1QB Information Technologies Inc
Vancouver, British Columbia, V6E 4B1, Canada
NCT Number: NCT04153045
xrAI (pronounced "X-ray") serves as a clinical assistance tool for trained clinical professionals who are interpreting chest radiographs. The tool is designed as a quality control and adjunct, limited, clinical decision support tool, and does not replace the role of clinical professionals. It highlights areas on chest radiographs for review by an interpreting clinician.
The objective of this study is to utilize machine learning and artificial intelligence algorithms (xrAI) to improve the quality and efficiency in the interpretation of chest radiographs by family doctors, nurse practitioners, emergency medicine physicians, internists, pulmonologists, and radiologists.
The hypothesis is that the addition of xrAI's analysis will reduce inter-observer variability in the interpretation of chest radiographs and increase participants' sensitivity, recall, and accuracy in pulmonary abnormality screening.
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Interventional
Not applicable
Vancouver, British Columbia, V6E 4B1, Canada
To investigate the effect of xrAI for clinicians that interpret chest radiographs as part of their daily responsibilities, the investigators have designed a randomized control trial.
The pulmonary abnormalities detected by xrAI and included in the definition of abnormal are as follows: any linear scar or fibrosis, atelectasis, consolidation, abscess or cavity, nodule, pleural effusion, severe cases of emphysema and COPD (mild cases with hyperinflation but not significant emphysema are not flagged), and pneumothorax.
To assess the causal effect of xrAI the investigators randomly assign 36 clinicians to either treatment (x-ray images processed by xrAI) or control (no xrAI processing) groups. Participants will only review images once. Each participant will perform 500 radiograph interpretations in total.
Participants in the control group will be asked to interpret the same 500 images without xrAI's analysis.
To increase the precision of the estimate and better investigate potential differences between clinical professionals, investigators block randomize the assignment of treatment or control group within each group of clinicians (family doctor, nurse practitioner, emergency medicine physician, internist, pulmonologist, radiologist). Within each group of clinicians, investigators will randomly assign half to treatment or control group. This randomized complete block design ensures that an equal number of each group of clinical professionals are represented in the treatment and control groups.
To analyse the effect of xrAI, the investigators will estimate the average treatment effect (ATE) for each subgroup by comparing the performance of the treatment and control groups using randomization-based inference (Green and Gerber, 2012).
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
The pulmonary abnormalities detected by xrAI and included in the definition of abnormality are as follows: any linear scar or fibrosis, atelectasis, consolidation, abscess or cavity, nodule, pleural effusion, severe cases of emphysema and COPD (mild cases with hyperinflation but not significant emphysema are not flagged), pneumothorax.
Participants in the treatment group will interpret 500 images presented alongside the results of xrAI's processing in a dark room and asked to categorize each image into one of the following categories: lungs are clear, at least one pulmonary abnormality is present, not sure.
Participants in the control group will be asked to interpret the same 500 images as the treatment group but without xrAI's analysis.
Time frame: Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.
Accuracy is defined as the ratio of the images where the physician's prediction matched the labels of the dataset.
Accuracy= (TP+FP) / (TP+FP+TN+FN)
TP (true positives) = cases interpreted as abnormal that are abnormal; FP (false positives) = cases wrongly interpreted to be abnormal; TN (true negatives) = cases correctly interpreted to be normal; FN (false negatives) = abnormal cases wrongly interpreted as normal.
Time frame: Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.
Precision is defined as the probability of a radiograph being abnormal if a physician makes the determination that it is abnormal.
Precision= TP / (TP+FP)
TP (true positives) = cases interpreted as abnormal that are abnormal; FP (false positives) = cases wrongly interpreted to be abnormal; TN (true negatives) = cases correctly interpreted to be normal; FN (false negatives) = abnormal cases wrongly interpreted as normal.
Time frame: Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.
Recall is defined as the probability of a physician catching an abnormality in an image if one exists (based on the labels of the dataset).
Recall= TP / (TP+FN)
TP (true positives) = cases interpreted as abnormal that are abnormal; FP (false positives) = cases wrongly interpreted to be abnormal; TN (true negatives) = cases correctly interpreted to be normal; FN (false negatives) = abnormal cases wrongly interpreted as normal.
Time frame: Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.
Investigators will calculate the mean of the accuracy of all participants in a group and the mean of the accuracy of all participants across all the groups.
Time frame: Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.
Investigators will calculate the mean of the precision of all participants in a group and the mean of the precision of all participants across all the groups.
Time frame: Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.
Investigators will calculate the mean of the recall of all participants in a group and the mean of the recall of all participants across all the groups.
1QB Information Technologies Inc.
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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