基于多参数 MRI 的活检前风险评分在前列腺特异性抗原 4-10ng/ml 的前列腺活检初筛男性中预测前列腺癌的价值
Prebiopsy multiparametric MRI-based risk score for predicting prostate cancer in biopsy-naive men with prostate-specific antigen between 4-10 ng/mL.
机构信息
Department of NMR & MRI Facility, All India Institute of Medical Sciences, New Delhi, India.
Department of Urology, All India Institute of Medical Sciences, New Delhi, India.
出版信息
J Magn Reson Imaging. 2018 May;47(5):1227-1236. doi: 10.1002/jmri.25850. Epub 2017 Sep 4.
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 -weighted, T -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.
背景
风险计算器传统上利用血清前列腺特异性抗原（PSA）值以及临床变量来预测前列腺癌（PCa）的可能性。
目的
旨在建立一种基于活检前多参数 MRI（mpMRI）的风险评分（RS）和统计方程，用于预测血清 PSA 为 4-10ng/ml 的活检初筛阴性男性中 PCa 的风险，以帮助减少不必要的活检。
研究类型
前瞻性横断面研究。
受试者
本研究共纳入 2009 年至 2015 年间 137 例血清 PSA 为 4-10ng/ml 的连续接受活检前 mpMRI（扩散加权 [DW]-MRI 和磁共振波谱成像 [MRSI]）的患者。
磁场强度/序列：1.5T（西门子医疗，德国埃朗根）；使用 T1 加权、T2 加权、DW-MRI 和 MRSI 序列。
评估
所有符合条件的患者均接受了 mpMRI 引导的、基于认知融合的经直肠超声（TRUS）引导的活检。
统计学检验
使用受试者工作特征（ROC）曲线分析和多变量逻辑回归方法建立方程模型和 RS。采用 10 倍交叉验证和模拟分析评估各种 mpMRI 参数组合的诊断性能。
结果
在 137 例患者中，32 例活检诊断为 PCa。多变量分析，经阳性病理校正，显示表观扩散系数（ADC）、代谢物比值和 PSA 是 PCa 的显著预测因子（P<0.05）。使用这些预测因子推导出一个统计方程。推导出了一种简单的基于 6 分 mpMRI 的 RS 来计算 PCa 的风险，结果表明该模型对 PCa 具有高度的预测性（优势比=3.74，95%置信区间[CI]：2.24-6.27，曲线下面积[AUC]：0.87）。两种模型（方程和 RS）在验证分析中均具有较高的预测性能（AUC≥0.85）。
数据结论
统计方程和简单的基于 6 分 mpMRI 的 RS 可作为一种床边工具，有助于限制血清 PSA 为 4-10ng/ml 的男性中阴性活检的数量。
证据水平
1 技术功效：2 级。磁共振成像杂志 2018；47：1227-1236。
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