Department of Breast, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, China.
Department of Surgery, Changting Maternity and Children's Hospital, Longyan, Fujian, China.
Front Public Health. 2023 Jan 18;10:1098639. doi: 10.3389/fpubh.2022.1098639. eCollection 2022.
Artificial intelligence breast ultrasound diagnostic system (AIBUS) has been introduced as an alternative approach for handheld ultrasound (HHUS), while their results in BI-RADS categorization has not been compared.
This pilot study was based on a screening program conducted from May 2020 to October 2020 in southeast China. All the participants who received both HHUS and AIBUS were included in the study ( = 344). The ultrasound videos after AIBUS scanning were independently watched by a senior radiologist and a junior radiologist. Agreement rate and weighted Kappa value were used to compare their results in BI-RADS categorization with HHUS.
The detection rate of breast nodules by HHUS was 14.83%, while the detection rates were 34.01% for AIBUS videos watched by a senior radiologist and 35.76% when watched by a junior radiologist. After AIBUS scanning, the weighted Kappa value for BI-RADS categorization between videos watched by senior radiologists and HHUS was 0.497 ( < 0.001) with an agreement rate of 78.8%, indicating its potential use in breast cancer screening. However, the Kappa value of AIBUS videos watched by junior radiologist was 0.39, when comparing to HHUS.
AIBUS breast scan can obtain relatively clear images and detect more breast nodules. The results of AIBUS scanning watched by senior radiologists are moderately consistent with HHUS and might be used in screening practice, especially in primary health care with limited numbers of radiologists.
人工智能乳腺超声诊断系统（AIBUS）已作为手持超声（HHUS）的替代方法引入，但其在 BI-RADS 分类中的结果尚未进行比较。
本研究为 2020 年 5 月至 2020 年 10 月在中国东南部进行的筛查项目的基础上进行的。所有接受 HHUS 和 AIBUS 检查的参与者均纳入本研究（n=344）。AIBUS 扫描后，由一名资深放射科医生和一名初级放射科医生独立观看超声视频。使用一致性率和加权 Kappa 值来比较他们在 BI-RADS 分类中的结果与 HHUS 的结果。
HHUS 检测到的乳腺结节检出率为 14.83%，而由资深放射科医生观看的 AIBUS 视频的检出率为 34.01%，由初级放射科医生观看的检出率为 35.76%。AIBUS 扫描后，资深放射科医生观看的视频与 HHUS 的 BI-RADS 分类之间的加权 Kappa 值为 0.497（<0.001），一致性率为 78.8%，表明其在乳腺癌筛查中具有潜在的应用价值。然而，与 HHUS 相比，由初级放射科医生观看的 AIBUS 视频的 Kappa 值为 0.39。
AIBUS 乳腺扫描可以获得相对清晰的图像并检测到更多的乳腺结节。由资深放射科医生观看的 AIBUS 扫描结果与 HHUS 中度一致，可能在筛查实践中使用，特别是在放射科医生人数有限的初级保健中。
