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Feasibility of artificial intelligence based on multimodal MRI(QSM, DTI and 3D-pcASL) to predict the prognosis of intravenous thrombolysis in patients with acute ischemic stroke.

Feasibility of artificial intelligence based on multimodal MRI(QSM, DTI and 3D-pcASL) to predict the prognosis of intravenous thrombolysis in patients with acute ischemic stroke.

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400094267
Enrollment
Unknown
Registered
2024-12-19
Start date
2025-01-01
Completion date
Unknown
Last updated
2025-01-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Acute ischemic stroke

Interventions

Good prognosis and poor prediction (divided by 90-day MRS score):All patients were treated with intravenous thrombolysis for acute ischemic stroke without intervention.

Sponsors

The Fourth Affiliated Hospital, Guangzhou Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
30 Years to 90 Years

Inclusion criteria

Inclusion criteria: A) The patient has symptoms such as weakness or numbness of one limb, slurred speech or difficulty in understanding, and is extremely suspected of acute ischemic stroke diagnosed by MRI in clinic. At the same time, laboratory tests (blood sugar, red blood cell distribution width (RDW) and neutrophil/lymphocyte ratio (NLR) should be improved. If the patient is treated with thrombolytic therapy after removing contraindications in order to clarify the onset time, MRI examination can be performed during treatment or within 24 hours after thrombolysis is completed. B) Patients who are eligible for intravenous thrombolysis and are treated.

Exclusion criteria

Exclusion criteria: A) Patients diagnosed with cerebral hemorrhage by MRI. B) Patients with acute ischemic stroke exceeding the time window of intravenous thrombolysis. Exit criteria: a) Patients with bleeding transformation or death during treatment.

Design outcomes

Primary

MeasureTime frame
Quantitative parameters of diffusion tensor imaging, DTI;Quantitative susceptibility mapping (QSM) quantitative parameters.;Quantitative parameters of three-dimensional pseudo-continuous arterial spin labeling (3D-PCASL).;

Countries

China

Contacts

Public ContactYe Haoyi

The Fourth Affiliated Hospital, Guangzhou Medical University

136262966@qq.com+86 176 6543 3101

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026