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临床试验/NCT06803004
NCT06803004已完成不适用

Blinded Randomized Control Trail of Artificial Intelligence-Assisted Ultrasound Screening for Neonatal Hip Dysplasia in a Clinical Cohort

RenJi Hospital1 个研究点 分布在 1 个国家目标入组 1,789 人开始时间: 2025年7月18日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
已完成
入组人数
1,789
试验地点
1
主要终点
Average diagnostic accuracy

研究概览

简要总结

To ascertain the efficacy of the DeepDDH system, a deep learning framework, in enhancing diagnostic accuracy and curtailing follow-up intervals for infants undergoing screening for developmental dysplasia of the hip (DDH), the researchers are executing a blinded, randomized controlled trial. This trial juxtaposes AI-only and AI-assisted assessments of DDH against sonographer interpretations across various proficiency levels in the preliminary analysis of ultrasound images.

详细描述

  1. Participating centers and doctors:

The data in the ultrasound screening sequence database in this part of the study were mainly from Renji Hospital and the Sixth People's Hospital in Shanghai between August 2014 and December 2021. Renji Hospital, the Sixth People's Hospital, and the Pediatric Hospital Affiliated to Fudan University, three top-three hospitals in Shanghai, started Graf ultrasound examination earlier, with an average history of more than 10 years. And they are responsible for providing expert sonographers with more than 5-10 years of DDH ultrasound diagnosis experience, and pediatric orthopedic experts with 5-10 years of DDH diagnosis experience to participate in the study. However, several other primary or remote medical institutions with late DDH ultrasound screening and insufficient diagnostic experience were mainly responsible for providing primary sonographers to participate in the study. Before the study, the sonographers involved in this study will be evaluated uniformly and quantitatively through examination papers. 2. Research process:

One week before the start of the study, the sonographers registered in the study received uniform training of the latest DDH ultrasound diagnosis in the form of PPT, video, literature study, and offline instruction.

For the included cases in the ultrasound screening sequence database, they would appear in different control groups in a random form, such as the AI model, the Expert sonographer group, the primary sonographer group, and the primary sonographer with AI 'aid group. All cases in the ultrasound screening sequence database were stratified and block-randomized into the above four groups (primary, experts, AI-independent, AI-assisted primary).

In the AI-assisted group, each sonographer was asked to choose whether to modify or confirm the diagnosis according to the measurement marks, diagnostic angles and typing results provided by the AI device. However, in the Expert sonographer group and junior sonographer unassisted group, the dedicated research assistant will turn off the AI display function to ensure that no additional information is provided to the sonographer. The consensus of two pediatric orthopedic expert with 5-10 years of experience in DDH ultrasound diagnosis was used as the gold standard. In case of disagreement, a third pediatric expert will evaluate the diagnosis results of DDH. The final consensus was used as the gold standard.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Diagnostic
盲法
Double (Investigator, Outcomes Assessor)

入排标准

年龄范围
28 Days 至 6 Months(Child)
性别
All
接受健康志愿者
否

入选标准

  • •Infants underwent DDH ultrasound examinations.
  • •Infants aged 28 days to 6 months.

排除标准

  • •Infants with lacking or incomplete ultrasound images.
  • •Infants with poor image quality, including non-compliance with anatomical identification and usability check.
  • •Infants with hip dysplasia caused by other diseases.

研究组 & 干预措施

Junior Sonographer Annotation

Active Comparator

Participants will not receive visual cues from the DeepDDH system. Junior sonographer technicians will offer preliminary interpretations before these are subjected to validation and subsequent review by expert's team.

干预措施: Junior sonographer measurement of DDH (Other)

Senior Sonographer Annotation

Active Comparator

Participants will not receive visual cues from the DeepDDH system. Senior sonographer technicians will offer preliminary interpretations before these are subjected to validation and subsequent review by expert's team.

干预措施: Senior sonographer measurement of DDH (Other)

DeepDDH system Annotation

Experimental

Through randomization, a subset of the preliminary interpretations will be conducted by AI technology, and the study team will evaluate the degree of divergence between these AI-generated preliminary interpretations and the final interpretations.

干预措施: Automated annotation of the DDH measurement through deep learning (Other)

DeepDDH-assist Junior Sonographer Annotation

Experimental

Participants will receive visual cues from the DeepDDH system.

干预措施: AI-assisted junior sonographer measurement of DDH (Other)

结局指标

主要结局

Average diagnostic accuracy

时间窗: up to 4 weeks

It is calculated by dividing the number of preliminary interpretations that are consistent with the expert team's grading by the total number of cases that should be diagnosed.

次要结局

  • Average diagnostic sensitivity(up to 4 weeks)
  • Average diagnostic specificity(up to 4 weeks)
  • Average times of follow-up visits(up to 4 weeks)
  • Diagnosis time(up to 4 weeks)
  • Bang's index(up to 4 weeks)
  • Frequency pediatrician adjusts preliminary annotation(up to 4 weeks)
  • Frequency pediatrician adjusts preliminary DDH type(up to 4 weeks)
  • Mean change in alpha angle between preliminary and final report(up to 4 weeks)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Lixin Jiang

Director of Department of ultrasound in medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine

RenJi Hospital

研究点 (1)

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