May 25, 2032 |
| Registry record updated | September 7, 2023 |
| Trial ID | NCT05449106 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include patients diagnosed with unruptured brain arteriovenous malformations who have not experienced any related hemorrhage.
✕Probably not a fit
Patients with simple arteriovenous fistulas, dural arteriovenous fistulas, or those with spinal cord arteriovenous malformations will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to assess the clinical outcomes of patients with unruptured brain arteriovenous malformations (bAVMs) who are managed medically. It utilizes multimodal CT imaging to analyze morphological, structural, and hemodynamic features of bAVMs, exploring their relationship with clinical outcomes. The study also employs deep learning algorithms to develop automated segmentation and prediction models based on imaging data. Patient follow-up will occur at multiple intervals over three years to gather comprehensive clinical information.
Why it matters
Potential benefit: If successful, this study could enhance the understanding and management of unruptured bAVMs, potentially leading to improved patient outcomes.
How similar studies have gone: While the use of multimodal CT and machine learning in this context is innovative, similar studies have shown promise in improving imaging and predictive capabilities in vascular conditions.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Patients with confirmed diagnosis of brain arteriovenous malformations in the brain, basal ganglia, thalamus, corpus callosum, cerebellum and other locations. 2. Patients with no history of previous arteriovenous malformation-related hemorrhage and no arteriovenous malformation-related hemorrhage confirmed by CT examination. 3. Patients with Radiographic examinations completed without any treatment Exclusion Criteria: 1. Patients with simple arteriovenous fistula. 2. Patients with combined dural arteriovenous fistulas. 3. Arteriovenous malformations occurring in the spinal cord. 4. Pregnant patients were not included in this study.
Where it's running
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Beijing Tiantan Hospital, Capital Medical University
Beijing, Beijing Municipality, China Recruiting -
Beijing Hospital
Beijing, Beijing Municipality, China Recruiting -
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China Recruiting -
The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School
Nanjing, Jiangsu, China Recruiting
Study contacts
- Principal investigator: Guosheng Zhou — The First Affiliated Hospital of Zhengzhou University
- Study coordinator: Shaosen Zhang, Doctor
- Email: longyoubafang@hotmail.com
- Phone: +8618611284839
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.