|Table of Contents|

Clinical application value of MRI radiomics in differentiating prostate cancer from prostatic hyperplasia

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2023 07
Page:
1301-1306
Research Field:
Publishing date:

Info

Title:
Clinical application value of MRI radiomics in differentiating prostate cancer from prostatic hyperplasia
Author(s):
FANG Xiaodong1; 2; DENG Lei1; ZHANG Lei2; YANG Quanxin1
1.The Second Affiliated Hospital of Xi'an Jiaotong University,Shaanxi Xi'an 710004,China;2.The 521 Hospital of Norinco Group,Shaanxi Xi'an 710065,China.
Keywords:
prostate cancer; benign prostatic hyperplasia; magnetic resonance imaging; radiomics; differential diagnosis
PACS:
R737.25
DOI:
10.3969/j.issn.1672-4992.2023.07.023
Abstract:
Objective:To investigate the application value of radiomics model based on T2WI and apparent diffusion coefficient(ADC) in diagnosis of prostate cancer(PCa) and benign prostatic hyperplasia(BPH).Methods:The clinical data and original MRI images of 72 patients with PCa and 64 patients with BPH confirmed by needle biopsy pathology were retrospectively analyzed.The region of interest(ROI) of the tumor(excluding cystic change,hemorrhage,necrosis and calcification) was manually delineated using ITK-SNAP software to volume of interest(VOI).High-throughput radiomics features were extracted from T2WI and ADC images using FAE software.Pearson correlation method and recursive feature elimination(RFE) method were used for feature screening.Support vector machine(SVM) was used as a classifier to construct the radiomics model.All cases were divided into training set and verification set according to 7∶3 by stratified random sampling.The receiver operating characteristic(ROC) curve and calibration curve analysis were used to analyze and evaluate the diagnostic efficacy and calibration ability of each radiomics model,and the differences between the models were evaluated by Delong's test.Results:After feature selection,12,15 and 11 image features were used to construct radiomics models based on T2WI,ADC and their combination.The area under the ROC curve(AUC) of each prediction model in the training set was 0.88,0.92 and 0.96, respectively,and the AUC of each prediction model in the validation set was 0.85,0.89 and 0.91,respectively.Delong test showed that the diagnostic performance of T2WI+ADC combined radiomics model was significantly higher than that of single sequence model,and the calibration curve showed that the combined radiomics model had better predictive ability.Conclusion:The T2WI+ADC combined radiomics model can distinguish PCa from BPH more comprehensively,objectively and accurately.

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Last Update: 2023-02-28