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Clinical Article
Radiomics prediction model for the improved diagnosis of clinically significant prostate cancer on biparametric MRI
LI Mengjuan  ZHANG Caiyuan  ZHAO Wenlu  WEI Chaogang  ZHANG Yueyue  DING Ning  WANG Chengcheng  JI Yiding  SHEN Junkang 

Cite this article as: Li MJ, Zhang CY, Zhao WL, et al. Radiomics prediction model for the improved diagnosis of clinically significant prostate cancer on biparametric MRI[J]. Chin J Magn Reson Imaging, 2022, 13(11): 76-81. DOI:10.12015/issn.1674-8034.2022.11.014.

[Abstract] Objective To evaluate the radiomics model constructed based on biparametric MRI for predicting clinically significant prostate cancer (csPCa).Materials and Methods The clinical, pathological and imaging data of 381 patients (non-csPCa group 239, csPCa group 142) were analyzed retrospectively. Through image preprocessing and segmentation, feature extraction and selection, the radiomics model was established and its diagnostic value was evaluated.Results The radiomics model based on biparametric MRI showed good intra-observer and inter-observer consistency, and the constructed radiomics model had high diagnostic value for csPCa. The area under the curve (AUC) values of the training group and the test group were 0.991 and 0.983, respectively.Conclusions The biparametric MRI is an effective method to detect csPCa. The radiomics model constructed by training and testing has high diagnostic value for csPCa, which is relatively objective and accurate. It can be used as an auxiliary method for clinical diagnosis of csPCa, and provide an important reference for clinical decision-making of patient diagnosis and treatment.
[Keywords] prostate cancer;magnetic resonance imaging;radiomics;diagnostic efficacy

LI Mengjuan1   ZHANG Caiyuan2*   ZHAO Wenlu2   WEI Chaogang2   ZHANG Yueyue2   DING Ning1   WANG Chengcheng1   JI Yiding1   SHEN Junkang2  

1 Department of Imaging, Suzhou Ninth People's Hospital, Suzhou 215004, China

2 Department of Imaging, Second Affiliated Hospital of Soochow University, Suzhou 215004, China

Zhang CY, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China Youth Science Foundation (No. 81801754); Suzhou Science and Technology Development Plan (No. SS2019012); the Hospital-Level Scientific Research Project of Suzhou Ninth People's Hospital (No. YK202020).
Received  2021-11-25
Accepted  2022-11-04
DOI: 10.12015/issn.1674-8034.2022.11.014
Cite this article as: Li MJ, Zhang CY, Zhao WL, et al. Radiomics prediction model for the improved diagnosis of clinically significant prostate cancer on biparametric MRI[J]. Chin J Magn Reson Imaging, 2022, 13(11): 76-81. DOI:10.12015/issn.1674-8034.2022.11.014.

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