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Enrolling By InvitationNCT06364293

An Early Warning Model of Unfavorable Outcomes Following Endovascular Interventional Treatment of Intracranial Aneurysm

An Early Warning Model of Unfavorable Outcomes Following Endovascular Interventional Treatment of Intracranial Aneurysms Based on Medical Image Analysis and Deep Learning Algorithm

Status
Enrolling By Invitation
Phase
Study type
Observational
Enrollment
750 (estimated)
Sponsor
Beijing Tiantan Hospital · Academic / Other
Sex
All
Age
18 Years – 80 Years
Healthy volunteers
Not accepted

Summary

Endovascular treatment has become one of the primary treatment methods for intracranial aneurysms. The unfavorable outcomes during follow-up included aneurysm recurrence and long-term incomplete-occlusion, which would bring a high risk of rebleeding and retreatment. Previous studies have tried to predict the outcomes of aneurysms following endovascular treatment based on aneurysm characteristics including morphology, embolization packing degree, etc, but the conclusion was inconsistent. Hemodynamics of aneurysms and parent artery played a greater role in predicting outcomes following endovascular treatments. Investigators also found that the outcomes were determined by many factors, in which the demography, clinical indicators, treatment methods, and material selection can not be ignored, and the mechanism of unfavorable imaging outcomes should be explored using large samples of clinical cases and numerous variable parameters. The pre-experiment of investigators confirmed that artificial intelligence technology can meet the calculation requirements for deep mining and analysis of large sample data. This study aims to use the deep learning model to identify relevant risk factors and weights, establish a stable and accurate prediction model, then incorporate the prospective study to verify the model. The results will be very helpful in accurately predicting the adverse outcomes such as recurrence and long-term non-occlusion after endovascular treatment and help to improve the therapeutic strategy and avoid risk factors. Besides, the occurrence of ischemic or hemorrhagic complications during follow-up may affect the final follow-up outcome, so the analysis was included as one of the outcome events to evaluate the prognosis after intervention.

Conditions

Interventions

TypeNameDescription
OTHERObservational design does not include interventional behavior.Observational design does not include interventional behavior.

Timeline

Start date
2024-01-01
Primary completion
2026-12-31
Completion
2026-12-31
First posted
2024-04-15
Last updated
2024-04-15

Locations

1 site across 1 country: China

Source: ClinicalTrials.gov record NCT06364293. Inclusion in this directory is not an endorsement.