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OpenTrials
Completed

NCT Number: NCT06803004

Diagnostic Efficacy Study of AI System in Screening Infants With Developmental Dysplasia of the Hip

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.

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Key information

Age range

28 day–6 month

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine

Shanghai, Shanghai Municipality, 200127, China

About this study

  • 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.

  • 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.

Then, the pediatric orthopedic expert group were given the initial annotations diagnosis results of DDH in the above four groups, including diagnostic images, diagnostic measurement marks, diagnostic angles and diagnostic types. And by reviewing the initial annotations, selecting "confirm" or "modify" the initial annotations, the final annotations are made again for those who need to be modified, and the final report results are obtained.

Finally, the operation results of the above different groups were summarized and analyzed by independent research assistants, including α Angle, β Angle, typing results, and the specific follow-up experience of the case including follow-up times, diagnosis time, Bang's index, proportion of studies the annotation is changed, proportion of studies the DDH type is changed in final report, and mean change in alpha angle between preliminary and final report.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

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

Exclusion criteria

  • 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.

Treatment and study plan

Junior sonographer measurement of DDH

Other

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.

Senior sonographer measurement of DDH

Other

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.

Automated annotation of the DDH measurement through deep learning

Other

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.

AI-assisted junior sonographer measurement of DDH

Other

Participants will receive visual cues from the DeepDDH system.

Primary outcomes

  1. Average diagnostic accuracy

    Time frame: 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.

Secondary outcomes

  1. Average diagnostic sensitivity

    Time frame: up to 4 weeks

    It is calculated by dividing the number of true positive cases by the sum of true positive cases and false negative cases.

  2. Average diagnostic specificity

    Time frame: up to 4 weeks

    It is calculated by dividing the number of true negative cases by the sum of true negative cases and false positive cases.

  3. Average times of follow-up visits

    Time frame: up to 4 weeks

    The average number of follow-up visits for each group is obtained by dividing the total number of follow-up visits for each participating infant within the group by the number of participating infants in that group.

  4. Diagnosis time

    Time frame: up to 4 weeks

    Time taken to make ultrasound diagnosis in each group

  5. Bang's index

    Time frame: up to 4 weeks

    Bang's index is used to evaluate whether the blind method is implemented successfully

  6. Frequency pediatrician adjusts preliminary annotation

    Time frame: up to 4 weeks

    Proportion of studies the annotation is changed

  7. Frequency pediatrician adjusts preliminary DDH type

    Time frame: up to 4 weeks

    Proportion of studies the DDH type is changed in final report

  8. Mean change in alpha angle between preliminary and final report

    Time frame: up to 4 weeks

    Average change in alpha angle between preliminary and final report

Sponsors and collaborators

Lead sponsor

RenJi Hospital

Other

Registry information

Official study title

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

Acronym: ASIDDH

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Jan 31, 2025
Registry last updated
Aug 28, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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