Subo Zhang, Jinxin Wan, Yongjun Xu, Leiming Huo, Lei Xu, Jiabao Xia, Zhitao Zhu, Jingfang Liu, Yan Zhao
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Meta-analyses were performed to calculate pooled areas under the curve (AUC) and prostate cancer detection rates.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":49283,"journal":{"name":"International Braz J Urol","volume":"51 3","pages":""},"PeriodicalIF":4.5000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12052022/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predictive Value of Multiparametric Magnetic Resonance Imaging (T2-weighted Imaging and Apparent Diffusion Coefficient) for Pathological Grading of Prostate Cancer: a Meta-Analysis.\",\"authors\":\"Subo Zhang, Jinxin Wan, Yongjun Xu, Leiming Huo, Lei Xu, Jiabao Xia, Zhitao Zhu, Jingfang Liu, Yan Zhao\",\"doi\":\"10.1590/S1677-5538.IBJU.2024.0509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":49283,\"journal\":{\"name\":\"International Braz J Urol\",\"volume\":\"51 3\",\"pages\":\"\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12052022/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Braz J Urol\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1590/S1677-5538.IBJU.2024.0509\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"UROLOGY & NEPHROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Braz J Urol","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1590/S1677-5538.IBJU.2024.0509","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
引用次数: 0
摘要
目的:本meta分析旨在评估多参数磁共振成像(mpMRI),特别是t2加权成像(T2WI)和表观扩散系数(ADC)图在前列腺癌病理分级中的预测价值。方法:在PubMed、中国国家知识基础设施数据库、Web of Science、施普林格Link和Cochrane Library等多个数据库进行综合文献检索。研究评估了mpMRI在前列腺癌分级中的应用。使用偏倚风险工具评估纳入研究的质量。进行荟萃分析,计算曲线下汇总面积(AUC)和前列腺癌检出率。结果:7项研究符合纳入标准,实验组843例,对照组962例。荟萃分析显示mpMRI在诊断性能上有显著改善,合并平均AUC差异为0.10(95%可信区间[CI]: 0.04-0.16, p = 0.002), mpMRI组更有利。前列腺癌的优势比为2.60 (95% CI: 1.57-4.29, p = 0.0002),与标准技术相比,mpMRI的检出率更高。研究间存在显著的异质性(AUC I²= 73%,检出率I²= 66%)。结论:本荟萃分析表明mpMRI,特别是T2WI和ADC成像对前列腺癌的病理分级具有重要的预测价值。与传统方法相比,该技术显示出更高的诊断准确性和更高的癌症检出率。然而,研究之间的巨大异质性表明,需要对mpMRI方案和解释标准进行标准化。
Predictive Value of Multiparametric Magnetic Resonance Imaging (T2-weighted Imaging and Apparent Diffusion Coefficient) for Pathological Grading of Prostate Cancer: a Meta-Analysis.
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.