xrAI - Improving Quality and Efficiency in Chest Radiograph Interpretation by Radiologists

NCT04221100 | Withdrawn

• 1 other identifier: xrAI ClinicalEvaluation Rads
• Study Type: interventional
• Target: N/A
• Locations: 0 countries
• Sites: N/A

Brief Summary

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 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.

Conditions

Pulmonary Disease

Outcome Measures

Primary Outcomes (3)

• Number of abnormalities identified divided by number of total of images analyzed (accuracy)

  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 needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.

• Number of true abnormalities identified divided by the total of abnormalities identified (precision)

  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 needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.

• Number of true abnormalities identified divided by the sum of true abnormalities identified and abnormalities missed (recall)

  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 needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.

Secondary Outcomes (3)

• Mean of radiologist accuracy (as defined in outcome 1)

  Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.

• Mean of radiologist precision (as defined in outcome 2)

  Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.

• Mean of radiologist recall (as defined in outcome 3)

  Time needed to analyze 500 images. Participants will be asked to completed the exercise within 2 weeks.

Study Arms (2)

Control

PLACEBO COMPARATOR

Participants will review the 500 chest radiographs without the assistance of xrAI

Device: Radiograph interpretation for pulmonary abnormalities

Treatment

EXPERIMENTAL

Participants will review the 500 chest radiographs with the assistance of xrAI

Device: Radiograph interpretation for pulmonary abnormalities

Interventions

Radiograph interpretation for pulmonary abnormalities DEVICE

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.

Control; Treatment

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Radiologist currently practicing at a Pureform Radiology clinic in Calgary, Canada.

You may not qualify if:

• Radiologists not currently practicing at a Pureform Radiology clinic in Calgary, Canada.
• Physicians currently practicing at a Pureform Radiology clinic in Calgary, Canada, but that are not radiologists by training.

Sponsors & Collaborators

• 1QB Information Technologies Inc.: lead

MeSH Terms

Conditions

Lung Diseases

Condition Hierarchy (Ancestors)

Respiratory Tract Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 6, 2020
• First Posted: January 9, 2020
• Study Start: March 1, 2021
• Primary Completion: May 1, 2021
• Study Completion: May 1, 2021
• Last Updated: February 23, 2021

Record last verified: 2021-02