Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis
1 other identifier
interventional
500
1 country
1
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Jun 2018
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
June 1, 2018
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 30, 2018
CompletedStudy Completion
Last participant's last visit for all outcomes
July 30, 2018
CompletedFirst Submitted
Initial submission to the registry
December 10, 2018
CompletedFirst Posted
Study publicly available on registry
December 12, 2018
CompletedDecember 12, 2018
December 1, 2018
2 months
December 10, 2018
December 10, 2018
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.
Up to 5 years
Study Arms (1)
Eligible patients for AI test.
OTHERDevice: An artificial system for the screening of scoliosis
Interventions
An artificial intelligence to make evaluation of scoliosis using back images
Eligibility Criteria
You may qualify if:
- 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.
You may not qualify if:
- \. 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).
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, 510000, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Haotian Lin
Zhongshan Ophthalmic Center, Sun Yat-sen University
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- DIAGNOSTIC
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Clinical Professor
Study Record Dates
First Submitted
December 10, 2018
First Posted
December 12, 2018
Study Start
June 1, 2018
Primary Completion
July 30, 2018
Study Completion
July 30, 2018
Last Updated
December 12, 2018
Record last verified: 2018-12