Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Using biparametric MRI radiomics signature to differentiate between benign and malignant prostate lesions | |
Xu, Min1,2![]() ![]() ![]() ![]() ![]() ![]() ![]() | |
发表期刊 | EUROPEAN JOURNAL OF RADIOLOGY
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ISSN | 0720-048X |
2019-05-01 | |
卷号 | 114页码:38-44 |
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. |
关键词 | Prostate cancer Radiomics Biparametric magnetic resonance imaging Medical imaging |
DOI | 10.1016/j.ejrad.2019.02.032 |
关键词[WOS] | ACTIVE SURVEILLANCE ; HISTOGRAM ANALYSIS ; CANCER STATISTICS ; TUMOR-DETECTION ; RESONANCE ; PREDICTION ; BIOPSY ; ELIGIBILITY ; MORTALITY ; DIAGNOSIS |
收录类别 | SCI |
语种 | 英语 |
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 ; 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研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000464983700006 |
出版者 | ELSEVIER IRELAND LTD |
七大方向——子方向分类 | 医学影像处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/24913 |
专题 | 中国科学院分子影像重点实验室 |
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 |
第一作者单位 | 中国科学院分子影像重点实验室 |
通讯作者单位 | 中国科学院分子影像重点实验室 |
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. |
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