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NCT05146193 | Recruiting | Spinal Deformity


AI-Powered Scoliosis Auto-Analysis System Multicenter Development and Validations
Sponsor:

The University of Hong Kong

Information provided by (Responsible Party):

Dr. Jason Pui Yin Cheung

Brief Summary:

The investigators aim to use artificial intelligence (AI) to help clinicians in diagnosing and assessing spinal deformities.

Condition or disease

Spinal Deformity

Intervention/treatment

Nude back photo

Detailed Description:

Background Spinal deformity is a prevalent spinal disorder in both paediatric and adult populations. The spine alignment need to be quantitively assessed for further treatment planning. However, the current practice requires spine surgeons to manually place landmarks of endplates and key vertebrae. The process is laborious and prone to inter- and intra-rater variance. Thus, the investigators have developed an AI-powered spine alignment assessment system (AlignProCARE) to facilitate clinicians in fast, accurate and consistent analytical results. The investigators aim to test and improve the performance of the spine alignment auto-analysis in all patients with spinal deformities in multiple centers including Malaysia, China, and Japan Objectives: prospectively test the alignment assessment of patients' spinal deformities with whole spine X-rays (both PA and lateral) and nude back image with the assessment via AlignProCARE. Collect 500 labeled deformity radiographs and nude back images in both PA and lateral views per center. 150 patients need to be followed up with radiographs and nude back photos collected (all parameters measured again). Use transfer learning to update the current AlignProCARE for scoliosis analysis to form AlignProCARE+. 4 Qualitatively analyse the AlignProCARE+ using an independent dataset.

Study Type : Observational
Estimated Enrollment : 2500 participants
Official Title: AI-Powered Scoliosis Auto-Analysis System Multicenter Development and Validations
Actual Study Start Date : May 1, 2022
Estimated Primary Completion Date : February 1, 2025
Estimated Study Completion Date : February 1, 2025

Information not available for Arms and Intervention/treatment

Ages Eligible for Study: 10 Years to 80 Years
Sexes Eligible for Study: All
Criteria
Inclusion Criteria
  • Idiopathic scoliosis, adult deformity (spondylolisthesis, idiopathic kyphosis, kyphoscoliosis, lordoscoliosis)
Exclusion Criteria
  • Refusal for imaging, postoperative patients

AI-Powered Scoliosis Auto-Analysis System Multicenter Development and Validations

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AI-Powered Scoliosis Auto-Analysis System Multicenter Development and Validations

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Locations


Recruiting

Hong Kong,

Duchess of Kent Children's Hospital

Hong Kong, Hong Kong,

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