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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.
Shi, Zhao; Hu, Bin; Lu, Mengjie; Chen, Zijian; Zhang, Manting; Yu, Yizhou; Zhou, Changsheng; Zhong, Jian; Wu, Bingqian; Zhang, Xueming; Wei, Yongyue; Zhang, Long Jiang.
Afiliación
  • Shi Z; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
  • Hu B; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
  • Lu M; Health Science Center, Ningbo University, Zhejiang, 315211, China.
  • Chen Z; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
  • Zhang M; Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 210002, China.
  • Yu Y; Department of Computer Science, The University of Hong Kong, Hong Kong, China.
  • Zhou C; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
  • Zhong J; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
  • Wu B; Jinling Hospital, Nanjing Medical University, Nanjing, 210002, China.
  • Zhang X; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
  • Wei Y; Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, 100191, China.
  • Zhang LJ; Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China. kevinzhlj@163.com.
Trials ; 25(1): 358, 2024 Jun 04.
Article en En | MEDLINE | ID: mdl-38835091
ABSTRACT

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 11 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.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aneurisma Intracraneal / Angiografía por Tomografía Computarizada Límite: Adult / Female / Humans / Male Idioma: En Revista: Trials Asunto de la revista: MEDICINA / TERAPEUTICA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aneurisma Intracraneal / Angiografía por Tomografía Computarizada Límite: Adult / Female / Humans / Male Idioma: En Revista: Trials Asunto de la revista: MEDICINA / TERAPEUTICA Año: 2024 Tipo del documento: Article País de afiliación: China