Journal Article

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

Wu, Bingqian, Hu, Bin, Zhang, Xueming, Zhou, Changsheng, Zhang, Long Jiang, Chen, Zijian, Zhong, Jian, Lu, Mengjie, Yu, Yizhou, Wei, Yongyue, Shi, Zhao, Zhang, Manting

2024

Overview

Background This multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneurysm detection in CT angiography (CTA) and its influence on patients’ short-term and long-term outcomes. Methods Study design : Prospective, multicenter, double-blinded RCT. Settings : The model was designed for the automatic detection of intracranial aneurysms from original CTA images. Participants : Adult inpatients and outpatients who are scheduled for head CTA scanning. Randomization groups: (1) Experimental Group: Head CTA interpreted by radiologists with the assistance of the True-AI-integrated intracranial aneurysm diagnosis strategy (True-AI arm). (2) Control Group: Head CTA interpreted by radiologists with the assistance of the Sham-AI-integrated intracranial aneurysm diagnosis strategy (Sham-AI arm). Randomization : Block randomization, stratified by center, gender, and age group. Primary outcomes: Coprimary outcomes of superiority in patient-level sensitivity and noninferiority in specificity for the True-AI arm to the Sham-AI arm in intracranial aneurysms. Secondary outcomes: Diagnostic performance for other intracranial lesions, detection rates, workload of CTA interpretation, resource utilization, treatment-related clinical events, aneurysm-related events, quality of life, and cost-effectiveness analysis. Blinding: Study participants and participating radiologists will be blinded to the intervention. Sample size : Based on our pilot study, the patient-level sensitivity is assumed to be 0.65 for the Sham-AI arm and 0.75 for the True-AI arm, with specificities of 0.90 and 0.88, respectively. The prevalence of intracranial aneurysms for patients undergoing head CTA in the hospital is approximately 12%. To establish superiority in sensitivity and noninferiority in specificity with a margin of 5% using a one-sided α  = 0.025 to ensure that the power of coprimary endpoint testing reached 0.80 and a 5% attrition rate, the sample size was determined to be 6450 in a 1:1 allocation to True-AI or Sham-AI arm. Discussion The study will determine the precise impact of the AI system on the detection performance for intracranial aneurysms in a double-blinded design and following the real-world effects on patients’ short-term and long-term outcomes. Trial registration This trial has been registered with the NIH, U.S. National Library of Medicine at ClinicalTrials.gov, ID: NCT06118840 . Registered 11 November 2023.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Adult / Aneurysms / Angiography / Artificial Intelligence / Biomedicine / Cerebral Angiography - methods / Clinical outcomes / Computed Tomography Angiography / Cost benefit analysis / CT imaging / Detection / Double blinded / Double-Blind Method / Equivalence Trials as Topic / Female / Health Sciences / Hospital patients / Humans / Informed consent / Intervention / Intracranial Aneurysm - diagnostic imaging / Intracranial aneurysms / Male / Medical diagnosis / Medical imaging / Medical research / Medicine / Medicine & Public Health / Medicine, Experimental / Multicenter Studies as Topic / Outcomes / Patient outcomes / Patients / Predictive Value of Tests / Prospective Studies / Randomized controlled trial / Randomized Controlled Trials as Topic / Statistics for Life Sciences / Study Protocol / Time Factors / Work stations