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

NCT ID: NCT03773458

Last Updated: 2018-12-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

500 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-06-01

Study Completion Date

2018-07-30

Brief Summary

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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.

Detailed Description

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Conditions

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Orthopedic Disorder of Spine Artificial Intelligence Scoliosis

Keywords

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Orthopedic Disorder of Spine

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Eligible patients for AI test.

Device: An artificial system for the screening of scoliosis

Group Type OTHER

An artificial system for the screening of scoliosis

Intervention Type DEVICE

An artificial intelligence to make evaluation of scoliosis using back images

Interventions

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An artificial system for the screening of scoliosis

An artificial intelligence to make evaluation of scoliosis using back images

Intervention Type DEVICE

Eligibility Criteria

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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).
Minimum Eligible Age

10 Years

Maximum Eligible Age

22 Years

Eligible Sex

Accepts Healthy Volunteers

Yes

Sponsors

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Sun Yat-sen University

OTHER

Sponsor Role lead

Responsible Party

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Haotian Lin

Clinical Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Haotian Lin

Role: PRINCIPAL_INVESTIGATOR

Zhongshan Ophthalmic Center, Sun Yat-sen University

Locations

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Zhongshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, China

Site Status

Countries

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China

Other Identifiers

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CCPMOH2018-China-13

Identifier Type: -

Identifier Source: org_study_id