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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AI-Assisted Diagnosis | Experimental | Patients in this group will undergo head CTA, interpreted by radiologists with the assistance of a previously validated deep learning AI model. The model highlights suspected aneurysm candidates on the CTA images to support diagnostic decision-making. |
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| Standard Diagnosis | Active Comparator | Patients in this group will undergo head CTA, which will be interpreted by radiologists following standard local diagnostic protocols. No AI assistance will be provided during image interpretation. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Detection rate of intracranial aneurysms | 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. | Day 1 |
| Measure | Description | Time Frame |
|---|---|---|
| Detection rates of other intracranial lesions except aneurysms | 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. | Day 1 |
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Inclusion Criteria:
-Patients in the outpatient setting who are scheduled to undergo head CTA scanning
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Longjiang Zhang, Ph.D, MD | Contact | +8613405833176 | kevinzhlj@163.com | |
| Bin Hu, MS | Contact | +8618851088705 | hubin011601@163.com |
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| Standard CTA Interpretation | Diagnostic Test | Head CTA interpretation performed by radiologists using local routine diagnostic workflows without AI support. |
|
| Follow-up visits and referrals |
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). |
| At 3-month and 12-month follow-up. |
| Hospitalization | 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. | At 3-month and 12-month follow-up. |
| Invasive DSA examinations | 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. | At 3-month and 12-month follow-up. |
| Aneurysm treatment decisions | Distribution of aneurysm management strategies, including conservative treatment, endovascular coiling, surgical clipping, and other approaches. | At 3-month and 12-month follow-up. |
| Intraoperative complications | The rate of aneurysm treatment-related complications-such as intraoperative rupture, , vasospasm, neurological injury, and other adverse events. | At 3-month and 12-month follow-up. |
| Postoperative complications | Postoperative complications, including cerebral edema, intracranial hematoma, hydrocephalus, and recurrent thrombosis. | At 3-month and 12-month follow-up. |
| In-hospital morbidity | 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). | At 3-month and 12-month follow-up. |
| In-hospital mortality | 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. | At 3-month and 12-month follow-up. |
| All-cause mortality | All-cause mortality during patient follow-up. | At 3-month and 12-month follow-up. |
| Aneurysm-related events during 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. | At 12-month follow-up. |
| ID | Term |
|---|---|
| D002532 | Intracranial Aneurysm |
| ID | Term |
|---|---|
| D020765 | Intracranial Arterial Diseases |
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D000783 | Aneurysm |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
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