Testing a Computational Model to Estimate Patient SizeVocMepAdarNCT03341546
Estimating Patient Size From a Single Radiograph
An observational study of Testing a Computational Model to Estimate Patient Size, run by NHS Tayside at 1 site in United Kingdom.
Trial summary
A computational model has been created to estimate the abdominal depth of a patient from a single x-ray image. The model has been tested using phantoms and found to be accurate; this study aims to test the accuracy of the model with patients and in a clinical setting. Read more about this study
- Who is it for?
- Ages 17 years and older
- Conditions the study is for
- Testing a Computational Model to Estimate Patient Size
- What is being tested?
- A single measurement of the patient's abdominal depth
- How many people
- 20 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 13 Mar 2018to 24 Aug 2018
- Phase
- Observational
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
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 17 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Ambulatory outpatients attending Ninewells Hospital's radiology department for an anterior-posterior abdomen x-ray examination
Who may be able to join
- Adult
- Referred to Ninewells Hospital for an anterior-posterior abdomen x-ray examination
Who cannot join
- Patients unable to give consent
- Patients who have had a contrast injection in the previous 24 hours
- Patients suffering abdominal pain at the time of the examination
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Validation of a Computational Model to Estimate Patient Anterior-posterior Dimension From an Abdominal Radiograph
A computational model has been created to estimate the abdominal depth of a patient from a single x-ray image. The model has been tested using phantoms and found to be accurate; this study aims to test the accuracy of the model with patients and in a clinical setting.
This will be achieved by enrolling patient's who have already been referred for an anterior-posterior abdomen x-ray examination to the trial, taking a physical measurement of their anterior-posterior abdominal depth and then comparing this measured value with a value as estimated using the computational model based on the patient's x-ray image.
Read the detailed description
A non-commercial computational model has been developed in-house to estimate the patient's anterior-posterior or lateral depth using the radiographic image and the known exposure factors with which it was undertaken. This model has been tested using single composition phantoms and found to be accurate. If it was found to be accurate for real clinical examinations, this would automate the measurement of patient size and give institutions the estimate of patient size required for local paediatric patient dose audit. In turn, this would provide the national data required to propose national reference values for paediatric x-ray examinations, which would give all institutions an important comparator for their performance. This would lead to optimisation in those sites most requiring it; nationally, paediatric x-ray imaging would improve in time.
This pilot study is necessary to determine if the computational model is accurate enough to be relied upon. Accuracy will be determined by comparing the estimate made by the computational model for each patient with an actual measurement of the patient's anterior-posterior abdomen depth made at the time of the examination.
- Being tested
- A single measurement of the patient's abdominal depth
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
A single measurement of the patient's abdominal depthOther
A single measurement of the patient's anterior-posterior abdominal depth
| Study group | Role | What they receive |
|---|---|---|
| Patient cohort | 20 patients referred to Ninewells Hospital radiology department for an anterior-posterior abdomen x-ray examination. All of these patients will have a measurement of their anterior-posterior depth before undergoing their x-ray examination. An estimate of their anterior-posterior depth will then be made from their x-ray image using the computational model. Receives: Other: A single measurement of the patient's abdominal depth |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of the Computational Model
The computational model was used to estimate the patient's anterior-posterior abdominal depth using the digital radiographic image, the exposure factors with which it was acquired and a priori knowledge relating to the x-ray unit and digital detector.
The outcome measure was the accuracy with which the computational model estimates the patient's anterior-posterior abdominal depth. It was determined by comparing the estimate to measured anterior-posterior abdominal depth (measured at the time of the x-ray examination). Results are expressed as a percentage deviation; a low % deviation is more accurate, a high % deviation less accurate.
Measured: 2 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Nov 2017
- Study start13 Mar 2018
- Primary completion7 May 2018
- Study completion24 Aug 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for Testing a Computational Model to Estimate Patient SizeStudies 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
- Case only
- Time perspective
- Cross-sectional
- Enrolment
- 20 participants (actual)
Sponsor and investigators
- Lead sponsor
- NHS Tayside
- Sponsor type
- Other government
- Collaborators
- University of Dundee
- Responsible party
- Principal investigator, Mark Worrall, NHS Tayside
- Investigators
- Sarah Vinnicombe, MD, Study chair, University of Dundee
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03341546
- Sponsor's protocol ID
- 2017RA01
- Acronym
- VocMepAdar
- Status last verified
- Jun 2019
- First submitted
- 31 Oct 2017
- Last updated
- 11 Jun 2019
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 11 Jun 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of a Computational Model to Estimate Patient Anterior-posterior Dimension From an Abdominal Radiograph
- ClinicalTrials.gov ID
- NCT03341546
- Acronym / sponsor ID
- VocMepAdar / 2017RA01
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 20 participants (actual)
- Lead sponsor
- NHS TaysideOther government
- Collaborators
- University of Dundee
- Study start
- 13 Mar 2018 (actual)
- Primary completion
- 7 May 2018 (actual)
- Study completion
- 24 Aug 2018 (actual)
- First posted
- 14 Nov 2017 (actual)
- Results
- Posted 11 Jun 2019
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
A computational model has been created to estimate the abdominal depth of a patient from a single x-ray image. The model has been tested using phantoms and found to be accurate; this study aims to test the accuracy of the model with patients and in a clinical setting.
This will be achieved by enrolling patient's who have already been referred for an anterior-posterior abdomen x-ray examination to the trial, taking a physical measurement of their anterior-posterior abdominal depth and then comparing this measured value with a value as estimated using the computational model based on the patient's x-ray image.
Detailed description
A non-commercial computational model has been developed in-house to estimate the patient's anterior-posterior or lateral depth using the radiographic image and the known exposure factors with which it was undertaken. This model has been tested using single composition phantoms and found to be accurate. If it was found to be accurate for real clinical examinations, this would automate the measurement of patient size and give institutions the estimate of patient size required for local paediatric patient dose audit. In turn, this would provide the national data required to propose national reference values for paediatric x-ray examinations, which would give all institutions an important comparator for their performance. This would lead to optimisation in those sites most requiring it; nationally, paediatric x-ray imaging would improve in time.
This pilot study is necessary to determine if the computational model is accurate enough to be relied upon. Accuracy will be determined by comparing the estimate made by the computational model for each patient with an actual measurement of the patient's anterior-posterior abdomen depth made at the time of the examination.
Study design
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patient cohort | – | Other: A single measurement of the patient's abdominal depth20 patients referred to Ninewells Hospital radiology department for an anterior-posterior abdomen x-ray examination. All of these patients will have a measurement of their anterior-posterior depth before undergoing their x-ray examination. An estimate of their anterior-posterior depth will then be made from their x-ray image using the computational model. |
Who may qualify
- Ages
- 17 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Ambulatory outpatients attending Ninewells Hospital's radiology department for an anterior-posterior abdomen x-ray examination
Key inclusion criteria (2 listed)
- Adult
- Referred to Ninewells Hospital for an anterior-posterior abdomen x-ray examination
Key exclusion criteria (3 listed)
- Patients unable to give consent
- Patients who have had a contrast injection in the previous 24 hours
- Patients suffering abdominal pain at the time of the examination
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 |
|---|---|---|
| A single measurement of the patient's abdominal depthA single measurement of the patient's anterior-posterior abdominal depth | Other | Patient cohort |
Primary outcome
Accuracy of the Computational Model
Time frame: 2 months
The computational model was used to estimate the patient's anterior-posterior abdominal depth using the digital radiographic image, the exposure factors with which it was acquired and a priori knowledge relating to the x-ray unit and digital detector. The outcome measure was the accuracy with which the computational model estimates the patient's anterior-posterior abdominal depth. It was determined by comparing the estimate to measured anterior-posterior abdominal depth (measured at the time of the x-ray examination). Results are expressed as a percentage deviation; a low % deviation is more accurate, a high % deviation less accurate.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Jun 2019.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Individual participant dataSharing planned: No
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.
Sarah Vinnicombe, MD study chair
University of Dundee
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 Testing a Computational Model to Estimate Patient Size, run by NHS Tayside at 1 site in United Kingdom.
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 2 inclusion and 3 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: finished, as of the sponsor's last update on 11 Jun 2019. 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 United Kingdom. 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?
Yes. Results are posted in the registry (first posted 11 Jun 2019). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
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?
Accuracy of the Computational Model (time frame: 2 months). 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 11 Jun 2019; AzTrials last refreshed its copy on 29 Oct 2026.