Trial Outcomes & Findings for Estimating Patient Size From a Single Radiograph (NCT NCT03341546)

NCT ID: NCT03341546

Last Updated: 2019-06-11

Results Overview

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.

• Recruitment status: COMPLETED
• Target enrollment: 20 participants
• Primary outcome timeframe: 2 months
• Results posted on: 2019-06-11

Participant Flow

Participant milestones

Measure	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. A single measurement of the patient's abdominal depth: A single measurement of the patient's anterior-posterior abdominal depth
Overall Study STARTED	20
Overall Study COMPLETED	20
Overall Study NOT COMPLETED	0

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Estimating Patient Size From a Single Radiograph

Baseline characteristics by cohort

Measure	Patient Cohort n=20 Participants 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. A single measurement of the patient's abdominal depth: A single measurement of the patient's anterior-posterior abdominal depth
Age, Categorical <=18 years	0 Participants n=5 Participants
Age, Categorical Between 18 and 65 years	15 Participants n=5 Participants
Age, Categorical >=65 years	5 Participants n=5 Participants
Sex: Female, Male Female	10 Participants n=5 Participants
Sex: Female, Male Male	10 Participants n=5 Participants
Ethnicity (NIH/OMB) Hispanic or Latino	0 Participants n=5 Participants
Ethnicity (NIH/OMB) Not Hispanic or Latino	0 Participants n=5 Participants
Ethnicity (NIH/OMB) Unknown or Not Reported	20 Participants n=5 Participants
Region of Enrollment United Kingdom	20 participants n=5 Participants

PRIMARY outcome

Timeframe: 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.

Outcome measures

Measure

Patient Cohort n=20 Participants 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. A single measurement of the patient's abdominal depth: A single measurement of the patient's anterior-posterior abdominal depth

Accuracy of the Computational Model

5.8 percentage agreement (est/measured) Standard Deviation 4.6

Adverse Events

Patient Cohort

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Mark Worrall

NHS Tayside

Phone: 01382632177

Email: markworrall@nhs.net

Results disclosure agreements

• Principal investigator is a sponsor employee
• Publication restrictions are in place