NCT04384211

Brief Summary

This project aims to develop and validate an automatic detection and classification system for vertebral compression fractures on computer tomography (CT) images using an artificial intelligence (AI) system (named Smart Bone) by Quanta.

Trial Health

43
At Risk

Trial Health Score

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

Trial has exceeded expected completion date
Enrollment
1,500

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jun 2019

Geographic Reach
1 country

1 active site

Status
unknown

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

Trial Relationships

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Study Timeline

Key milestones and dates

Study Start

First participant enrolled

June 1, 2019

Completed
11 months until next milestone

First Submitted

Initial submission to the registry

May 7, 2020

Completed
5 days until next milestone

First Posted

Study publicly available on registry

May 12, 2020

Completed
1.1 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

May 31, 2021

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

May 31, 2021

Completed
Last Updated

October 8, 2020

Status Verified

October 1, 2020

Enrollment Period

2 years

First QC Date

May 7, 2020

Last Update Submit

October 6, 2020

Conditions

Compression Fracture

Outcome Measures

Primary Outcomes (1)

  • Concordance rate

    CT Imaging Reporting and Data System descriptors suggested by Smart Bone are in good agreement with those selected by experts. In other words, the CT Imaging Reporting and Data System generated by Smart Bone are not statistically different from the consensus of experts. CT Imaging Reporting and Data System Assessment Category Score: The user makes the final decision on the Assessment Category Score. Using this Score, Smart Bone displays the assessment description. Grade 0: Normal Vertebrae Grade 1: Mild Fracture, 20-25% Grade 2: Moderate Fracture, 26-40% Grade 3: Severe Fracture, \>40%

    2019.06 to 2020.03

Secondary Outcomes (1)

  • Accuracy

    2019.06 to 2020.03

Study Arms (2)

Radiologists

A computer search of CT scans (2010.01.01-2018.09.30) was performed in Wan Fang Hospital. These CT images were retrospectively reviewed by an experienced radiologist who classified and marked with annotations of vertebral fractures by the Genant's semiquantitative method.

Smart Bone

The same CT images were separately reviewed and processed by the artificial intelligence system (Smart Bone) by Quanta for compression fractures. The two results, one by the radiologists and the other by artificial intelligence system, will be compared to statistically quantify equivalence (CADe).

Other: Computer Assisted Detection Software For Vertebral Fractures

Interventions

Computer Assisted Detection Software For Vertebral FracturesOTHER

A device named Smart Bone that is using CT image retrospectively acquired to entails a second review of CT images with Vertebral Compression Fractures through an interactive AI program developed by Quanta Computer Inc. was applied to the CT images. The device is a computer-aided detection (CADe) software application and is designed to assist radiologists to analyze Spine CT images. The device uses deep learning methods to perform vertebrae detection and classification of images.

Also known as: Smart Bone
Smart Bone

Eligibility Criteria

Age50 Years - 90 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

A total of 1000-1500 subjects were recruited in both sex, aged 50 and above, and who had come to Wan Fang Hospital for CT scans, including those with or without vertebral compression fractures as the compression fractures group and the control group respectively.

You may qualify if:

  • Cases with CT examinations acquired between 2010.01-2018.09
  • Cases with CT examinations performed with one of the following protocol: whole body, abdomen, and spine
  • Cases must be \>/= 50 years of age
  • Cases with reports from CT examinations ditched as positive or negative compression fractures within a search range from T12 to L5 vertebrae.
  • CT images with raw data that are allowed to be reconstructed in axial view with a slice thickness of 1.3 mm
  • CT images with raw data that are allowed to be reconstructed in sagittal view with a slice thickness of 2.5 mm

You may not qualify if:

  • CT images with imaging artifacts, foreign bodies, or implants
  • Cases with comorbid conditions, such as infection, cancer metastasis, chronic osteomyelitis, or other nonosteoporotic compression fracture

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Taipei Medical University WanFang Hospital

Taipei, Taiwan

Location

MeSH Terms

Conditions

Fractures, Compression

Condition Hierarchy (Ancestors)

Fractures, BoneWounds and Injuries

Study Officials

  • Wing P. Chan, M.D.

    Taipei Medical University WanFang Hospital

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
RETROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Professor and Chief, Department of Radiology, Wan Fang Hospital, Taipei Medical University

Study Record Dates

First Submitted

May 7, 2020

First Posted

May 12, 2020

Study Start

June 1, 2019

Primary Completion

May 31, 2021

Study Completion

May 31, 2021

Last Updated

October 8, 2020

Record last verified: 2020-10

Locations

TW(1)