Orthopedic Disorder of SpineNCT03773458
Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis
A study testing An artificial system for the screening of scoliosis in people with Orthopedic Disorder of Spine and Artificial Intelligence, run by Sun Yat-sen University at 1 site in China.
Trial summary
Traditional school scoliosis screening approaches remains debatable due to unnecessary referal and excessive cost. Deep learning algorithms have proven to be powerful tools for the detection of multiple diseases; however, the application of such methods in scoliosis screening requires further assessment and… Read more about this study
- Who is it for?
- Ages 10 to 22 yearsHealthy volunteers can take part
- Conditions the study is for
- Orthopedic Disorder of Spine, Artificial Intelligence, Scoliosis
- What is being tested?
- An artificial system for the screening of scoliosis
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 500 participants
- Where
- 1 siteChina
- Study dates
- 1 Jun 2018to 30 Jul 2018
- 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 10 to 22 years
- Healthy volunteers accepted
- Child, Adult
Who may be able to join
- 1.Patients included both pretreatment back photos and whole spine (C7-S1) standing X-ray or ultrasound images (for healthy population); 2. All the documents are clear to be recognized by naked eyes; 3. Back photos and are taken at the same time (not >1month); 4.Patients were consider as idiopathic scoliosis according to clinical photos.
Who cannot join
- 1. Patients were considered as non-idiopathic scoliosis for obvious abnormal features of trunck,such as Cafe-au-Lait spots for neurofibromatosis, Spider finger, Abnormal hair spot of back, pelvic tilt, lower limb discrepancy and so on; 2.The taken time between back photo and X-ray or ultrasound was more than 1month; 3.The clinical photos and images were not clear; 4. The X-ray film or ultrasound images not including whole spine (C7-S1).
Trial locations and contacts
1 site in 1 country.
China1 site
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, 510000
About this study
Official title: Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis Using Back Images
Traditional school scoliosis screening approaches remains debatable due to unnecessary referal and excessive cost. Deep learning algorithms have proven to be powerful tools for the detection of multiple diseases; however, the application of such methods in scoliosis screening requires further assessment and validation. Here, the investigators develop an artificial system for the automated screening of scoliosis using disrobed back images, and conduct clinical trial to validate if the diagnostic system can offsetting the shortcomings of human doctors.
- Being tested
- An artificial system for the screening of scoliosis
- Keywords
- Orthopedic Disorder of Spine
- Medical subject headings
- Scoliosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
An artificial system for the screening of scoliosisDevice
An artificial intelligence to make evaluation of scoliosis using back images
| Study group | Role | What they receive |
|---|---|---|
| Eligible patients for AI test. | Other | Device: An artificial system for the screening of scoliosis Receives: Device: An artificial system for the screening of scoliosis |
What is being measured
The primary outcome is the main question the study is designed to answer.
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Measured: Up to 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Dec 2018
- Study start1 Jun 2018
- Primary completion30 Jul 2018
- Study completion30 Jul 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Orthopedic Disorder of SpineStudies of the same condition, open and under way.
- More trials run by Sun Yat-sen UniversityThe 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
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 500 participants (actual)
Sponsor and investigators
- Lead sponsor
- Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Haotian Lin, Sun Yat-sen University
- Investigators
- Haotian Lin, Principal investigator, Zhongshan Ophthalmic Center, Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03773458
- Sponsor's protocol ID
- CCPMOH2018-China-13
- Status last verified
- Dec 2018
- First submitted
- 10 Dec 2018
- Last updated
- 12 Dec 2018
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 12 Dec 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis Using Back Images
- ClinicalTrials.gov ID
- NCT03773458
- Acronym / sponsor ID
- CCPMOH2018-China-13
- Keywords
- Orthopedic Disorder of Spine
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 500 participants (actual)
- Lead sponsor
- Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 1 Jun 2018 (actual)
- Primary completion
- 30 Jul 2018 (actual)
- Study completion
- 30 Jul 2018 (actual)
- First posted
- 12 Dec 2018 (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.
Traditional school scoliosis screening approaches remains debatable due to unnecessary referal and excessive cost. Deep learning algorithms have proven to be powerful tools for the detection of multiple diseases; however, the application of such methods in scoliosis screening requires further assessment and validation. Here, the investigators develop an artificial system for the automated screening of scoliosis using disrobed back images, and conduct clinical trial to validate if the diagnostic system can offsetting the shortcomings of human doctors.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Eligible patients for AI test. | Other | Device: An artificial system for the screening of scoliosisDevice: An artificial system for the screening of scoliosis |
Who may qualify
- Ages
- 10 to 22 years
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
Key inclusion criteria (1 listed)
- 1.Patients included both pretreatment back photos and whole spine (C7-S1) standing X-ray or ultrasound images (for healthy population); 2. All the documents are clear to be recognized by naked eyes; 3. Back photos and are taken at the same time (not >1month); 4.Patients were consider as idiopathic scoliosis according to clinical photos.
Key exclusion criteria (1 listed)
- 1. Patients were considered as non-idiopathic scoliosis for obvious abnormal features of trunck,such as Cafe-au-Lait spots for neurofibromatosis, Spider finger, Abnormal hair spot of back, pelvic tilt, lower limb discrepancy and so on; 2.The taken time between back photo and X-ray or ultrasound was more than 1month; 3.The clinical photos and images were not clear; 4. The X-ray film or ultrasound images not including whole spine (C7-S1).
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 |
|---|---|---|
| An artificial system for the screening of scoliosisAn artificial intelligence to make evaluation of scoliosis using back images | Device | Eligible patients for AI test. |
Primary outcome
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Time frame: Up to 5 years
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 12 Dec 2018.
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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.
Haotian Lin principal investigator
Zhongshan Ophthalmic Center, Sun Yat-sen University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing An artificial system for the screening of scoliosis in people with Orthopedic Disorder of Spine and Artificial Intelligence, run by Sun Yat-sen University 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 1 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 12 Dec 2018. 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?
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system. (time frame: Up to 5 years). 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 12 Dec 2018.