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Recruiting NCT06645405

AI-Driven CTA Reconstruction for Intracranial LVO

No phase Interventional Acute Ischemic Stroke Artificial Intelligence (AI) Endovascular Thrombectomy CT Angiography

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: AI algorithm.
Who it may be relevant to
Registry conditions: Acute Ischemic Stroke, Artificial Intelligence (AI), Endovascular Thrombectomy, CT Angiography. Basic parameters: 18 years — 95 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Segmentation and Modeling for Accurate Reconstruction of CT Angiography of Intracranial Large Vessel Occlusion with Artificial Intelligence: a Stepped-wedge, Cluster-randomized Controlled Trial

Overview

Acute ischemic stroke (AIS) caused by intracranial large vessel occlusion (LVO) in the anterior circulation significantly contributes to stroke-related disability and mortality. Recent randomized controlled trials have demonstrated substantial benefits of endovascular thrombectomy (EVT) when patients are appropriately triaged beforehand. However, accurately orienting the 'missed segment' during EVT remains challenging. Guide-wires often fail to navigate through the occlusion or are mistakenly directed into the small tranches or even cause vessel rupture. To address this clinical need, the investigators developed an artificial intelligence (AI) algorithm to automate the reconstruction of CT angiography (CTA), focusing on the occluded LVO segment. To evaluate the clinical utility of this AI algorithm, the investigators propose a prospective, stepped-wedge cluster-randomized study to determine whether integrating our AI algorithm into AIS care flow can reduce the time for first pass of the thrombus by improving the visualization of the occluded segment on CTA. Physicians will assess patient eligibility for thrombectomy, and all selected patients will receive standard care according to current guidelines. This approach is expected to enhance patient treatment outcomes for endovascular thrombectomy by leveraging readily available data.

Interventions

  • Behavioral AI algorithm
    Artificial intelligence algorithms in the automated reconstruction of intracranial large vessel occlusion (LVO)

Primary outcome measures

  • AFAT [Time frame: Immediately after EVT]
Secondary outcome measures (8)
  • PRT [Time frame: Immediately after EVT]
  • IPT [Time frame: Immediately after EVT]
  • IRT [Time frame: Immediately after EVT]
  • The rate of successful flow restoration immediately after EVT [Time frame: Immediately after EVT]
  • The rate of symptomatic intracerebral hemorrhage within 24 hours post-EVT [Time frame: 24 hours post-EVT]
  • The rate of procedure-related complications [Time frame: Immediately after EVT]
  • The rate of functional independence at 90 days post-EVT [Time frame: 90 days post-EVT]
  • The mortality rate within 90 days post-EVT [Time frame: 90 days post-EVT]

Eligibility criteria

Inclusion criteria

  • Male or Female, 18 years of age or older.
  • Patients who present with signs and/or symptoms concerning acute ischemic stroke.
  • Patients who undergo noncontrast CT and CT angiography imaging.
  • Patients determined to have an intracranial large vessel occlusion (including the internal carotid artery, middle cerebral artery M1 segment, and M2 segment), and eligible for endovascular treatment.

Exclusion criteria

1\) CT imaging with severe motion artifacts.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Sequential
Masking
Open label
Primary purpose
Supportive care

Study locations

China · 2 centers
  • Shanghai Sixth People's Hospital — Shanghai
  • Shanghai Sixth People's Hospital — Shanghai

Identifiers

NCT: NCT06645405 · SMART-AI

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗