Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA.
Department of Radiology, University Hospital, Palermo, Italy.
J Ultrasound Med. 2022 Jan;41(1):97-105. doi: 10.1002/jum.15684. Epub 2021 Mar 5.
We study the performance of an artificial intelligence (AI) program designed to assist radiologists in the diagnosis of breast cancer, relative to measures obtained from conventional readings by radiologists.
A total of 10 radiologists read a curated, anonymized group of 299 breast ultrasound images that contained at least one suspicious lesion and for which a final diagnosis was independently determined. Separately, the AI program was initialized by a lead radiologist and the computed results compared against those of the radiologists.
The AI program's diagnoses of breast lesions had concordance with the 10 radiologists' readings across a number of BI-RADS descriptors. The sensitivity, specificity, and accuracy of the AI program's diagnosis of benign versus malignant was above 0.8, in agreement with the highest performing radiologists and commensurate with recent studies.
The trained AI program can contribute to accuracy of breast cancer diagnoses with ultrasound.
我们研究了一种旨在协助放射科医生诊断乳腺癌的人工智能（AI）程序的性能，该程序与放射科医生进行的常规阅读获得的测量值相对比。
总共 10 名放射科医生阅读了一组经过精心挑选的、匿名的 299 张乳腺超声图像，这些图像至少包含一个可疑病变，并且有独立的最终诊断。此外，由一名首席放射科医生初始化 AI 程序，然后将计算结果与放射科医生的结果进行比较。
AI 程序对乳腺病变的诊断与 10 名放射科医生在多项 BI-RADS 描述符上的阅读结果一致。AI 程序对良性与恶性病变的诊断的灵敏度、特异性和准确性均高于 0.8，与表现最佳的放射科医生一致，与最近的研究结果相符。
经过训练的 AI 程序可以提高超声诊断乳腺癌的准确性。
