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Prebiopsy multiparametric MRI‐based risk score for predicting prostate cancer in biopsy‐naive men with prostate‐specific antigen between 4–10?ng/mL

机译:基于前列药物 - 幼稚男性的前列腺癌预测前列腺癌前列腺癌前列腺癌预测癌前列腺癌

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Background Risk calculators have traditionally utilized serum prostate‐specific antigen (PSA) values in addition to clinical variables to predict the likelihood of prostate cancer (PCa). Purpose To develop a prebiopsy multiparametric MRI (mpMRI)‐based risk score (RS) and a statistical equation for predicting the risk of PCa in biopsy‐naive men with serum PSA between 4–10?ng/mL that may help reduce unnecessary biopsies. Study Type Prospective cross‐sectional study. Subjects In all, 137 consecutive men with PSA between 4–10?ng/mL underwent prebiopsy mpMRI (diffusion‐weighted [DW]‐MRI and MR spectroscopic imaging [MRSI]) during 2009–2015 were recruited for this study. Field Strength/Sequence 1.5T (Avanto, Siemens Health Care, Erlangen, Germany); T 1 ‐weighted, T 2 ‐weighted, DW‐MRI, and MRSI sequences were used. Assessment All eligible patients underwent mpMRI‐directed, cognitive‐fusion transrectal ultrasound (TRUS)‐guided biopsies. Statistical Tests An equation model and an RS were developed using receiver operating characteristic (ROC) curve analysis and a multivariable logistic regression approach. A 10‐fold crossvalidation and simulation analyses were performed to assess diagnostic performance of various combinations of mpMRI parameters. Results Of 137 patients, 32 were diagnosed with PCa on biopsy. Multivariable analysis, adjusted with positive pathology, showed apparent diffusion coefficient (ADC), metabolite ratio, and PSA as significant predictors of PCa ( P 0.05). A statistical equation was derived using these predictors. A simple 6‐point mpMRI‐based RS was derived for calculating the risk of PCa and it showed that it is highly predictive for PCa (odds ratio?=?3.74, 95% confidence interval [CI]: 2.24–6.27, area under the curve [AUC]?=?0.87). Both models (equation and RS) yielded high predictive performance (AUC ≥0.85) on validation analysis. Data Conclusion A statistical equation and a simple 6‐point mpMRI‐based RS can be used as a point‐of‐care tool to potentially help limit the number of negative biopsies in men with PSA between 4 and 10?ng/mL. Level of Evidence : 1 Technical Efficacy : Stage 2 J. Magn. Reson. Imaging 2018;47:1227–1236.
机译:背景技术除了临床变量之外,风险计算器传统上使用血清前列腺特异性抗原(PSA)值,以预测前列腺癌(PCA)的可能性。目的是开发预生物的核心的风险评分(RS)和统计方程式,以及预测活组织检查 - 幼稚男性在4-10μA的血清PSA中PCA的风险,可能有助于减少不必要的活组织检查。研究型前瞻性横截面研究。在本研究中招募了2009 - 2015年期间,在4-10℃的所有PSA的主题中,具有4-10μg/ mL的PSA的连续137名患有PSA的PSA。场实地力/序列1.5T(Avanto,西门子医疗保健,Erlangen,德国);使用T 1-重量,T 2-重量,DW-MRI和MRSI序列。评估所有符合条件的患者接受了MPMRI定向的认知融合经灭绝超声(TRUS) - 帘式活组织检查。统计测试使用接收器操作特性(ROC)曲线分析和多变量逻辑回归方法开发了等式模型和RS。进行了10倍的交叉验样和仿真分析,以评估MPMRI参数各种组合的诊断性能。结果137例患者,32例被诊断为活组织检查的PCA。用阳性病理学调整的多变量分析显示出明显的扩散系数(ADC),代谢物比和PSA作为PCA的重要预测因子(P <0.05)。使用这些预测器导出统计方程。用于计算PCA的风险的基于简单的6点MPMRI的RS,并且它表明它对PCA的高度预测性(差异比值?= 3.74,95%置信区间[CI]:2.24-6.27,区域曲线[AUC]?=?0.87)。模型(方程和RS)都会产生高预测性能(AUC≥0.85)验证分析。数据结论是统计方程和基于简单的6点MPMRI的RS可以用作护理点工具,以潜在有助于限制在4到10℃之间的粘合剂中的男性的负活检数量。证据水平:1技术效果:第2阶段J. MANG。恢复。 2018年成像; 47:1227-1236。

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