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Utilization of artificial intelligence to triage patients with delayed follow-up of probably benign breast ultrasound findings
Tali Amir , Kristen Coffey, Jeffrey S Reiner, Varadan Sevilimedu, Victoria L Mango
Memorial Sloan Kettering Cancer Center, New York, United States
Corresponding Author: Tali Amir ,Tel: +1201-775-7153, Fax: NA, Email: amirt@mskcc.org
Received: November 16, 2024;  Accepted: January 21, 2025.  Published online: January 21, 2025.
ABSTRACT
Purpose:
To evaluate our institution's experience in using AI decision support as part of the clinical workflow to triage patients with Breast Imaging Reporting and Data System (BI-RADS) 3 sonographic lesions whose follow-up was delayed during the COVID-19 pandemic, against subsequent imaging and/or pathologic follow-up results.
Methods:
This retrospective study included patients with a BI-RADS category 3 (i.e., probably benign) breast ultrasound assessment from August 2019–December 2019 whose follow-up was delayed during the COVID-19 pandemic and whose breast ultrasounds were re-reviewed using Koios DS™ Breast AI as part of the clinical workflow for triaging these patients. The output of Koios DS was compared with the true outcome of a presence or absence of breast cancer defined by resolution/stability on imaging follow-up for at least 2 years or pathology results.
Results:
The study included 161 women (mean age, 52 years) with 221 BI-RADS category 3 sonographic lesions. Of the 221 lesions, there were 2 confirmed cancers (0.9% malignancy rate). Koios DS assessed 112/221 (51%) lesions as benign, 42/221 (19%) lesions as probably benign, 64/221 (29%) lesions as suspicious, and 3/221 (1%) lesions as probably malignant. Koios DS had a sensitivity of 100% (2/2; 95% CI: 16–100%), specificity of 70% (154/219; 95% CI: 64–76%), negative predictive value of 100% (154/154; 95% CI: 98–100%), and false positive rate of 30% (65/219; 95% CI: 24–36%).
Conclusion:
When many follow-up appointments are delayed, e.g., natural disaster, or scenarios where resources are limited, breast ultrasound AI decision support can help triage patients with probably benign breast ultrasounds.
Keywords: Artificial intelligence; Breast ultrasonography; Decision support systems; Clinical; COVID-19; Triage
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