Artificial Intelligence-based Models for Spine Malalignment Auto-analysis
Artificial Intelligence-based Models Enabling Robust and Precise Spine Malalignment Auto-analysis in China: a Multicentre, Retrospective Cohort Study
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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Hong Kong, Hong Kong
- Digital Health Laboratory, Li Ka Shing Faculty of Medicine, The University of Hong Kong
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Participants aged between 10 and 18 years old,
- A pathological confirmation of the presence or absence of AIS
Exclusion Criteria:
- Patients with other types of scoliosis, such as congenital or neuromuscular scoliosis
- Patients with skin diseases, such as acne, psoriasis, skin pigmentation and rash that can affect imaging
- Individuals that cannot stand up
- Cases where standing imaging was not feasible or other conditions that could impair image acquisition.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
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QMH&DKCH cohort
A total of 1,950 whole spine posteroanterior X-rays collected from two local hospitals (QMH and DKCH) were utilized for the development and internal validation of our model.
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PUMCH cohort
314 whole spine posteroanterior X-rays from Peking Union Medical College Hospital, Beijing, China
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NFH cohort
94 whole spine posteroanterior X-rays from Nanfang Hospital, Guangzhou, China
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JSTH cohort
187 whole spine posteroanterior X-rays from Jishuitan Hospital, Beijing, China
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RJH cohort
294 whole spine posteroanterior X-rays from Ruijin Hospital, Shanghai, China
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HSH cohort
176 whole spine posteroanterior X-rays from Huashan Hospital, Shanghai, China
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Cobb Angle prediction accuracy
Time Frame: through study completion, an average of 1 year
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Coronal Cobb angle was adopted as the standard measurement to evaluate the coronal alignment of each AIS patient.
We evaluate the performance of our artificial intelligence model based on Cobb Angle prediction accuracy.
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through study completion, an average of 1 year
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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AIS severity classification accuracy
Time Frame: through study completion, an average of 1 year
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Deformities with a CA exceeding 40° were deemed severe, those ranging from 20° to 40° were labelled as moderate, and angles from 0° to 20° were identified as normal to mild.
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through study completion, an average of 1 year
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimated)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- UW 24-350
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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