trial testing A single measurement of the patient's abdominal depth in Testing a Computational Model to Estimate Patient Size in 20 participants. Completed in 24 August 2018.
17 and older, any sex, with Testing a Computational Model to Estimate Patient Size. Patients with the condition only — healthy volunteers not accepted.
Results — posted to ClinicalTrials.gov
Per-arm endpoint measurements with 95% confidence intervals where reported. Source: trial results section.
Accuracy of the Computational ModelPrimary· 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
Group
Value
95% CI
Patient Cohort
5.8
± 4.6
Sponsor's own description
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.
Publications & conference data
No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.
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Sponsor: as reported to ClinicalTrials.gov by NHS Tayside
Last refreshed: 11 June 2019
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