Efficiency And Impact Factors of Anatomical Intelligence For Breast And Hand-Held Ultrasound In Lesion Screening: A Pilot Study

Abstract

Objective: To investigate the efficiency and impact factors of anatomical intelligence for breast (AI-Breast) and hand-held ultrasound (HHUS) in lesion screening. Methods: A total of 172 outpatient women were randomly selected, underwent AI-Breast ultrasound (Group AI) once and HHUS twice. HHUS was performed by breast image radiologists (Group A) and general radiologists (Group B). For the AI-Breast examination, a trained technician performed the whole-breast scan and data acquisition, while other general radiologists performed image interpretation. The examination time and lesion detection rate were recorded. The impact factors for breast lesion screening, including breast cup size, lesion number (LN), and benign or malignant lesions were analyzed.Results: Scan times of Groups AI, A, and B were 262.15±40.4 s, 237.5±110.3 s, 281.2±86.1 s, respectively. The scan time of Group AI was significantly higher than Group A (P<0.01), but was slightly lower than Group B (P>0.05). The detection rates of Group AI, A, and B were 92.8±17.0%, 95.0±13.6%, and 85.0±22.9%, respectively. Comparable lesion detection rates were observed in Group AI and Group A (P>0.05), but a significantly lower lesion detection rate was observed in Group B compared to the other two (both P<0.05). Regarding missed diagnosis rates of malignant lesions, comparable performance was observed in Group AI, Group A, and Group B (8% vs. 4% vs. 14%, all P>0.05). We found a strong linear correlation between scan time and cup size in Group AI (r=0.745). No impacts of cup size and LN were found on the lesion detection rate in Group AI (P>0.05). Conclusions: The screening efficiency of AI-Breast ultrasound was comparable to that of a breast image radiologist and superior to that of the general radiologist. AI-Breast ultrasound may be used as a potential approach for breast cancer screening.