Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis
Primary Purpose
Orthopedic Disorder of Spine, Artificial Intelligence, Scoliosis
Status
Completed
Phase
Not Applicable
Locations
China
Study Type
Interventional
Intervention
An artificial system for the screening of scoliosis
Sponsored by
About this trial
This is an interventional diagnostic trial for Orthopedic Disorder of Spine focused on measuring Orthopedic Disorder of Spine
Eligibility Criteria
Inclusion Criteria:
- 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.
Exclusion Criteria:
- 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).
Sites / Locations
- Zhongshan Ophthalmic Center, Sun Yat-sen University
Arms of the Study
Arm 1
Arm Type
Other
Arm Label
Eligible patients for AI test.
Arm Description
Device: An artificial system for the screening of scoliosis
Outcomes
Primary Outcome Measures
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Secondary Outcome Measures
Full Information
NCT ID
NCT03773458
First Posted
December 10, 2018
Last Updated
December 10, 2018
Sponsor
Sun Yat-sen University
1. Study Identification
Unique Protocol Identification Number
NCT03773458
Brief Title
Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis
Official Title
Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis Using Back Images
Study Type
Interventional
2. Study Status
Record Verification Date
December 2018
Overall Recruitment Status
Completed
Study Start Date
June 1, 2018 (Actual)
Primary Completion Date
July 30, 2018 (Actual)
Study Completion Date
July 30, 2018 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Sun Yat-sen University
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
5. Study Description
Brief 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 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.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Orthopedic Disorder of Spine, Artificial Intelligence, Scoliosis
Keywords
Orthopedic Disorder of Spine
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
500 (Actual)
8. Arms, Groups, and Interventions
Arm Title
Eligible patients for AI test.
Arm Type
Other
Arm Description
Device: An artificial system for the screening of scoliosis
Intervention Type
Device
Intervention Name(s)
An artificial system for the screening of scoliosis
Intervention Description
An artificial intelligence to make evaluation of scoliosis using back images
Primary Outcome Measure Information:
Title
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Time Frame
Up to 5 years
10. Eligibility
Minimum Age & Unit of Time
10 Years
Maximum Age & Unit of Time
22 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria:
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.
Exclusion Criteria:
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).
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Haotian Lin
Organizational Affiliation
Zhongshan Ophthalmic Center, Sun Yat-sen University
Official's Role
Principal Investigator
Facility Information:
Facility Name
Zhongshan Ophthalmic Center, Sun Yat-sen University
City
Guangzhou
State/Province
Guangdong
ZIP/Postal Code
510000
Country
China
12. IPD Sharing Statement
Learn more about this trial
Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis
We'll reach out to this number within 24 hrs