NCT06950411

Brief Summary

Spinal degeneration and its associated clinical diseases are common ailments in aging societies. With the advent of a super-aging society, the importance of assistive technologies for spinal image interpretation is increasingly significant to enhance care efficiency and reduce medical personnel expenditure. Recently, due to the rapid development of artificial intelligence (AI) algorithm, AI-based computer-assisted detection (CADe) devices gradiually become a convenient method for spinal anatomy measurement. However, the accuracy of these devices has not been fully established. This study aims to validate the performance of RadiSpine (an application program) in spinal anatomy segmentation and measurement.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
150

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Sep 2024

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

September 12, 2024

Completed
7 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

March 31, 2025

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

March 31, 2025

Completed
10 days until next milestone

First Submitted

Initial submission to the registry

April 10, 2025

Completed
20 days until next milestone

First Posted

Study publicly available on registry

April 30, 2025

Completed
Last Updated

April 30, 2025

Status Verified

April 1, 2025

Enrollment Period

7 months

First QC Date

April 10, 2025

Last Update Submit

April 24, 2025

Conditions

Keywords

Artificial Intelligence(AI) Algorithm Spinal anatomy

Outcome Measures

Primary Outcomes (1)

  • Segmentation accuracy (Mean)

    The minimum Mean Dice Coefficient (MDC), defined as the lower limit of the 95% confidence interval (CI) for MDC, is above a predetermined allowable limit equal to 0.8

    30 mins per individual

Secondary Outcomes (1)

  • Measurement accuracy

    30 mins per individual

Eligibility Criteria

Age22 Years - 75 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

The subjects should be aged 20 or older and younger than 75, with an equal gender distribution of 50% male and 50% female. From this group, 150 subjects with reasonable datavalues will be selected, with a requirement that at least 30% of them are male and at least 30% are female.

You may qualify if:

  • The subjects should be aged 20 or older and younger than 75, with an equal gender distribution of 50% male and 50% female. From this group, 150 subjects with reasonable datavalues will be selected, with a requirement that at least 30% of them are male and at least 30% are female.

You may not qualify if:

  • With history of spinal surgery
  • Spinal trauma
  • Spinal osteoporosis
  • Spinal metastasis or infection

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Taipei Veterans General Hospital

Taipei, Taipei, 112, Taiwan

Location

MeSH Terms

Conditions

Spinal Cord Compression

Condition Hierarchy (Ancestors)

Spinal Cord DiseasesCentral Nervous System DiseasesNervous System DiseasesSpinal Cord InjuriesWounds and Injuries

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
PROSPECTIVE
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

April 10, 2025

First Posted

April 30, 2025

Study Start

September 12, 2024

Primary Completion

March 31, 2025

Study Completion

March 31, 2025

Last Updated

April 30, 2025

Record last verified: 2025-04

Data Sharing

IPD Sharing
Will not share

Locations