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NCT Number: NCT07124624

Stepped-Wedge Cluster Randomized Trial of AI-Assisted CTA Detection for Intracranial Aneurysms in Regional Hospitals

This study (IDEAL 2) is a nationwide stepped-wedge cluster-randomized trial designed to prospectively enroll over 14,400 patients undergoing outpatient head CT angiography (CTA). The trial will be conducted across more than 72 regional hospitals in China. Clusters were randomly assigned to nine randomization groups. In accordance with the stepped-wedge design, clusters will sequentially transition from the control condition (standard human diagnosis) to the intervention condition (AI-assisted diagnosis) at regular intervals over a 10-month period, until all clusters receive the intervention. The primary outcome is the detection rate of intracranial aneurysms. Secondary outcomes include patient prognosis and clinical outcomes.

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Key information

About this study

A multicenter, stepped-wedge cluster-randomized trial will be conducted in regional hospitals, specifically prefecture-level and county-level institutions across China. Each cluster (i.e., hospital) will enroll approximately 200 patients undergoing head computed tomography angiography (CTA), yielding a total sample size of at least 14,400 participants. The trial consists of nine steps, each lasting one month. Clusters will transition sequentially from the control condition to the intervention condition based on stratified randomization, until all clusters have received the intervention.

In the control group, diagnoses and treatments will follow local standard clinical protocols. In the intervention group, diagnostic procedures will be supported by an artificial intelligence (AI)-assisted system. The primary outcome is the detection rate of intracranial aneurysms, as determined from radiology reports at the patient level. Secondary outcomes include additional diagnostic performance metrics on CTA, such as the detection of intracranial arterial stenosis, occlusion, and tumors.

Follow-up evaluations at 3 and 12 months will assess treatment-related indicators-including repeat head CTA or magnetic resonance angiography (MRA), hospitalization rates, and digital subtraction angiography (DSA) utilization-as well as clinical outcomes related to aneurysm events. These measures aim to evaluate both the short- and long-term impacts of AI-assisted diagnosis on routine clinical practice and patient prognosis.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

-Patients in the outpatient setting who are scheduled to undergo head CTA scanning

Exclusion criteria

  • Age < 18 years
  • History of cerebrovascular surgery involving any metallic implants (e.g., aneurysm embolization, aneurysm clipping, or vascular stenting)
  • Modified Rankin Scale (mRS) score > 3
  • Refuse to sign written informed consent
  • Contraindications to CTA examination
  • CTA scan failure, incomplete imaging data, or image quality insufficient for diagnostic evaluation

Treatment and study plan

AI-Assisted CTA Interpretation

Device

A locked, independently validated deep learning model was used to assist radiologists in interpreting head CTA scans. The model was trained on 16,546 CTA cases and externally validated on an independent set of 900 DSA-verified CTA cases, achieving a patient-level sensitivity of 0.943 and an average of 0.187 false positives per case.

Standard CTA Interpretation

Diagnostic Test

Head CTA interpretation performed by radiologists using local routine diagnostic workflows without AI support.

Primary outcomes

  1. Detection rate of intracranial aneurysms

    Time frame: Day 1

    The proportion of patients diagnosed with intracranial aneurysms among all individuals undergoing CTA during the observation period. This outcome is used to compare the diagnostic effectiveness of conventional radiologist interpretation based on local clinical practice versus AI-assisted diagnosis in detecting intracranial aneurysms.

Secondary outcomes

  1. Detection rates of other intracranial lesions except aneurysms

    Time frame: Day 1

    The proportion of patients diagnosed with intracranial arterial stenosis, occlusion, arteriovenous malformation (AVM), Moyamoya disease, or other vascular abnormalities among all individuals undergoing CTA during the observation period.

  2. Follow-up visits and referrals

    Time frame: At 3-month and 12-month follow-up.

    The number of follow-up or referral visits, including the number of follow-up visits, number of referrals, and repeated noninvasive vascular imaging examinations (e.g., CTA, MRA, or high-resolution vessel wall MRI).

  3. Hospitalization

    Time frame: At 3-month and 12-month follow-up.

    Subsequent hospitalization outcomes during patient follow-up, including the rate of hospitalization, rate of hospitalization specifically related to intracranial aneurysms and the length of hospital stay.

  4. Invasive DSA examinations

    Time frame: At 3-month and 12-month follow-up.

    Rate of patients undergoing digital subtraction angiography (DSA), along with the distribution of findings, including positive identification of aneurysms, other vascular abnormalities, or no detectable abnormalities.

  5. Aneurysm treatment decisions

    Time frame: At 3-month and 12-month follow-up.

    Distribution of aneurysm management strategies, including conservative treatment, endovascular coiling, surgical clipping, and other approaches.

  6. Intraoperative complications

    Time frame: At 3-month and 12-month follow-up.

    The rate of aneurysm treatment-related complications-such as intraoperative rupture, , vasospasm, neurological injury, and other adverse events.

  7. Postoperative complications

    Time frame: At 3-month and 12-month follow-up.

    Postoperative complications, including cerebral edema, intracranial hematoma, hydrocephalus, and recurrent thrombosis.

  8. In-hospital morbidity

    Time frame: At 3-month and 12-month follow-up.

    In-hospital morbidity, defined as a Modified Rankin Scale (mRS) score of 3-5 at hospital discharge. The Modified Rankin Scale ranges from 0 to 6, with higher scores indicating greater disability (scores of 3-5) or death (score of 6).

  9. In-hospital mortality

    Time frame: At 3-month and 12-month follow-up.

    In-hospital mortality, defined as a Modified Rankin Scale (mRS) score of 6 at hospital discharge. The Modified Rankin Scale ranges from 0 to 6, with a score of 6 indicating death.

  10. All-cause mortality

    Time frame: At 3-month and 12-month follow-up.

    All-cause mortality during patient follow-up.

  11. Aneurysm-related events during follow-up

    Time frame: At 12-month follow-up.

    Proportion of patients with aneurysm-related events during follow-up, including aneurysm growth (≥1 mm in any dimension), aneurysm rupture (non-traumatic subarachnoid hemorrhage), stroke (hemorrhagic or ischemic), de novo aneurysm formation, and aneurysm recurrence after treatment.

Study contacts

Contact information is provided by the study sponsor or research team.

Bin Hu, MS

CONTACT

[email protected]

+8618851088705

Longjiang Zhang, Ph.D, MD

CONTACT

[email protected]

+8613405833176

Sponsors and collaborators

Lead sponsor

Jinling Hospital, China

Other

Registry information

Official study title

Impact of an AI-Driven CT Angiography Model on Intracranial Aneurysm Detection and Clinical Outcomes in Regional Hospitals (IDEAL2): A Nationwide Stepped-Wedge Cluster-Randomized Trial

Acronym: IDEAL2

Important dates

Study start
2025
Primary completion
2026
Study completion
2029
First posted
Aug 15, 2025
Registry last updated
Aug 20, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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