Role of Hiraoka's transurethral detachment of the prostate combined with biopsy of the peripheral zone during the same session in patients with repeated negative biopsies in the diagnosis of prostate cancer

BACKGROUND Persistent suspicion of prostate cancer(PCa)due to a rising prostate-specific antigen(PSA)level after repeated negative biopsies is a serious challenge in clinical practice.AIM To determine the role of Hiraoka’s transurethral detachment of the prostate(TUDP)combined with biopsy of the peripheral zone during the same session in patients with repeated negative biopsies in the diagnosis of PCa.METHODS We retrospectively evaluated the records of 10 patients who were eligible for inclusion in our hospital between December 2012 and August 2017.Patient demographics,a family history of PCa,the number of biopsies,prostate volume,pathological examination,and perioperative PSA level were obtained.RESULTS Two of 10 patients were pathologically diagnosed with PCa after surgery;the Gleason scores were 4+4 and 4+3,respectively.Both patients subsequently underwent laparoscopic radical prostatectomy.The median PSA levels preoperatively,and 3 mo and 1 year postoperatively in the other eight patients who were diagnosed with benign prostate hyperplasia after surgery were 19.10 ng/mL,1.10 ng/mL,and 1.15 ng/mL,respectively.The adjusted P values of the 3-mo and 1-year post-operative PSA level vs pre-operative PSA level were 0.003 and 0.026,respectively.None of the patients had increased PSA levels or PCa detected after a median 35 mo of follow-up.CONCLUSION TUDP combined with peripheral zone biopsy may improve the detection rate of PCa in patients with repeated negative biopsies.The PSA level declined rapidly in patients who had negative pathological examinations after TUDP,which remained stable 1 year after surgery.

数值天气预报模式对雅砻江下游强降水预报能力检验研究（英文）

目的:检验数值天气预报模式(WRF)在雅砻江下游对强降水的预报能力,并找出表现最优的参数化方案组合。创新点:首次针对雅砻江流域检验WRF模式对强降水的预报能力,并加入了计算时间作为评价的重要参考。方法:通过三场强降水事件,利用七种常用的云微物理参数化方案(Kessler,Lin et al.(Lin),SingleMoment 3-class(WSM3),Single-Moment 5-class(WSM5),Ferrier,Single-Moment 6-class(WSM6),和New Thompson et al.(NTH))和3种积云对流参数化方案(Kain-Fritsch(KF),Betts-Miller-Janjic(BMJ)和Grell-Devenyi(GD))的组合,对WRF模式在雅砻江下游的降水预报能力进行检验。为了评价WRF模式的预报能力,引入探测率(POD),空报率(FAR),BIAS和公平预报评分(ETS),对比不同方案组合的降水空间分布和站点预报的有效性。同时,均方根误差(RMSE)等指标被用来评价面雨量预报的精确性。除常规评价外,还将计算时间作为方案评价的重要参考,在满足精度需求的前提下优先选择计算效率高的方案组合。结论:1.WRF模式能够适用于雅砻江下游强降水预报;2.WSM3以及GD参数化方案组合的表现最为有效和稳定。