Compression FractureNCT04384211
QOCA®-Image Medical Platform - Smart VCF Risk Management System
An observational study of Compression Fracture, run by Taipei Medical University WanFang Hospital at 1 site in Taiwan.
Trial 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. Read more about this study
- Who is it for?
- Ages 50 to 90 yearsHealthy volunteers can take part
- Conditions the study is for
- Compression Fracture
- What is being tested?
- Computer Assisted Detection Software For Vertebral Fractures
- How many people
- 1,500 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Jun 2019to 31 May 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 50 to 90 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
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.
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Smart Bone: An Intelligent Fracture Risk Capture and Management System
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.
Read the detailed description
A computer search of CT scans (2010.01.01-2018.09.30) was performed in Wan Fang Hospital. Those CT images that were retrospectively reviewed by experienced radiologists. The CT scans of 1000-1500 subjects aged 50 and above with and without thoracic or lumbar compression fractures were included in this project for machine learning and deep learning. The control group included those without compression fractures while the patient group were those with compression fractures. Subjects that did not meet the inclusion criteria were excluded.
The cortical layer of the T12-L5 spine images were manually labelled with the labeling software by the the technologists and confirmed the correctness of the image by an experienced radiologist. All the de-linked and completed images were provided to Quanta Computer Inc. for subsequent classification and analysis of AI machines for deep learning to facilitate the development of a system for automatic detection of pressure fractures by CT. This newly developed automatic system will be of valuable clinical impact in assisting radiologists to detect and classify vertebral compression fractures precisely and accurately.
- Conditions
- Compression Fracture
- Being tested
- Computer Assisted Detection Software For Vertebral Fractures
- Medical subject headings
- Fractures, Compression
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Computer Assisted Detection Software For Vertebral FracturesOther
Also called Smart Bone
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.
| Study group | Role | What they receive |
|---|---|---|
| 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). Receives: Other: Computer Assisted Detection Software For Vertebral Fractures |
What is being measured
The primary outcome is the main question the study is designed to answer.
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%
Measured: 2019.06 to 2020.03
Secondary outcomes (1)
Accuracy
Comparing to the accuracy of CT imaging results by radiologists with and without CADe will be evaluated.
Measured: 2019.06 to 2020.03
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 May 2020
- Study start1 Jun 2019
- Primary completion31 May 2021 (estimated)
- Study completion31 May 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Compression FractureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Taipei Medical University WanFang Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Quanta Computer Inc.
- Responsible party
- Principal investigator, Wing P Chan, Taipei Medical University WanFang Hospital
- Investigators
- Wing P. Chan, M.D., Principal investigator, Taipei Medical University WanFang Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04384211
- Sponsor's protocol ID
- N201909056
- Status last verified
- Oct 2020
- First submitted
- 7 May 2020
- Last updated
- 8 Oct 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 8 Oct 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Smart Bone: An Intelligent Fracture Risk Capture and Management System
- ClinicalTrials.gov ID
- NCT04384211
- Acronym / sponsor ID
- N201909056
- Conditions
- Compression Fracture
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- Taipei Medical University WanFang HospitalUniversity, hospital or other
- Collaborators
- Quanta Computer Inc.
- Study start
- 1 Jun 2019 (actual)
- Primary completion
- 31 May 2021 (estimated)
- Study completion
- 31 May 2021 (estimated)
- First posted
- 12 May 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
A computer search of CT scans (2010.01.01-2018.09.30) was performed in Wan Fang Hospital. Those CT images that were retrospectively reviewed by experienced radiologists. The CT scans of 1000-1500 subjects aged 50 and above with and without thoracic or lumbar compression fractures were included in this project for machine learning and deep learning. The control group included those without compression fractures while the patient group were those with compression fractures. Subjects that did not meet the inclusion criteria were excluded.
The cortical layer of the T12-L5 spine images were manually labelled with the labeling software by the the technologists and confirmed the correctness of the image by an experienced radiologist. All the de-linked and completed images were provided to Quanta Computer Inc. for subsequent classification and analysis of AI machines for deep learning to facilitate the development of a system for automatic detection of pressure fractures by CT. This newly developed automatic system will be of valuable clinical impact in assisting radiologists to detect and classify vertebral compression fractures precisely and accurately.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| 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 | – | Other: Computer Assisted Detection Software For Vertebral FracturesThe 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). |
Who may qualify
- Ages
- 50 to 90 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (6 listed)
- 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
Key exclusion criteria (2 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Computer Assisted Detection Software For Vertebral FracturesAlso: Smart BoneA 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. | Other | Smart Bone |
Primary outcome
Concordance rate
Time frame: 2019.06 to 2020.03
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%
1 secondary outcome
Accuracy
Time frame: 2019.06 to 2020.03
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Oct 2020.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Wing P. Chan, M.D. principal investigator
Taipei Medical University WanFang Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Compression Fracture, run by Taipei Medical University WanFang Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 8 Oct 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Concordance rate (time frame: 2019.06 to 2020.03). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Oct 2020.