IDEAL Study: Blinded RCT for the Impact of AI Model for Cerebral Aneurysms Detection on Patients' Diagnosis and Outcomes
IDEAL
Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patients' Diagnosis and Outcomes: The IDEAL Study - A Web-Based Multicenter, Double-Blinded Randomized Controlled Trial
1 other identifier
interventional
6,450
1 country
21
Brief Summary
This study (IEDAL study) intends to prospectively enroll more than 6450 patients who will undergo head CT angiography (CTA) scanning in the outpatient clinic. It will be carried out in 21 hospitals in more than 10 provinces in China. The patient's head CTA images will be randomly assigned to the True-AI and Sham-AI group with a ratio of 1:1, and the patients and radiologists are unaware of the allocation. The primary outcomes are sensitivity and specificity of detecting intracranial aneurysms. The secondary outcomes focus on the prognosis and outcomes of the patients.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started May 2024
Typical duration for not_applicable
21 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 29, 2022
CompletedFirst Posted
Study publicly available on registry
November 7, 2023
CompletedStudy Start
First participant enrolled
May 20, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 1, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 1, 2026
October 7, 2025
October 1, 2025
2.1 years
August 29, 2022
October 1, 2025
Conditions
Outcome Measures
Primary Outcomes (2)
To compare diagnostic sensitivity of intracrnial aneurysms between intervention and control arm.
The proportion of examinations in which at least one aneurysm is discovered and indicated among groundtruth aneurysms.
6 months.
To compare diagnostic specificity of intracrnial aneurysms between intervention and control arm.
The proportion of examinations in which no aneurysms are spotted by the reader among groundtruth non-aneurysms.
6 months.
Secondary Outcomes (30)
To compare other diagnostic performances for intracranial aneurysms between intervention and control arm.
6 months.
To compare diagnostic performances for other intracranial lesions between intervention and control arm.
6 months.
To compare detection rates of intracranial lesions according to Radiology Reports between intervention and control arm.
6 months.
To assess the workload of head CT angiography interpretation.
6 months.
To assess resource use.
At 3-month and 12-month follow-up.
- +25 more secondary outcomes
Other Outcomes (7)
Patient-wise sensitivity and specificity at different centers, provinces, geography areas and levels of physician.
6 months.
Subgroup analysis of different size (< 5 mm vs. ≥ 5 mm), locations of intracranial aneurysms.
6 months.
Subgroup analysis of different gender (male vs. female), age (≤ 54 years or. >54 years), subarachnoid hemorrhage status (with vs. without SAH) of patients
6 months.
- +4 more other outcomes
Study Arms (2)
True-AI-integrated intracranial aneurysms diagnosis strategy
EXPERIMENTALFor patients who underwent head CTA and assigned to True-AI group, they will be diagnosed by a radiologist who are aided by the True-AI-integrated intracranial aneurysms diagnosis strategy.
Sham-AI-integrated intracranial aneurysms diagnosis strategy
SHAM COMPARATORFor patients who underwent head CTA and assigned to Sham-AI group, they will be diagnosed by a radiologist who are aided by the Sham-AI-integrated intracranial aneurysms diagnosis strategy. To mimic the True-AI, the Sham-AI had a sensitivity close to 0% and a similar specificity to the True-AI.
Interventions
The True-AI deep-learning based model for intracranial aneurysms detection had a patient-wise sensitivity, lesion-wise sensitivity and specificity of 0.96, 0.87, and 0.80 in the internal validation dataset.
The Sham-AI deep-learning based model for intracranial aneurysms detection is designed to have a sensitivity close to 0% and a similar specificity to the True-AI. In the internal validation dataset, the Sham-AI had a patient-wise sensitivity, lesion-wise sensitivity, specificity of 0.02, 0.01, and 0.80, respectively.
Eligibility Criteria
You may qualify if:
- Adult inpatients and outpatients who are scheduled for head CTA scanning.
You may not qualify if:
- Age under 18 years.
- Patients with contraindications to CTA.
- Modified Rankin Scale (mRS) score \> 3.
- Refuse to sign informed consent.
- Participation in other clinical studies of intracranial aneurysms.
- Patients with failed head CTA scanning or incomplete image data, or poor image quality.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (21)
The First Affiliated Hospital of University of Science and Technology of China
Hefei, Anhui, China
The First Affiliated Hospital of Wannan Medical College
Wuhu, Anhui, China
Guizhou Provincial People's Hospital
Guiyang, Guizhou, China
First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan, China
Shiyan People's Hospital
Shiyan, Hubei, China
Research Institute Of Medical Imaging Jinling Hospital
Nanjing, Jiangsu, 210018, China
Affiliated Hospital of Xuzhou Medical University
Xuzhou, Jiangsu, China
The First Hospital of Jilin University
Changchun, Jilin, China
Shandong Provincial Hospital Affiliated to Shandong First Medical University
Jinan, Shandong, China
Yidu Central Hospital Affiliated to Shandong Second Medical University
Weifang, Shandong, China
The First Affiliated Hospital of Kunming Medical University
Kunming, Yunnan, China
Hainan General Hospital
Haikou, China
The First People's Hospital of Kashgar Region
Kashgar, China
University Second Hospital
Lanzhou, China
First People's Hospital of Lianyungang
Lianyungang, China
Ma'anshan People's Hospital
Ma’anshan, China
BenQ Medical Center, Affiliated BenQ Hospital of Medical School, Nanjing Medical University
Nanjing, China
Long Gang Central Hospital of Shenzhen
Shenzhen, China
The Affiliated Suqian First Hospital of Nanjing Medical University
Suqian, China
Tianjin Medical University General Hospital
Tianjin, China
General Hospital of Ningxia Medical University
Yinchuan, China
Related Publications (1)
Shi Z, Hu B, Lu M, Chen Z, Zhang M, Yu Y, Zhou C, Zhong J, Wu B, Zhang X, Wei Y, Zhang LJ; China Aneurysm AI Project Group. Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)-a protocol for a multicenter, double-blinded randomized controlled trial. Trials. 2024 Jun 4;25(1):358. doi: 10.1186/s13063-024-08184-9.
PMID: 38835091DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Trial Manager
Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- QUADRUPLE
- Who Masked
- PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
- Masking Details
- Study participants, nurses acquiring for patients' consent and radiographers acquiring head computered tomograhy angiography exams will be blinded to the randomization as it is automatically performed after the exam has been acquired. A Sham-AI for the automatic detection of intracranial aneurysms has been delicately designed to mimic the True-AI model with a sensitivity close to zero and a similar specificity to True-AI. Thereforem, the participating radiologists interpreting head computered tomograhy angiography exams will also be blinded to the allocation of the AI models.
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Head of Radiology
Study Record Dates
First Submitted
August 29, 2022
First Posted
November 7, 2023
Study Start
May 20, 2024
Primary Completion (Estimated)
July 1, 2026
Study Completion (Estimated)
December 1, 2026
Last Updated
October 7, 2025
Record last verified: 2025-10
Data Sharing
- IPD Sharing
- Will not share