Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis

Scoliosis Clinical Trial

Official title:

Validation of the Utility of an Artificial System for the Large-scale Screening of Scoliosis Using Back Images

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03773458
• Other study ID #: CCPMOH2018-China-13
• Status: Completed
• Phase: N/A
• Start date: June 1, 2018
• Est. completion date: July 30, 2018

Study information

• Verified date: December 2018
• Source: Sun Yat-sen University
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical 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 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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 500
• Est. completion date: July 30, 2018
• Est. primary completion date: July 30, 2018
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 10 Years to 22 Years

Eligibility

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).

Related Conditions & MeSH terms

• Artificial Intelligence
• Musculoskeletal Diseases
• Orthopedic Disorder of Spine
• Scoliosis
• Spinal Diseases

Intervention

Device:
• An artificial system for the screening of scoliosis
An artificial intelligence to make evaluation of scoliosis using back images

Locations

Country	Name	City	State
China	Zhongshan Ophthalmic Center, Sun Yat-sen University	Guangzhou	Guangdong

Sponsors (1)

Lead Sponsor	Collaborator
Sun Yat-sen University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The proportion of accurate, mistaken and miss detection of the intelligent visual acuity diagnostic system.		Up to 5 years