Development and validation of a logistic regression model to distinguish transition zone cancers from benign prostatic hyperplasia on multi-parametric prostate MRI
Development and validation of a logistic regression model to distinguish transition zone cancers from benign prostatic hyperplasia on multi-parametric prostate MRI
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DOI：
10.1007/s00330-017-4775-2
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发表时间：
2017-09-01
影响因子：
5.9
通讯作者：
Yamashita, Yasuyuki
中科院分区：
文献类型：
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作者：
Iyama, Yuji;Nakaura, Takeshi;Yamashita, Yasuyuki
为建立多参数前列腺磁共振成像(MP-MRI)诊断移行区(TZ)癌和良性前列腺增生症(BPH)的预测模型，对60例BPH和TZ癌患者进行了3次T-MRI检查。我们为T2加权像(T2WI)、弥散加权像(DWI)和动态MRI生成了10个参数。运用t检验和多元Logistic回归分析评价参数的准确性，建立多元Logistic回归模型。我们用留一法交叉验证的方法计算了LR模型的受试者工作特征曲线下面积，并将LR模型的性能与放射科医生的意见和前列腺成像报告和数据系统(PI-RADS v2)的评分进行了比较。多元LR分析显示，只有标准化的T2WI信号和平均表观扩散系数(ADC值)保持了它们的独立值(P<；0.001)。验证分析表明，最终的LR模型的AUC与委员会认证的放射科医生的AUC相当，并优于PI-RADS评分。标准化的T2WI和平均ADC是区分BPH和TZ癌的独立因素。A欧元我们在多参数磁共振成像中进行了定量图像分析。a欧元标准化T2WI和Mean-ADC是诊断TZ癌的独立因素。a欧元我们建立了Logistic回归分析来准确地诊断TZ癌。
To develop a prediction model to distinguish between transition zone (TZ) cancers and benign prostatic hyperplasia (BPH) on multi-parametric prostate magnetic resonance imaging (mp-MRI).This retrospective study enrolled 60 patients with either BPH or TZ cancer, who had undergone 3 T-MRI. We generated ten parameters for T2-weighted images (T2WI), diffusion-weighted images (DWI) and dynamic MRI. Using a t-test and multivariate logistic regression (LR) analysis to evaluate the parameters' accuracy, we developed LR models. We calculated the area under the receiver operating characteristic curve (ROC) of LR models by a leave-one-out cross-validation procedure, and the LR model's performance was compared with radiologists' performance with their opinion and with the Prostate Imaging Reporting and Data System (Pi-RADS v2) score.Multivariate LR analysis showed that only standardized T2WI signal and mean apparent diffusion coefficient (ADC) maintained their independent values (P < 0.001). The validation analysis showed that the AUC of the final LR model was comparable to that of board-certified radiologists, and superior to that of Pi-RADS scores.A standardized T2WI and mean ADC were independent factors for distinguishing between BPH and TZ cancer. The performance of the LR model was comparable to that of experienced radiologists.aEuro cent It is difficult to diagnose transition zone (TZ) cancer.aEuro cent We performed quantitative image analysis in multi-parametric MRI.aEuro cent Standardized-T2WI and mean-ADC were independent factors for diagnosing TZ cancer.aEuro cent We developed logistic-regression analysis to diagnose TZ cancer accurately.aEuro cent The performance of the logistic-regression analysis was higher than PIRADSv2.