efficiency of ai reporting (eair).

Conditions: Coronary Artery Disease

Summary: while there are features on a ccta that are correlated with plaque vulnerability and can be reported on, this is not always done. this is important as it is thought that vulnerable plaques present the greatest risk of myocardial infarction. this study will assess the correlation between software and human classification of these plaques, as well as demonstrating the time efficiency of ai reporting when compared to a clinician.

this is a retrospective observational study. it will be performed at london northwest healthcare nhs trust (lnwh -northwick park hospital (nph), harrow and ealing hospital, southall). patients who have had a ccta in the last 12 months will be contacted about the study. their ccta scans will already have been reported and the patient aware of the results. after giving informed consent, 100 patients will have their clinical ccta images uploaded to the artrya salix software for analysis. simultaneously the images will be re-reported by the physician as per standard of care. both reports will be obtained and any differences noted. the time the images are sent to artrya salix and report received will be recorded. the time the clinician opens the image to analyse and the time when the report is complete will also be recorded using a stopwatch. all images will be analysed by both expert readers to take account of inter-observer variability. the first 30 patients will be treated as a pilot for the study and after their recruitment and image upload and analysis, the team will meet to discuss any issues that have arisen. during the analysis, any patient who has plaque identified by the software or expert reader will have further analysis of their images. this is to look at the plaques in detail and to compare the sensitivity and specificity of the expert reader analysis. the time it takes for the clinician to report the scans on this group of patients will also be recorded. in addition, assessment will be made of the plaques using comparison of stenosis to calcium score. . data that will be collected will include: 1. demographic data (age, gender, ethnicity) 2. ccta results - standard of care 3. ccta results - artrya salix 4. time from image upload to artrya salix to time report received from artrya salix 5. time clinician takes to analyse scan 6. clinical assessment of plaque for vulnerable characteristics. the data will be from the electronic medical records of lnwuh nhs trust. a level 2 or level 3 cardiology imaging or radiology consultant will report the ccta images. data will be captured on an ecrf. the time of image upload to artrya salix will be recorded by the system and transposed directly into the ecrf. the time starting and ending image analysis by the clinician will be recorded on a worksheet as source documentation and then entered into the ecrf. a score will be given by the physician as to the likelihood of a plaque being vulnerable where 1= unlikely and 5 = highly likely.

Eligibility criteria:
inclusion criteria: * clinical ccta * able to provide informed consent exclusion criteria: * unable / unwilling to give informed consent * previous cabg or stent insertion

Keywords: artificial intelligence coronary artery disease ccta atherosclerotic plaque vulnerable plaque