基于mp-MRI和PSAD建立PI-RADS评分 4～5 分患者的前列腺靶向穿刺预测模型

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ABSTRACT：ObjectiveTo construct a prediction model for targeted biopsy（TB）of the prostate based on multiparameter magnetic resonance imaging（mp-MRI） and prostate-specific antigen density（PSAD）to predict the outcomes TB in patients with a score of 4-5 on the Prostate Imaging Reporting and Data System （PI-RADS）.MethodsClinical data of 669 patients with PI-RADS 4-5 receivig transperineal TB in our hospital during Jan.2O2 and Dec.2O23 were retrospectively analyzed. The data were divided into the training set and validation set with a ratio of Ω2：Ω1 . Independent predictors of TB results were identified withunivariate and multivariate logisticregression toconstructa formula for thepredictionmodel.A prediction modelwas subsequentlyconstructed and validated using thevalidation settoasssits efficacyand predictive performance with the area under thereceiveroperating characteristiccurve（AUC）.Therelative importanceof each independentpredictor in the formula wasanalyzed.ResultsUnivariate and multivariate logistic regression analyses showed that age，total number of lesions，histological location，PI-RADS score and PSAD were significantly associated with the TB outcomes （ P<0.05 ）and could be used as independent predictors，with PI-RADS score and PSAD making the highest contribution tooutcome prediction， accounting for 27.59% and 37.58% ，respectively.The training set had an AUC of 0.840 （ 95%CI ： 0.800-0.881 ，which was more predictivethanothersingle predictors，and thehigh-risk groupbasedontheoptimal thresholdofO.833 increased the positive biopsy rate from 79.3% to 94.4% .The validation set had an AUC of 0.865 （95%CI：0.810-0.920） ，and the high-risk group based on the optimal threshold of O.594 increased the positive biopsy rate from 80.0% to 96.2% .ConclusionThe prediction model has good predictive ability for lesions with PI-RADS 4-5 ，which can significantly improve the positive detection rate and reduce a large number of unnecessary systematic puncture.

KEY WORDS： prostate cancer； targeted biopsy；systematic biopsy；Prostate Imaging Reporting and Data System; multiparameter magnetic resonance imaging；clinically significant prostate cancer

摘要：目的探讨基于多参数磁共振（mp-MRI）和前列腺特异抗原密度（PSAD）构建前列腺靶向穿刺活检（TB）预测模型，并预测前列腺影像报告和数据系统（PI-RADS）评分 4～5 分患者的TB结果。（剩余10968字）