Predictive Value of Multiparametric Magnetic Resonance Imaging (T2-weighted Imaging and Apparent Diffusion Coefficient) for Pathological Grading of Prostate Cancer: a Meta-Analysis

被引:0
作者
Zhang, Subo [1 ,2 ,3 ]
Wan, Jinxin [1 ,2 ,3 ]
Xu, Yongjun [1 ,2 ,3 ]
Huo, Leiming [1 ,2 ,3 ]
Xu, Lei [1 ,2 ,3 ]
Xia, Jiabao [1 ,2 ,3 ]
Zhu, Zhitao [1 ,2 ,3 ]
Liu, Jingfang [1 ,2 ,3 ]
Zhao, Yan [4 ]
机构
[1] Second Peoples Hosp Lianyungang, Dept Med Imaging, Lianyungang, Jiangsu, Peoples R China
[2] Jiangsu Univ, Lianyungang Clin Coll, Dept Med Imaging, Lianyungang, Jiangsu, Peoples R China
[3] Nanjing Med Univ, Dept Med Imaging, Affiliated Kangda Coll, Peoples Hosp Lianyungang 2, Lianyungang, Jiangsu, Peoples R China
[4] Second Peoples Hosp Lianyungang, Dept Resp, 41 Hailian East Rd, Lianyungang 222000, Jiangsu, Peoples R China
来源
INTERNATIONAL BRAZ J UROL | 2025年 / 51卷 / 03期
关键词
Prostatic Neoplasms; Multiparametric Magnetic Resonance Imaging; Meta-Analysis [Publication Type; BIOPSY; GUIDELINES; DIAGNOSIS; MRI;
D O I
10.1590/S1677-5538.IBJU.2024.0509
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Objective: This meta-analysis aimed to evaluate the predictive value of multiparametric magnetic resonance imaging (mpMRI), specifically T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) maps, in the pathological grading of prostate cancer. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, the China National Knowledge Infrastructure dataset, Web of Science, Springer Link and Cochrane Library. Studies evaluating the use of mpMRI for prostate cancer grading were included. The quality of the included studies was assessed using the risk of bias tool. Meta-analyses were performed to calculate pooled areas under the curve (AUC) and prostate cancer detection rates. Results: Seven studies met the inclusion criteria, comprising 843 patients in the experimental group and 962 in the control group. The meta-analysis revealed a significant improvement in diagnostic performance with mpMRI, with a pooled mean difference in AUC of 0.10 (95% confidence interval [CI]: 0.04-0.16, p = 0.002) favouring the mpMRI group. The odds ratio for prostate cancer detection was 2.60 (95% CI: 1.57-4.29, p = 0.0002), indicating a higher detection rate with mpMRI compared with standard techniques. Substantial heterogeneity was observed among the studies (I2 = 73% for AUC and 66% for detection rate). Conclusion: This meta-analysis demonstrates that mpMRI, particularly T2WI and ADC imaging, has a significant predictive value in the pathological grading of prostate cancer. The technique shows improved diagnostic accuracy and higher cancer detection rates compared with conventional methods. However, the substantial heterogeneity among studies suggests that standardisation of mpMRI protocols and interpretation criteria is needed.
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页数:11
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共 30 条
[21]  
Schmit S, 2024, INT BRAZ J UROL, V50, P37, DOI [10.1590/S1677-5538.IBJU.2023.032, 10.1590/s1677-5538.ibju.2023.0321, 10.1590/S1677-5538.IBJU.2023.0321]
[22]   Comparison of MR/Ultrasound Fusion-Guided Biopsy With Ultrasound-Guided Biopsy for the Diagnosis of Prostate Cancer [J].
Siddiqui, M. Minhaj ;
Rais-Bahrami, Soroush ;
Turkbey, Baris ;
George, Arvin K. ;
Rothwax, Jason ;
Shakir, Nabeel ;
Okoro, Chinonyerem ;
Raskolnikov, Dima ;
Parnes, Howard L. ;
Linehan, W. Marston ;
Merino, Maria J. ;
Simon, Richard M. ;
Choyke, Peter L. ;
Wood, Bradford J. ;
Pinto, Peter A. .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2015, 313 (04) :390-397
[23]   Cancer statistics, 2020 [J].
Siegel, Rebecca L. ;
Miller, Kimberly D. ;
Jemal, Ahmedin .
CA-A CANCER JOURNAL FOR CLINICIANS, 2020, 70 (01) :7-30
[24]   MRI in prostate cancer diagnosis: do we need to add standard sampling? A review of the last 5 years [J].
Stabile, Armando ;
Giganti, Francesco ;
Emberton, Mark ;
Moore, Caroline M. .
PROSTATE CANCER AND PROSTATIC DISEASES, 2018, 21 (04) :473-487
[25]   Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2 [J].
Turkbey, Baris ;
Rosenkrantz, Andrew B. ;
Haider, Masoom A. ;
Padhani, Anwar R. ;
Villeirs, Geert ;
Macura, Katarzyna J. ;
Tempany, Clare M. ;
Choyke, Peter L. ;
Cornud, Francois ;
Margolis, Daniel J. ;
Thoeny, Harriet C. ;
Verma, Sadhna ;
Barentsz, Jelle ;
Weinreb, Jeffrey C. .
EUROPEAN UROLOGY, 2019, 76 (03) :340-351
[26]   Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference [J].
Vargas, H. A. ;
Hotker, A. M. ;
Goldman, D. A. ;
Moskowitz, C. S. ;
Gondo, T. ;
Matsumoto, K. ;
Ehdaie, B. ;
Woo, S. ;
Fine, S. W. ;
Reuter, V. E. ;
Sala, E. ;
Hricak, H. .
EUROPEAN RADIOLOGY, 2016, 26 (06) :1606-1612
[27]   Evaluation of Multiparametric Magnetic Resonance Imaging in Detection and Prediction of Prostate Cancer [J].
Wang, Rui ;
Wang, He ;
Zhao, Chenglin ;
Hu, Juan ;
Jiang, Yuanyuan ;
Tong, Yanjun ;
Liu, Ting ;
Huang, Rong ;
Wang, Xiaoying .
PLOS ONE, 2015, 10 (06)
[28]   PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2 [J].
Weinreb, Jeffrey C. ;
Barentsz, Jelle O. ;
Choyke, Peter L. ;
Cornud, Francois ;
Haider, Masoom A. ;
Macura, Katarzyna J. ;
Margolis, Daniel ;
Schnall, Mitchell D. ;
Shtern, Faina ;
Tempany, Clare M. ;
Thoeny, Harriet C. ;
Verma, Sadna .
EUROPEAN UROLOGY, 2016, 69 (01) :16-40
[29]   Monitoring radiotherapy induced tissue changes in localized prostate cancer by multi-parametric magnetic resonance imaging (MP-MRI) [J].
Wu, X. ;
Reinikainen, P. ;
Kapanen, M. ;
Vierikko, T. ;
Ryymin, P. ;
Kellokumpu-Lehtinen, P-L .
DIAGNOSTIC AND INTERVENTIONAL IMAGING, 2019, 100 (11) :699-708
[30]   Deep learning algorithm-based multimodal MRI radiomics and pathomics data improve prediction of bone metastases in primary prostate cancer [J].
Zhang, Yun-Feng ;
Zhou, Chuan ;
Guo, Sheng ;
Wang, Chao ;
Yang, Jin ;
Yang, Zhi-Jun ;
Wang, Rong ;
Zhang, Xu ;
Zhou, Feng-Hai .
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2024, 150 (02)