Quality in MR reporting (include improvements in acquisition using AI)

doi:10.1259/bjr.20210816

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

	Quality in MR reporting (include improvements in acquisition using AI)
	Wang, Liang 4; Margolis, Daniel J.2; Chen, Min 3; Zhao, Xinming 6; Li, Qiubai 5; Yang, Zhenghan 4; Tian, Jie 1,7; Wang, Zhenchang 4
刊名	BRITISH JOURNAL OF RADIOLOGY
	2022
卷号	95 期号:1131 页码:7
ISSN号	0007-1285
DOI	10.1259/bjr.20210816
通讯作者	Wang, Liang(1311935272@qq.com)
英文摘要	The high quality of MRI reporting of the prostate is the most critical component of the service provided by a radiologist. Prostate MRI structured reporting with PI-RADS v. 2.1 has been proven to improve consistency, quality, guideline-based care in the management of prostate cancer. There is room for improved accuracy of prostate mpMRI reporting, particularly as PI-RADS core criteria are subjective for radiologists. The application of artificial intelligence may support radiologists in interpreting MRI scans. This review addresses the quality of prostate multiparametric MRI (mpMRI) structured reporting (include improvements in acquisition using artificial intelligence) in terms of size of prostate gland, imaging quality, lesion location, lesion size, TNM staging, sector map, and discusses the future prospects of quality in MR reporting.
资助项目	National Natural Science Foundation of China[82071887,81671656]
WOS关键词	PROSTATE-CANCER ; CLINICALLY SIGNIFICANT ; PREDICTION ; CLASSIFICATION ; SYSTEM
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	BRITISH INST RADIOLOGY
WOS记录号	WOS:000768233900002
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/48090]
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	Wang, Liang
作者单位	1.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China 2.Weill Cornell Med New York Presbyterian, Dept Radiol, New York, NY USA 3.Chinese Acad Med Sci, Beijing Hosp, Natl Ctr Gerontol, Inst Geriatr Med,Dept Radiol, Beijing, Peoples R China 4.Capital Med Univ, Dept Radiol, Affiliated Beijing Friendship Hosp, Beijing, Peoples R China 5.Univ Iowa, Dept Radiol, Roy Carver Coll Med, Iowa City, IA 52242 USA 6.Chinese Acad Med Sci & Peking Union Med Coll, Natl Canc Ctr, Dept Diagnost Radiol, Natl Clin Res Ctr Canc,Canc Hosp, Beijing, Peoples R China 7.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wang, Liang,Margolis, Daniel J.,Chen, Min,et al. Quality in MR reporting (include improvements in acquisition using AI)[J]. BRITISH JOURNAL OF RADIOLOGY,2022,95(1131):7.
APA	Wang, Liang.,Margolis, Daniel J..,Chen, Min.,Zhao, Xinming.,Li, Qiubai.,...&Wang, Zhenchang.(2022).Quality in MR reporting (include improvements in acquisition using AI).BRITISH JOURNAL OF RADIOLOGY,95(1131),7.
MLA	Wang, Liang,et al."Quality in MR reporting (include improvements in acquisition using AI)".BRITISH JOURNAL OF RADIOLOGY 95.1131(2022):7.