Deep learning models of ultrasonography significantly improved the differential diagnosis performance for superficial soft-tissue masses: a retrospective multicenter study

doi:10.1186/s12916-023-03099-9

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Deep learning models of ultrasonography significantly improved the differential diagnosis performance for superficial soft-tissue masses: a retrospective multicenter study
	Long, Bin 6,7; Zhang, Haoyan 4,5; Zhang, Han 3; Chen, Wen 6; Sun, Yang 6; Tang, Rui 6,7; Lin, Yuxuan 2; Fu, Qiang 1; Yang, Xin 4,5; Cui, Ligang 6,7
刊名	BMC MEDICINE
	2023-10-26
卷号	21 期号:1 页码:11
关键词	Superficial soft-tissue masses Deep learning model Ultrasound Diagnosis Computer-assisted diagnosis
ISSN号	1741-7015
DOI	10.1186/s12916-023-03099-9
通讯作者	Cui, Ligang(cuijuegang@126.com) ; Wang, Kun(kun.wang@ia.ac.cn)
英文摘要	BackgroundMost of superficial soft-tissue masses are benign tumors, and very few are malignant tumors. However, persistent growth, of both benign and malignant tumors, can be painful and even life-threatening. It is necessary to improve the differential diagnosis performance for superficial soft-tissue masses by using deep learning models. This study aimed to propose a new ultrasonic deep learning model (DLM) system for the differential diagnosis of superficial soft-tissue masses.MethodsBetween January 2015 and December 2022, data for 1615 patients with superficial soft-tissue masses were retrospectively collected. Two experienced radiologists (radiologists 1 and 2 with 8 and 30 years' experience, respectively) analyzed the ultrasound images of each superficial soft-tissue mass and made a diagnosis of malignant mass or one of the five most common benign masses. After referring to the DLM results, they re-evaluated the diagnoses. The diagnostic performance and concerns of the radiologists were analyzed before and after referring to the results of the DLM results.ResultsIn the validation cohort, DLM-1 was trained to distinguish between benign and malignant masses, with an AUC of 0.992 (95% CI: 0.980, 1.0) and an ACC of 0.987 (95% CI: 0.968, 1.0). DLM-2 was trained to classify the five most common benign masses (lipomyoma, hemangioma, neurinoma, epidermal cyst, and calcifying epithelioma) with AUCs of 0.986, 0.993, 0.944, 0.973, and 0.903, respectively. In addition, under the condition of the DLM-assisted diagnosis, the radiologists greatly improved their accuracy of differential diagnosis between benign and malignant tumors.ConclusionsThe proposed DLM system has high clinical application value in the differential diagnosis of superficial soft-tissue masses.
资助项目	Not applicable.
WOS关键词	ULTRASOUND ; TUMORS ; CT
WOS研究方向	General & Internal Medicine
语种	英语
出版者	BMC
WOS记录号	WOS:001086980200002
资助机构	Not applicable.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54352]
专题	自动化研究所_中国科学院分子影像重点实验室
通讯作者	Cui, Ligang; Wang, Kun
作者单位	1.Beijing Civil Aviat Gen Hosp, Dept Ultrasound, Beijing, Peoples R China 2.Capital Med Univ, Beijing Friendship Hosp, Dept Ultrasound, Beijing, Peoples R China 3.Hebei Med Univ, Hosp 2, Dept Ultrasound, Shijiazhuang, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 5.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 6.Peking Univ Third Hosp, Dept Diagnost Ultrasound, Beijing, Peoples R China 7.Peking Univ Hlth Sci Ctr, Inst Med Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Long, Bin,Zhang, Haoyan,Zhang, Han,et al. Deep learning models of ultrasonography significantly improved the differential diagnosis performance for superficial soft-tissue masses: a retrospective multicenter study[J]. BMC MEDICINE,2023,21(1):11.
APA	Long, Bin.,Zhang, Haoyan.,Zhang, Han.,Chen, Wen.,Sun, Yang.,...&Wang, Kun.(2023).Deep learning models of ultrasonography significantly improved the differential diagnosis performance for superficial soft-tissue masses: a retrospective multicenter study.BMC MEDICINE,21(1),11.
MLA	Long, Bin,et al."Deep learning models of ultrasonography significantly improved the differential diagnosis performance for superficial soft-tissue masses: a retrospective multicenter study".BMC MEDICINE 21.1(2023):11.