Effectiveness of artificial intelligence-assisted ultrasound for breast cancer screening in Chinese women

doi:10.19401/j.cnki.1007-3639.2023.11.005

Abstract

Abstract:

Background and purpose: Artificial intelligence (AI) technology is increasingly being used in the medical field. This study aimed to assess the effectiveness of artificial intelligence ultrasound system for identifying breast lesions in Chinese women and its role in breast cancer early detection. Methods: A prospective study was conducted on healthy women aged 35-74 years who came to Fudan University Shanghai Cancer Center from August 2020 to December 2020 for breast ultrasonography. All the women were examined by AI-assisted ultrasound first, and then by conventional ultrasonography. We compared the differences between AI-assisted ultrasound and conventional ultrasonography in identifying breast lesions in Chinese women. One year later, we looked up the hospital medical history and Shanghai Cancer Registration Management System for the final diagnosis of breast cancer. Results: A total of 360 women were included in the study and received breast examinations using both AI-assisted ultrasound and conventional ultrasound. A total of 2 504 breast lesions were detected, of which, 2 217 were detected by AI-assisted ultrasound, with a lesion recognition rate of 88.5%. Conventional ultrasound identified 1 090 lesions, with a lesion recognition rate of 43.5%. Using conventional ultrasound as the standard, the sensitivity and specificity of AI-assisted ultrasound for Breast Imaging Reporting and Data System (BI-RADS) level 4 and above lesions were 93.3% (95% CI: 80.7-98.3) and 100.0% (95% CI: 99.5-100.0), respectively. During one-year follow-up, 10 patients were diagnosed with breast cancer, and 8 of whom were identified by both AI-assisted ultrasound and conventional B ultrasound. The sensitivity of AI-assisted ultrasound and conventional ultrasound for breast cancer was 80.0% (95% CI: 44.2-96.4), and the specificity was 88.6% (95% CI: 84.6-91.6). Conclusion: AI-assisted ultrasound has good identification ability for breast lesions in Chinese women. The recognition ability for high-risk breast lesions (BI-RADS 4A and above) and early breast cancer is equivalent to that of conventional ultrasound, which is suitable for breast cancer screening in large-scale community of women with general risk.

Key words: Breast cancer screening, Artificial intelligence, Breast ultrasonography

CLC Number:

R737.9

SHEN Jie, LIU Yajing, MO Miao, ZHOU Jin, WANG Zezhou, ZHOU Changming, ZHOU Shichong, CHANG Cai, ZHENG Ying. Effectiveness of artificial intelligence-assisted ultrasound for breast cancer screening in Chinese women[J]. China Oncology, 2023, 33(11): 1002-1008.

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Item		Conventional ultrasound
Item		BI-RADS 4	BI-RADS 2-3
AI-assisted ultrasound	BI-RADS 4	TP	FP
AI-assisted ultrasound	BI-RADS 2-3	FN	TN

BI-RADS	0	2-3	4A	4B	4C	Total
AI-assisted ultrasound	6 (100.0)	2 169 (88.4)	31 (93.9)	8 (100.0)	3 (75.0)	2 217 (88.5)
Conventional ultrasound	6 (100.0)	1 039 (42.4)	33 (100.0)	8 (100.0)	4 (100.0)	1 090 (43.5)
Total	6	2 453	33	8	4	2 504

Item	Conventional ultrasound^#		Total
Item	BI-RADS 4	BI-RADS 2-3	Total
AI-assisted ultrasound
BI-RADS 4	42	0	42
BI-RADS 2-3	3	1 039	1 042
Total	45	1 039	1 084^*

Item	Breast cancer^*		Total
Item	Positive	Negative	Total
AI-assisted ultrasound
Positive	8	40	48
Negative	2	310	312
Total	10	350	360

Item	Breast cancer^*		Total
Item	Positive	Negative	Total
Conventional ultrasound
Positive	8	40	48
Negative	2	310	312
Total	10	350	360