Hip Dysplasia, DevelopmentalASIDDHNCT06803004
Diagnostic Efficacy Study of AI System in Screening Infants With Developmental Dysplasia of the Hip
A study testing Junior sonographer measurement of DDH, Senior sonographer measurement of DDH and Automated annotation of the DDH measurement through deep learning in people with Hip Dysplasia, Developmental, run by RenJi Hospital at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 28 days to 6 months
- Conditions the study is for
- Hip Dysplasia, Developmental
- What is being tested?
- Junior sonographer measurement of DDH, Senior sonographer measurement of DDH and Automated annotation of the DDH measurement through deep learning
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,789 participants
- Where
- 1 siteChina
- Study dates
- 18 Jul 2025to 20 Aug 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 28 days to 6 months
- All sexes
- No healthy volunteers
- Child
Who may be able to join
- Infants underwent DDH ultrasound examinations.
- Infants aged 28 days to 6 months.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
China1 site
Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, 200127
About this study
Official title: Blinded Randomized Control Trail of Artificial Intelligence-Assisted Ultrasound Screening for Neonatal Hip Dysplasia in a Clinical Cohort
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.
Read the detailed description
- 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.
- Conditions
- Hip Dysplasia, Developmental
- Being tested
- Junior sonographer measurement of DDH, Senior sonographer measurement of DDH, Automated annotation of the DDH measurement through deep learning, AI-assisted junior sonographer measurement of DDH
- Medical subject headings
- Developmental Dysplasia of the Hip
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Junior sonographer measurement of DDHOther
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 DDHOther
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 learningOther
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 DDHOther
Participants will receive visual cues from the DeepDDH system.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Other: Junior sonographer measurement of DDH |
| 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. Receives: Other: Senior sonographer measurement of DDH |
| 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. Receives: Other: Automated annotation of the DDH measurement through deep learning |
| DeepDDH-assist Junior Sonographer Annotation | Experimental | Participants will receive visual cues from the DeepDDH system. Receives: Other: AI-assisted junior sonographer measurement of DDH |
What is being measured
The primary outcome is the main question the study is designed to answer.
Average diagnostic accuracy
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.
Measured: up to 4 weeks
Secondary outcomes (8)
Average diagnostic sensitivity
It is calculated by dividing the number of true positive cases by the sum of true positive cases and false negative cases.
Measured: up to 4 weeks
Average diagnostic specificity
It is calculated by dividing the number of true negative cases by the sum of true negative cases and false positive cases.
Measured: up to 4 weeks
Average times of follow-up visits
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.
Measured: up to 4 weeks
Diagnosis time
Time taken to make ultrasound diagnosis in each group
Measured: up to 4 weeks
Bang's index
Bang's index is used to evaluate whether the blind method is implemented successfully
Measured: up to 4 weeks
Frequency pediatrician adjusts preliminary annotation
Proportion of studies the annotation is changed
Measured: up to 4 weeks
Frequency pediatrician adjusts preliminary DDH type
Proportion of studies the DDH type is changed in final report
Measured: up to 4 weeks
Mean change in alpha angle between preliminary and final report
Average change in alpha angle between preliminary and final report
Measured: up to 4 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Jan 2025
- Study start18 Jul 2025
- Primary completion1 Aug 2025
- Study completion20 Aug 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Hip Dysplasia, DevelopmentalStudies of the same condition, open and under way.
- More trials run by RenJi HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Investigator, Outcomes assessor
- Enrolment
- 1,789 participants (actual)
Sponsor and investigators
- Lead sponsor
- RenJi Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Lixin Jiang, RenJi Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06803004
- Sponsor's protocol ID
- LY2025-004-C
- Acronym
- ASIDDH
- Status last verified
- Aug 2025
- First submitted
- 20 Jan 2025
- Last updated
- 28 Aug 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The clinical demographic information of the subjects was recorded through the Case Record Form, and the data will be collected and managed electronically through the ResMan platform.
Study at a glance
From the registry record, last updated by the sponsor on 28 Aug 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Blinded Randomized Control Trail of Artificial Intelligence-Assisted Ultrasound Screening for Neonatal Hip Dysplasia in a Clinical Cohort
- ClinicalTrials.gov ID
- NCT06803004
- Acronym / sponsor ID
- ASIDDH / LY2025-004-C
- Conditions
- Hip Dysplasia, Developmental
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 1,789 participants (actual)
- Lead sponsor
- RenJi HospitalUniversity, hospital or other
- Study start
- 18 Jul 2025 (actual)
- Primary completion
- 1 Aug 2025 (actual)
- Study completion
- 20 Aug 2025 (actual)
- First posted
- 31 Jan 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
- 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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (investigator, outcomes assessor)
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| Junior Sonographer Annotation | Active comparator | Other: Junior sonographer measurement of DDHParticipants 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 Annotation | Active comparator | Other: Senior sonographer measurement of DDHParticipants 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. |
| DeepDDH system Annotation | Experimental | Other: Automated annotation of the DDH measurement through deep learningThrough 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. |
| DeepDDH-assist Junior Sonographer Annotation | Experimental | Other: AI-assisted junior sonographer measurement of DDHParticipants will receive visual cues from the DeepDDH system. |
Who may qualify
- Ages
- 28 days to 6 months
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
Key inclusion criteria (2 listed)
- Infants underwent DDH ultrasound examinations.
- Infants aged 28 days to 6 months.
Key exclusion criteria (3 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Junior sonographer measurement of DDHParticipants 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. | Other | Junior Sonographer Annotation |
| Senior sonographer measurement of DDHParticipants 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. | Other | Senior Sonographer Annotation |
| Automated annotation of the DDH measurement through deep learningThrough 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. | Other | DeepDDH system Annotation |
| AI-assisted junior sonographer measurement of DDHParticipants will receive visual cues from the DeepDDH system. | Other | DeepDDH-assist Junior Sonographer Annotation |
Primary outcome
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.
8 secondary outcomes
Average diagnostic sensitivity
Time frame: up to 4 weeks
Average diagnostic specificity
Time frame: up to 4 weeks
Average times of follow-up visits
Time frame: up to 4 weeks
Diagnosis time
Time frame: up to 4 weeks
Bang's index
Time frame: up to 4 weeks
Frequency pediatrician adjusts preliminary annotation
Time frame: up to 4 weeks
Frequency pediatrician adjusts preliminary DDH type
Time frame: up to 4 weeks
Mean change in alpha angle between preliminary and final report
Time frame: up to 4 weeks
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Aug 2025.
- Individual participant dataSharing planned: Yes. The clinical demographic information of the subjects was recorded through the Case Record Form, and the data will be collected and managed electronically through the ResMan platform.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Junior sonographer measurement of DDH, Senior sonographer measurement of DDH and Automated annotation of the DDH measurement through deep learning in people with Hip Dysplasia, Developmental, run by RenJi Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 28 Aug 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Average diagnostic accuracy (time frame: up to 4 weeks). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Aug 2025.