Hip Dysplasia, DevelopmentalNCT06765525
Efficacy Study of DeepDDH System in Screening Infants with Developmental Dysplasia of the Hip (DDH)
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
- 1,976 participants
- Where
- 1 siteChina
- Study dates
- 15 Jan 2025to 30 Apr 2025
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 aged 28 days to 6 months who underwent DDH ultrasound examination in Renji Hospital, Shanghai Jiaotong University School of Medicine and the Sixth People's Hospital, Shanghai Jiaotong University School of Medicine between August 2014 and December 2021
Who cannot join
- Patients lacking or incomplete ultrasound images;
- Patients with poor image quality and unusable images after assessment, including non-compliance with Anatomical identification (Checklist I consists of seven anatomical structures: 1. Chondro-osseous border, 2. Femoral head, 3. Synovial fold, 4. Joint capsule and perichondrium, 5. Labrum, 6. Cartilagineous roof, 7. Bony roof) and Usability check (Checklist II includes three anatomical landmarks: 1. Lower limb of the os ilium, 2. Parallel middle plane, and 3. Labrum);
- Infants with hip dysplasia caused by other diseases such as cerebral palsy, joint contracture, suppurative coxitis, etc., or with other hip diseases and limb deformities.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, 200127
Hui Cao, +86 021-6838-3364, rjllb3364@163.com
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, Shanghai Jiao Tong University School of Medicine and the Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine. Renji Hospital, the Sixth People's Hospita, 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. Each unit can perform Graf ultrasound examination maturely, and has good quality control and management. The technology is relatively mature, and they are responsible for providing 6 expert sonographers with more than 5-10 years of DDH ultrasound diagnosis experience, more than 600 DDH ultrasound operations, and 1 pediatric orthopedic expert 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 8 primary sonographers (trained residents who performed 20 DDH ultrasound operations) to participate in the study. The other 4 primary sonographers who participated in the study were provided by the Sixth People's Hospital and the Pediatric Hospital Affiliated to Fudan University, so a total of 12 primary sonographers participated in the study. Before the study, the sonographers involved in this study will be evaluated uniformly and quantitatively through online examination papers.
- Research process:
One week before the start of the randomized diagnostic trial study, which prospectively reevaluated the retrospective data set of the ultrasound screening sequence database, the sonographers registered in the study received uniform training in 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 (composed of 6 ultrasound experts), the primary sonographer group (composed of 6 primary sonographers), and the primary sonographer (composed of 6 primary sonographers) + AI-assisted group. All the image data in the ultrasound screening sequence database were independently divided into measurement points and measurement lines by each group, and the final diagnosis of α Angle, β Angle and classification results were given by the system.
The random occurrence of cases in the ultrasound screening sequence database has certain rules: (1) According to the date of ultrasound examination, the 2152 ultrasound screenings were divided into 848 days. (2) Block randomization was applied to the 848-day study, using a computer-generated sequence of random numbers, with randomization performed in blocks of four or eight. That is, the cases examined for the first time in each day were divided into one group (AI group, advanced ultrasound expert group, primary sonographer group, AI-assisted primary sonographer group), and the cases for follow-up examination were divided according to the first examination group. Randomization was repeated within each group according to block randomization of 6 or 12 block sizes.
When non-first subsequent follow-up cases were randomly presented, the results of the previous examination were included as a reference. In the AI-assisted group, each sonographer was asked to choose whether to modify or confirm the diagnosis according to the measurement points, diagnostic angles and typing results provided by the AI device. However, in the advanced ultrasound expert group, 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 ultrasound experts with 10 years of experience in DDH ultrasound diagnosis was used as the gold standard. In case of disagreement, a third pediatric expert with 5-10 years of experience in DDH diagnosis and treatment was used to evaluate the diagnosis and treatment of DDH. The final consensus was used as the gold standard.
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 and follow-up time).
- 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 meaturement 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
Also called Junior Sonographer Annotation
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
Also called Senior Sonographer Annotation
Participants will not receive visual cues from the DeepDDH system.
Automated annotation of the DDH measurement through deep learningOther
Also called DeepDDH system Annotation
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 meaturement of DDHOther
Also called DeepDDH-assist Junior Sonographer Annotation
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. 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 meaturement 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: 30 Minutes
Secondary outcomes (3)
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: 30 Minutes
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: 30 Minutes
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. The specific calculation of follow-up visits is as follows: For each participating infant, if a false positive diagnosis is made and there are no more subsequent follow-up examination results, the number of follow-up visits is increased by 1; if a false negative diagnosis leads to the end of the follow-up process for the participating infant, then no further follow-up visits are counted.
Measured: 30 Minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jan 2025
- Study start15 Jan 2025 (estimated)
- Primary completion30 Mar 2025 (estimated)
- Study completion30 Apr 2025 (estimated)
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
- 1,976 participants (estimated)
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
- NCT06765525
- Sponsor's protocol ID
- KY2021-286-B
- Status last verified
- Jan 2025
- First submitted
- 3 Jan 2025
- Last updated
- 9 Jan 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 was collected and managed electronically through the ResMan platform.
Study at a glance
From the registry record, last updated by the sponsor on 9 Jan 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
- NCT06765525
- Acronym / sponsor ID
- KY2021-286-B
- Conditions
- Hip Dysplasia, Developmental
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,976 participants (estimated)
- Lead sponsor
- RenJi HospitalUniversity, hospital or other
- Study start
- 15 Jan 2025 (estimated)
- Primary completion
- 30 Mar 2025 (estimated)
- Study completion
- 30 Apr 2025 (estimated)
- First posted
- 9 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, Shanghai Jiao Tong University School of Medicine and the Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine. Renji Hospital, the Sixth People's Hospita, 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. Each unit can perform Graf ultrasound examination maturely, and has good quality control and management. The technology is relatively mature, and they are responsible for providing 6 expert sonographers with more than 5-10 years of DDH ultrasound diagnosis experience, more than 600 DDH ultrasound operations, and 1 pediatric orthopedic expert 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 8 primary sonographers (trained residents who performed 20 DDH ultrasound operations) to participate in the study. The other 4 primary sonographers who participated in the study were provided by the Sixth People's Hospital and the Pediatric Hospital Affiliated to Fudan University, so a total of 12 primary sonographers participated in the study. Before the study, the sonographers involved in this study will be evaluated uniformly and quantitatively through online examination papers.
- Research process:
One week before the start of the randomized diagnostic trial study, which prospectively reevaluated the retrospective data set of the ultrasound screening sequence database, the sonographers registered in the study received uniform training in 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 (composed of 6 ultrasound experts), the primary sonographer group (composed of 6 primary sonographers), and the primary sonographer (composed of 6 primary sonographers) + AI-assisted group. All the image data in the ultrasound screening sequence database were independently divided into measurement points and measurement lines by each group, and the final diagnosis of α Angle, β Angle and classification results were given by the system.
The random occurrence of cases in the ultrasound screening sequence database has certain rules: (1) According to the date of ultrasound examination, the 2152 ultrasound screenings were divided into 848 days. (2) Block randomization was applied to the 848-day study, using a computer-generated sequence of random numbers, with randomization performed in blocks of four or eight. That is, the cases examined for the first time in each day were divided into one group (AI group, advanced ultrasound expert group, primary sonographer group, AI-assisted primary sonographer group), and the cases for follow-up examination were divided according to the first examination group. Randomization was repeated within each group according to block randomization of 6 or 12 block sizes.
When non-first subsequent follow-up cases were randomly presented, the results of the previous examination were included as a reference. In the AI-assisted group, each sonographer was asked to choose whether to modify or confirm the diagnosis according to the measurement points, diagnostic angles and typing results provided by the AI device. However, in the advanced ultrasound expert group, 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 ultrasound experts with 10 years of experience in DDH ultrasound diagnosis was used as the gold standard. In case of disagreement, a third pediatric expert with 5-10 years of experience in DDH diagnosis and treatment was used to evaluate the diagnosis and treatment of DDH. The final consensus was used as the gold standard.
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 and follow-up time).
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. |
| 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 meaturement 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 (1 listed)
- Infants aged 28 days to 6 months who underwent DDH ultrasound examination in Renji Hospital, Shanghai Jiaotong University School of Medicine and the Sixth People's Hospital, Shanghai Jiaotong University School of Medicine between August 2014 and December 2021
Key exclusion criteria (3 listed)
- Patients lacking or incomplete ultrasound images;
- Patients with poor image quality and unusable images after assessment, including non-compliance with Anatomical identification (Checklist I consists of seven anatomical structures: 1. Chondro-osseous border, 2. Femoral head, 3. Synovial fold, 4. Joint capsule and perichondrium, 5. Labrum, 6. Cartilagineous roof, 7. Bony roof) and Usability check (Checklist II includes three anatomical landmarks: 1. Lower limb of the os ilium, 2. Parallel middle plane, and 3. Labrum);
- Infants with hip dysplasia caused by other diseases such as cerebral palsy, joint contracture, suppurative coxitis, etc., or with other hip diseases and limb deformities.
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 DDHAlso: Junior Sonographer AnnotationParticipants 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 DDHAlso: Senior Sonographer AnnotationParticipants will not receive visual cues from the DeepDDH system. | Other | Senior Sonographer Annotation |
| Automated annotation of the DDH measurement through deep learningAlso: DeepDDH system AnnotationThrough 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 meaturement of DDHAlso: DeepDDH-assist Junior Sonographer AnnotationParticipants will receive visual cues from the DeepDDH system. | Other | DeepDDH-assist Junior Sonographer Annotation |
Primary outcome
Average diagnostic accuracy
Time frame: 30 Minutes
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.
3 secondary outcomes
Average diagnostic sensitivity
Time frame: 30 Minutes
Average diagnostic specificity
Time frame: 30 Minutes
Average times of follow-up visits
Time frame: 30 Minutes
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Jan 2025.
- Individual participant dataSharing planned: Yes. The clinical demographic information of the subjects was recorded through the Case Record Form, and the data was 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.
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 1 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: opening soon, as of the sponsor's last update on 9 Jan 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Lixin Jiang, PhD (+86 18930173496, jinger_28@sina.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Average diagnostic accuracy (time frame: 30 Minutes). 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 9 Jan 2025.