Danish startup company’s combined hand scanner and artificial intelligence analyzer perform similarly to human rheumatologists in determining joint severity.
WASHINGTON — A fully automated ultrasound scanning system combined with artificial intelligence–based disease activity scoring performed as well as expert rheumatologists in hand joint assessment of patients with, comprises an ultrasound scanner called ARTHUR that interacts directly with the patient and scans 11 joints per hand and a neural network–based software system, DIANA , that evaluates the images and monitors RA activity.
Gardner said it’s an advantage that the patient could potentially have an ARTHUR scan with a DIANA report and get blood tests done prior to a visit with the rheumatologist. “It’s really time-consuming for a human to do these studies, so if you automate it, that’s a step forward in terms of having the data available for the rheumatologist to view and use sequentially to follow how patients are doing.
A woman has the metacarpophalangeal joint of the index finger examined by the ARTHUR ultrasound scanner. For repeatability between the two ARTHUR scans, percent exact agreement was 63% for synovial hypertrophy, 75% for Doppler activity, and 60% combined. Percent close agreements were 93%, 94%, and 92%, respectively. Binary agreements as to whether the joint was healthy vs diseased were 88%, 91%, and 85%, respectively.
At the patient level , ARTHUR and DIANA’s binary disease assessment of healthy vs disease showed agreement with the ground truth of 87% for synovial hypertrophy, 83% for Doppler activity, and 87% combined. Here, the rheumatologists scored lower, at 53%, 67%, and 60%, respectively.
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