Validating racial and ethnic non-bias of artificial intelligence decision support for diagnostic breast ultrasound evaluation.

Purpose: Breast ultrasound suffers from low positive predictive value and specificity. Artificial intelligence (AI) proposes to improve accuracy, reduce false negatives, reduce inter- and intra-observer variability and decrease the rate of benign biopsies. Perpetuating racial/ethnic disparities in healthcare and patient outcome is a potential risk when incorporating AI-based models into clinical practice; therefore, it is necessary to validate its non-bias before clinical use. Approach: Our retrospective review assesses whether our AI decision support (DS) system demonstrates racial/ethnic bias by evaluating its performance on 1810 biopsy proven cases from nine breast imaging facilities within our health system from January 1, 2018 to October 28, 2021. Patient age, gender, race/ethnicity, AI DS output, and pathology results were obtained. Results: Significant differences in breast pathology incidence were seen across different racial and ethnic groups. Stratified analysis showed that the difference in output by our AI DS system was due to underlying differences in pathology incidence for our specific cohort and did not demonstrate statistically significant bias in output among race/ethnic groups, suggesting similar effectiveness of our AI DS system among different races (p>0.05 for all). Conclusions: Our study shows promise that an AI DS system may serve as a valuable second opinion in the detection of breast cancer on diagnostic ultrasound without significant racial or ethnic bias. AI tools are not meant to replace the radiologist, but rather to aid in screening and diagnosis without perpetuating racial/ethnic disparities.

Axillary adenopathy following COVID-19 vaccination: A single institution case series.

Axillary adenopathy is a potential side effect following COVID-19 vaccination. We report four cases of axillary adenopathy in the setting of recent COVID-19 vaccination (Moderna and Pfizer-BioNTech) at our institution. Our cases show unilateral axillary adenopathy, as well as adenopathy persisting for two to three weeks following vaccination. The Society of Breast Imaging (SBI) and Harvard University have each released guidelines for management of axillary adenopathy following COVID-19 vaccination. While SBI recommends short term imaging 4-12 weeks following the second dose, a group of physicians from Harvard suggest clinical follow-up with sonographic imaging if clinical concern persists beyond six weeks. As a larger percentage of the general population becomes vaccinated, it is important for radiologists to be aware of potential vaccine-induced ipsilateral axillary adenopathy on screening and diagnostic breast imaging to reduce the number of unnecessary biopsies performed in this patient population.