Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions

doi:10.1016/j.ejrad.2019.02.032

	Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions
	Xu, Min1,2 ; Fang, Mengjie2,3 ; Zou, Jian 5; Yang, Shudong 6; Yu, Dongdong2,3 ; Zhong, Lianzhen 2,3; Hu, Chaoen2,3 ; Zang, Yali2,3 ; Di, Dong 2,3,4; Tian, Jie2,3,4
刊名	EUROPEAN JOURNAL OF RADIOLOGY
	2019-05-01
卷号	114 页码:38-44
关键词	Prostate cancer Radiomics Biparametric magnetic resonance imaging Medical imaging
ISSN号	0720-048X
DOI	10.1016/j.ejrad.2019.02.032
通讯作者	Di, Dong(di.dong@ia.ac.cn) ; Tian, Jie(jie.tian@ia.ac.cn) ; Fang, Xiangming(xiangming_fang@njmu.edu.cn)
英文摘要	Purpose: To investigate the efficiency of radiomics signature in discriminating between benign and malignant prostate lesions with similar biparametric magnetic resonance imaging (bp-MRI) findings. Experimental design: Our study consisted of 331 patients underwent bp-MRI before pathological examination from January 2013 to November 2016. Radiomics features were extracted from peripheral zone (PZ), transition zone (TZ), and lesion areas segmented on images obtained by T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and its derivative apparent-diffusion coefficient (ADC) imaging. The individual prediction model, built using the clinical data and biparametric MRI features (Bp signature), was prepared using data of 232 patients and validated using data of 99 patients. The predictive performance was calculated and demonstrated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results: The Bp signature, based on the six selected radiomics features of bp-MRI, showed better discrimination in the validation cohort (area under the curve [AUC], 0.92) than on each subcategory images (AUC, 0.81 on T2WI; AUC, 0.77 on DWI; AUC, 0.89 on ADC). The differential diagnostic efficiency was poorer with the clinical model (AUC, 0.73), built using the selected independent clinical risk factors with statistical significance (P < 0.05), than with the Bp signature. Discrimination efficiency improved when including the Bp signature and clinical factors [i.e., the individual prediction model (AUC, 0.93)]. Conclusion: The Bp signature, based on bp-MRI, performed better than each single imaging modality. The individual prediction model including the radiomics signatures and clinical factors showed better preoperative diagnostic performance, which could contribute to clinical individualized treatment.
资助项目	special program for science and technology development from the Ministry of science and technology, China ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences ; National Natural Science Foundation of China
WOS关键词	ACTIVE SURVEILLANCE ; HISTOGRAM ANALYSIS ; CANCER STATISTICS ; TUMOR-DETECTION ; RESONANCE ; PREDICTION ; BIOPSY ; ELIGIBILITY ; MORTALITY ; DIAGNOSIS
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
语种	英语
出版者	ELSEVIER IRELAND LTD
WOS记录号	WOS:000464983700006
资助机构	special program for science and technology development from the Ministry of science and technology, China ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/24912]
专题	中国科学院自动化研究所
通讯作者	Di, Dong; Tian, Jie; Fang, Xiangming
作者单位	1.Nanjing Med Univ, Imaging Ctr, Wuxi Peoples Hosp, 299 Qingyang Rd, Wuxi 214023, Jiangsu, Peoples R China 2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China 4.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China 5.Nanjing Med Univ, Ctr Clin Res, Wuxi Peoples Hosp, 299 Qingyang Rd, Wuxi 214023, Jiangsu, Peoples R China 6.Nanjing Med Univ, Wuxi Peoples Hosp, Dept Pathol, 299 Qingyang Rd, Wuxi 214023, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Xu, Min,Fang, Mengjie,Zou, Jian,et al. Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions[J]. EUROPEAN JOURNAL OF RADIOLOGY,2019,114:38-44.
APA	Xu, Min.,Fang, Mengjie.,Zou, Jian.,Yang, Shudong.,Yu, Dongdong.,...&Fang, Xiangming.(2019).Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions.EUROPEAN JOURNAL OF RADIOLOGY,114,38-44.
MLA	Xu, Min,et al."Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions".EUROPEAN JOURNAL OF RADIOLOGY 114(2019):38-44.